The signal that arrived too late.

A corporate venture team identifies a strong signal in Q2. The signal indicates retention is compounding, and that a customer segment is emerging that the team did not anticipate but cannot ignore. They need to commit resources to it now, while the signal is still hot.

The annual budget was set in November. Headcount was approved in January. The next planning cycle begins in nine months.

By the time the resources arrive, the window has narrowed. Sometimes it has closed. The venture continues, but the version of the venture that gets resourced is not the one the signal called for. It is the one the budget could accommodate.

This is not bureaucratic resistance. The CFO is not the antagonist. The planning team is not obstructing innovation. Each part of the system is doing what it was designed to do. The system itself was built for a different job.

Corporate ventures do not fail from under-funding. They fail because the resource system is running on the wrong clock at the wrong scale.

This pattern holds whether the venture is built internally, spun out as an independent entity, invested in through corporate venture capital, acquired through M&A or acqui-hire, or pursued through partnership.

The execution path changes. The structural condition does not.

This is a different argument from the one most readers expect as many discussions about innovation funding focus on volume. Addressing questions such as how much capital is allocated, what proportion of revenue is committed, and where the budget sits in the organisational chart. That conversation matters, but it is the second-order question. The first-order question is whether the resource system can move at all when evidence demands it. Volume without velocity is the most expensive failure mode in corporate venturing. It produces big and late.

The deeper diagnosis.

Issue #9 named the absence of reallocation as a portfolio-level failure. A real portfolio redistributes resources when signals strengthen. Most corporate innovation portfolios do not. That essay left a question unresolved. Even when the portfolio decides to reallocate, can the underlying resource system enforce the decision? The answer, in most cases, is no.

The reason is upstream of any particular budgeting failure. Most resource problems in corporate venturing trace to a single structural decision. Innovation is treated as a contained function with a fixed allocation, rather than as a distributed capability with a claim on enterprise resources. The innovation team has its budget. The ventures within it compete for that budget. They do not have a structural mechanism to draw from elsewhere when signals justify it.

Once that classification is made, four downstream conditions follow. Two govern cadence. Two govern volume. Together, they produce the asymmetry the title names.

Cause 1: Ventures are governed on Calendar Time, not Venture Time

Corporate planning runs on calendar time. There is an annual budget with an annual headcount plan, all being managed through quarterly reviews. The calendar is a rhythm imposed for reasons of accountability, forecasting, and governance. Those reasons are legitimate for established business units operating on year-over-year improvement cycles.

Ventures do not operate on calendar time. They operate on venture time, a composite of three distinct rhythms.

There is “evidence time,” when signals strengthen, and the venture has new information about what should happen next. Evidence cycles run in weeks or months, not years. A retention curve that compounds in Q2 is information the team did not have in Q1. Acting on it in Q4, after the next budget cycle, is acting on a snapshot of a market that has moved.

There is an “opportunity time”. When external windows open and close on market clocks, the corporation cannot influence them. A venture round worth participating in. A target available for acquisition. A partnership that becomes possible because a particular configuration of buyers, suppliers, and competitors has briefly aligned. Opportunity time is the world telling the venture when it must move. The corporate calendar is irrelevant to it.

There is an “ad-hoc” time component. Unscheduled but consequential moments. A spin-out is succeeding faster than expected and needs additional staff before the next hiring round. A partnership requiring fast technical resourcing to meet a contract milestone. A pilot showing enough signal that a step-change investment is warranted before the next gate review.

Calendar time is one rhythm, but Venture time is three. The mismatch is not occasional; it is constant. The corporate planning cycle was never designed to accommodate any of the three, because the operations it governs do not require them.

Cause 2: Talent lock-in once deployed

The first cadence problem is about putting resources in. The second is about moving resources between ventures once they are in.

Capital can be reallocated faster than people. A venture that needs less can have its budget trimmed at the next quarterly review. A venture that earns more can have funding lifted. The money moves quickly once the decision is made.

People do not move on the same clock. Once a person is deployed onto a venture, redeploying them onto a stronger signal elsewhere in the portfolio requires unwinding a network of arrangements. Performance reviews are linked to the current scope. Manager relationships have been built. Career narratives have been constructed around the current venture. HR systems treat redeployment as a re-hire process, not a reallocation. Even when the portfolio decides to concentrate talent on the strongest signal, the system makes the decision unenforceable on any timeline that matters.

This is the second clock, and it is often slower than the first. A portfolio with fast capital reallocation and slow talent reallocation is still a portfolio that can change its slide deck but not its execution. The same dynamic applies in spin-outs, where pulling additional people into a successful spin-out from the parent often runs through the parent’s HR cycle. The spin-out’s capital independence does not extend to the flow of talent.

Cause 3: Resource competition with the core business (the floor)

Cadence is one face of the asymmetry. Volume is the other.

When ventures sit inside the corporate budget process, they compete with established business units for resources from the same pool. Every additional dollar to a venture is a dollar removed from a known-return P&L line. The CFO does not need to oppose innovation. The budget structure does it for them.

The rational response, given that comparison, is to set the venture allocation low. Low enough that it does not threaten any meaningful business unit line item. Low enough that approval is uncontested. Low enough that no individual decision-maker has to defend a transfer of capital from operations to experimentation.

This produces a structural floor where ventures get just enough to keep going, never enough to compound. The result, the venture does not have the funding the signal would justify. In CVC structures, the same pattern appears at the deal level. A corporate venture fund weighing follow-on participation in a hot round against operating returns will write a smaller cheque than the round requires. The fund is in the room. It is not in the round at the level of strategic interest it warrants.

Cause 4: No concentration mechanism for compounding signals (the ceiling)

The volume problem has both a ceiling and a floor. Even when a venture earns the right to more resources through evidence, there is no mechanism to concentrate capital on it excessively.

A venture that doubles its retention curve does not automatically receive double the budget. A spin-out that signs a major customer ahead of plan does not automatically secure step-change follow-on capital from the parent. An acquisition target whose strategic value has become obvious does not automatically jump to the top of the M&A queue. Each of these requires a fresh approval against the same competing claims as before. The system can fund maintenance. It cannot fund conviction.

This is the structural difference between a venture portfolio and a venture system. A portfolio decides which bets to make. A system decides which bets to concentrate on as evidence accumulates. Without a concentration ceiling, every venture in the portfolio is funded as if it had the same compounding probability, regardless of the evidence.

The cumulative cost

Each cause is bearable in isolation. A venture operating under all four conditions is not. The system funds these ventures at exactly the level required to keep them alive and exactly nothing more, which is the slow accumulation of stalled ventures, Issue #9 named.

The four resource states

Cadence and volume are not coequal. Cadence is upstream. Volume is downstream. A fast clock with thin volume can still read signals and place small bets. A slow clock with heavy volume produces capital that arrives after the signal has decayed. The 2x2 below maps the four states corporate innovation functions occupy.

Most corporate innovation functions live in the top-left quadrant. Some, after a budget increase that did not include a cadence redesign, move to the bottom-left and discover that more money on a slower clock produces larger zombie pilots, not better ventures. A few, usually structurally separated from the parent, sit in the top-right. The bottom-right is where venture-grade execution actually happens. It is also where most corporate innovation functions claim to be.

The four exits

Most readers will already be reaching for reasons their organisation is exempt from this argument. Four exits, in order of how often they are used.

• We have a fast-track process for urgent resourcing.
  Many fast-track processes are political escape valves, not structural mechanisms, depending on a senior sponsor invoking them. They run on relationship capital, not governance design. A fast-track that requires a leader to personally champion each invocation is not a system. It is a workaround that works once or twice a year, then collapses. A real cadence correction does not require anyone to champion it. The default cadence is the fast cadence.

• We have an innovation fund. That is our pre-authorised pool.
  Named innovation funds are often accounting re-classifications of the same annual budget. The capital lives within the pool, but the cadence and volume rules governing its release remain unchanged. The pool cannot be deployed without going back through the business unit planning cycle, without a quarterly committee, or without an exception process that takes longer than the signal allows. A pool you cannot deploy on venture time is not a venture pool. It is a labelled bucket inside the existing system.

• We have a governance committee that can make resource decisions.
  A quarterly meeting committee cannot operate on venture time. A committee that requires consensus cannot concentrate capital on a single signal at the expense of others. A committee whose members each represent a different function will optimise for proportionality rather than conviction. The committee is not the answer to absent decision rights. It is often the structural reason that decision rights are absent.

• The real problem is we just need a bigger innovation budget.
  This is the most expensive exit. Volume without velocity is dead capital. BCG’s 2024 research found 83% of leaders rank innovation as a top-three priority, while only around 30% feel ready to execute. Adding to the volume side cannot close that gap while cadence remains untouched. A larger budget on the wrong clock does not produce more ventures. It produces more zombie pilots with bigger headcount lines.

What changes

The fix is structural, not procedural. A faster approval process inside the existing architecture will not produce venture-grade resourcing. The architecture itself has to change, with a mechanism that enables the venture pool to sit outside the annual planning cycle. This is not a labelled bucket. A genuinely separate structure with its own governance, its own decision rights, and its own deployment triggers.

Governance

The pool is governed by a small group with explicit authority to deploy capital and assign talent on evidence triggers, without requiring approval from the next BU planning round. The group is structurally separated from the operating P&L, which means its decisions cannot be vetoed by line-of-business managers protecting their allocations. The group’s accountability is for the ventures that pool resources, not for the operating revenue lines those resources might have served instead.

This structure is not unfamiliar. It is roughly how independent venture firms operate: a partner group with capital deployment authority, evidence-based decision triggers, and accountability to a portfolio rather than to an operating P&L. The novel work in a corporate context is making the structure compatible with the rest of the organisation without surrendering its independence.

Triggers

The pool deploys on evidence triggers, not on calendar triggers. A retention curve crossing a defined threshold. A customer concentration signal exceeding a stated level. An external event such as a competitor move, a regulatory change, or the availability of a target. A spin-out hitting a milestone that warrants follow-on. The triggers are documented, monitored, and acted on without requiring fresh approval each time.

This does not mean the pool deploys without evaluation. It means the judgment runs on the venture’s clock, not the corporation’s. A trigger fires, causing a decision within the pool’s governance. Capital and talent move. The annual planning cycle does not need to be known in advance.

Size

The pool needs to be large enough to fund concentration, not just continuation. If the pool can support only N ventures at the maintenance level, the concentration ceiling remains unchanged. The pool must carry headroom for a step-change investment in the strongest signal, meaning it must be sized as if at least one venture will require multiples of its initial allocation. A typical starting frame: pool size equal to two to three times the sum of initial venture allocations, with explicit reserves for follow-on concentration.

The pool fixes cadence first. It also creates the structural conditions for volume to flow to the strongest signals, because there is somewhere for that volume to go without contesting BU allocations.

The pool addresses capital cadence. Talent cadence requires a parallel structure, with pre-authorised talent slots that are reassignable on evidence triggers, and HR treating venture redeployment as strategic rather than a re-hire. Without that, the pool can move money but not people.

Diagnosing Resource Velocity

Six questions. Three on cadence. Three on volume. Each has a named failure mode. Apply this to your own innovation function. Answer honestly.

Cadence

1. When was the last time your innovation function reallocated capital outside the annual planning cycle? If the answer is “in the last quarter,” you have a working cadence. If the answer is “during last year’s reset,” or you cannot recall, you do not.
   Failure mode: You have a calendar, not a clock.

2. If a venture team identified a strong signal next month, how long until additional capital and headcount could be deployed in response?
   Measure the answer in weeks. If the answer is in quarters, the signal will have decayed by the time the resourcing arrives.
   Failure mode: signal-to-deployment lag is measured in quarters, not weeks.

3. What evidence threshold triggers an out-of-cycle resource decision in your governance system?
   If you can name the threshold, you have evidence-based cadence. If the answer is “when the CEO asks,” you have political cadence.
   Failure mode: there is no threshold, only a calendar.

Volume

1. When a venture demonstrates compounding evidence, can it secure step-change resourcing without joining the next BU planning round?
   If yes, you have a concentration mechanism. If no, the venture is graded on a curve set by the core business.
   Failure mode: Ventures are evaluated against operating returns, not venture returns.

2. Is there pre-authorised capital sitting in a venture pool, or does every increment require fresh approval against competing BU bids?
   A pool you cannot deploy without re-approval is not a pool.
   Failure mode: Venture capital is contested capital.

3. Is there a defined ceiling on how much a single venture can absorb when signals justify concentration, or does every dollar above baseline require an exception?
   If your strongest venture cannot draw step-change resources without exception treatment, your system is designed to maintain ventures, not to bet on them.
   Failure mode: your system can fund maintenance but not conviction.

Reading the pattern

Five or six yes answers: you have venture-grade resourcing. Confirm by reviewing how the system performed under pressure in the last 24 months.

Three or four yes answers: one axis is functioning while the other is broken. Identify which. Cadence-strong / volume-weak organisations make many small bets quickly, but cannot concentrate when one of them works. Volume-strong / cadence-weak organisations have meaningful capital that arrives after the signal has decayed. Both states are unstable.

Less than three positive answers: you are operating in stalled-and-starved territory. The portfolio is on the wrong clock at the wrong scale. The structural fix is upstream of any particular budget conversation.

The Australian context: A capital constrained ecosystem.

The cost of resource asymmetry compounds in capital-constrained ecosystems. Australia is one such ecosystem, and four features make the structural argument harder to escape locally.

A decade of mixed venture outcomes

The most publicly documented Australian evidence sits in corporate venture capital, because external investments leave a paper trail and external structures attract external commentary. The same structural conditions apply to internal builds, spin-offs, M&A, and partnerships, but those failures are usually invisible outside the organisation. The CVC story below is illustrative, not definitional. The same patterns play out across every execution path.

Over the last ten years, each of Australia’s major banks built corporate venture vehicles. Their structural designs differed materially.

• Some were internal funds governed under the parent’s financial architecture.

• Some were spun out into independent entities with the parent as sole funder.

• Some were externally-managed funds with the parent as one limited partner among several.

• Some were venture scalers with partial separation: a separate legal entity and technology stack, but inside the parent’s strategic gravity.

The outcomes have not divided cleanly along the lines most people would predict. Externalisation alone has not been the answer. Internal models have not always failed. The variable that better explains durability is something more specific: how robust the structural separation was, and how much it depended on the parent’s continued willingness to fund and not interfere.

• One of the major banks set up an internal innovation and investment arm. Close to a decade later, it had evolved and was spun out into an independent entity, to operate outside the “gravitational pull” of the parent entity. Thereby, driving improvements across delivery speed, agility, lower costs, and easier talent recruitment. The entity ran for several years. with several meaningful investments, including a position in one of Australia’s most successful fintechs. In late 2025, under new leadership and amid a broader restructure, the bank closed the entity. The remaining portfolio was folded back into a non-operating holding company. The structural fix had been correctly implemented and then unwound.

• A different bank ran an internal fund for several years and approximately $100M of deployed capital before substantially slowing its activity. The fund still exists and still has a public-facing investment process and a portfolio, however new investments have dropped from its peak. The structural separation was real. The funding potentially was not over time.

• A third, took a different mode, operating a venture scaler, with partial separation, that started with a stated ambition of 25 ventures by 2025. It has since re-positioned to scaled back on volume, to fewer but larger bets. It too more recently has extended its model through a partnership with an external fintech fund.

• And a fourth, the earliest mover, structured its CVC as an externally-managed fund with the bank as a limited partner. That fund made early bets that produced material returns, including a position in a US crypto exchange that yielded a reported $500M-plus windfall on listing. It ran three funds. Ahead of its fourth fund, it decoupled from the bank, partly because the bank was reluctant to back the categories the fund manager wanted to pursue. The fund continues to operate. It is no longer a pure corporate venture vehicle solely for its parent entity.

Two patterns matter in this evidence.

The first is that the durability of separation explains more than the presence of separation. Independent entities funded solely by the parent have a weaker form of structural separation than independent funds with diversified limited partners. The kill switch is in different hands. When the parent’s leadership changes or its cost pressure rises, the parent-funded entity is exposed in a way the diversified-LP fund is not.

The second is that even correctly implemented structural fixes are not durable unless they are institutionalised beyond any single leadership team. The structural argument the essay has made operates over decision cycles measured in months. Corporate leadership cycles run on multi-year clocks. A venture architecture that depends on the goodwill of a particular CEO will be vulnerable at the next transition, regardless of how well it was designed.

The lesson is not that externalisation is the answer. It is that resource architecture is the binding constraint; the architecture has to be designed for durability rather than initial separation, and the durability has to be earned over time and across leadership transitions, not just established at inception. The structures that survived longest in the Australian evidence were those whose continuation did not depend on any single corporate decision-maker continuing to back them.

The same pattern, less visible: internal builds and spin-outs

The CVC examples above are documented because external investments leave a paper trail. The much larger pool of evidence sits in internal builds, where the structural pattern is identical but the failures are visible only inside the organisations that own them.

The pattern is recognisable. An internal venture is launched with a strategic mandate. It receives an annual allocation that is rational by core-business standards but starves it by venture standards. It runs for several years. Customer acquisition is steady but slow. Headcount lifts incrementally. The product roadmap moves at the cadence permitted by the parent’s planning cycle. Years later, when the organisation needs to accelerate to keep up with a market that has moved, the internal venture cannot. The acceleration option chosen is usually external: a competitor neobank is acquired, an external partnership is signed, a fintech is bolted on. The structural problem the internal build was designed to solve is eventually solved by paying market rates for someone who was free to operate on venture time.

One Australian example sits in plain view. A major bank launched an internal direct bank in 2008. Roughly thirteen years later, with a customer base that had grown but had not kept pace with newer entrants, the parent bought a younger competitor folded it into the original venture, taking the competitor’s technology platform and team alongside the original brand.

The internal build was not a failure. It worked, by every measure the parents’ planning cycle had set for it. It was simply unable to meet the market’s timeline. The acceleration had to be purchased externally because the parent’s architecture could not generate it.

That is the structural pattern at the internal-build level. The venture had funding for over a decade. What it did not have was the cadence and concentration mechanism to compound. The eventual fix was not to redesign the resource architecture. It was to acquire what the architecture had failed to produce. That works once. It does not work as a system.

The acquisition pattern reveals the same condition from a different angle. When organisations cannot resource at venture velocity internally, they buy. The acquired venture often arrives with the velocity intact, only for the integration process to destroy it. Bain’s M&A research has found that talent retention is the second-largest contributor to acquisition deal success, behind only deal thesis. Acquired venture teams that operated on venture time before acquisition find themselves slowed to the parent’s pace within the first integration cycle. The volume problem has been solved by the acquisition price. The cadence problem has not.

If an organisation repeatedly chooses to buy what it cannot build internally, the binding constraint is not capability or talent. It is a resource architecture. The pattern may repeat every five to seven years.

A capital ecosystem that compounds the cost.

The Cut Through Venture and Folklore Ventures State of Australian Startup Funding 2025 report shows the structural shape of local capital. $5.48 billion was raised across 390 deals in 2025, but the top 20 deals captured 58% of the total. Series B remains a bottleneck, and 66% of all 2025 deals included at least one international investor, up from 57% in 2024. At Series A and beyond, offshore participation is now the norm rather than the exception.

For corporate ventures, this matters because the fallback option after missing an internal resourcing window is much narrower than in deeper capital markets. A US-based corporate venture that misses its parent’s funding window can usually find domestic bridge capital. An Australian corporate venture that misses its parent’s window often cannot. Internal cadence is not just a governance question. In Australia, internal cadence often is the capital availability for corporate ventures.

