Showing posts with label innovation. Show all posts
Showing posts with label innovation. Show all posts

Mentorship Cafe [GFS Rising Founders]

Mike's Notes

I had to get up yesterday morning at 3am (NZ Time) to attend the Mentorship Cafe organised by Google. I learned a lot from the mentors. Thanks for the help, guys.

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Last Updated

16/10/2026

Mentorship Cafe [GFS Rising Founders]

By: Mike Peters
On a Sandy Beach: 15/10/2026

Mike Peters: Mike invented and designed Pipi and founded Ajabbi.

...

Google for Startups (GFS) Rising Founders Community is a global initiative Google created to support high-potential tech startup founders.

I have been attending some of it from New Zealand, as long as the hours aren't in the middle of the night. It has been useful.

Yesterday, there was a 90-minute Mentorship Cafe. I had applied to attend and was successful. There were two 30-minute one-on-one sessions with a mentor. It was excellent; this is what I learned from Georg, Nsikak and Kennedy.

Context

Ajabbi is mission-led, bootstrapped, with no investor funding planned. All profits go to a non-profit foundation. Its SaaS product, Pipi, solves a very hard, expensive problem. There is no competition. The algorithms and maths involved require top-notch talent.

My questions

How do I recruit a remote workforce for the mission? How do I know that I have found the right people? How do I connect directly with Google DeepMind scientists, since connecting Pipi to Gemini will be a 2-way experiment by both teams?

Suggestions from mentors

  • Build a community first.
  • Grad students want a project anyway.
  • Creds on their CV for career building.
  • Internship program.
  • Be associated with a big name (University, etc.).
  • Need to connect to a senior Google scientist who understands what Mike is talking about.

Discussion

  • Ajabbi is using "Honey Traps" to attract people with the right mindset/talent. They all have to prove themselves; all the work is frontier and hard.
  • Pipi doesn't use LLM vectors, skills, transformers, or harnesses. It is based on how a biological cell works, so it uses different algorithms. High-level mathematicians are needed. MCP may not work here.

Actions

  • Update Stealth Mode plan

Innovation Portfolio Management: Strategy Before Tools or Framework

Mike's Notes

Everything from Tristan Komer is deeply insightful. The same goes for Steve Blank, Alex Osterwalder, and Jason Cohen. I use them to figure out what to do.

Ajabbi aims to make money to provide a good service. All future profits will go to a yet-to-be-established non-profit foundation to fund open research, science communication, and support for the Pipi user community. Ajabbi has many moving parts: the Business Model Canvas and the Mission Model Canvas are useful tools.

Resources

References

  • The Real Startup Book (2nd edition, 2026) by Tristan Komer

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Last Updated

27/09/2026

Innovation Portfolio Management: Strategy Before Tools or Framework

By: Tristan Kromer
Kromatic: 09/07/2019

Tristan Kromer: Tristan Kromer is an innovation coach and the founder of Kromatic. He helps enterprise companies build innovation ecosystems and works with startups and intrapreneurs worldwide to create better products for real people. Editor of The Real Startup Book (2nd edition, 2026), a free field guide to 51 experiments for finding product/market fit. Speaker and longtime advocate for lean startup and innovation accounting methods, now focused on how AI changes (and does not change) the customer-discovery work that decides whether a startup lives.

Martin Kupp: Martin Kupp is an associate professor for entrepreneurship at ESCP Europe in Paris and a visiting professor at the ESMT European School of Management and Technology in Berlin. His work has appeared in California Management Review, MIT Sloan Management Review, Business Strategy Review, Info Journal, Financial Times, the Economist, the Economic Times of India and the Wall Street Journal.

...

Stop shopping for frameworks until you know what you're optimizing for

...

Quick Answer: An innovation portfolio without a clear strategy behind it is just innovation theatre. Before choosing any framework or tool — whether McKinsey’s Three Horizons, the Innovation Ambition Matrix, or Strategyzer’s Portfolio Map — we need to define our innovation strategy, understand our risk tolerance, and ensure alignment with senior leadership. Each tool is simply a lens that emphasizes different dimensions (resources, timing, risk, options), so as innovation managers, we should mix, match, or create our own frameworks optimized for the specific decisions we need to make.