A concentrated corporate landscape.

our banks. Three miners. Two insurers. Annual planning cycles in these organisations are not just embedded, they are load-bearing. The structural mismatch between calendar time and venture time is therefore especially costly here, because the organisations most likely to operate corporate venture functions are also the ones with the most deeply entrenched planning architectures.

The Australian innovation ecosystem cannot fix the cadence problem from the outside. The fix has to come from inside the organisations that hold the largest balance sheets, and the design of that fix is the structural question this issue has tried to name.

A doctrine close.

Volume without velocity funds zombie pilots. Velocity without volume funds experiments. Ventures need both.

A corporate venture system running on the wrong clock at the wrong scale is not a venture system. It is an operational system with a venture label. The label provides cover. The structure produces the outcomes the structure was designed to produce. Calendar time and contested volume produce stalled ventures. Venture time and pre-authorised concentration produce ventures.

Issue #9 ended on the line that a portfolio without kill discipline is just a list. Issue 10 extends that argument one structural layer down. A portfolio without resource velocity is just a list with a budget.

Closing note

This is Issue #10, the fourth or six in the Corporate Venturing Under Constraint series. Issue #9 named the absence of reallocation as the portfolio-level failure. Issue #10 has named the resource architecture that makes reallocation unenforceable.

Still to come:

Issue #11 takes up the question this issue leaves open: who, inside the organisation, holds the authority to design and operate this architecture in the first place. Governance maturity. Decision rights. The role that does not yet exist in most corporate innovation functions.

Issue #12 closes the series by naming the function itself. The Venture Operator Function a category that this body of work has been describing.

If you found this useful, the diagnostic above is designed to be run on your own function. Save it, screenshot it, share it with someone who needs to see it. The structural conversation is easier to have when both parties are looking at the same diagnostic.

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References & Further Reading

1. Bain & Company. (2022). Reimagining Talent in M&A: 2022 M&A Report. https://www.bain.com/insights/reimagining-talent-m-and-a-report-2022/

2. Boston Consulting Group. (2024). Most Innovative Companies 2024: Innovation Systems Need a Reboot. https://www.bcg.com/publications/innovation-strategy-delivery-insights

3. Capital Brief. (October, 2024). x15 Ventures celebrates first major ‘exit’ as Unloan graduates into CBA division. https://www.capitalbrief.com/article/x15-ventures-celebrates-first-major-exit-as-unloan-graduates-into-cba-division-40a3cdc7-fd35-4b61-8cbe-cf996c92780d/

4. Capital Brief. (October, 2025). ‘Makes sense’: ANZ confirms 1835i closure. https://www.capitalbrief.com/newsletter/makes-sense-anz-confirms-1835i-closure-4c965396-a6f1-45ee-bd68-3df1167291f5/

5. Capital Brief. (December, 2024). ‘Pleased it’s over’: Ubank CEO on the 86 400 merger and the neobank’s future at NAB. https://www.capitalbrief.com/article/pleased-its-over-ubank-ceos-on-the-86-400-merger-and-the-neobanks-future-at-nab-649af10e-6eab-4e2a-aa91-adb62100144f/

6. Capital Brief. (August, 2024). From Reinventure to reinvention: Westpac’s mutating VC journey. https://www.capitalbrief.com/article/from-reinventure-to-reinvention-westpacs-turbulent-vc-journey-418322dc-ff80-4f50-954b-917e6330831f/

7. Collective Campus. Corporate Venture Capital in Australia: Fueling Innovation and Growth. https://www.collectivecampus.io/blog/corporate-venture-capital-in-australia-fueling-innovation-and-growth

8. Cut Through Venture and Folklore Ventures. (February, 2025). State of Australian Startup Funding 2025. https://www.cutthrough.com/insights/state-of-australian-startup-funding-2025

9. iTnews. (June 2022). CBA’s x15ventures switches focus from build to benefits. https://www.itnews.com.au/news/cbas-x15ventures-switches-focus-from-build-to-benefits-580793

10. Mi3. (December, 2023). Fewer, bigger bets: CommBank’s X15 ventures doubles down on scaling winners. https://www.mi-3.com.au/05-12-2023/banking-deeper-tech-integration-and-innovation-drive-customer-loyalty-well-commercial

11. Startup Daily. (October, 2025). ANZ bank has killed off its venture arm, 1835i. https://www.startupdaily.net/topic/venture-capital/anz-bank-has-killed-off-its-venture-arm-1835i/

Now consider how most corporate innovation functions use the word “portfolio.”

They mean: the things we are currently doing.

That is not a portfolio. That is a collection. And the distance between those two words is where most innovation value gets destroyed.

The Collection Problem

Most organisations arrive at their “innovation portfolio” the same way. Individual initiatives get proposed, evaluated, and approved through separate business cases. Each one clears its own hurdle. Each one gets its own budget line. Each one reports on its own progress against its own milestones.

At some point, someone assembles a slide that shows all of these experiments, options, ventures or initiatives on a single page. Maybe they get sorted into horizons. Someone may draw a 2x2 with risk on one axis and strategic fit on the other. The slide gets presented at a quarterly review. Everyone nods. The word “portfolio” is used.

But nothing about that process constitutes portfolio management. No one asked whether these ventures, taken together, represent a coherent set of strategic bets. No one assessed whether the risk is concentrated or distributed. No one has the authority to move resources from one initiative to another based on relative performance. No one is measuring return at the portfolio level.

What exists is a collection of individually approved projects that are visible on the same slide. The slide creates the appearance of portfolio thinking without any of the underlying mechanics.

Why the Gap Exists

The collection-to-portfolio gap is not an oversight. It is a structural consequence of how many organisations set up their innovation functions. The gap has at least four root causes, and they compound.

The mandate is undefined.

Before you can construct a portfolio, you need to answer a question that most organisations skip entirely: what is the role of innovation in this organisation’s strategy, and what methods are in scope?

This is a scoping decision that sits upstream of everything else. It determines which instruments are available to the innovation function or functions and which belong elsewhere. An organisation might decide that its innovation mandate covers internal venture building and spinouts, but that partnerships and strategic investments sit with corporate development. Another may include invest-to-partner models within the innovation remit. A third might limit the scope to incremental improvements within existing business lines.

None of these choices is inherently wrong. An organisation that says “we build from within and occasionally spin out” has made a legitimate strategic decision. It narrows the option set but creates clarity about what the portfolio can contain, what capabilities are needed, and what a return looks like.

The problem is when this scoping decision never gets made. Innovation becomes whatever anyone decides it is. Different business units pursue different types of activity under the same label. Some run small incremental projects. Some attempt genuine ventures. Some call process improvements “innovation” because the word carries budget protection.

Without a mandate, there is no boundary. Without a boundary, there is no portfolio. There is just accumulation.

The instruments are treated as interchangeable.

Even where a mandate exists, most organisations fail to recognise that different types of innovation activity are fundamentally different instruments.

Building a venture from within the organisation is not the same as investing in an external startup. A spinout operates under different constraints than a partnership. An invest-to-partner model, where you take a position in an external company with the intent of integrating capability over a three to five-year horizon, looks nothing like a twelve-month internal build.

In finance, no one would manage equities, fixed income, and options as if they were the same thing. The portfolio exists precisely because these instruments are different, and the value comes from how they interact as a set.

Most innovation functions treat every initiative as the same type of bet. The same stage-gate process. The same milestone structure. The same quarterly reporting cadence. This flattening erases the very differences that portfolio construction is designed to exploit.

The structural design prevents portfolio-level decisions.

How the innovation function is organised determines whether portfolio management is even possible.

In a centralised model, a single team owns the innovation mandate. This creates the possibility of portfolio-level authority: someone who can see the full set of bets and make trade-offs across them. But centralised models often lack proximity to the business context where ventures need to operate.

In a decentralised model, each business unit runs its own innovation activity. This provides business context but eliminates portfolio-level visibility. No one can see all the bets. No one can reallocate resources across the set. Each unit optimises locally, and the organisation’s total innovation spend is just the sum of uncoordinated parts.

The hub-and-spoke model is the most common attempt to resolve this tension. A central hub holds processes, standards, budget, governance, and capability. Spokes in business units run execution closer to the operating context. Larger or cross-cutting bets escalate to the hub. Day-to-day innovation stays in the spokes.

In theory, this combines centralised coherence with decentralised proximity. In practice, it drifts. The hub becomes administrative rather than strategic, running reporting cycles and stage-gate reviews rather than making portfolio decisions. The spokes diverge in their methods and definitions, each developing its own view of what counts as innovation. Decision rights between hub and spoke become contested. The quarterly review becomes a status update rather than a governance forum. And no one is confident about where portfolio-level authority actually sits, because in practice, it sits nowhere.

This is also where Issue 8’s stop authority problem becomes a portfolio-level problem. If no one in the structure has the authority to kill an individual initiative, no one can rebalance the set. Stop authority at the project level is a prerequisite for portfolio management. Without it, the portfolio can only grow. It can be difficult to reshape.

The structural design choice matters less than whether the chosen structure enables someone to manage the portfolio as a whole. If no one has authority over the set, the set cannot function as a portfolio regardless of how it is organised.

There is no connection to strategy.

A portfolio without an investment thesis is just a scatter plot.

In finance, the thesis determines the construction: which sectors to overweight, which risks to accept, and which time horizon to optimise for. The portfolio is the execution layer of the thesis.

In corporate innovation, the equivalent is the connection between the innovation portfolio and the organisation’s strategic plan. The portfolio should be the set of strategic options the organisation is actively pursuing to create future value. Each position should trace back to a strategic question the organisation needs to answer or a capability it needs to develop.

Not every bet needs to map neatly to an existing strategic priority. A well-constructed portfolio includes exploratory positions: deliberate, bounded investments in areas where the organisation has no current thesis but wants to develop one. Adjacency plays. Emerging technology watches. Genuine moonshots where the organisation is spending to learn whether a space is relevant to its future.

The critical distinction is that exploratory positions are still deliberate. They are in the portfolio because someone decided to allocate resources to that space, not because they drifted in through an enthusiastic business unit. They still carry a return expectation, even if that return is defined as “develop enough understanding to make a strategic decision within eighteen months.” Exploratory does not mean exempt from rigour.

When innovation operates as a standalone function with its own strategy, disconnected from the organisation’s strategic planning process, the portfolio becomes self-referential. It serves the innovation function’s goals rather than the organisation’s strategic needs. This is how you end up with innovation teams that can demonstrate impressive activity metrics while the organisation’s strategic gaps remain unaddressed.

The connection needs to run in both directions. Strategy should inform what the portfolio contains. And the portfolio’s performance should inform strategic planning, updating the organisation’s view of which options are maturing, which are failing, and where new bets are needed.

To put it plainly, many innovation functions have no defined boundary around what they are responsible for, treat fundamentally different types of bets as if they were interchangeable, are structured in ways that prevent anyone from managing the set as a whole, and operate with little or no connection to the organisation’s strategic plan. Any one of these gaps would prevent real portfolio management. Most organisations have all four. That is not a portfolio with room for improvement. It is a collection with a label.

Before You Diagnose: The State of Play

Before applying any diagnostic, there is a prior step that most organisations skip. And it is broader than most expect.

You need an inventory. Not of what the innovation function is currently running, but of everything the organisation is doing that could constitute innovation or venturing activity, anywhere, under any label.

This means looking beyond the innovation team’s pipeline. Corporate development might be running invest-to-partner plays that are functionally innovation bets but governed as transactions. A business unit might have a skunkworks project that nobody reports centrally. The strategy team might be funding exploratory research that never touches the innovation function’s pipeline. M&A might be doing acqui-hires that are capability bets dressed as deals.

The broad state of play needs to capture each activity’s type, stage, committed resources, expected return, and the strategic question it is intended to answer. It also needs to note where the activity currently sits organisationally and who governs it.

Most organisations cannot produce this on demand. When they try, the exercise itself becomes revealing. Initiatives surface that no one at the centre knew were running. Committed resources turn out to be higher than anyone estimated because costs are spread across business unit budgets that are never consolidated. Several initiatives turn out to be pursuing overlapping objectives with no coordination between them. Activities that one function calls “innovation”, another calls “business development” or “continuous improvement,” and the definitional inconsistency is itself a finding.

The broad inventory matters because it inverts the usual sequence. Most organisations define the mandate first and then inventory what falls within it. This is circular; you end up scoping around what is already visible rather than what should be managed. The stronger sequence is to see the full landscape first, then draw the boundary. The mandate becomes a decision informed by evidence rather than a top-down decree that inherits whatever definitional problems already exist.

Once the mandate is defined, the state of play narrows to the portfolio boundary. But it does not become a one-time exercise. It is the foundation of portfolio governance: updated regularly, reviewed against strategic priorities, and used as the basis for rebalancing decisions. If you cannot produce an accurate state of play, you cannot manage a portfolio. You are navigating without an inventory.

The Portfolio Reality Diagnostic

Six questions to help determine whether what the organisation has is a portfolio or a collection.

1. Can you define the mandate?

Write down, in one paragraph, what your innovation function is authorised to pursue and what methods are in scope. If you cannot do this, or if the answer is “it depends on the business unit,” you do not have a portfolio boundary. You have an accumulation.

2. Can you produce a state of play?

List every activity across the organisation that could constitute innovation or venturing, not just what the innovation function manages. Include its type, stage, committed resources, and expected return. If you cannot produce this list within a week, if the exercise reveals activities no one at the centre knew were running, or if different functions cannot agree on what counts, you do not have portfolio visibility. You have fog.

3. Can you name the instruments?

Take that list and categorise each initiative by type: internal build, spinout, partnership, investment, invest-to-partner, exploratory position, or other. If every initiative is the same type, your portfolio has no diversification. If you cannot categorise them because the types have never been distinguished, your portfolio has no composition logic.

4. Can you state the expected return (desired outcomes) for each position?

For each initiative, articulate the return the organisation expects and the time horizon. The return does not have to be financial. It can be strategic optionality, capability development, or market learning. But it must be defined. If most initiatives have no stated return expectation, you have no basis for portfolio-level measurement.

5. Can one person or body rebalance the portfolio?

Identify who has the authority to move resources between initiatives, accelerate one at the expense of another, or kill a position based on the portfolio’s overall performance. If the answer is “no one” or “it would require separate approvals from each business unit,” you have a collection governed by its parts, not a portfolio governed as a whole.

6. Can you trace each position to a strategic question?

For each initiative, identify the strategic question it answers or the strategic capability it develops. This includes exploratory positions, which should trace to a question the organisation is actively trying to answer, even if the answer is not yet clear. If many initiatives cannot be connected to the organisation’s strategic plan or to a deliberate exploration thesis, the portfolio is self-referential. It serves the innovation function, not the organisation.

Reading the pattern: If you answered “no” to one or two of these, you have specific gaps to close. If you answered “no” to three or more, what you have is not a portfolio in any meaningful sense. It is a collection of individually approved activities that share a label but lack the connective tissue that enables portfolio management.

But We Are Different

Two versions of this argument appear reliably when portfolio discipline is proposed.

This inverts the logic. Uncertainty is precisely why portfolio discipline exists. Financial portfolios are not built for environments of certainty. They are built because individual positions are unpredictable, and the portfolio is the mechanism for managing that unpredictability across a set of bets. Diversification, rebalancing, and position sizing all exist because no one knows which individual bet will pay off.

The same principle applies to innovation. Individual ventures are uncertain. That is not a reason to abandon portfolio logic. It is the reason you need it.

A 2022 study published in Production and Operations Management by Si, Kavadias, and Loch at Cambridge Judge Business School found that the results of innovation portfolio management processes remain widely perceived as unsatisfactory, but not because the problem is too uncertain for structure. The root cause they identified was an overemphasis on generic individual project selection, without connection to the organisation’s specific strategy. The problem is not too much rigour. It is the wrong kind of rigour, applied at the wrong level.

McKinsey has consistently found that while more than 80% of executives say innovation is among their top three priorities, fewer than 10% are satisfied with their organisation’s innovation performance. That gap has persisted for nearly a decade. BCG’s 2024 Most Innovative Companies report tells the same story at scale. The report surveyed more than 1,000 senior innovation executives globally and found that the readiness gap is widening. In 2022, 20% of companies qualified as “innovation ready” on BCG’s maturity benchmark. By 2024, that figure had fallen to 3%, even as 83% of companies ranked innovation as a top-three priority. Only 12% of executives reported a strong link between their business and innovation strategies. BCG described the emerging pattern as “zombie” innovation systems: organisations going through the motions without a clear strategy to focus their efforts. The parallel with Issue 8’s zombie pilots is not coincidental. The same structural absence, no one with the authority or mandate to make hard decisions, produces the same outcome at every level: activity without accountability.

McKinsey’s late-2024 survey of over 1,000 C-level executives across 99 countries reinforced this. Most organisations struggle to make trade-offs between short- and longer-term initiatives or among projects with different risk profiles. That is not a description of organisations with too much structure. It is a description of organisations with no portfolio-level decision-making at all.

Complexity is not an exemption from portfolio logic. It is the reason you need it.

Large organisations with multiple business units, geographies, and innovation models will never have a simple portfolio. But the alternative to a single portfolio view is not to have no view; it is multiple uncoordinated views that no one can reconcile. Without a portfolio-level view, the organisation cannot see concentration risk, identify duplication, or make trade-offs across the set.

The operational challenge is real. Constructing a portfolio view across a complex organisation requires shared definitions, consistent categorisation, and a governance layer with authority over the whole. That is difficult. But the difficulty of construction is not an argument against the necessity. It is a description of the work that needs to be done.

The Real Cost of the Illusion

The danger of the portfolio illusion is not just that it is inaccurate. It creates false confidence.

An organisation that knows it has a collection of ad hoc innovation projects at least understands what it is working with. The constraints are visible. The lack of coordination is acknowledged.

An organisation that believes it has a portfolio may assume it is diversified, even though it may be concentrated. It assumes it has strategic coverage when it may have gaps. It assumes someone is managing the set, even though no one has that authority.

The portfolio’s language creates a governance assumption that the structure does not support.

This is how organisations find themselves with twenty innovation initiatives and no strategic options. Activity is high. The slide looks full. But nothing in the collection is constructed to deliver portfolio-level returns, because no one is managing it at that level.

What a Portfolio Actually Means

A portfolio is a deliberately constructed set of strategic options, scoped by mandate, composed across instruments, governed as a whole, measured against return, and connected to strategy.

A portfolio you never rebalance is just a list you approved. And collections do not compound.

References & Further Reading

Si, H., Kavadias, S. and Loch, C. (2022) ‘Managing Innovation Portfolios: From Project Selection to Portfolio Design’, Production and Operations Management.
Available at: https://onlinelibrary.wiley.com/doi/10.1111/poms.13860

Boston Consulting Group (2024). Innovation Systems Need a Reboot: The 2024 Most Innovative Companies Report.
Available at: https://www.bcg.com/publications/2024/innovation-systems-need-a-reboot

McKinsey & Company (2025) ‘Investing in Innovation: Three Ways to Do More with Less’, McKinsey Global Survey on Innovation.
Available at: https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/investing-in-innovation-three-ways-to-do-more-with-less

This article is based on the author's professional experience and interpretation of publicly available information. It is provided for general informational purposes only and does not constitute advice. Any views expressed are the author's own and do not refer to any specific organisation, program, or individual.

This is Issue 9 of Put Ideas To Work, a biweekly newsletter currently discussing corporate venturing under constraint. If this issue was useful, consider sharing it with someone who manages an innovation function. The diagnostic works best when it prompts a conversation, not just a self-assessment.

Issue 8 explored stop authority and why corporate pilots rarely get killed. Issue 9 extends that logic to the portfolio level: stop authority is necessary but insufficient if no one has authority over the set.

The ecosystem’s capital stack was thin, its infrastructure underdeveloped, and its policy support inconsistent. If you wanted to build a large technology company, the common wisdom was that you would eventually need to go offshore.

But over the past eighteen months, a series of seemingly unrelated developments suggests something more structural may be happening.

Australia’s innovation ecosystem is quietly rewiring itself.

Not through a single policy announcement or a blockbuster funding round, but through a gradual expansion of the institutions, capital sources, and infrastructure that support innovation.

Individually, these developments appear to be incremental progress. Taken together, they point toward a more mature ecosystem emerging.

The capital stack is expanding.

Historically, venture capital has carried a large segment of the burden of startup financing in Australia. In doing so, it created a structural weakness. When venture markets slowed, as they did through 2022 and 2023, the ecosystem slowed with them.

Now new layers of capital are beginning to appear.

International venture debt and private credit providers are increasingly targeting Australian technology companies, offering non-dilutive financing to startups that have already demonstrated revenue traction. HSBC launched a dedicated venture debt offering in Australia in late 2023, initially allocating A$228 million to loans of A$10 million to A$30 million to late-stage venture-backed companies.¹ In August 2025, the bank expanded this with the launch of HSBC Innovation Banking in Australia, which HSBC described as the first specialised banking offering in the country dedicated to venture-backed businesses.²

More significantly, in March 2026, Silicon Valley growth lender Partners for Growth announced a new, later-stage technology private credit strategy with commitments exceeding A$250 million.³ The PFG Income Fund provides growth debt, asset-backed financing, and structured credit to later-stage Australian technology-enabled businesses, fintechs, and alternative lenders. Partners for Growth has operated in Australia since 2007 and has backed more than 85 local companies, including Employment Hero, Koala, and Bridgit.

This is a meaningful shift. Venture debt and private credit have not traditionally been common funding instruments for Australian tech startups chasing growth capital. As Partners for Growth noted, founders are becoming more deliberate about financing as their businesses scale, and many are incorporating structured private credit to support growth while preserving ownership and business flexibility.

At the same time, universities are launching their own investment vehicles designed to fund research spinouts at the earliest stages. In February 2026, UNSW committed A$35 million to research commercialisation, including a A$25 million Pre-Seed Fund for early-stage spinouts and a A$10 million investment in High Street Ventures, an independent venture capital fund supporting companies as they grow.⁴ The University of Sydney has also launched a A$25 million spinout fund.⁵ More than half of Australia’s 43 universities now have access to an investment fund that can help commercialise academic research. This is a penetration rate that surpasses both the United States (33%) and Europe (40%).⁶

Meanwhile, governments are entering the earliest stages of risk capital through commercialisation grants and sector-focused funds. The National Reconstruction Fund has allocated A$15 billion overall, with A$1 billion directed toward priority areas including renewables, medical technology, and advanced manufacturing.⁷ The Western Australian Government recently launched a A$45 million venture capital initiative expected to leverage A$150 million in new VC funds for local startups.⁸

The result is that Australia’s startup capital stack is beginning to look less like a single pipeline and more like a layered system. Founders now have access to a variety of grants, university-backed funds, venture capital, and increasingly, venture debt rather than only venture capital.

It is a subtle change over time, but an important one.

A maturing innovation ecosystem is defined not just by the presence of capital, but also by its diversity.

Infrastructure is becoming strategic.

Another shift underway is the expanding emphasis on technological infrastructure. In the early days of the startup ecosystem, the focus was almost entirely on founders and venture funding. Infrastructure rarely entered the conversation.

That is beginning to change.

Governments are increasingly directing capital toward data centres, compute infrastructure, and advanced technology capabilities. In June 2025, Amazon Web Services announced a A$20 billion investment in Australian data centres. This is one of the largest technology investments in the nation’s history.⁹ Microsoft had previously committed A$5 billion in late 2023 to broaden its footprint to 29 centres across Sydney, Melbourne, and Canberra.¹⁰

In March 2026, the National Reconstruction Fund Corporation made a A$200 million hybrid investment in ASX-listed Macquarie Technology Group to support the development of sovereign cloud services, AI-enabled cybersecurity capability, and new sovereign data facilities.¹¹ It was the NRF’s largest single technology sector investment to date. The funding is meant to support the accelerated use of sovereign cloud and AI by Australian government agencies, the Department of Defence, the defence industry, and critical infrastructure sectors. As NRF CEO David Gall noted, the investment fits squarely within the fund’s mandate by “building the country’s digital industrial capability.”

Meanwhile, global AI firms are signalling serious interest in Australia. In late March 2026, Anthropic signed a memorandum of understanding with the Australian government and announced it was “exploring investments in data centre infrastructure and energy throughout the country.”¹² The company, which confirmed Sydney as its fourth Asia-Pacific office following openings in Tokyo, Bengaluru, and Seoul, cited Australia’s renewable energy potential and pledge to AI safety as reasons for the partnership.

These investments are frequently framed through the lens of national security or economic resilience, but they likewise play an important role in shaping the innovation ecosystem. The Clean Energy Finance Corporation estimates the Australian data centre industry will attract between A$85 billion and A$135 billion in investment over the next decade.¹³

In March 2026, the Australian Government took the next step by releasing its expectations for data centre and AI infrastructure developers as part of the National AI Plan.¹⁴ The framework specifies five expectations covering national interest, energy transition, water sustainability, skills investment, and strengthening research and innovation. Critically, it expects hyperscalers to make compute available to Australian startups wanting to create Australian AI and to partner with the local innovation ecosystem.

In other words, innovation policy is increasingly appearing less like startup support and more like industrial strategy.

This raises an important question for the ecosystem: is Australia building a platform for AI creation, or is it primarily presenting itself as an AI consumer? The answer likely depends on whether the infrastructure investments translate into meaningful access for local startups and researchers, or whether they primarily serve the regional operations of global players.

That shift mirrors developments in the United States, Europe, and parts of Asia, where governments have begun to treat advanced technology infrastructure as an important asset.

Australia appears to be moving in the same direction.

Universities are becoming venture studios.

One interesting structural shift is taking place within universities.

or decades, universities have been central to the country’s research output but peripheral to its startup ecosystem. Commercialisation pathways were often slow, fragmented, or dependent on external venture capital. The current model is beginning to evolve.

Universities are now creating venture funds, incubators, and startup studios designed specifically to transform research into companies. UNSW, which describes itself as Australia’s leading entrepreneurial university based on spinout volume, launched 25 new spinout companies in 2025 and topped the Knowledge Commercialisation Australasia Survey of Commercialisation Outcomes from Public Research Report for the fourth consecutive year. ¹⁵

Uniseed, one of the world’s oldest university venture funds, covers more than 20% of Australian universities and has established a track record of converting academic research into commercially viable ventures. In 2025, its incoming CEO, Alastair Hick, called for more streamlining of venture capital investment to accelerate dealmaking following a spurt of new funds forming in the country.¹⁶ In Victoria, the state government’s A$2 billion Breakthrough Victoria fund is partnering with universities including Deakin, La Trobe, Monash, RMIT, and Swinburne to set up dedicated commercialisation funds. ¹⁷

This reflects a broader global trend in which universities increasingly operate as entrepreneurial platforms rather than purely academic institutions.

If this trend continues, the origin point for many of Australia’s most significant startups may shift from garages and coworking spaces to research laboratories.

That could be particularly important for deep-tech sectors such as artificial intelligence, advanced materials, climate technology, and biotechnology, where the underlying intellectual property often originates in academic research.

Australia has long had world-class research institutions. The challenge has always been translating that research into commercial outcomes.

University-backed venture programs may finally start to close that gap.

Global capital is still decisive.

Although these encouraging structural changes, one constant remains: international investors still drive the largest growth rounds in Australian startups.

According to the State of Australian Startup Funding 2025 report by Cut Through Venture and Folklore Ventures, 66% of all deals in 2025 included at least one international investor, up from 57% in 2024. At Series A and beyond, offshore investor participation has become the standard rather than the exception. Global firms, including Andreessen Horowitz, Bessemer Venture Partners, and Lightspeed Venture Partners, all backed Australian-founded companies during 2025.¹⁸

The pattern continues into 2026. In March, stablecoin payments platform KAST, while not Australian-headquartered, raised US$80 million in Series A funding led by US investors QED Investors and Left Lane Capital, with participation from Peak XV Partners, HSG, and DST Global Partners.¹⁹ Founded by former Circle executive Raagulan Pathy, the Singapore-based company illustrates the wider pattern: the round valued it at US$600 million, casting it as a potential unicorn. KAST, which has scaled to more than one million users and processes nearly US$5 billion in annualised transaction volume, expects its annual revenue run rate to reach US$100 million in 2026.

Founders cited larger cheque sizes, deeper follow-on capacity, and support for global expansion as the primary reasons for seeking international capital.

This pattern is not necessarily a weakness. In many cases, global capital accelerates growth and connects companies to international markets. Australia’s major domestic venture firms, including Blackbird Ventures, Square Peg Capital, and Airtree Ventures, continue to raise significant funds and often co-invest alongside international partners. In February 2026, Square Peg completed the first close on its Fund 6 and Opportunities Fund 3, locking in A$650 million from institutional investors.²⁰

But it does highlight an ongoing challenge for the ecosystem.

Australia has become increasingly effective at producing promising startups. Australian startups raised A$5.4 billion across 390 deals in 2025, a 31% increase year-on-year and the third-largest funding year on record.²¹

The harder question is whether the ecosystem can consistently support those companies through the scale-up phase without relying on external capital.

The expanding capital stack may eventually help address that challenge, but it is still early.

The fragmentation question

The optimistic reading of these developments is that Australia is building a more mature, diversified innovation ecosystem. But there is a less comfortable interpretation: the ecosystem may be diversifying without integrating.

Consider the evidence of continued stress beneath the headline numbers. According to the State of Australian Startup Funding 2025 report, 46% of investors surveyed saw at least one portfolio company shut down during the year. 77% reported layoffs across their portfolios. Bridge rounds remained common as companies extended their runways rather than raising full-priced rounds during the recovery period.²²

These figures show the delayed effects of the 2022-2023 funding contraction. Companies that raised at elevated valuations during the boom and then struggled to grow into those valuations continued to face difficult choices throughout 2025.

More structurally, the report reveals a two-speed market. A small number of mega-rounds lifted headline totals, while median deal sizes rose partly because fewer very early-stage rounds are happening. The pre-seed and seed funding pipeline, which produces tomorrow’s Series A companies, has shown weakness for four consecutive quarters.²³

Capital is also concentrated by sector. AI-at-the-core companies commanded valuation premiums and sharper competition, while non-AI deals were priced within tighter, more disciplined bands. 15 of 25 tracked sectors saw a fall in capital raised compared to 2024.²⁴

Meanwhile, the proliferation of new capital sources, university funds, government programs, venture debt providers, and state-backed commercialisation vehicles creates coordination challenges. Uniseed’s incoming CEO, Alastair Hick, identified this directly, highlighting that syndicates are forming with multiple investors. Each brings different investment committees, decision-making procedures, and views on commercial and legal terms. The result is friction that slows dealmaking precisely when the ecosystem needs speed. ²⁵

The risk is not that any single initiative fails. It is that Australia builds multiple parallel systems, university spinout programs here, government infrastructure funds there, private credit vehicles elsewhere, without the connective tissue to move companies fluently from one stage to the next.

A diversified capital stack is valuable. A fragmented one is not.

A quiet transition

None of these developments, on their own, represents a dramatic turning point.

There has been no single moment where the Australian startup ecosystem suddenly became more mature or globally competitive.

Instead, the transformation appears to be happening through a series of incremental shifts.

New forms of capital are entering the market. Universities are becoming more entrepreneurial. Governments are investing in strategic technology infrastructure. Global companies are expanding their presence locally. According to IMARC Group, the Australian venture capital market reached US$4.5 billion in 2025 and is projected to reach US$10.3 billion by 2034, exhibiting a CAGR of 8.74%.²⁶

Taken together, these signals suggest that Australia’s innovation ecosystem may be entering a new phase.

The first phase of the ecosystem involved proving that world-class startups could emerge from Australia. The next phase may be about building the institutions, capital markets, and infrastructure required to sustain them.

If that transition succeeds, the defining characteristic of the Australian startup ecosystem will no longer be that its best companies eventually leave.

It will be so that they can scale where they started. And that would denote a significant evolution in how Australia turns ideas into work.

A final thought

The signals are there. The capital stack is broadening. Universities are stepping up. Infrastructure is becoming strategic. But whether these shifts connect into a coherent system or remain a collection of parallel initiatives is still unfolding.

So I will leave the question with you:

Notes & Sources

1. HSBC, “HSBC launches venture debt offer for Australian scaleups,” November 2023

2. HSBC, "HSBC Innovation Banking launches in Australia," August 2025

3. Partners for Growth / Australian FinTech, "Partners for Growth launches A$250m+ growth debt fund for Australian tech and fintech companies," March 2026

4. UNSW Sydney, "NSW Treasurer praises UNSW spinouts at fund launch," February 2026

5. University of Sydney, "$25m fund helps bring research from the lab to market," April 2025

6. Global Venturing, "Half of Australian universities have a spinout fund, ahead of US and Europe," August 2025

7. The Investor Standard, "Australia Startup Funding Surge, 2026 Grants and ASX Implications," February 2026

8. Inspirepreneur Magazine, "Top Venture Capital Firms in Australia 2026," March 2026

9. Australian Stock Report, "Australia's Data Centre Boom: ASX Stocks Powering the AI Revolution," December 2025

10. Microsoft, "Microsoft announces A$5 billion investment in computing capacity and capability to help Australia seize the AI era," October 2023

11. National Reconstruction Fund Corporation, "National Reconstruction Fund invests in Macquarie Technology Group to strengthen Australia's sovereign cloud and cybersecurity capabilities," March 2026

12. Australian Financial Review, "AI giant Anthropic says 'exploring' Australia data centre investments," April 2026

13. Pinsent Masons, "Australian government unveils prioritised support for 'national interest' data centres," April 2026

14. Australian Government Department of Industry, Science and Resources, "Expectations of data centres and AI infrastructure developers," March 2026

15. UNSW Sydney, “NSW Treasurer praises UNSW spinouts at fund launch,” February 2026

16. Global Venturing, "Australia needs to move faster on spinning out companies – Uniseed new head Hick," November 2025

17. Global Venturing, "Half of Australian universities have a spinout fund — ahead of US and Europe," August 2025

18. Cut Through Venture & Folklore Ventures, “State of Australian Startup Funding 2025,” February 2026

19. CoinDesk / KAST, "Stablecoin payments platform KAST raises $80 million Series A at $600 million valuation," March 2026

20. Capital Brief, "Square Peg locks in $650m as new fund vintage hits first close," February 2026

21. Cut Through Venture & Folklore Ventures, “State of Australian Startup Funding 2025,” February 2026

22. Cut Through Venture & Folklore Ventures, "State of Australian Startup Funding 2025," February 2026

23. Cut Through Venture & Folklore Ventures, “State of Australian Startup Funding 2025,” February 2026

24. Cut Through Venture & Folklore Ventures, "State of Australian Startup Funding 2025," February 2026

25. Global Venturing, “Australia needs to move faster on spinning out companies – Uniseed new head Hick,” November 2025

26. IMARC Group, "Australia Venture Capital Market Report 2025-2034

This article is based on the author's professional experience and interpretation of publicly available information. It is provided for general informational purposes only and does not constitute advice. Any views expressed are the author's own and do not refer to any specific organisation, program, or individual.

Most corporate innovation portfolios contain at least one idea, one venture, one initiative that everyone privately acknowledges is not working, but no one stops it.

Sometimes it is the quiet kind. Modestly funded, never celebrated, simply persisting. Quarter after quarter, it appears on the slide, absorbs a small allocation, and generates just enough activity to avoid the question no one wants to answer.

But there is a second variant that is harder to name and more expensive to ignore. This one is not starved of resources. It has dedicated headcount, meaningful budget, and sometimes even executive sponsorship. The team is busy. The updates are polished. And yet nothing has structurally moved. No market validation has landed. No revenue has materialised. No one has narrowed the scope or made a commitment that would actually put the initiative at risk of being tested by reality.

The resources keep flowing, not because the evidence justifies them. They continue because the commitment was made publicly. Now the sponsor’s credibility is attached to its continuation. The larger the investment, the harder it becomes to determine whether it is still warranted. This version of the zombie pilot does not appear to be neglected. It looks like conviction. That is what makes it dangerous.

Both are zombie pilots.

One starves quietly in the margin while the other feeds comfortably at the centre. Neither is alive in any meaningful operational sense. Neither is dead because no one has the authority, incentive, or structural mechanism to kill it. Together, they represent the most common and least discussed failure mode in corporate innovation governance.

The interesting question is not why these pilots fail. It is why they do not stop.

This is not a small problem. IDC’s research with Lenovo found that for every 33 proofs of concept launched across enterprise environments, only 4 reached production. The rest were not cancelled. They had not progressed. They existed in what the researchers described as a permanently provisional state, consuming budget and eroding executive confidence without ever reaching a clear resolution. That description is precise. It is also a description of a governance failure, not a technology failure.

Built to start. Not built to stop.

The obvious explanation is sunk cost. Someone invested political capital to launch the pilot, and stopping it publicly means writing off that investment. But sunk cost is a psychological explanation. It is incomplete. The deeper problem is structural.

Most innovation governance systems are designed to do one thing well … approve. It might not always be as efficient as operators would like, but of there are clear stage gates for funding. They have review boards for launch. They have sponsors who champion initiatives through internal resistance. The entire architecture is oriented around getting things started.

In Issue #7, I examined why well-resourced innovation functions still fail to produce ventures. Systems designed around activity metrics rather than execution outcomes create what amounts to “innovation theatre”. The zombie pilot is a specific expression of that same structural condition. The function can start things. It can run things. What it cannot do is stop things, because the stop authority was never built into the governance architecture.

Stop authority, the clearly assigned right to kill an initiative, is the most absent governance capability in corporate innovation. Not because leaders lack courage, but because the system was never designed to require it. There is no stage gate for cessation. No review trigger that asks “should this still exist?” No role whose explicit accountability includes recommending termination.

Multiple research programmes have identified the same gap from different angles. What researchers at RT Insights, Bain Capital Ventures, and others independently describe as an “ownership vacuum,” where the experiment has a sponsor but the outcome does not have an owner, is the structural condition that allows zombie pilots to persist. Without an owner accountable for the outcome, there is no one with the standing to recommend cessation. The vacuum is not an oversight. It is a predictable result of governance systems that were designed to launch initiatives, not to resolve them.

Without a stop authority, the default state of any initiative is continuation.

This matters because continuing is not neutral. Every zombie pilot, whether it is starving in the margin or feeding at the centre, consumes more than its line-item budget. It occupies a portfolio slot that signals “we are already doing something in that space.” It absorbs management attention, even if only the attention required to avoid deciding it. And it provides cover for the sponsor who launched it, the executive who approved it, and the team that would otherwise need redeployment.

The well-funded variant compounds this. The scale of investment creates its own justification, and the more the organisation has committed, the harder it becomes to ask whether the commitment is still warranted. At some point, the sunk cost becomes the strategy.

The zombie pilot does not survive because it is succeeding. It survives because the cost of stopping it is borne by an individual, while the cost of continuing the venture is distributed across the organisation. Stopping requires someone to raise their hand, absorb the political risk, and trigger a process that probably does not exist.