...

Innovation portfolio by Martin Kupp & Tristan Kromer

Martin Kupp is an associate professor for entrepreneurship at ESCP Europe in Paris and a visiting professor at the ESMT European School of Management and Technology in Berlin. His work has appeared in California Management Review, MIT Sloan Management Review, Business Strategy Review, Info Journal, Financial Times, the Economist, the Economic Times of India and the Wall Street Journal.

Tristan Kromer works with innovation teams and leaders to create amazing products and build startup ecosystems. He has worked with companies from early stage startups with zero revenue to enterprise companies with >$1B USD revenue (Unilever, Swisscom, Salesforce, Fujitsu, LinkedIn). Newly appointed VPs of Innovation have been popping up in every company these days. While they are often given vague tasks such as “install the entrepreneurial mindset in the core business” and “look to the future,” managing the innovation portfolio is one of their most important responsibilities. To manage your innovation portfolio, you need to know what to optimize for.

What Is Innovation Portfolio Management?

Innovation Portfolio Management is the process of allocating finite resources into potentially infinite opportunity arenas and then into specific projects to capture a strategic objective. Decisions are not based on individual projects, but on an ideal mix of investments over arenas due to the uncertainty of innovation projects.

Why Bother? Isn’t Innovation Unpredictable?

While it is virtually impossible to predict the financial output of a highly transformational innovation at the very early stages, some projects are substantially less risky. There is a big difference between the transformational approach of moving financial transactions to blockchain and a core innovation of simply providing SMS updates on the status of the same financial transaction. No innovation is certain — they all represent different risk profiles. Just as a good retirement fund will spread its investment into high-, medium-, and low-risk categories, companies must decide where and how to allocate their resources in an ever-changing environment. By diversifying investments into many different bets instead of one big transformation project, managing our innovation portfolio can make the overall output more predictable. The primary goal of building innovation portfolios is to make the unpredictable more predictable.

It’s Not About the Tools

From the McKinsey Three Horizons model, to the Innovation Ambition approach used by Google, to the Strategyzer Innovation Portfolio, academics and consultancies alike are putting ever more tools on the market, each promising to solve the difficult task of managing innovation. A person with tools in his mindEven the word tool is confusing. What used to be a piece of paper presenting a framework or template is now called a tool by many companies and consultants. The innovation portfolio management software used to visualize all this information is now called a platform. The number of frameworks, tools, and platforms to manage innovation is growing almost as fast as the number of salespeople pitching them. 5 People with a laptop computer in their hands and their innovation manager.Before measuring the pros and cons of one tool versus another, an innovation manager needs to understand why they are building an innovation portfolio, and more importantly, what interdependencies need to be identified, monitored, and visualized. The right tool should not only provide a broad overview of the portfolio, but should also help the manager allocate resources, set priorities, and develop options for the future. In helping innovation managers visualize the portfolio, the right tool will force them to make decisions by making the need for decisions obvious. Ultimately it is up to the manager to say no to projects that would only distract the team and suck up resources. This requires strategy.

Prerequisites for Innovation Portfolio Tools

Before choosing their tools, a surgeon knows exactly what they have to do and what they want to achieve. No one wants a surgeon just cutting away without a clear objective. The same is true for innovation managers and CEOs.A surgeon asking his patient if he's using his foot a lot. Innovation Strategy The first prerequisite of any innovation portfolio is that there is an actual innovation strategy. What is promoted inside the company as a strategy is often no more than an empty slogan like “Be the most innovative.” A viable strategy will tell you which projects belong in the portfolio and which do not.

Vision

Similarly, slogans such as “Unlock the innovation potential of digital transformation” are equally useless. This simply tells the company that anything with a mobile app will get approval while worthwhile cost-cutting measures and routine operations are out of favor. The strategy must clearly state what trends are impacting the business environment, where the tipping points are, and where the company wishes to position itself in the future. Are there technological, social, economic, or other trends? Are they predictable linear trends, or do they represent exponential changes that will appear very slowly, but will quickly reach a tipping point? Where does the company need to be positioned when the tipping point happens to make use of the opportunity?