Continuing requires nothing. It is the organisational equivalent of leaving a subscription running, because cancelling it means finding the login details.

Courage is not the fix.

The implication is not “be braver about killing pilots.” That is a mindset recommendation disguised as strategy, and it misses the point entirely. If stopping required only courage, organisations with strong leaders would never have zombie pilots. They do.

The implication is that stop authority must be designed into the governance system with the same rigour as start authority. It needs to be structural, not heroic.

This means several things in practice.

1. Every pilot approved should have a pre-committed termination trigger.
   Not a vague milestone review, but a specific condition under which the default shifts from persistence to cessation. The question at review should not be “is there a reason to stop this?” It should be “has this earned the right to continue?” The burden of proof matters enormously. When continuation remains the default, evidence of failure must accumulate to an extraordinary threshold before anyone acts. When cessation is the default, even modest initiatives must periodically demonstrate that they deserve the resources they consume.

2. The stop authority must be assigned to a role rather than left to emerge.
   Someone in the governance structure needs the explicit right, and the explicit expectation, to recommend kills. Not as a punishment. Not as a failure of sponsorship. As a routine function of portfolio discipline. The absence of this role is why zombie pilots cluster. No one’s job includes the line item “identify initiatives that should no longer exist.”

3. The cost of continuation must be made visible.
   Zombie pilots persist partly because their cost is illegible. The budget line looks modest. But the portfolio slot they occupy, the strategic space they block, the opportunity cost of the team’s time, the signal they send about what the organisation tolerates. However, none of this shows on a dashboard. Making the full cost of continuation visible is a governance design choice. It does not happen by accident, and its absence is not neutral.

The deeper pattern here extends well beyond innovation portfolios.

Organisations are generally better at creating than at ceasing. They are better at launching than at landing. The muscles for initiation are well-developed. The muscles for termination are atrophied, not because of disuse, but because they were never built.

Having a stop authority is not an optional governance refinement. It is a structural prerequisite for portfolio discipline. Without it, every portfolio will accumulate drag. Not because the people are wrong, but because the system makes stopping harder than continuing.

And in any system where stopping is harder than continuing, things that should stop will not.

The Stop Authority Diagnostic

The pattern described above can be diagnosed. Pilots that persist not because they are succeeding but because stopping them is structurally harder than continuing. It does not require a transformation programme or a governance overhaul to identify. It requires five questions.

These questions are not designed to evaluate whether a specific pilot is good or bad. Rather, they are designed to assess whether your governance system has the structural capacity to stop anything.

Is a stop authority assigned?

For any active initiative or venture in the portfolio, can you name the person whose role includes the explicit authority to recommend termination?

Not the sponsor.

Not the executive who approved it.

A role with the standing to say “this should no longer exist” without that statement being read as a political act. If you cannot name that person, the stop authority is absent. It does not matter how strong your leaders are. The capability has not been built.

Where does the burden of proof sit?

When an initiative comes up for review, what is the default?

Does the team need to demonstrate that the pilot has earned continuation, or does someone need to build a case for stopping it?

If the burden of proof sits with cessation, if you need a reason to stop but not a reason to continue, the system is architecturally biased toward accumulation.

Zombie pilots are the predictable result.

Do termination triggers exist before launch?

When the pilot was approved, was there a pre-committed condition under which it would end?

Not a milestone.

Not a KPI target.

A specific observable condition: “if X has not occurred by Y, the default is termination.” If the answer is no, the pilot was launched with an open-ended claim on resources.

Every venture pursued without a termination trigger is a future zombie candidate.

Is the full cost of continuation visible?

Can you see, on a dashboard, in a review pack, anywhere, the total cost of an active pilot beyond its budget line?

The portfolio slot it occupies. The strategic space it blocks. The management attention it absorbs. The opportunity cost of the team assigned to it. If only the direct budget is visible, the cost of continuation remains illegible, and illegible costs cannot drive decisions.

When was the last kill?

Not a pivot. Not a “strategic redirection.” Not a quiet de-funding that let something expire without anyone acknowledging what happened.

An explicit, deliberate decision to stop an initiative and communicate that decision as a governance outcome. If you cannot point to one in the past twelve months, the stop muscle has not been exercised. It may not exist.

Understanding the pattern

These five questions do not produce a score, but rather they produce a structural picture.

If you answered “no” to three or more, your governance system lacks functional stop authority. You have a system that can start things, but cannot stop them. Your portfolio will accumulate drag, not because of bad judgement, but because the architecture makes continuation the path of least resistance.

Each gap the diagnostic reveals maps to a specific governance design choice: assigning the authority, shifting the burden, pre-committing the trigger, or surfacing the cost. These are not cultural goals. They are built decisions.

The fix is not about becoming more “ruthless” or “disciplined” in the abstract. It is about building the specific governance capabilities that make stopping as operationally routine as starting.

The muscles that were never built

Zombie pilots are a symptom of a bigger issue. Organisations have spent decades improving the architecture of initiation with stage gates, investment committees, innovation sprints, accelerator programmes and even venture boards. The infrastructure for starting things is sophisticated, well-resourced, and culturally celebrated. However, the infrastructure for stopping things barely exists.

This asymmetry is not limited to innovation portfolios. It appears in product lines that no longer serve the strategy. In committees that outlived their purpose. In reporting structures that persist because no one has the standing to dissolve them. The inability to cease is an organisational condition, and innovation portfolios are where it becomes most visible, because the gap between activity and value is hardest to ignore.

Scott Kirsner observed in Harvard Business Review that when a CEO reveals a major innovation initiative, you should mark your calendar. Three years later, many of these ventures will have quietly expired without an obituary. That quiet expiry is the zombie pilot’s final form. Not a dramatic failure. Not an explicit decision. Just a slow fade that no one is accountable for, because the system never assigned accountability for cessation in the first place.

I have written separately about how this pattern is playing out across Australia’s government, enterprise, and venture portfolios, where audit bodies and digital transformation agencies have documented the same structural failure for years.

The language varies, including “Pilotitis” or “Pilot purgatory.” The underlying condition is identical, that systems that can start things but cannot force a scale-or-stop decision once a pilot has done the job it was meant to do.

Execution discipline is not only about doing things well. It is about stopping things cleanly.

When stopping an initiative is structurally harder than persisting with it, the portfolio does not have a performance problem. It has a governance problem.

References & Further Reading

• IDC, research undertaken in partnership with Lenovo, CIO Playbook 2025: 88% of AI proofs of concept fail to reach production. https://www.cio.com/article/3850763/88-of-ai-pilots-fail-to-reach-production-but-thats-not-all-on-it.html

• Scott Kirsner, The Stage Where Most Innovation Projects Fail, Harvard Business Review, 2017. https://hbr.org/2017/04/the-stage-where-most-innovation-projects-fail

• SoftwareSeni, The Enterprise AI Pilot Purgatory Problem: What the Statistics Actually Tell Us, 2026. Synthesises research from IDC, MIT NANDA, McKinsey, BCG, RT Insights, Bain Capital Ventures, and others on the “ownership vacuum” pattern. https://www.softwareseni.com/the-enterprise-ai-pilot-purgatory-problem-what-the-statistics-actually-tell-us/

• The Venture Operator, Observation: Australia’s Zombie Pilot Problem, Put Ideas To Work, 2026. https://www.putideastowork.com/p/observation-australias-zombie-pilot

• The Venture Operator, Issue 07: When Nothing Changes, Put Ideas To Work, 2026. https://www.putideastowork.com/p/when-nothing-changes

This article is based on the author's professional experience and interpretation of publicly available information. It is provided for general informational purposes only and does not constitute advice. Any views expressed are the author's own and do not refer to any specific organisation, program, or individual.

This is Issue 08 of Put Ideas To Work. It builds on the structural patterns explored in Issue 07: When Nothing Changes, which examined why well-resourced innovation functions still fail to produce ventures. If the Stop Authority Diagnostic is useful, share it with someone who runs a portfolio review. It takes five minutes and the pattern will be obvious. And if you are not yet subscribed, Put Ideas To Work publishes biweekly. Each issue builds a diagnostic framework for venture execution under constraint.

Six weeks later, nothing has structurally changed.

No capital moved. No initiative received dedicated resourcing. No decision rights shifted. The teams are still operating on the same budgets, with the same headcount, inside the same reporting lines.

The showcase was a success. The innovation program is active, but nothing has happened to change the trajectory of a single venture within the organisation.

This is not a failure of effort or intent. It is a structural condition. It is innovation theatre.

Activity without consequence

Innovation theatre occurs when innovation functions are designed around activity metrics rather than execution outcomes.

The activity is real. Ideas are generated, workshops are held, pilots are built, and teams prepare status updates on schedule. But the structural indicators of execution remain unchanged.

No additional capital has been reallocated, authority and decision rights have not shifted, and scope has not narrowed. In summary, nothing has stopped or significantly changed to double down on the bets made.

The innovation function exists inside the organisation’s communication layer, presentations, updates, reports, showcases, but outside its decision layer. It does not influence how budgets are constructed, how resources are deployed, or how strategic priorities are adjusted.

Steve Blank identified this pattern in Harvard Business Review in 2019, describing how organisations adopt innovation activities, hackathons, workshops, and design sprints, that produce the appearance of innovation without its structural consequences. He distinguished between organisational theatre, innovation theatre, and process theatre. What he named as a behavioural tendency is, more precisely, a governance design problem. The activities are real. The structural authority to act on what they produce is not.

This creates a peculiar dynamic. The function appears healthy on the surface. Internally, the teams running initiatives often sense that something is missing, but struggle to articulate exactly what.

What is missing is execution authority.

Innovation without execution authority is not a program, nor a priority. It is a marketing newsletter.

Why does the system reward appearance?

Innovation mandates are often issued by leadership but not structurally empowered. A CEO or board declares that innovation is a strategic priority. This leads to the formation of a team or teams and the issuance of mandates, but the organisation’s decision architecture does not change to accommodate it.

The innovation operation receives permission to explore, but not the authority to execute. It can generate ideas, run experiments, and build prototypes. But it cannot reallocate capital, reassign talent, narrow the portfolio, or stop initiatives that are not working.

This is not a personality problem. It is an incentive and governance design problem.

Innovation teams are typically measured on:

• Number of ideas generated or submitted.

• Number of workshops and hackathons were conducted.

• Pilots launched, or partners engaged.

• Presentations delivered to leadership.

• Internal participation and engagement rates.

• Progress is reported as stakeholder alignment, strategic conversations, or engagement quality, measures that are difficult to challenge precisely because they are difficult to define.

These are activity metrics that measure the function’s performance, not the performance of the ventures it pursues.

Execution metrics look different and operate on two levels. The first level measures whether the system has reorganised. Whether signals actually changed how the organisation behaves:

• Capital reallocated based on evidence.

• Initiatives stopped when signals decayed.

• Decision rights assigned to venture leads.

• Resources concentrated on compounding signals.

• Scope narrowed as conviction increased.

The second level measures whether that reorganisation produced results:

• Ventures that generated measurable commercial outcomes, revenue, customers acquired, contracts signed, or return on invested capital.

• Time from validated signal to resourced commitment, the speed at which the system converts evidence into structural action.

Most innovation functions track neither level. Some may track the first without the second, which creates structural movement without accountability for outcomes. The combination is what matters; did the system reorganise, and did that reorganisation produce a venture, regardless of whether the method used was build, invest or partner, worth the resources it consumed?

In most corporate innovation functions, no one is measured on either. And what is not measured is rarely prioritised.

The result is a system that rewards the appearance of innovation without requiring its structural consequences or its commercial outcomes.

A Structural Disconnect

There is a pattern I have seen repeated across large organisations, in financial services, resources, government-linked enterprises, and increasingly inside universities, establishing venture mandates.

An innovation team identifies a genuine opportunity with promising signals identified early. The team is motivated, and the work is credible. But when the initiative reaches the point where it needs structural support, dedicated capital, decision authority, and talent reallocation, the organisation does not respond.

Not because leadership disagrees or the evidence is weak, but because the system is not designed to convert innovation signals into structural decisions when consequences start to matter, to the executive sponsors and the organisation broadly.

The triple mandate.

Corporate innovation functions are often expected to operate across multiple roles simultaneously. In a startup ecosystem, these functions are typically separated: capital allocators decide where funding flows, venture builders build ventures, and operators execute under uncertainty. Within a corporate innovation function, one team often handles all three. They allocate “budgetted” capital across a portfolio of initiatives, build internal experiments/ventures, and are expected to deliver execution discipline that turns signals into structural commitment.

That triple mandate creates a specific governance tension. When the same team is responsible for funding decisions (within a stated risk tolerance), exploration venture creation, and execution oversight, the execution layer almost always suffers. It is the least visible of the three roles and the least rewarded. Capital allocation decisions get board attention. New ventures get showcased. Execution discipline, narrowing scope, stopping initiatives, and reallocating resources happen quietly, if at all.

Given the matrixed structure of most large organisations, this problem compounds. Even where innovation teams have capable people and clear intent, the decisions required to convert a validated signal into a resourced venture do not rest solely within the innovation function. They are distributed across the organisation.

Capital reallocation requires finance and strategic planning approval. Governance sign-off involves a separate committee with its own cadence and risk appetite. Legal review follows its own timeline. Risk assessment introduces additional conditions. Procurement, if an external partner or vendor is involved, adds another layer. Each of these functions operates with different incentives, different timelines, and critically, no shared accountability for venture outcomes.

The innovation team may have identified the signal, built the business case, and demonstrated early traction. But the decisions required to act on that evidence are scattered across five or six organisational functions, none of which are measured on whether the venture succeeds. Each can slow or stop progress, as none has the mandate to accelerate it.

This is not bureaucracy for its own sake. These functions exist for legitimate reasons: risk management, capital stewardship, and legal compliance. The problem is that they were designed to govern established business operations, not to coordinate around new-venture timelines for unexpected, uncertain opportunities where speed and evidence-based resource allocation are critical.

Budget cycles are annual, and headcount is planned and allocated twelve months in advance. Governance committees meet quarterly, and legal review queues are measured in weeks. The venture’s signal is compounding now.

By the time the system responds, the window may have narrowed or closed.

And so the innovation team continues to operate in the margin. It can run experiments. It can present results. But it cannot trigger the structural changes that would turn a promising initiative into a funded venture with execution authority, because those changes require coordination across functions that were never designed to move at venture speed.

This is the structural disconnect at the heart of innovation theatre. The front end of innovation, ideation, exploration, and experimentation, is well resourced and largely contained within the innovation function. The back end, commitment, resource movement, and governance escalation are fragmented across the organisation, operating on fundamentally different rhythms.

The evidence supports this. McKinsey has reported that nearly two-thirds of organisations remain stuck in pilot mode, unable to scale projects across the enterprise. The framing is often about technology adoption or digital transformation. Still, the structural pattern is identical: organisations that are effective at launching experiments but are unable to convert them into scaled execution. The bottleneck is not the front end. It is the transition from exploration to structural commitment, a transition that requires organisational coordination, which the system was not built to handle.

The front end of corporate innovation is well built and largely self-contained. The back end, where signals become structural commitment, is fragmented across the organisation. That is where ventures stall.

The Quiet Cost

Innovation theatre does not produce dramatic failures. That is part of why it persists.

There is no crisis point, no public failure, no sudden loss. The function continues, and updates are positive. Activity is sustained, and from the outside, everything appears functional. The cost is quieter and cumulative.

BCG’s 2024 Most Innovative Companies report quantified this gap. Eighty-three per cent of senior executives now rank innovation among their top three priorities. Yet only 3 per cent of companies qualified as innovation-ready, a sharp decline from 20 per cent just 2 years earlier. The aspiration has been rising, but the ability to execute has been falling. A lack of ideas or investment does not explain that divergence. It is explained by the structural gap between innovation activity and the authority to execute.

Talent attrition is the earliest signal. High-capability operators inside innovation teams eventually recognise the structural ceiling. They leave, not because they are disengaged, but because they have learned that the system will not convert their work into execution. The organisation loses its most execution-oriented people first.

Organisational credibility erodes next. When successive cohorts of initiatives fail to produce structural outcomes, leadership begins to question the function’s value. External credibility follows. Startup founders and partners who engage with corporate venturing functions learn quickly which organisations have execution authority and which are performing the function without it. In ecosystems like Australia, where the corporate innovation community is relatively concentrated, this reputation moves fast.

The cumulative cost is not the money spent on the function. It is the ventures that were not built, the talent that left, and the organisational patience that is consumed without producing structural change.

From Communications to Execution

The shift is not about running fewer initiatives or generating fewer ideas. Exploration has genuine value. The shift is about what the organisation measures and what authority the innovation function holds.

The diagnostic question is simple:

What capital, authority, or resources moved because of this initiative?

If the answer is nothing, the function produced content, not execution. The initiative may have generated learning, relationships, or internal visibility. Those are not worthless, but they are not venture creation.

For corporate innovation functions to produce ventures rather than activity, three conditions need to be present:

Execution authority must exist within the function. Someone within the innovation function must be able to recommend capital reallocation, talent movement, or scope narrowing. That recommendation must connect to a decision-maker who can act on it within the venture’s timeline, not the organisation’s planning cycle.

Measurement must shift from activity to structural consequence. If the function is measured by how many ideas it generates, it will generate ideas. If it is measured by how many initiatives received dedicated resources, had their scope narrowed, or were stopped based on evidence, it will produce execution discipline.

The stop authority must be safe. Innovation theatre persists partly because stopping is politically expensive. Ending a pilot, deprioritising an initiative, or narrowing the portfolio creates visibility. If that visibility is punished rather than rewarded, the rational response is to continue everything. The system must make stopping as structurally safe as starting.

Let’s Execute

This is not a strategy exercise. It is a structural audit you can run this week.

Answer these five questions about your innovation function. Answer them honestly, not optimistically.

1. Does anyone inside the innovation function have the authority to recommend resource reallocation?

Not in theory. In practice. Has it happened in the last twelve months? If the answer is no, the function operates inside the communication layer, not the decision layer.

2. When was the last time an initiative was stopped based on evidence?

Not paused. Not “deprioritised.” Stopped. If nothing has been stopped, the function lacks kill discipline. Every active initiative is consuming resources that could be concentrated on stronger signals.

3. What changed structurally after your last showcase or review?

Did capital move? Did headcount shift? Did decision rights change? If the answer to all three is no, the review is a communication event, not a decision event.

4. How is the innovation function measured?

List the metrics. Separate them into two categories: activity metrics (ideas generated, workshops held, pilots launched) and execution metrics (capital reallocated, initiatives stopped, resources concentrated). Count each column. The ratio tells you what the function is designed to produce.

5. If your strongest initiative needed dedicated resources next month, could the system deliver them?

Not next budget cycle. Next month. If the answer is no, the organisation’s resource clock runs on a fundamentally different cadence from its venture clock. That mismatch is where promising initiatives stall.

If three or more of these answers reveal structural gaps, the function is not yet designed to produce ventures. It is designed to produce activity.

That is not a judgement of the people running it. It is a description of the system they operate within.

A Closing Thought

Corporate innovation functions inside large organisations are often staffed by capable people doing credible work under significant constraints. The problem is rarely effort, intent, or even the quality of ideas.

The problem is that the system around them was not designed to convert their work into structural change.

Execution authority is not a reward for proving yourself. It is a precondition for the production of ventures. Without it, even the strongest signals remain observations rather than decisions.

Ideas do not scale. Execution does. And execution begins when something in the structure actually moves.