Risk Tolerance

Does the company have a high tolerance for risk, and does it seek to transform the way all businesses in the industry operate? Does it have a low tolerance for risk, or does it operate in a very slow-to-change environment? Companies must understand their own vision for the future and their tolerance for risk, and use them to define the scope of their innovation ambition. Many companies state lofty ambitions but focus their entire rewards and performance reviews system on quarterly goals. This leads to focus only on core innovation. But what is core innovation other than the acceptance of the status quo? Without clear alignment, any attempt at strategic innovation portfolio management is useless.

Strategic Alignment & Communication

Developing and aligning the strategy with action requires good communication between innovation managers and senior management. Senior managers should be actively involved in the development of the innovation-portfolio approach to help innovation departments not only fund projects to some level of success, but to prevent them from being orphaned when no one from the C-suite is interested in adopting the project into the core business. — a company may start with a clear portfolio strategy and only discover during execution a better, emergent strategy that requires a pivot. It is during this iterative portfolio management process that innovation managers and executives discover the insight needed to continuously improve their company’s innovation potential.

Portfolios Are About Interdependencies

The underlying premise of developing and using an innovation portfolio lies in balancing key aspects of the business: resources, time, risk, options, and last (but not least) profitability. Each of these elements can serve as the main perspective of a dedicated portfolio approach, or implicitly integrated into an alternate approach. In the early days of innovation portfolios, one of the central concerns was whether the company or business unit would have enough resources to support all of the innovation efforts, and a number of innovation portfolios were developed that tried to better understand or predict the resources involved in new product development. In 1992, Wheelwright and Clark developed a tool for mapping five types of development projects: derivative, breakthrough, platform, R&D, and alliances and partnerships. Their initial observation was that many companies initiate too many projects and ultimately lack the resources to follow through, leading to high failure rates. Companies would have to understand the nature of their projects to be able to balance the necessary resources for different types of innovation. One of the weaknesses of this approach is centered around the “going concern” principle. In other words, infrastructure is maintained, even if it might soon be obsolete — so investments in some platforms, alliances, and R&D capacity may also become obsolete. Accepting that some projects or capabilities will eventually be stopped makes it necessary to “overbook” the innovation pipeline, much like an airline overbooks seats. Some people are bound to cancel, so the seats are kept full. But what is the right amount of overbooking? This is where timing and throughput become critical. Two people can only afford to buy a half of a car.

Only four years later, in 1996, McKinsey consultants Baghai, Coley, and White published their “Three Horizons of Growth” model, which distinguishes between the current core business, emerging growth businesses, and options for future staircases. 

McKinsey's chart, The Three Horizons of Growth.

While the main focus here is on the timeline, there is also a link to risk in the sense that Horizon 1 is close to the existing core business and therefore less risky, while Horizons 2 and 3 lie farther away from the core business, and are therefore inherently more risky. And given that disruption is happening faster than ever, hoping that disruption is always 5-10 years away seems itself a risky proposition.

In 2012, Bansi Nagji and Geoff Tuff wrote about the Innovation Ambition Matrix to facilitate conversations about portfolio management based on risk and scale of ambition. The matrix is based on mathematician H. Igor Ansoff’s classic diagram to help companies allocate funds among growth initiatives, but it replaces Ansoff’s binary choices of product and market (old versus new) with a range of values. In addition to providing an overview of all innovation initiatives (which all portfolio approaches aim to do), this matrix focuses on the overall ambition for the company’s innovation portfolio and thus its appetite for risk.

Diagram of Innovation Ambition Matrix.

Although time may be an implicit consideration—transformational initiatives are more likely to be long-term — this approach clearly focuses on risk. Companies typically use such a risk matrix to allocate resources based on their ambition and risk tolerance.

A more recent approach, the 2017 Business Model Portfolio Map by Osterwalder and Pigneur, combines elements of the Innovation Ambition Matrix with a clear focus on business models. The Explore section on the left represents transformational projects that give way to more adjacent projects in the middle, while the Exploit section on the right represents the core or adjacencies that are ready for execution.