What’s coming next? Execution authority is one structural gap. But even when functions have some authority, individual initiatives can persist long past the point where signals justify continuation. The next issue examines the most common expression of this: the corporate pilot that cannot die. Not because it is succeeding, but because stopping it is structurally harder than continuing.

This article draws on patterns observed across corporate venturing and innovation functions, startups, venture studios, and university commercialisation environments. Individual context matters.

For example, imagine a seed-stage SaaS startup. Growth has been uneven for months; churn is unpredictable, and the team is trying out several acquisition channels at once. The product roadmap remains broad to keep options open.

Then things start to change. One customer segment renews at much higher rates. Expansion revenue shows up without much extra effort. Support tickets from this group drop while their engagement goes up.

It is not a dramatic shift, but it is steady. The signal is clear.

The temptation is to notice the signal but keep running all current projects, hold onto every option, hedge your bets, and keep experimenting in parallel. But a signal only counts if it leads to action, like narrowing your focus, moving capital, or shifting your team’s attention.

• Low-performing acquisition experiments are shut down.

• Product capacity is concentrated around this segment.

• Marketing spend is redirected.

• Other feature bets are paused.

Making a commitment raises your exposure and changes how you handle risk.

This applies both when you are deciding whether to commit resources based on market signals and when you are following through on that commitment.

The tougher question comes next: If making commitments in uncertain times is the real work, who’s responsible for making sure it’s done well?

Signals Do Not Execute Themselves

Signals are open to interpretation, but execution depends on the structure.

• A customer cohort responds.

• Retention stabilises.

• Unit economics improves.

These are just inputs; they do not automatically reorganise teams, change budgets, or clarify who’s in charge. Many early-stage startups and innovation teams think that once something is validated, disciplined execution will just follow.

But that is not the case.

The market can change, but systems will not adapt unless someone actively reconfigures them.

If you do not reorganise your structure, commitment just becomes a story you tell, which leads to drift over time.

Signals do not turn into action on their own. Systems make execution happen.

Venture Operator as a Function

The Venture Operator is not just a job title. It’s about having someone accountable for structure when exposure grows faster than certainty in how capital is allocated. This role is responsible for making the necessary changes.

This responsibility might fall to a founder, a venture lead, a general manager, a board member, or a capital partner. When it’s clearly defined, escalation is straightforward. When it is missing, things get more ambiguous.

This role exists to turn a signal into real action:

• What narrows?

• What stops?

• What moves?

• Who decides?

• When is it reviewed again?

Without decision authority, this function becomes mere coordination.
Without a “stop” authority, it defaults to optimism.
Without capital reallocation power, it is reduced to an advisory role.

This is not just general management. It comes into play at key turning points, when spending goes up before you have certainty. Discipline won’t remove uncertainty, but it makes sure you deal with it on purpose.

With this structure, commitment turns into real action. Without it, commitment is just for how.

Commitment Lacking Re-organisation

Commitment increases burn against uncertainty. Exposure rises immediately, whether the system changes or not. The risk is not that commitment is wrong. The real risk is that you start spending faster, but your structure is still set up to keep all options open.

That is when dilution starts, not equity dilution, but structural dilution. This means your capital gets spread out, and decision-making becomes less clear. In short, you start to drift.

Drift usually is not caused by bad signals. It happens because structural changes are too slow.

• Scope stays broad.

• Resources remain spread thin.

• Decision rights remain unclear.

• Governance remains informal.

• Cadence is inconsistent.

• And capital moves faster than structure.

In this setup, good news can make you overconfident, while bad news makes you defensive. Neither leads to disciplined changes. Reorganising is the price you pay for making a commitment.

If you do not tighten your structure, your conviction is just for show.

The Cost of Over-Optionality

Keeping your options open is often seen as smart, especially early in the process. But too much optionality just makes things more complicated.

• Every active initiative increases coordination cost.

• Every preserved option dilutes signal precision.

• Every deferred decision slows capital movement.

Optionality can make you feel comfortable, but it rarely guarantees results. In environments where capital is tight, too much optionality is costly. It spreads your resources thin, muddies accountability, and slows down changes needed.

Focusing on your efforts is not about being aggressive, it is about being disciplined.

Incentive Asymmetry

Structural fragility is usually not an accident. In many systems, it feels easier to let things drift than to make changes. People fear losing status, being blamed, or admitting something isn’t working, and these emotions create strong barriers. Leaders often avoid tough decisions, hoping new evidence will appear and save them from the discomfort of making a visible stop or reallocation. The system keeps moving, not because the evidence is unclear, but because changing direction feels emotionally costly.

• Stopping creates visibility.

• Narrowing the scope creates risk.

• Reallocating capital creates political exposure.

• Ending an initiative creates reputational friction.

• Continuation appears safer.

This imbalance explains why it’s rare for someone to have the authority to stop things, and why optionality lasts longer than it should. Mature governance solves this by making disciplined changes safer than letting things drift.

Capital Depth Changes Consequence

Structural discipline matters in any venture environment. It cannot make up for a weak market, but it does prevent avoidable structural fragility.

The amount of capital you have affects the outcome.

In ecosystems with plenty of late-stage capital, inefficiency can be absorbed. Optionality can last longer. Governance immaturity can survive for a few more quarters.

Australia has less follow-on capital despite its ambition. The domestic market is smaller, with tighter error margins and stronger signaling effects. When startups face a big change in capital, like FinTechs relying on international funding that suddenly dries up, their cash runway shrinks fast, forcing a year’s planned growth into just a few months. In these conditions, missing even one milestone can mean the difference between recalibrating and shutting down.

In this environment, letting things drift burn through your runway even faster.

Structural discipline doesn’t guarantee success, but without it, capital-constrained systems will always be fragile. This isn’t just an opinion; it’s a fact about how capital works.

When there’s less follow-on capital than ambition, your ability to adapt quickly becomes a key advantage.

Structural Discipline at Inflection

Inflection points are rarely dramatic. Usually, there are quiet shifts as evidence builds up.

• Retention stabilises.

• CAC improves.

• Pipeline quality sharpens.

• Sales cycles compress and so on.

Just interpreting signals does not drive change. Structural discipline at inflection needs five things:

1. Clear signal ownership

2. Defined decision rights

3. Visible resource movement

4. Explicit stop authority

5. Fixed cadence for evidence interpretation

Without these, an inflection point turns into a discussion instead of a decision.

What Must Exist for Productive Execution

Disciplined execution depends on the structure. It shapes how capital and authority move, and how teams behave. Clear structure sets the culture for decisiveness, transparency, and accountability. Over time, these habits define the team’s identity. As discipline grows, confidence and clarity spread. When structure and culture align, results and progress come faster, making disciplined execution a shared standard.

At inflection points, five conditions need to be in place.

1. Clear Signal Ownership

• Who defines the threshold?

• Who declares it crossed?

• Who initiates escalation?

• If ownership is collective, exposure is diffused.

2. Defined Decision Rights

• Who can narrow the scope immediately?

• Who can reallocate capital inside the cycle?

• Who can override sunk cost logic?

• Governance maturity is decision clarity under pressure.

3. Visible Resource Movement

Conviction must concentrate capital and talent.

• If budget lines don’t change in the next allocation window, conviction is just talk.

• If headcount doesn’t shift, optionality still dominates.

• Moving resources is proof of real structural change.

4. Explicit Stop Authority

Stopping is structurally harder than starting.

• Who can terminate?

• What threshold triggers review?

• How quickly are resources reclaimed?

If stopping something requires political bargaining, governance isn’t mature yet.

5. Fixed Cadence for Evidence Interpretation

Ad hoc interpretation favours narrative. Disciplined systems establish cadence:

• Weekly evidence review.

• Monthly capital checkpoint.

• Quarterly scope revalidation.

Cadence reduces bias, while irregular interpretation amplifies it. Evidence without cadence becomes opinion.

Let’s Execute

If commitment has been declared, the structure must already reflect it.
Answer these without narrative.

Signal

• Who owns the conviction signal?

• What threshold defines continuation?

• When was it last formally reviewed?

Authority

• Who can narrow the scope without consensus?

• Who can reallocate the budget immediately?

• Who can stop this?

Capital

• What stopped when conviction increased?

• Which budget line lost funding?

• Which initiative was deprioritised?

Cadence

• Is evidence interpreted on a fixed rhythm?

• Or only when tension rises?

If these answers are unclear, commitment increases risk without increasing discipline. Execution is not just effort; it is reconfigured under uncertainty.

Governance Maturity

Many early-stage founders resist the word governance. It sounds like a process.

It sounds like oversight. It sounds like something that slows innovation and gets in the way of the “scrappy” approach many founders want to be.

Early on, informality is an advantage, enabling faster decisions, flexible scoring, and concentrated authority. This flexibility is a strength, but inflection points change the equation. As burn increases, headcount grows, outside capital comes in, and conviction deepens; exposure goes up. The informality that once made things fast can start to hide risk.

Governance maturity is not bureaucracy. It is exposure management.

It answers a simple question: As risk goes up, does clarity go up too?

Mature governance:

• Tightens decision rights as exposure increases

• Aligns capital deployment with evidence density

• Protects the stop authority from politics

• Narrowing the scope as conviction strengthens

It does not slow down innovation. It keeps innovation from drifting, of course.

It does not reduce ambition. It makes sure ambition is funded intentionally.

Structural discipline cannot compensate for a weak market.

But it does help prevent avoidable structural problems.

In capital-constrained places like Australia, this matters even more. There is less follow-on capital; error margins are tighter, missed signals compound faster, and there are fewer ways to recover.

In this context, mature governance gives you an even bigger advantage. It increases reconfiguration speed.

• It reduces capital waste.

• It sharpens decision clarity under pressure.

Where authority remains ambiguous, inflection dissolves into committee.

Where stop authority is politically unsafe, optionality persists past its value. Governance maturity isn’t about adding more processes. It ensures that as exposure increases, the system becomes more precise, not more scattered. In thin capital environments, that precision isn’t just for show. It’s protective.

A Closing Thought

Scale does not fix weak structure; it makes it worse. Structural discipline cannot make up for a weak market, but it does prevent avoidable fragility.

Committing when things are uncertain increases your exposure, which means you need to reconfigure.

In ecosystems with little follow-on capital, the cost of being imprecise compounds quickly. In a capital-constrained environment, scale doesn’t reward enthusiasm; it rewards structural discipline.

Disclaimer

This article reflects general observations drawn from venture and operating environments. It is provided for informational purposes only and does not constitute legal, financial, or investment advice. Any application should be considered in light of your specific circumstances.

This is where many ventures lose momentum.

Signal identification is essential.
But it is not the end.

Effective early stage venture building relies on distinguishing real signals from noise. This discipline is critical as pursuing the wrong signals misdirects resources. More critically, not making a decision and chasing every signal concurrently will fragment focus and exhaust a venture’s limited capacity.

Strong venture builders will test early, disprove quickly, and use evidence to narrow the options in front of them.

But it is after the signal are validated that breakdowns will occur as escalation or prioritisation is deferred to preserve flexibility, because “everything is important” or “we are still not certain.”

This will shift optionality from being an asset to a liability.

When optionality because structural risk.

Options are valuable early, permitting rapid learning and low-cost course correction.

Beyond a certain point, however, preserving options becomes a substitute for making a decision. Teams focus on keeping paths open rather than advancing decisively in one direction.

This may seem familiar:

• “We need slightly more data.”

• “It may be too early to escalate.”

• “Let’s sustain parallel paths for now.”

Individually, these positions are reasonable. Collectively, they create an environment in which retaining the status quo feels safer than committing.

The compounding cost of delay.

Delay consumes optionality rather than preserving it, particularly as signals lose strategic value faster than most organisations assume.

When commitment is deferred, consequences accumulate:

• Opportunity windows narrow as markets, partners, and competitors move.

• Strategic alternatives degrade as attention is divided.

• High-calibre talent disengages in the absence of directional clarity.

• Capital continues to burn without proportionate return, eroding confidence.

• Decision debt accumulates, making future escalation heavier and slower.

These costs are rarely confined to a single startup, venture or initiative.

If action is delayed too long, ventures do not just miss opportunities but also weaken the capital, talent, and conviction required for decisive action.

Translation requires decision exposure

Turning a signal into a strategy requires action, not just analysis.

A signal matters only when it produces decisions that change behaviour. In practice, those shifts should be visible:

• Scope narrows.

• Capital is reallocated.

• Talent is added, redeployed, or removed.

If these changes do not occur, the signal has been observed but not absorbed.

Many ventures stall at this point; the analysis is sound, the deck is coherent, and the evidence is defensible. But the system is not designed to internalise the consequences of commitment, making strategy just documentation rather than direction.

Why this pattern persists.

This failure rarely stems from weak thinking or poor intent.

Often it is reinforced by structural conditions, such as:

• Incentive structures that reward preservation instead of resolution.

• Diffuse accountability for escalation.

• Unclear decision rights.

• Execution capability is assumed rather than deliberately built.

In environments like these, optionality is not simply preferred; it is safer.

And so ventures drift, not because they lack insight, but because commitment is culturally and structurally harder than continuation

Let’s execute, even if under partial certainty.

Decision then subsequent execution does not require full certainty. Nor should it be expected to. It requires directional commitment based on a sufficient signal.

Disciplined translation from signal to action involves:

1. Clearly articulating the signal
   What has changed and why it matters now?

2. Explicitly narrowing the field
   Strategy is defined as much by exclusion as by pursuit.

3. Forcing a near-term commitment
   Time-box the decision and make it visible.

4. Realigning resources immediately
   Capital and talent must reflect the chosen direction.

5. Maintaining reversibility without tolerating drift
   Direction can change, but indecision cannot persist.

Discomfort at this stage is not a warning, nor a negative.
It is evidence that translation is occurring.

The operating gap.

At this stage, a deeper pattern emerges. Ventures stall not only because signals are absent, but because accountability for translating validated signals into execution remains unclear.

Recognition occurs.

Discussion expands.

Commitment diffuses.

This is not primarily a strategic deficiency; it is an operating gap.

Addressing that gap does not always require a new title or structure. It does need explicit ownership.

In strong founding teams, one person typically assumes responsibility for narrowing options and driving commitment.In others, defined mechanisms, clear escalation triggers, decision rights, and resource alignment rules exist.

Where neither exists, discussion proliferates and execution fragments. Momentum slows not from lack of insight, but from lack of disciplined translation.

The gap between signal and structured commitment is often a more significant contributor to venture stagnation than weak ideas alone.

A closing thought.

The ability to recognise signals is table stakes. But the ability to act on them, consistently, visibly, and under uncertainty is what differentiates ventures that compound traction from those that stall.

That distinction is not conceptual. It is operational.

What is coming next? In the final issue of this series, we will deal with the implications directly. If commitment in conditions of uncertainty is the real work, who is accountable for operating it well?

Disclaimer

This article reflects general observations drawn from venture and operating environments. It is provided for informational purposes only and does not constitute legal, financial, or investment advice. Any application should be considered in light of your specific circumstances.

Pilots do not fail. They linger.

They generate activity, updates and learning decks, similar to any corporate project, long after learning has stopped compounding. A pilot continues to receive funding (to a point), remains staffed, and is regularly reported on, yet it never quite crosses the threshold into real operational commitment. The point where experimentation stops and implementation starts.

This is frequently framed as an innovation problem. But it is not.

What Australia is experiencing, across government, enterprise, and venture portfolio, is a decision failure. Specifically, a failure to force scale-or-stop decisions once a pilot has done the job it was meant to do.

That is why expressions such as “pilotitis” and “pilot purgatory” are no longer simply hallway language. They are explicitly named in Australian contexts because the pattern is persistent and recognisable.

When a pattern gets a name, it is already widespread.

Australian enterprise and technology commentary has increasingly used the term “pilot purgatory” to describe promising proofs of concept that never graduate to implementation. This does not refer to experiments that collapse or receive a timely stop decision when hypotheses are disproved through rigour. This refers to experiments that continue, as no one ever defines what “good enough to scale” actually means. Experiments that have no entry criteria, no exit criteria and no moment when continuation has to be actively re-earned.

Australia’s Digital Transformation Agency used the term “pilotitis” in the context of AI and digital government, referring to initiatives that demonstrate feasibility but stall before wider implementation and adoption.

When a central digital authority adopts this language, it signals that the issue is not about capability or creativity; it is about how decisions are structured.

The audit trail tells the same story.

Australia’s audit bodies have been documenting this failure mode for years. The Australian National Audit Office has been clear about the purpose of pilots: they exist to inform adoption decisions. Monitoring and evaluation are not box-ticking exercises; they are meant to support judgments about impact, efficiency, and whether something should scale, change, or stop.

Yet the recurring finding is that evaluation is often not designed to force a decision.

Performance reporting focuses on activity rather than effect. This means the reporting is focused on reporting outputs and the tracking of milestones. However, outcomes are not framed in a way that compels a material commitment or a clean stop.

The same theme appears again in audits of performance statements across major government entities, where reporting describes what was done rather than what was achieved in terms that would justify scaling. Or even the inverse: a quick, efficient stop decision. Both are valuable.

At the state level, the NSW Audit Office has identified similar issues, particularly the lack of effective planning to scale successful pilots. When scale is not planned for, pilots do not fail. They simply remain pilots.

How zombie pilots are created

It is this environment where zombie pilots thrive:

• Enough activity to look legitimate

• Enough ambiguity to avoid hard calls

• Enough sunk cost to make stopping uncomfortable

As a result, effort stays high, but learning plateaus and continuation get quietly re-approved. This is not because the case is strong, but because stopping carries consequences that someone has to own up to.

But you can also usually tell a zombie pilot by how it is talked about.

Often, the update is jam-packed, full of activity, and increases over time, and the team is always engaged and ready for the next iteration of the experiment. But when someone asks the simple question -

“So are we actually committing to this?” 

the room goes quiet. Not because people do not care, but because no one is quite sure who is meant to answer. That pause is the tell. The pilot is not blocked by technology or talent. It is blocked by ownership.

This is not a flaw in the people involved. It is a predictable outcome of systems in which decision rights are diffuse and risk is asymmetric.

AI did not create this problem. It exposed it.

AI has become the most effective stress test of these decision systems, as pilots are being launched faster than governance frameworks can absorb them. They touch regulated data, workforce impact, reputational risk, and external examination simultaneously, and scaling them is no longer a technical decision; it is an organisational one, raising the stakes.

AI pilots often succeed on activity metrics:

• models trained

• vendors engaged

• proofs delivered

• workshops run

But they avoid outcome-based measures that would force the real question:

Are we equipped to operationalise this, or should it stop?

This is exactly what the Digital Transformation Agency was pointing to. AI does not tolerate fuzzy ownership or vague decision rights. It exposes them.

Why is this flaring now

This pattern is strengthening as Australia’s innovation and funding environment has rebounded in aggregate terms. Experimentation is still encouraged. Pilots are still funded. Venture and innovation activity continues. But governance has not kept up.

As capital tightens and tolerance narrows, continuation bias increases. It is often easier, politically, operationally, and personally, to extend a pilot than to terminate it. Especially when stopping means reallocating people, admitting uncertainty, or absorbing short-term discomfort.

In the end, pilots persist, not because they are winning, but because the system makes stopping expensive.

The issue underneath

Strip away the language and the decks, and the same three unanswered questions appear again and again:

1. What must be true for this pilot to move to production?
   Not “what did we test,” but what evidence would justify real commitment.

2. Who owns the operational and reputational risk if it does scale?
   Technical risk is easy to discuss. Organisational risk is not.

3. Who is explicitly authorised to stop it when learning plateaus?
   Not slow it. Not reshape it. Stop it.

Until those questions have owners, pilots will continue to build up without compounding value.