Explore and Exploit Business Model Portfolio Map. This model allows for adjacent projects to be compared to more transformational projects in terms of expected returns and “innovation risk,” which is another way of identifying the amount of validation a business model currently has. (An adjacent business model that only changes one element of the core business already has a high degree of validation.) so it’s not surprising that scholars like Rita McGrath focus on Arenas of opportunity. For McGrath, an arena is “a combination of a customer segment, an offer, and a place in which that offer is delivered.” Others may use different terms and talk about emerging trends or micro-battles, but McGrath’s main point is that these opportunities are transient and must be captured and exploited immediately. There is no sustainable, long-term advantage. As the consumer landscape shifts, companies can look for growing markets and invest more where the growth exists. McGrath developed a prescriptive portfolio approach based on understanding what type of options need to be developed in any given arena. For example, if a company is not well organized to address an arena and the market is unclear but the technology seems to already exist, then generating options by scouting existing companies is a viable path.

McGrath's portfolio.

Be Creative, Create Your Own!

The portfolio tool an innovation manager chooses serves as a lens through which they see the company’s innovation efforts, and will ultimately influence the decisions being made. So choosing the appropriate portfolio tool is a key part of the innovation manager’s job. This simple task can become increasingly complex as each executive demands that their viewpoint be included in the portfolio map. Some want to focus on a mix of projects leading to healthy returns in a certain timeframe, while others see disruption as more urgent and want to balance risk. New frameworks often attempt to combine one or more of these attributes.

The 4:3 Corporate Startup Portfolio framework by Dan Toma is exactly such a tool, combining the Three Horizons Model with the Innovation Ambition Matrix. Here, they have mapped out Alphabet’s innovation portfolio as an example.

Alphabet’s innovation portfolio.

Radar charts are another approach to combine several attributes, as they can compare different projects across multiple axes. Despite this flexibility, they tend to be difficult to use for a portfolio of more than a few dozen projects. They also don’t effectively show overall investment levels in any given area (although a cumulative radar chart can be used to this effect).

A radar chart.

A divided pie chart can roughly combine different Arenas of opportunity with either the Three Horizons Model or the Innovation Ambition Matrix. For example, the core business (Horizon 1) is the center of the pie chart while transformational (Horizon 3) is the outermost portion. The Arenas are represented by slices. This visually represents that there is more surface area in the outermost portion and thus more opportunity in transformational or Horizon Three projects. That’s simply due to the fact that there is more uncertainty and thus more possibilities. Those possibilities may collapse at some point, but the future generally has more options.

A pie chart.

There are additional options to represent investment by the size of the dot or the level of business model validation by color. But trying to make a visually impressive slideshow that represents everything at once can turn into a useless decision-making tool.


Pie Chart with Project Dots

Perhaps by now you’ve noticed that there is no right or wrong in portfolio management. You can and should create your own portfolio approach that takes your specific situation into account (or mix and match existing tools). You can choose what you want to focus on (resources, time, risk, options) and how you might integrate additional points of view.

Conclusion

Ultimately, innovation managers need to build frameworks that are useful for making decisions. They cannot be so complex that no one understands them, but they cannot be so simple as to remove rigorous thinking from the process. A good framework for building innovation portfolios should uncover where companies are overinvesting and where they are not investing. This transparency will allow executives to make coherent decisions on how to reallocate resources. Having multiple frameworks and dimensions to measure the portfolio is an absolute must. Managers should understand constraints and requirements in terms of resources, time frame, risk, and optionality, and how they fit into the overall strategy. Without that basis in strategy, any portfolio map is an academic waste of time at best, and innovation theatre at worst.

Lessons Learned:

  1. A portfolio framework without strategy is a performance, not a usable tool.
  2. Know what you are optimizing for (resources, timing, risk, options).
  3. Be creative: use existing tools, mix and match, and develop your own toolkit.

Special thanks to those who contributed early feedback to this post: Rob Aalders, Dan Toma, Franck Debane, Jorge Castellote, Esther Gons, Josh Berry, Chris Cannon, Megan Kennedy, Alexia van Schaardenburg.

Frequently Asked Questions

What is innovation portfolio management and why does it matter?

Innovation portfolio management is the process of allocating finite resources across opportunity arenas and specific projects to achieve strategic objectives. Rather than betting on individual projects, we diversify investments across different risk levels — much like a retirement fund — to make the inherently unpredictable nature of innovation more predictable and manageable overall.