This is what leads to an unwelcome truth:

The blocker is rarely the pilot itself. It is the cost of being the person who turns it off.

A final observation

Australia may not necessarily have an innovation problem, but there are indications of a decision problem. And until continuation has to be actively re-earned, zombie pilots will remain a rational outcome of an irrational system.

This is not an interesting observation. It is a solvable problem, but only if decision-making and outcomes, not ongoing experimentation, become the focus.

References / Further Reading

• Australian National Audit Office, Evaluation of Australian Government Pilot Programs
  https://www.anao.gov.au/work/performance-audit/evaluation-of-australian-government-pilot-programs

• Australian National Audit Office, Performance Statements of Major Australian Government Entities: Outcomes of the 2024–25 Audit Program.
  https://www.anao.gov.au/work/performance-statements-audit/performance-statements-of-major-australian-government-entities-outcomes-of-2024-25-audit-program

• NSW Audit Office - Their futures matter (program evaluation and scale challenges)

  https://www.audit.nsw.gov.au/our-work/reports/their-futures-matter

• Digital Transformation Agency, Global leaders come together in Australia to shape the future of digital government and AI

  https://www.dta.gov.au/articles/global-leaders-come-together-australia-shape-future-digital-government-and-ai

• Australia’s startup funding outlook / ecosystem commentary, SmartCompany

  https://www.smartcompany.com.au/startupsmart/australia-startups-2025-funding-report/

Disclaimer

This article is based on the author’s professional experience and interpretation of publicly available information. It is provided for general informational purposes only and does not constitute advice. Any views expressed are the author’s own and do not refer to any specific organisation, program, or individual.

Work continues, roadmaps are revised, and additional capital is allocated. Updates commonly assert the idea remains plausible, without confirming or disproving its validity.

However, a systemic shift occurs when signals that formerly guided direction and priority stop compounding.

This is not failure, but non-compounding drift. The venture continues, yet learning, traction, and strategic clarity no longer accelerate.

This state persists not from lack of discipline or intent, but due to continuation bias: the tendency to extend time and capital simply because the idea remains plausible.

Issue #4 examines when stopping is most difficult, not because the venture has failed, but because continuing is no longer justified.

Non-compounding drift:
When movement replaces progress.

In the early stages of a venture, learning compounds with each experiment and action. All contributing towards reducing uncertainty, sharpening direction and ability to make clearer decisions.

However, when this situation reverses, non-compounding drift starts to set in.

• Experiments repeat common patterns.

• Progress increasingly requires justification rather than genuine insight.

• Decisions feel harder, not clearer.

• Activity remains high while insights plateau.

Nothing is fundamentally broken, and at this point, nothing has failed.

The venture stops improving meaningfully and enters stagnation or perpetual pivots.

Why rational teams persist.

In non-compounding drift, continuation bias is the main driver of persistence.

Continuation bias is the tendency to allocate additional time and capital after signals stop compounding, simply because the idea remains plausible.

This bias does not stem from ignorance or poor intent, but from plausibility serving as a rationale to continue.

As long as an idea has not clearly failed:

• Founders can justify their continued commitment.

• Corporate venture teams can justify sponsorship and priority.

• Investors can justify follow-on exposure.

Two phrases reliably appear at this point:

We just need more time.

We just need more capital.

Both statements may seem reasonable, but they frequently delay addressing the same unresolved question:

What, specifically, would need to change for continuation to be justified, and is that change actually underway?

When this question is not answered, continuation becomes the default and bias replaces disciplined decision-making.

When time and capital no longer enable progress.

At the early stages, time and capital are meant to buy learning.

When signals compound:

• Time increases clarity

• Capital increase optionality

When non-compounding drift takes hold, their roles reverse.

Time becomes a strategic distraction as attention moves to a venture that no longer improves quickly enough to justify exclusive focus.

Capital turns into commitment escalation, with funding used to preserve continuity rather than enhance competitive advantage.

Nothing dramatic occurs, yet opportunity quietly narrows.

The unreported loss.

Opportunity cost rarely appears in venture updates, burn rates, or runway charts, and it does not trigger alarms.

It accumulates quietly with every additional month spent on a venture in non-compounding drift carrying a further cost:

• Another idea not explored.

• Another market not tested.

• Another strategic option was not considered or pursued.

For founders, opportunity cost appears as a strategic distraction, with attention monopolised by a venture that no longer deserves full commitment.

For corporate venture teams, it appears as portfolio crowding, where plausible initiatives consume resources that could support more viable opportunities.

For investors, it appears as capital inertia, with follow-on funding maintaining existing positions rather than increasing expected value.

Opportunity cost becomes visible only when teams are forced to articulate what they would pursue instead.

The most significant opportunity cost is not financial, but the loss of alternative pursuits that could have been undertaken by stopping earlier.

When persistence stops creating leverage -
(A Founder’s Lens)

Founders feel this situation viscerally.

You are still working hard. Your team is still engaged. And, Nothing has failed.

However, the shift has occurred, and leverage dissipates with each pivot yielding less new information.Efforts to influence the narrative begin to rival the focus on product development. And, decisions demand more justification, not less.

What appears externally as resilience usually feels internally like unfocused effort.

Founders lose optionality not by stopping too soon, but by persisting past the point of diminishing returns.

The limit to productive pivoting.

Founders are often advised to pivot, and this is sometimes appropriate. However, the effectiveness of pivoting diminishes over time.

Initially, pivots help narrow the hypothesis space. Later, they may perpetuate ambiguity.

It is important to take into account that each pivot consumes:

• Team belief,

• External credibility

• Strategic consistency

• Learning bandwidth

Eventually, pivoting stops generating new understandings and only delays necessary decisions and the underlying drift remains.

Learning has diminishing returns.

Failure can generate insight, but only up to a point.

What is often missed is that learning becomes finite and incurs costs.

Early learning is reinforcing, but depending on tactics, it can later plateau. Often during non-compounding drift, saying “we are still learning” becomes a justification rather than an objective observation.

Continuing to learn is only rational when:

• The learning still reduces meaningful uncertainty.

• And the cost of extracting it is justified by what it enables next.

When these conditions are no longer met, continued learning does not justify further action and only postpones the decision it was meant to inform.

Disciplined teams prioritise stopping before extracting learning. This process is explicit and bounded, focused on generating transferable findings rather than repairing the narrative.

When exploration turns into inertia -
(A Corporate Venture’s Lens)

In corporate venturing, continuation bias often hides within governance.

Ventures persist because:

• They remain sufficiently aligned with the strategy or mandate.

• They have internal sponsors.

• They avoid political friction.

Over time:

• strategic relevance weakens

• Narratives become harder to sustain

• Capital is used to maintain appearances rather than to create strategic options.

“More time” becomes one more reporting cycle.

“More capital” avoids a difficult internal call.

The main risk is not direct loss, but the displacement of better opportunities while maintaining an illusion of progress.

In a corporate setting, an essential factor is the design of incentives and roles.

In many corporate innovation models, roles, reporting structures, and success metrics are tied to the survival of individual programs rather than portfolio outcomes. Teams are organised around specific ventures, progress is reported by initiative, and career advancement depends on sustaining ongoing projects.

In these conditions, stopping a venture is no longer only a deliberate decision. It can seem like the removal of a mandate, a team, or a career path.

Continuation becomes rational, even when signals stop compounding.

Discipline becomes less about individual resolve and more about separating continuation decisions from initiative-based incentives. This allows cessation free of personal, political, or career consequences.

When follow-on becomes default -
(An Investor’s Lens)

From an investor’s perspective, this is when discipline erodes.

The venture does not fail quickly enough to warrant termination, nor does it succeed enough to justify further investment. As a result, follow-on capital is often rationalised as:

• Supporting the founder

• Protecting the initial position

• Preserving optionality

However, optionality is not maintained by default continuation. It is preserved by relative improvement versus alternatives.

Capital allocated to ventures in non-compounding drift is unavailable for investments with higher return potential.

This is not pessimism. It is portfolio discipline.

Discipline without performance

Discipline is sometimes mistaken for managing external perceptions.
Shutdown announcements, retrospective clarity, and lessons-learned narratives emerge later.

Real discipline is quieter. It is seen as:

• Re-earning continuation, not extending it

• Treating time and capital as conditional

• Accepting that plausibility is not progress.

• Allowing outcomes without identity defence

Legitimate decisions to cease operations are justified by evidence and process, not by external approval. Stopping does not require recognition to be valid.

Let’s execute.

A founding team, corporate venture group, or investment committee can use this diagnostic when reviewing continuation.

Answer the following questions directly and concisely.

1. What is the present-tense justification for continuing this venture?

2. Which signals have strengthened in the last 90 days, reducing uncertainty?

3. If no additional capital were available, what would materially change?

4. If this venture did not exist, what would this team focus on instead?

5. What decision is being deferred by asking for more time or more capital?

If these questions cannot be answered clearly, the ambiguity is a critical signal.

A closing thought.

Most ventures do not end because the case for stopping is clear.

They end because the case for continuing is never re-earned.

Walking away is not a loss of belief, resilience, or ambition. It is the result of disciplined action, applied when signals stop compounding and opportunity cost outweighs potential gains.

Stopping creates space, not for reflection or narrative repair, but for better decisions in other areas.

The work does not end when the venture stops. It begins again with greater clarity about what deserves commitment going forward.

What’s coming next? Stopping is one side of discipline. Deliberate continuation is the other. The next issue will examine actions taken once signals become clear, including:

• How disciplined teams translate evidence into strategy?

• How do they choose what to double down on?

• and how continuation remains deliberately re-earned?

This series and perspectives draws on patterns observed across startups, corporate ventures and innovation decision-making. It is not a checklist to be blindly followed. 

Most of the signals people rely on to judge progress are misleading.

Activity. Interest. Pilots. Positive conversations. Narratives of early traction. Each may seem convincing, yet all can be misleading.

Once this becomes clear, a predictable pattern often follows.

Teams rarely change direction immediately. They do not stop. They do not suddenly become more disciplined. They hesitate.

This leaves two questions:

1. If existing signals are unreliable, what should teams focus on instead?

2. How can progress continue without substituting one set of weak signals for another?

At this stage, teams often seek additional information. More data. More validation. More conversations.

This is not to clarify the decision, but to delay making it. The problem is rarely a lack of signals. The problem is a lack of signal strength.

This issue focuses on recognising that distinction and will guide you through how to differentiate among signals as you decide what matters most. Before exploring the types of signals, it’s important to understand why typical responses to early uncertainty often fall short.

Not all signals are equal.

A common mistake among founders, venture builders, and corporate innovation teams is treating all signals as equally significant. They are not.

Some signals are noisy, some are fragile and some exist only while attention is actively applied to them. Others however compound.

The strongest signals rarely appear clearly. They do not arrive with certainty and often seem unremarkable at first. On their own, they may not feel decisive. What distinguishes them is what happens next.

They reappear.

They reinforce each other.

They begin to narrow the range of reasonable options.

Over time, they start to force decisions even when no one is explicitly pushing for one. Some signals need constant explanation. Others do not. Most teams do not miss this because they are not paying attention. This occurs because early signals often feel urgent to those closely involved.

Why “more data” is rarely the answer?

When confidence in existing signals erodes, the instinctive response is measurement. I have observed multiplying dashboards, perpetual pilot extensions and repeating research or discovery loops.The work becomes busy, structured and defensible.

However, it often the venture begins to feel stagnant. There are more updates, but fewer decisions. More evidence, but no change in direction. More activity, without a corresponding shift in commitment.

This is often described as rigour. In practice, there is usually hesitation.

Weak signals benefit from ambiguity. They survive when interpretation remains optional, and decisions can be deferred.

Alternatively, strong signals behave differently, they will often have an impact on the decision to be made. They reduce ambiguity. They make trade-offs harder to avoid. They narrow the space between “interesting” and “necessary.”

The question is not whether you have signals. It is whether those signals are compounding or quietly fading.

Compounding vs decaying signals

The difference between weak and strong signals rarely shows up in a single moment. It happens up over time.

Decaying signals tend to remain isolated and require repeated explanation. Their urgency fades unless someone actively sustains it. When attention shifts, they disappear.

Compounding signals behave differently. They resurface without effort. They create secondary effects. They start interacting with other parts of the system.

Often, the distinction becomes clear only in retrospect, when it is evident that some signals required ongoing support to remain visible, while others persisted independently.

This is not about optimism or skepticism.
It is about accumulation.

What real demand looks like in the wild?

This issue is not about tools, steps, or validation techniques. It is about learning to observe what is already occurring.

Across startups, spin-outs, and corporate innovation programs, a small number of patterns recur where real demand exists, long before success is obvious.

Behaviour that costs something

Real demand shows up where people are already paying a price.

For founders, that price is often personal or financial. Time is lost. Manual workarounds persist. Resources are committed earlier than they feel comfortable. People accept inconvenience rather than revert to the status quo.

For corporate innovation leaders, the currency is different. The cost is organisational.

Exceptions are made. Standard pathways are bypassed and work happens unofficially because the alternative is worse. Leaders tolerate risk they would normally deflect.

This is often uncomfortable to observe, particularly when it becomes clear that people are solving the problem independently rather than due to your involvement.

Where people consistently pay a price, demand is rarely theoretical.

Workarounds that scale socially

One workaround proves very little. The same workaround appearing independently across customers, teams, or parts of an organisation is a different signal.

For founders, this repetition is usually external: similar spreadsheets, parallel hacks, familiar patterns emerging across different buyers.

Inside large organisations, repetition is often hidden. The same problem is solved badly in multiple places. Shadow systems appear and local fixes replicate quietly because no one is rewarded for surfacing them.

When many people independently arrive at the same imperfect solution, the underlying problem is usually real.

Escalation without prompting

Weak signals need chasing. Strong signals escalate on their own.

For founders, escalation often moves outward. Introductions happen without asking. Conversations expand. Procurement or finance enters earlier than expected. Questions begin to imply consequences rather than curiosity.

Inside organisations, escalation moves upward. Senior leaders ask how this fits with strategy. Risk and compliance surface implications. Ownership becomes unclear.

At this stage, the situation often feels less contained.

For founders, escalation creates opportunity.
For corporates, it creates accountability.

In both cases, it signals that the work is no longer optional.

Decisions forced by success

Positive outcomes are often mistaken for strong signals.

A pilot that performs well but allows everyone to defer a “buy or do not buy” decision is weak. A prototype that works but doesn’t challenge an existing process is weak.

Strong signals create consequences.

For founders, success collapses optionality. Pricing must be set, contracts negotiated and resources are reallocated.

For corporate innovation teams, success creates friction. Existing systems are challenged. Ownership becomes contested. Funding conversations move out of innovation budgets and into the business.

Within organisations, a lack of friction following success is often a warning sign.

Compression of time

One of the most reliable indicators of real demand is what happens over time.

For founders, this often shows up as shortened cycles. Decisions happen faster and follow-ups occur without chasing.

Inside organisations, time compression looks different. Deadlines appear suddenly. Executive updates are pulled forward. Decisions that were expected later become uncomfortable to delay.

This is not urgency for its own sake. It is exposure. When time compresses within a system, it is usually because delay has become risky.

The quiet pressure of real demand

At this point, many teams begin to sense a shift, even if they struggle to articulate it. Nothing dramatic has happened and there is no single breakthrough moment.

Yet, continuing as before begins to feel misaligned.

The work still moves forward, but with less effort. Certain conversations keep resurfacing and certain questions refuse to stay contained.

At the same time, other things fade.

Updates that once felt important stop changing anything. New information no longer alters the picture. Momentum appears to be assumed rather than actively generated.

At this stage, experienced teams often realise how much they have relied on narrative rather than evidence.

Strong signals do not demand attention. They create pressure.

They do not ask to be believed. They make delays harder to justify.

Strong signals accumulate, driving necessary decisions and making delays hard to justify. Weak signals require explanation, fade without support, and produce activity without real progress.

Recognise which type you have prioritise compounding signals, act decisively, and avoid relying on plausibility alone. The key is to focus on signals that reinforce themselves, force decisions, and compress time. These are the indicators of real demand.

A decision fork in the road.

This is usually the moment teams underestimate. This is not due to subtlety, but rather because it is inconvenient.

By the time you reach this point, you rarely lack information. What is often missing is the self-granted permission to act on what the signals already indicate.

The decision point does not announce itself. There is no sudden deadline or failure. Instead, it becomes clear that nothing new is emerging.

Conversations repeat.
The same signals and justification are repeatedly cited.
The same explanations are repeated to justify maintaining the current course.

At this stage, most teams do not continue because they believe the idea is right.
They continue because the idea is still plausible.

Plausibility sustains the narrative. It keeps options open and makes delay appear responsible rather than evasive. But plausibility is not momentum.

The decision point is where you determine whether you are responding to compounding evidence or maintaining decaying justification.

When signals compound, continuation becomes structurally obvious. Venture builds should be able to observe, resources shifts, clearer ownership and trade-offs being accepted rather than debated. Continuing may not feel easy, but it feels necessary.

When signals decay, something else happens. The work continues, but the pressure disappears. Energy is maintained through explanation rather than through tangible consequences. Progress becomes something described rather than experienced.

This is where many capable teams linger.

Not because they are careless.

Not because they lack discipline.

But because stopping feels disproportionate when nothing has failed.

Walking away from a failing idea is straightforward. It is much more difficult to walk away from a good idea supported by weak signals. That is why this fork matters.

It is not a test of optimism.

It is  not a test of resilience.

It is a test of whether you are willing to treat the absence of momentum as meaningful information.

For founders, delaying this decision quietly consumes runway and credibility.
For corporate innovation leaders, it consumes political capital and organisational patience.

In both cases, the cost is real, though deferred.

The decision fork is not able certainty. It is about recognising when continuing no longer improves the quality of your information. Once you reach this point, continued activity is no longer a neutral choice.

It is a choice.

Let’s execute

This is not a growth exercise.
It is a recognition exercise.

This process is more challenging than it appears, not due to complexity, but because it eliminates places to hide.

Set aside an hour to complete this exercise independently.

1. List the signals you are currently relying on.

   For each, ask yourself the following:

   1. Has this signal strengthened or weakened over time?

   2. Did it escalate without prompting, or require chasing?

   3. Did it force a decision, or allow deferral?

   4. Did time compress or stretch?

Now group them into two columns:

1. Compounding

2. Decaying

Do not debate the categories.

If you need to justify why a signal belongs in the first column, it likely does not.

Finally, answer one question honestly:

• If you removed all decaying signals, would you still continue?

This exercise is intentionally designed to be uncomfortable.

It quietly distinguishes those building genuine progress from those simply maintaining activity.

A closing thought

Strong signals do not guarantee success.
Weak signals almost guarantee drift.

The role of a venture operator, founder, or corporate innovation leader is not to create artificial confidence. It is to interpret evidence and make timely decisions.

Most people can generate activity.

Fewer can recognise momentum.

Very few are willing to act when signals indicate it is time to stop.

Whats coming next? The next issue will look to address the decision most teams avoid. Not when the idea fails, that part is straightforward. When the idea remains plausible, work continues, but the signals do not compound.

It will examine:

1. Why teams stay longer than they should?

2. What discipline looks like in practice, without becoming performative?

3. How to disengage without turning it into a personal narrative that requires justification?

Because the ability to stop is not a personality trait. It is an operating capability.

This series reflects patterns observed across startups, corporates, and research-led ventures, not a checklist to be blindly followed.

The last event I went to last year finished in a way that felt quietly important.

On stage, a founder spoke about their journey so far. Not only the highlights, but the reality of it. The reality of the venture and the reality of life. What stayed with me most was how often the conversation came back to resilience.

Resilience here was not just about optimism or toughness. It was about being able to keep going when you do not have all the information, resources are limited, and the next steps are not clear.

How you think about resilience matters. That framing matters.

In early-stage ventures, you rarely have enough data to make perfect decisions. Most of the time, you are making the best decision you can at that moment, with partial evidence, limited resources, and pressure coming from multiple directions. Some of that pressure comes from the venture itself. Some of it comes from life.

Founders do not operate in a vacuum. Life events can and will often intervene, your capacity changes, momentum can break, and your energy will drop. At the same time, the venture still asks for progress.

Demand signals are weak, evidence is noisy, and what you hoped would validate the direction often refuses to cooperate. Or, it can say something that you do not want to hear.

Resilience, in that context, is the ability to stay engaged despite the challenges.

Sometimes that means working with what you have rather than what you planned for. Sometimes it means trusting your judgement before the data has fully caught up, and being willing to live with the consequences. And sometimes it means being stubborn enough to continue. Not blindly, but deliberately, because the goal still matters even when the route keeps changing.

This is also where some of the hardest choices show up.

Resilience is tested when founders realise the team they started with may not be the team they need to continue. When roles need to change. When co-founders need to step back. When the founding group needs to grow. These decisions are rarely clear, rarely clean, and almost never arrive at a convenient time.

Avoiding them often feels easier in the short term. Making them is usually what keeps the venture moving forward.

Resilience is also about time. Staying in the game long enough for signals to mature, for evidence to accumulate, and for second-order effects to reveal themselves. And sometimes, for the mind and body to recover.

This is where resilience connects directly to demand, evidence, and coherence.

Without it, teams optimise for relief. They reach for cleaner stories, safer tests, and smaller decisions that reduce discomfort but avoid the harder questions. Teams with resilience stay with those questions long enough for weak signals to either strengthen into real evidence or disappear entirely.

Resilience is not about ignoring evidence. It is about staying engaged until the evidence is strong enough to justify change, or clear enough to know when to stop.

Across founders, venture builders, and spin-out teams, the pattern is consistent. The ventures that progress are not defined by certainty or uninterrupted momentum. They are defined by their ability to hold things together while making imperfect decisions under pressure.

That is not inspirational.

It is operational.

And without it, you cannot keep going.

This observation prompted by an article from Global Corporate Venturing (linked below) maps high activity and capital flows, providing insight into how various corporate investors engage the market. It notes that “artificial intelligence continues to absorb the lion’s share of corporate venture capital,” but also emphasises that the landscape reflects “increasingly strategic and diversified capital deployment,” not just “AI exuberance.”

This perspective is useful and raises important questions.

The investor landscape is diverse, including infrastructure leaders such as NVIDIA, established venture arms like GV and Salesforce Ventures, and crypto-native firms like Coinbase and Animoca Brands.

This diversity shows where corporates are focusing their attention.

However, activity alone can be an ambiguous signal for founders. High deal volume may reflect strategic clarity or alternatively ongoing uncertainty and hedging. While calling this “strategic and diversified” is reasonable at the capital-allocation level, it raises the question of how often this activity leads to real changes in decision-making, integration, or execution within the parent organisation.

From an operator’s perspective, this capital deployment suggests that venture investing may serve as a strategic input. In practice, this can involve exploring adjacencies, preserving optionality, and informing build, buy, or partner decisions. However, the article does not assess whether or how often these signals are acted upon.

That distinction is especially relevant for founders.

A CVC’s presence on a “most active” list does not guarantee that, for a founder:

• Your solution, and more importantly, the specific problem it addresses, is already recognised internally rather than just aligned with a priority theme,

• real demand exists inside the organisation, or

• pilots will convert into contracts, revenue, or integration.

Regardless of a corporate investor’s activity level, founders must clearly define the problem they are solving and identify where genuine demand exists.

This requires clarity regarding:

• Who experiences the problem today, and who controls the budget?

• Whether demand is demonstrated through actions, such as budget ownership, workaround adoption, or active engagement, rather than narrative, and

• What specific decision would the corporation need to make if the solution is successful?

CVC activity does not create demand. But it can amplify clarity when demand is already real.

There are examples where corporate venture activity leads to internal decisions, integration, and long-term value creation. Achieving this is rarely straightforward and often depends on factors beyond the investment itself, including organisational readiness, incentive alignment, and execution capacity. The variability means that activity alone is not the complete signal unless viewed alongside how each individual corporation actually leverages and acts on its venture investments.

The key takeaway for founders is that investment volume and thematic momentum indicate where attention is focused. Ultimately, effectiveness depends on whether this activity leads to changes in decisions or execution.

Source: Global Corporate Venturing, “Most active CVC units of 2025”

This issue examines the critical gap between demand signals and their interpretation.

A True Failure

Rarely do teams skip validation. New venture founders and teams conduct customer interviews, they pilot solutions, they collect feedback and encouragement.

Despite following best practices, many early ventures still stall, rarely due to a lack of effort but from misjudgement. Teams misread signals or mistake early interest for validation, progressing through presentations, workshops and even pilots. However, they eventually fail when tested against actual behaviour.

To recap The First Test is not only a method for validating solutions; it serves as a filter to determine whether a problem is worth pursuing. A problem without a real demand signal, no actual behaviour should be avoided.

The problems to avoid.

Three types of problems often emerge and should be avoided.

• Problems that are theoretical. They exist in strategy documents and future-state narratives, align with trends, and make sense intellectually. But they do not appear in workflows, budgets, or daily behaviour. If a problem exists only in abstraction, there is no demand signal to address.

• Problems that are aesthetic. They sound reasonable, such as “It would be nice if…” or “I wish we had a cleaner way to…”. While they may feel modern, they rarely prompt action. Aesthetics create preference, not pull, and pull drives adoption.

• Problems that are low velocity. Even if real, they occur too infrequently to create urgency. Low frequency leads to low recall and low priority, causing ventures to stall before execution.

The most successful ventures address problems that are frequent, costly, and difficult to ignore. They have found urgency and repeated impact when evaluating opportunities.

A quick reminder on innovation

When a venture stalls or even fails, many teams are often given a familiar explanation.

“Maybe it is just too new. Maybe demand has not formed yet.”

This explanation is rarely accurate.

Innovation succeeds by solving existing problems more effectively, not by inventing new ones. When there is no existing behaviour, workaround, compensation, effort, or cost, then urgency has not been established, indicating a weak signal of demand.

Novel solutions succeed. Novel problems rarely do.

Recognising patterns in failed ventures helps prevent future mistakes. Accurate signal interpretation protects against wasting resources on weak problems.

Beware the false positives.

Finding a strong demand signal is encouraging, but some signals collapse under scrutiny. These traps create the illusion of demand that founders, corporations, and professionals misread.

Interest is not intent. A stakeholder may say, “Yes, we would use this,” yet nothing changes: workflow stays the same, no contract is signed. People often love new ideas in conversation. They enjoy sounding supportive. However, a verbal endorsement is not a commitment.

Enthusiasm is not urgency. A pilot meeting may be energetic, and the demo well received, but if no budget is allocated, no deadlines shifted, and no risk is accepted, there is no urgency. Urgency always involves a cost, even for unproven solutions. Energy is not evidence.

Imagination is not truth. In interviews, people may describe what they would do, but in practice, they continue to use spreadsheets, manual checks, and long-standing workarounds. Often, this is driven by the interviewer, who asks leading questions about future behaviour. The questions often sound like

“If this existed, would you …”

“In theory, could this help you … “

“Would you use a tool that … “

As a result, they imagine rather than report reality. They talk about hypotheticals project where as real demand needs to exist in the present.

Persona pain is not real pain. A presentation may claim the CFO struggles, but analysts absorb the burden. The system suffers, but the persona is unaffected. Personas point to pain but do not prove its existence.

Corporate sponsorship is not adoption. An innovation lead may champion an idea, and leadership may align with it. But if procurement stalls, legal hesitates, or operations deprioritises it, the organisation supports change without enacting it.

Socially convincing demand signals may seem strong, but only those that withstand testing result in real action. Always look for practical proof, not appearances.

A necessary clarification on pilots

Pilots exist at the boundary between genuine signals and illusion.

Pilots can be valuable and often represent the first serious engagement with a new idea or capability. However, they are typically low cost, low commitment, and low risk, making them easier to approve. This is especially true when dealing with large organisations.

However, a pilot does not prove demand; it demonstrates permission to explore. Pilots can be misleading if they lack clear success criteria, a defined path to scale, a pre-allocated budget, or an accountable business owner. In these cases, pilots generate learning rather than commitment.

Pilots are meaningful when they are designed to inform a clear buy-or-not-buy decision, address a specific operational problem, are sponsored by someone directly affected, and are linked to an existing cost line.

The intent behind a pilot matters more than the pilot itself. True demand is revealed by commitment, not just participation.

When Demand Hides

Even good tests can mislead if you do not know where to look.

These are situations in which demand exists, but the signals are more complex to discern. Not because the problem is not real, but because the behaviour that expresses it is obscured, fragmented, or absorbed into other parts of the system.

Some signals are invisible at first. Teams often hide their hacks in workarounds, shadow systems, manual checks, and “temporary” fixes that persist. If you ask only how the process should work, you will miss how it does. Real demand lies between policy and practice.

Sometimes the pain is carried by someone else. Executives feel nothing while front line teams compensate daily. If a downstream operator quietly compensates for a broken process, the problem may appear small from above, even when it is structurally significant. This is common in corporates and regulated environments. You may not find the signals in the boardroom. You may find them where the work happens.

Sometimes behaviour is fragmented across roles. One team wastes time; another absorbs cost; a third manages risk; a fourth cleans errors. Individually, the signal looks weak. Collectively, the behaviour is loud. The First Test still applies but must be performed at the system level.

And sometimes long-standing pain disappears into tolerance. People adapt. They stop complaining. Resignation replaces expectation. But overall tolerance is not satisfaction.

How the operator can distort the signals

When The First Test appears to fail, it is rarely because the test is flawed. It is because assumptions distort what is being observed.

One distortion is being too broad. “Improve efficiency” is not a problem. Real problems are concrete enough to be recognised in context.

Another distortion is smuggling the solution into the problem. When language shifts to solutions, observation gives way to justification.

The First Test only works when problems are expressed in human terms: what breaks, who compensates, and what it costs.

Interpreting signals depends on your perspective.

The First Test is universal. However, how signals are misread depends on your role and incentives. Though the failure is shared, the blind spots are not.

Founders often mistake encouragement for inevitability. Early interest feels like momentum, but without workflow, budget, or priority change, the signal is social, not economic.

Investors can confuse activity for evidence. Busy pipelines and strong pilots feel reassuring. But capital amplifies clarity; it does not create it. When signals are weak, funding extends false momentum.

Corporate innovation leaders most often confuse alignment with adoption. If stakeholders agree and governance is satisfied, it feels like progress. But alignment is permission, not demand. Adoption begins when a business unit owns the problem and absorbs the cost.

Advisors and operators are in a challenging position. Their primary risk is assuming clarity exists when it does not. The operator’s role is not to create confidence, but to ensure consequences are addressed.

In essence, actions that demonstrate behaviour, cost, and decisive choices are the most reliable indicators of real demand. Use these as your guideposts.

Finding Real Demand Signals Matter

The First Test exists to prevent a specific, expensive mistake by building on belief rather than behaviour. Passing it does not guarantee success, but misreading it almost guarantees waste.

Most teams do not fail because they did not test. They failed because:

• They trusted the wrong signals.

• They mistook politeness for pull.

• They mistook activity for urgency.

• They mistook permission for commitment.

Identifying demand signals through the First Test does not protect you from failure; it helps to protect yourself from self-deception.

Let’s Execute

Pressure test the signal, not the story.

In Issue 01, you executed the First Test. This time lets challenge early demand signals before committing resources beyond what is necessary.

Let’s apply the First Test discipline immediately without waiting for a solution, a product, or adoption. This matters most in early ventures, where demand must be inferred before workflows change or budgets move.

1. Pick the signal you are currently relying on and downgrade it

Choose one signal you have been treating as traction, a pilot approval, a supportive conversation, a warm intro, positive feedback, or an investor interest.

Now ask a harder question:

What cost is someone already paying because this problem exists?

If the answer is no time wasted, no risk absorbed, no workaround created, then you are not looking at demand. You may be looking at politeness. In early ventures, cost precedes solutions. If no one is paying a price today, they will not pay for relief tomorrow.

2. Translate “workflow change” into early-stage reality

Early ventures often get stuck because they interpret “no workflow change” as failure. Before a solution exists, the workflow change shows up as:

• unofficial workarounds

• spreadsheets next to systems

• manual checks

• duplicated effort

• fragile processes people babysit

Ask:

What are people already doing despite not having a solution?

Those compensations are the early signal. No workaround usually means no urgency.

3. Translate “budget movement” into early-stage cost

Before money moves, time and effort move.

Ask:

Who is spending hours fixing this?

Who is double-checking outputs?

Who is absorbing the risk when it breaks?

Who is cleaning up the downstream impact?

Time is the first currency people spend on real problems. If no one spends time today, the budget will not move later.

4. Force a decision, even without a product

Early founders often default to “more discovery” when signals are weak.

Instead, force clarity:

• If this problem were removed tomorrow, whose job would materially change?

• If the answer is vague, distributed, or hypothetical, the signal is weak.

You are not looking for agreement; you are looking for a consequence.

5. Pause if the signal never strengthens, even if the idea is good

Most wasted effort does not come from bad ideas.

It comes from continuing when the same conversations repeat, the same enthusiasm shows up, but no additional cost or urgency appears.

Stopping is not failure. Continuing without strengthening signals is.

A closing thought

Demand signals can be misread and then defended.

• Encouragement was treated as inevitability.

• Activity was mistaken for urgency.

• Permission was confused with commitment.

• The First Test was passed but not interpreted.

Before solutions exist, demand does not announce itself politely. It shows up as compensation, friction, risk, and workarounds. It costs something, even when no one is paying yet.

Your job is not to prove the idea deserves to exist. It is to decide whether the signal is strong enough to earn execution.

Reflection: When demand never strengthened

One of the earliest mistakes I made as a founder was not building too soon.

It was waiting for a signal to strengthen that never did. I had a prototype and early users engaged with it. Corporate innovation teams were supportive and happy to stay involved.

Interest never disappeared and conversations kept happening, but feedback became repetitive and consistent. What never happened was effort. I noticed no one stayed late to make it work. No one chased it internally. No one felt exposed if it failed. Every conversation sounded like progress, but each one reset back to the same place.

At the time, I told myself this was what “early” looked like. In hindsight, it was repetition without urgency.

The mistake was not building a prototype. It was mistaking recognition and politeness for demand.

That experience is why I now watch for behaviour before belief, not because ideas are fragile, but because founder time is.

What’s coming next? The next issue will focus on signals that do not need defending, those that compound, force decisions, and make momentum inevitable rather than hoped for. Execution does not reward belief. It rewards judgment.

This series reflects patterns observed across startups, corporates, and research-led ventures, not a checklist to be blindly followed.

Before you build anything, test the problem, not the solution.

Here is the fastest way to know whether an idea deserves your time.

The Familiar Failure

Many of us who work with, advise, or invest in founders have seen this pattern.

A founder presents an early-stage venture deck or a polished working prototype.

There is a thoughtful UI. Clean logic. Weeks of work evidenced. And sometimes even $40K spent.

They have spoken to people.
They have had meetings.
They have heard encouraging feedback.

“This is interesting!”

“I’d definitely use something like this.”

Two weeks later, the idea is dead, if they are lucky. Some continue for months or even years. Not because the solution was wrong. Not because the execution was poor.

But because the problem was not real.

What it means for a problem to be NOT real?

A problem is not real when there is:

• No workaround.

• No urgency.

• No repeated behaviour.

• No signal anyone cared enough to act.

The founder did not misread their idea. They misread the problem. It was not worth pursuing, at least not yet.

That is where The First Test begins.

A Venture Operator’s First Test

If you want to know whether an idea is worth pursuing, start with one question:

Is this a problem people are already expending effort to deal with today?

Not could, should or might once a product exists.

But what people are actually doing right now, in the absence of a good solution.

Across technology, sector, healthcare, deep tech, and research-led domains, real problems create observable behaviour.

That behaviour may look different by domain, but it always exists when demand is real.

Reading demand signals in the wild

In practice, demand shows up as people paying a price to cope.

That price may include:

• manual effort and workarounds including spreadsheets, scripts, shadow systems, repeated manual tasks

• risk, delay, and mitigation including interim protocols, monitoring regimes, acceptance of known limitations

• a form of spend such as time, money, external consultants, political capital, compliance overhead

The form varies by domain.
The signal does not.

Where behaviour exists, there is demand.
Where behaviour does not exist, there is no evidence of urgency.

Assessing signal strength

To make this concrete, ask:

• Is the problem active, are people taking action today?

• What is the workaround? Every real problem produces one.

• How painful is it? Pain drives urgency, adoption, and willingness to pay.

• What is the cost of the workaround? Time, money, risk, delay, frustration, compliance overhead … all count.

• How frequently does this behaviour occur? Recurring pain compounds. One-off pain rarely does.

If there is sustained behaviour, there is an initial signal the idea may be worth exploring. If there is no behaviour, you have noise.

The diagram is not a maturity model. It is not a funnel. And it is not a scorecard designed to make weak ideas feel better.

It is a simply a way to visualise how demand shows up in the real world.

As you move up the levels, you are not moving toward sophistication. You are moving toward observable reality.

At the bottom (Levels 1-2), signals are cheap. People talk, they speculate, they express interest. Nothing changes in how work gets done.

In the middle (Level 3), pain becomes visible. The problem show sup repeatedly. It causes friction, delays,m error or inefficiency. But action is still inconsistent. People tolerate the pain rather than actively compensate for it.

At the top (Levels 4-5), behavior changes. People start doing something about the problem, even if the solution is imperfect. They build workarounds, add manual step, bring tools or external help, therefore spend time, money, political capital or accept the risk to cope.

This is the point where the problem can be considered initially investable.

The diagram is intentionally simple because the judgement it supports is simple:

if people are not already expending effort to deal with the problem, you do not yet have evidence of demand. 

How strong does the signal need to be?

To justify investment, even your own time, you should be aiming for a signal strength of 4 or 5. Anything below that is speculation.

If the world is not already expending effort to deal with the problem, it will not magically start when your solution appears.

This is not about optimism or belief.
It is about observable reality.

A common objection

This does not apply to healthcare, biotech, or deep tech.
People cannot solve the problem yet, that’s why the innovation is needed.

This objection usually comes from a good place.

In regulated or science-led domains, the final solution genuinely may not exist yet.
But that does not invalidate the test.

It clarifies what kind of behaviour you should be looking for.

What the test is really asking?

The First Test is not about whether the problem can be fully solved today.
It is about whether people are already paying a price to live with it.

In the areas of Medtech, Biotech, Deep Tech and other research-led sectors, that price often appears long before a new solution exists.

For example:

• In MedTech, clinicians adapting procedures or workflows to compensate, increased monitoring, manual checks, or secondary confirmation steps or even hospitals absorbing higher operating costs to manage the limitation. These are behavioural signals, even if no one can “fix” the problem yet.

• In BioTech or Therapeutics, where there is no effective treatment for an illness or condition, off-label use of existing drugs, multi-drug regimens to manage symptoms imperfectly or funding flowing into adjacent or partial solutions. Again, these are cost-bearing behaviours, not hypotheticals.