What do I need before choosing an innovation portfolio tool?

Before selecting any tool, we need three prerequisites: a clearly defined innovation strategy (not just a slogan like “be the most innovative”), an honest understanding of our organization’s risk tolerance, and strong strategic alignment between innovation managers and senior leadership. Without these foundations, any portfolio map becomes innovation theatre rather than a useful decision-making instrument.

What are the main frameworks for innovation portfolio management?

Key frameworks include Wheelwright and Clark’s resource-based project mapping, McKinsey’s Three Horizons of Growth model (focused on time), Nagji and Tuff’s Innovation Ambition Matrix (focused on risk), Osterwalder’s Business Model Portfolio Map, and McGrath’s Arenas of opportunity approach. Each emphasizes different dimensions — resources, timing, risk, or options — and we can mix and match them to fit our specific context.

Should I create my own innovation portfolio framework?

Yes. There’s no single right answer in innovation portfolio management. We should feel empowered to combine existing tools or build custom approaches that reflect our specific strategic situation. The key is ensuring the framework helps uncover where we’re overinvesting or underinvesting, while remaining simple enough to drive actual decisions rather than just creating impressive slideshows.

Why shouldn’t I focus on tools first when managing an innovation portfolio?

Tools are only lenses through which we view innovation efforts — they shape the decisions we make. If we start with tools before understanding what we’re optimizing for (resources, timing, risk, or options) and how those interdependencies relate to our strategy, we risk making decisions based on whatever the tool happens to highlight rather than what actually matters strategically.

Rarely is your first idea your best idea, with Mitti's Luke Anear

Mike's Notes

I agree with this. I spent 10 years working on solving a set of very hard problems, trying everything along the way. The solution wasn't obvious at the beginning; I discovered it through grit, a lot of luck, and surprise.

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Last Updated

31/08/2026

Rarely is your first idea your best idea, with Mitti's Luke Anear

By: Kate Glazebrook
Blackbird WildHearts: 26/08/2026

Kate is the Head of Impact & Operating Principal at Blackbird in Australia.

...

Luke Anear began his working life as a private investigator, sitting in cars and filming people who had been injured at work.

He says it was the coolest job he ever had. It was also where the problem found him. He was watching people whose lives had been altered by something preventable, paid by the system that let it happen. Once he understood he was part of the problem, he had to become part of the solution.

That was 2004, in a garage on the northern outskirts of Townsville. No software industry, no co-founder, about 30 computer science graduates a year coming out of James Cook University and maybe two of them staying in the field. Twenty-one years later, Mitti has passed a billion dollars in revenue since it began, and Luke is still running product.

Rarely is your first idea your best idea

It took a long time to look like this. Luke is unusually honest about the years of things that didn't work. He built a training platform in 2007, which he describes as a bad version of PowerPoint. There was a document management system in 2010. For a while, there were telemarketers ringing businesses to ask whether they wanted safety paperwork. The checklist app that made the company's name didn't arrive until 2012, eight years in.

His point isn't that the failures were noble; rather, it's that the insights we all recognise today could only emerge after experiencing those failures. "The simplicity comes from the complexity of unravelling all the different variables until you can distil it down," he explains. You can't skip that process. 

"I was cooked”

Two years ago Luke stepped down as CEO. He rang the chair, Robin Denholm, and told her he was done. She was direct with him, and told him he needed to understand he could not come back. He accepted it. Then she rang and asked him to come back anyway.

Upon returning, he realised it wasn't the job that broke him. The way he had built the job broke him. "You have a million things coming to you if you allow your job to be set up that way, which is what I'd done." So he came back to a different shape entirely. He isn't in the weekly exec meeting. He runs product and strategy, and gets pulled in when he's needed.

More experts, not fewer

AI now writes 90% of Mitti's code, and a research and design process that used to run three months resolves into a prototype in 24 hours. The obvious conclusion is that you need fewer people. Luke has drawn the opposite one.

When you can build almost anything in a day, the scarce thing is knowing what to build. So they're hiring subject matter experts into product: a former construction manager, the COO of a quick service restaurant chain. In a two-hour session with one of them, the team makes fifty product decisions. The old research process made ten in three weeks.