• For research-led or deep tech domains, even when the core breakthrough does not exist yet, you may still see, organisations investing heavily in mitigation rather than resolution or policy, compliance, or safety layers added to manage known risk. If people are reorganising work, absorbing risk, or allocating capital around the problem, the signal is real.

If people are reorganising work, absorbing cost, or accepting risk around a problem, the signal is real.

“Unsolvable today” does not mean “not urgent.”

“No workaround” usually means “no urgency.”

Why the Demand Signals Matters

Different audiences. Same failure mode.

The First Test is universal because the mistake it prevents is universal: building before understanding.

However, its value appears differently depending on who you are.

• For the founder, it prevents months of building something elegant, impressive and irrelevant. Many early-stage failures are not execution failures; they are problem-selection failures. The First Test forces founders to earn the right to build.

• For the corporate innovator, it cuts through internal enthusiasm, political sponsorship and innovation theatre. Internal alignment is not external demand. The First Test recentres the conversation on reality rather than narratives.

• For researchers or Universities, it bridges the gap between technical novelty and real-world application. The question shifts from “What could this technology do?” to “Where is the world already struggling without it?

• For the investor, it helps to focus on a team that understands markets, not just ideas. It is a fast, cheap initial filter for your pipeline.

That shift is the difference between publications and impact.

Let’s Execute

No workshops. No frameworks. No theatre.

You do not need permission, funding or a team to run The First Test. You need curiosity and discipline.

1. Write the problem once.
   One sentence. Plain language. No solutions.If you cannot do this, stop.

2. Hunt for behaviour.
   Look for where the problem already shows up, in workflows, reports, budgets, complaints, manual effort, workarounds, etc. If you cannot find three real examples, you do not yet have a problem.`

3. Validate one workaround.
   Talk to the person doing the work. Not what they think. Not what they believe. What they do. Ask them to show you what they actually do. Behaviour rarely lies.

4. Score what you see.
   Not emotionally. Not optimistically. But honestly

   1. How often does this occur?

   2. How painful is it?

   3. What does it cost?

   4. What happens if nothing changes?

High scores earn progress. Low scores earn restraint.

5. Decide.
   Proceed, reposition, or pause. Most teams drift. Operators decide.

A Closing Thought

Innovation begins with observation, not invention.

The market leaves breadcrumbs everywhere.

Follow the behaviour. If people are not already solving the problem today with time, money, or effort. It is improbable that people will suddenly start once your product appears. Developing an understanding on this will help you to choose problems that justify your scarce time, capital, and focus.

Novel solutions win. Novel problems do not.

What coming next?

Passing The First Test does not guarantee you are right, or will be successful.

In the next issue, we will look at why even strong-looking demand signals are often misread, how enthusiasm, pilots, sponsorship and alignment can create the illusion of traction.

We will unpack most common false positives, the signals that quietly matter more to help minimise time, capital and credibility are wasted.

If you are building a startup or a new venture within a corporation, you have probably been told that failure is part of the process. But let's be honest - knowing that does not make rejections, pivots, or financial struggles feel any less brutal.

• The sleepless nights.

• The rejections from investors.

• The pivots feel like starting over.

• The overwhelming question: "Am I wasting my time?"

But (most likely) every founder who has succeeded in their mission has been where you may be today.

The difference? They did not stop.

You will never have everything right the first time when building something new from scratch.

You need to get just one big thing right. And that one big thing maybe something unexpected and never planned for. Potentially directly from your friends, your customers, or potential investors, not necessarily directly from your head.

Stay in the game.

Some may think that a founder's success comes from a series of perfect decisions, but history tells us a different story.

• Airbnb was rejected by many investors.

• Slack started as a gaming company. They spent years building a game but noticed their internal messaging tool was useful. That "failure" turned into a billion-dollar business.

• WhatsApp was just another messaging app. But they focused relentlessly on simplicity, privacy, and zero ads. That single insight made them indispensable, leading to one of the most significant acquisitions in tech history.

While luck is a factor, you can’t always control it. Yet, these ventures, teams, and founders showed unwavering determination. Through continuous learning, iteration, and adaptation, they discovered a game-changing move.

And that's the game you're playing. Not perfection. Not overnight success. But the constant search for that one move.

Why failure is just data in disguise?

Let’s reframe failure.
Failure is not a dead end—it is market feedback.
Every misstep is actually giving you invaluable information:

• Customers not paying at your pricing point? Now you know what does not work.

• Did your MVP flop? Now you know what is missing.

• Investors passed? Now you know where your pitch needs improvement.

Every “failure” is a step forward if you’re paying attention.

The best founders, leaders and teams aren’t avoiding failure—they’re using it as a learning tool.

That pivot, that one move that changes everything.

Many desired unicorns and successful ventures often no longer look like their original idea.

• Instagram started as Burbn, a location-based check-in app. However, users only cared about the photo-sharing feature. So, the founders scrapped everything else.

• PayPal originally built encryption software before pivoting into digital payments. If they had never pivoted from their initial intent, the early success of online auctioning and shopping may have looked very different.

Your first idea is rarely your best idea, but like wine can get better over time.

What matters is whether you're listening, iterating, and willing to adapt when the proper insight appears.

The Founder Mindset Shift: Play the Long Game

If you are struggling at work and thinking about quitting, take a deep breath, pause and reflect. Here’s how to shift your mindset:

• Done is better than perfect. Stop overthinking and get something into the hands of real users. The best insights come from the market, not from your own head.

• Failure is an experiment, not an ending. Every setback is a data point. Ask yourself: What did I learn? What should I try next?

• Flexibility is your greatest asset. If users love one unexpected feature—double down on it. If investors give consistent feedback,—adjust your pitch.

• Small wins compound. You do not need to build a billion-dollar company overnight. Just land one great customer, one key investor, one small validation. That’s how you build momentum and gain traction.

Keep pushing. Keep iterating. Keep believing.

In startups and new ventures, you do not always need to be right; sometimes, you need to be right once. It could be the next thing you try.

Interesting Content Found:

1. Airbnb's Early Rejections: In 2008, Airbnb co-founders Brian Chesky and Joe Gebbia sought to raise $150,000 at a $1.5 million valuation, offering a 10% stake in their company. They approached seven investors, five of whom sent rejection emails, while two did not respond.
   https://medium.com/%40bchesky/7-rejections-7d894cbaa084

2. Slack's Pivot from a Failed Gaming Company: Slack originated as an internal communication tool used within Stewart Butterfield's company, Tiny Speck, during its work on the development of "Glitch," an online video game. After realizing the game's lack of profitability, Butterfield decided to repurpose the communication tools into what became Slack.
   https://techcrunch.com/2019/05/30/the-slack-origin-story/

3. WhatsApp's founders, Jan Koum and Brian Acton, emphasised simplicity and user privacy as core principles. They deliberately avoided advertisements and prioritised a straightforward, user-friendly interface, which contributed to the app's widespread adoption and eventual acquisition by Facebook.
   https://www.wired.com/story/whats-app-owner-founder-jan-koum-facebook/
   https://www.fastcompany.com/40459142/whatsapps-cofounder-on-how-it-reached-1-3-billion-users-without-losing-its-focus

Let's skip the fluff before we start the echo chamber to each other, "This is my year," let the dust settle, embrace recovery and regeneration with friends and family and set yourself up for success.

Start with Gratitude

The first and most crucial step is to take stock of what happened in 2024. Because if you are anything like me, last year was a ride - some interesting wins, some glorious fails and a lot of figuring it out as we went.

Building something from scratch is not a simple task, and here's the truth: no one does it alone. Think about it beyond what worked and what did not, and ask yourself:

• Who was there when you wanted to quit?

• Who made you laugh when it all felt too heavy?

• Who gave you the push you needed—or just quietly believed in you?

For me, multiple people, family, friends, mentors, fellow founders and clients played a role in my 2024 journey, providing support, guidance, skills, and even renewed belief in continuing to pursue those crazy challenges despite the obstacles and criticisms. Before diving into 2025, I recognise the people who had my back last year. The ones who were there when it was not pretty. Because no matter how hard we grind, no one builds anything worthwhile entirely on their own.

Now, let's talk about goals.

2025 may still feel like a blank canvas, but let's not just throw paint on it and call it a masterpiece. Whether you are still pre-seed and flying solo or getting ready to raise your Series B capital investment. Let's get intentional. Ask yourself some tough questions.

• What's the one bold move you were holding off because of the fear of failure?

• Where do you want to be by this time next year—and what's the first step to get there?

• Who do you need to surround yourself with to make it happen?

Irrespective of your goal or goals for your venture in 2025, stay focused, make them specific, avoid burnout, build support, and revert to your original why when things get tough.

Five Quick Tips for setting goals up for success.

1) Be Focused:

Many things will probably pull you in different directions throughout the year. Remember, you cannot do everything, and you cannot be everything to everyone. I did state one intentionally as you do not need 20 goals; you need a few right ones—Prioritise quality over quantity. Focus on what matters most and break it down.

Any big goal can feel overwhelming, but breaking it into smaller, actionable steps makes it manageable. Instead of saying, "I want to grow my startup," try, for example:

• Q1: Launch the MVP

• Q2: Establish a sales pipeline.

• Q3: Onboard my ten first-paying clients.

2) Be Specific:

Nothing fancy. Make your goals specific and measurable.

"Get better at marketing" is not a goal; some say this would be a vague wish. Try, instead: "Run three paid ad experiments and measure return on investment at the end of March."

When goals are clear, they are easier to track, achieve, and learn from. Break them into smaller milestones to track how far you have come. Celebrate the wins—even the small ones—and learn from the stumbles. Achieving traction and progress is better than finding perfection.

3) Avoid Burnout / Avoid the noise

Do not do everything simultaneously. Focus your own and your team's energy on where it counts. It is okay to say no to projects, ideas, or tasks that do not align with your core vision.

4) Build Up your Goal Support

Encircle yourself with a reference group that provides support. Find your people: mentors, co-founders, advisors, or a community of peers who'll challenge and cheer for you. The right people will keep you accountable and remind you why you started.

5) It is all about the Why

Above all, remember the "why." When the going gets tough (and it will), reconnect with why you started. Your "why" is the anchor that keeps you grounded and instils the culture and mindset needed in your team to push forward and achieve progress.

Lastly, Growth

And let us not forget growth; growth is not just about hitting milestones—it is about learning, adapting, and becoming a better version of yourself, even when it becomes uncomfortable and life throws you an impressive curveball. Growth happens in the messy middle, so embrace it.

Now, thank and recognise those who got you through 2024, and here to a 2025 jam-packed packed with big and scary goals, achievable outcomes, showing up for the people who matter and embracing the messy but beautiful journey of growth and venturing.

Comment below what you’re grateful for from 2024 and your number one goal for 2025! Let’s inspire each other to grow and thrive.

—

As we step into a brand new year, it is a perfect time to reflect, reset and re-imagine what is possible.

Take a moment to reflect on the year that was.

• What goals or milestones did you achieve?

• What lessons came disguised as #challenges?

• What sparked gratitude even at the toughest points?

• What changes will you make for the year to come?

For founders and change makers, each step, big or small, is progress. No matter your year’s progress—launch, pivot, scaling, holding back, or simply surviving—celebrate your achievements, especially those steps that are nonlinear.

Now, get ready for 2025 and for the journey you are planning to take and ask yourself:

• Do the bold ideas you want to achieve still align with your original “why”?

• How will your habits and rituals realise progress every single day?

• What will keep you accountable even when your motivation may fade?

• What changes will you make for the year to come?

Discipline is not a limitation—its is a critical capability to enable execution. It is execution that transforms your new idea or venture from “what could be” into “what is.”

Commit to building and strengthening those bridges that will help you get to where you want to be.

Intentional action builds the extraordinary.

Here’s to another year of growth, gratitude, and game-changing potential.

Disclaimer: The information provided in this article is for informational purposes only and should not be construed as management, financial, legal, or any other form of professional advice. The content is general in nature and does not consider your individual or entity-specific circumstances, needs, objectives, or goals. The views expressed in this article, including those of any interviewee(s) or any other party(ies), are solely their own and do not necessarily reflect the opinions, policies, or positions of the author, affiliated entities, or related organisations. Readers are encouraged to seek tailored advice from qualified professionals before making any personal or business decisions. No guarantees or warranties are provided, nor are there any representations made to the accuracy, completeness and reliability of the information presented. Use of this information and any resources or links provided is at the reader's own risk.

In research, development, and innovation, perfection is not built overnight. It is the small, consistent steps forward that lead to groundbreaking discoveries and impactful solutions.

Every #experiment, every #prototype, every tweak brings you closer to transforming your ideas into reality. Progress is not about getting everything right in one go—it is about showing up, #learning, and #growing each day.

Whether you are in the lab, transforming your organisation, or pitching your idea to investors, remember: progress today is the beginning of tomorrow's success.

Share with someone who inspires you to keep moving forward.

Image generated using Leonardo.ai

Ideas are the seeds of innovation, the spark that ignites the entrepreneurial spirit.

This is not to diminish the value of creativity but to underscore a critical truth: success lies not in having a great idea but in the relentless effort required to bring that idea to life.

This distinction is crucial for founders, entrepreneurs, and enterprises driving change. The journey from idea to execution is fraught with resource constraints, market uncertainties, and the grind of building something from scratch.

You and your team's ability to execute, stay motivated, and be resilient could be your most significant advantage.

Disclaimer: The information provided in this article is for informational purposes only and should not be construed as management, financial, legal, or any other form of professional advice. The content is general in nature and does not take into account your individual or entity-specific circumstances, needs, objectives, or goals. The views expressed in this article, including those of any interviewee(s) or any other party(ies), are solely their own and do not necessarily reflect the opinions, policies, or positions of the author, affiliated entities, or related organisations. Readers are encouraged to seek tailored advice from qualified professionals before making any personal or business decisions. No guarantees or warranties are provided, nor are there any representations made to the accuracy, completeness and reliability of the information presented. Use of this information and any resources or links provided is at the reader's own risk.

• Australia is a leader in cutting edge research, with deep tech and life sciences driving innovation.

• There are systemic challenges hindering our potential to commercialise our research.

• Successfull commercialisation can delivered positive economic impact, including diversifying Australia’s economy.

• University of Melbourne’s TRAM, is one such initiative working foster strong collaboration between Universities, Industry Leaders and Venture Capitalist to start to overcome those challenges.

Research commercialisation is the vital bridge that transforms groundbreaking academic discoveries into impactful, market-ready solutions, driving innovation and economic growth.

Image generated using Runway’s Text-to-Image AI.

In Australia, the journey from lab bench to global markets enriches industries, boosts national productivity, and creates high-value jobs. Yet, this process has challenges that must be navigated strategically, especially in high-potential sectors like deep tech and life sciences.

Both deep tech and life sciences are at the forefront of solving humanity's most pressing challenges through cutting-edge scientific and engineering innovation.

These sectors are defined by:

• Foundational Innovation: Breakthroughs in AI, quantum computing, robotics, advanced materials, and biotechnology.

• High Barriers to Entry: Demanding significant time, capital, and expertise.

• Transformational Impact: Solutions that reshape industries, tackle societal challenges like climate change, and redefine healthcare.

• Longer Time Horizons: Requiring patient capital and long-term commitment to succeed.

These ventures aspire to deliver tangible human betterment—a goal worth pursuing despite the challenges.

Australia’s vibrant research ecosystem has proven to be a global innovation powerhouse, making strides in medical devices, quantum computing, synthetic biology, and advanced materials. When successfully commercialised, these ventures:

• Propel Australia’s leadership in cutting-edge industries.

• Generate significant economic value through exports and new revenue streams.

• Drive job creation in high-value STEM fields.

• Cement Australia’s reputation as a hub for world-class innovation.

Beyond immediate economic gains, these sectors strategically diversify Australia’s economy, reduce reliance on cyclical industries like mining, and build resilience against global supply chain disruptions.

They inspire the next generation to pursue STEM careers and entrepreneurial ventures.

Key Challenges

Despite its robust research foundation, Australia faces several barriers to turning ideas into market-ready solutions:

• Funding Gaps: Early-stage funding for high-risk, high-reward ventures is limited, particularly in deep tech and life sciences.

• Limited Academia-Industry Collaboration: Long-term partnerships between researchers and industry need strengthening to drive innovation.

• Complex Regulatory Pathways: Sectors like biotech and medtech face additional hurdles in navigating compliance.

• Venture Capital Limitations: Australia’s venture capital ecosystem is smaller and less focused on research-based ventures than its global counterparts.

• Talent Shortage: The lack of experienced operators and risk-tolerant entrepreneurs slows the path to scaling innovative ventures.

In the thick of it

Australia is already taking steps to address these challenges.

More Venture Capital Firms are turning their attention towards deep tech and life sciences, and Universities and Governments (local, state and federal) are looking to encourage, educate and foster more opportunities for research papers to have a chance to impact society.

Programs like the University of Melbourne’s TRAM initiative, part of the Melbourne Entrepreneurial Centre, are making significant contributions to addressing these challenges by equipping academics and making them consider tacking on an entrepreneurial venture and fostering a stronger connection between research, industry and investors. To learn more about TRAM visit the institution’s website.

The TRAM Air program specifically focuses on helping researchers translate advanced projects into real-world applications, preparing them for investment. Its annual Investor Breakfast event connects venture capitalists and industry leaders with TRAM’s latest cohort, fostering partnerships that turn ideas into impactful enterprises.

The 2024 cohort includes transformative projects that address global and local challenges:

• Revolutionary treatments for dementia and cognitive disorders - Meizon Innovations

• Quantum computing innovations to enhance iron disorder detection - FeBi Technologies

• AI-driven tools to optimise the grid’s energy transition - Voltmind

• Earlier detection of visual cognition issues in children to improve learning outcomes - Vis-Cat

• Retinal regeneration for combating blindness - Mirugen

• Aerosol treatment advancements to fight infectious diseases - Misti

Well done to all the teams taking these groundbreaking ideas into the next stage of their commercialisation journey!

Turning to the horizon

Australia is poised to lead the global innovation economy, but unlocking its full potential hinges on collaborative efforts to advance research commercialisation. By addressing key challenges and fostering stronger partnerships between academia, industry, and investors, initiatives like TRAM ensure that brilliant ideas do not remain confined to the lab. Instead, they transform industries, improve lives, and drive long-term economic growth.

I am looking forward to what new ventures start in the new year.

Sources, Resources & References:

1. The TRAM Current Cohort - https://www.tram.org.au/current-cohort

2. Translating Research at Melbourne - https://www.tram.org.au/

3. This is a real quantum leap: local computing concern downplayed, May 20th 2024, The Australian

4. New Life Sciences Hub set for Sydney, June 17th 2024, The Australian

5. Nicholas Opie and the future of Australian deep tech, March 8th, 2024, InnovationAus

6. Building a Ladder to Commercial Success for Deep Tech Founders, February 5th 2024, Tenacious Ventures

7. Realising Australia’s Biomedical Potential with Targeted Capability Attraction, December 15th 2023, BCG

Disclaimer: The information provided in this article is for informational purposes only and should not be construed as management, financial, legal, or any other form of professional advice. The content is general in nature and does not take into account your individual or entity-specific circumstances, needs, objectives, or goals. The views expressed in this article, including those of any interviewee(s) or any other party(ies), are solely their own and do not necessarily reflect the opinions, policies, or positions of the author, affiliated entities, or related organisations. Readers are encouraged to seek tailored advice from qualified professionals before making any personal or business decisions. No guarantees or warranties are provided, nor are there any representations made to the accuracy, completeness and reliability of the information presented. Use of this information and any resources or links provided is at the reader's own risk.