He's honest about the cost too. Shipping faster means a team fails at five things where it used to fail at one, and that takes something out of people.

In this episode, Kate Glazebrook talks with Luke about the store manager who replaced a 700-question checklist with a single question, why the insurance industry hasn't changed since 1666, the month he spent sleeping in his car on a Darwin beach at twenty, and plenty more.

YouTube interview

26/08/2026 1:06:12

Innovation Accounting in Practice

Mike's Notes

Ajabbi is a bootstrapped not-for-profit startup. Which is a tough way to go. Innovation accounting will help. I had an online meeting earlier this year with Tristan Kromer, and I gained valuable insights from him. Kenny was originally a musician.

The Kromatic resources are testable and strongly maths-based. They also don't make a fetish of Business Canvases like the innovation theatre crowd. The focus is on finding tools that are actually useful in a specific context. If they don't quite work, tweak them so they do, or invent one.

The Monte Carlo simulation is fantastic.

Ajabbi will pay for support from Kromatic once it has the financial resources. 

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Last Updated

27/06/2025

Innovation Accounting in Practice

By: Tristan Kromer & Elijah Eilert
Kromatic: Copied 25/06/2025

It is not enough to say, “We’re early stage and we shouldn’t focus on a business plan or metrics.” It is not enough to say, “We’re focusing on qualitative data.” And it is certainly not enough to say, “We’ll figure out how to monetize later.”

As an early-stage venture, you don’t need a business plan, but you do need a business model from Day Zero.

You don’t need a financial plan projecting cash flows 4 years out, but you do need a financial model on Day Zero.

Pointing to examples like Twitter and Facebook and how they found their financial model much later is not a good excuse. Even social media products have clear metrics that they measure in the early stages. Social media and game companies count on the fact that they are acquiring a user’s attention and data, and those are valuable assets that can be quantified and monetized later. But we can measure the user’s attention and willingness to relinquish data right away.

Social media companies are similar to a mining operation. If you were digging up gold from a mine shaft, no one would complain that you didn’t have a detailed plan and metrics to sell it in the market. We know gold is valuable and we can figure out how to sell it later. The value is clear. We just need to know if there is gold down there and how much.

To say, “we’re an early-stage mining operation and we don’t need to focus on a business plan or metrics,” would be an absurd statement. We can quantify how deep, far, and fast we’re digging. We can quantify the mineral content of the soil and the geology of the area. No one would accept the qualitative data of a dowsing rod to make a serious mining investment.

Startups, more than ever, should start with a hypothesis-driven financial model from Day Zero. That is why we use innovation accounting.

In the last article, we discussed why standard business cases don’t work in an innovation context, and the three principles we need in order to replace the standard business case with something better. In this article, we’ll go through how to actually do it. Using innovation accounting, we can build a financial model that is accurate, true, and testable.

How to Solve the Problem

To implement innovation accounting for an early-stage project we need to:

  • Identify assumptions
  • Construct a visual model
  • Build a hypothesis-driven financial model
  • Integrate uncertainty


Four steps innovation accounting method

1. Identify Assumptions

step one - innovation accounting method

There are a ton of assumptions that we make when starting a new innovation project. Fortunately, there are a number of different templates and frameworks that capture those assumptions, such as the business model canvas and customer personas. But none are as useful to innovation accounting as a Storyboard.

A storyboard, similar to a user-journey map, maps each step of the user journey from start to finish. This includes hearing about the product or service, actually using it, renewing their subscription, inviting friends, or simply finishing their use and throwing it in the trash.

Storyboards can be used to organize our assumptions into a clear series of actions that the user must take in order for us to both provide value and capture the revenue (or impact if you are a non-profit organization.) The advantage of a storyboard is that it represents observable moments that we can measure. Frame to frame, step to step, each moment in the user journey transitions into another — and we can measure that conversion rate from moment to moment.

If the first step of the story is downloading an app, and the second step is signing up for an account, that is a conversion rate we can measure — the % of people who sign up for an account after downloading the app. If the next step is applying a filter to a photo, then we can measure the % of users that apply a filter. From qualitative data about what the customer wants (to take beautiful pictures) we can map out our ideal story to deliver that value on quantitative metrics.

Even from Day Zero with just a nascent idea, we can create the step by step measurable process by which a person becomes a customer. We may not know the actual conversion rates, but we know what we need to estimate and measure. From there, it is tempting to go straight to a spreadsheet, but sometimes a quick detour will help.

2. Visual Business Model


step two - innovation accounting method

Once you have the basic story down, it’s useful to abstract this into a visual financial model. This really is the same thing as a storyboard where the user’s journey from acquisition to purchase is mapped out. However, we will want to simplify some aspects and include retention (if and how customers buy again) and virality (if and how customers refer their friends to become new customers) which are often left out of the storyboard.

A storyboard or user-journey map is often too detailed for what we need in our financial model. We don’t need to know what % of users apply a filter to a photo, we need to know how many users upgrade, stick around after four weeks, or purchase something so we can zoom out to the bigger picture and only use the most critical metrics that signify important progress towards our business model.

Startup Metrics for Pirates is a widely adopted framework with the right level of simplification for the purposes of innovation accounting. The five components of this framework are Acquisition, Activation, Revenue, Retention and Referral (AARRR, hence the pirate name.)

Acquisition (getting a user to your service or product), Activation (getting the user to have a great first experience and recognize the value), and revenue (getting the user to pay something) should already be on your storyboard. It is only a matter of identifying the step in the storyboard that represents the critical points in your business and thus represent the most useful metrics. This simplified, three-step user journey is often represented as a vertical funnel (although representing it horizontally makes no difference).

However, Retention and Referral are usually not included. That’s just because a storyboard or user-journey map are typically linear. Assembled with yellow sticky notes, it’s hard to represent retaining a customer or referring a friend (although we’ve seen some creative uses of blue sticky tape). But with a journey simplified into a shorter conversion funnel, loops can be more easily added to show where a user retains or refers a friend from a later stage (such add Revenue) back to Acquisition.

With an easy-to-understand visual model and these last two Pirate Metrics in place, we’re ready to make the leap to a spreadsheet.

3. Hypothesis-Driven Financial Model


step three - innovation accounting method

A hypothesis-driven financial model sounds complex, but it is not. It can and should be as simple as your visual model. Each step can be converted into a row in a spreadsheet, starting with Acquisition for the top line to represent the consistent number of organic visitors to your website or storefront.

However, unlike a traditional financial model, the number of visitors is not guessed from month to month and hard coded. Instead, a single assumption sets the number for that variable, and a formula varies the value from month to month in the spreadsheet. That way, if the assumption turns out to be wrong, changing a single cell in the spreadsheet will correct it throughout the model.

Each subsequent row applies the same logic as the visual model. The % of visitors that activate in your user journey becomes a variable that is held constant from month to month, changing visitors into users. The next row might convert users into paying customers who have taken a trial of your product and decided to buy based on another variable, the % of customers who purchase after trial.

Referral and Retention loops require a bit more thought as they impact Month 2 based on Month 1, but still only require a couple of additional rows of calculation.

With minimal effort – most teams take 1-2 hours to do this under guidance – a simple spreadsheet is constructed which is driven by a few variables. Those variables can be updated as more information is available.

Of course, this is a wild oversimplification. But with startups, start simple. We can add complexity over time.

With a tech startup, we often don’t even model costs on Day 1 because user growth might be all that matters for a social media app or game. However, costs can be introduced and more complexity added as the company grows.

This basic model allows us to do some basic scenario testing. We can immediately start testing out different acquisition and retention rates to see what the impact on our growth will be. We can even set certain conditions our business must reach in order to meet our growth targets.

With a limited number of variables, we can see that if our actual retention rate falls below 20%, our referral rate must increase accordingly if we are to continue to grow. This sort of scenario analysis is basic, but effective for helping early-stage innovation tests set pivot-or-persevere thresholds for their business and start designing tests to establish the actual numbers.

Although entrepreneurs can dictate the shape of their business model, reality will ultimately dictate what numbers go into the variables.

Here is a financial modeling template for startups if you would like to try it out.

4. Integrate Uncertainty

step four - innovation accounting method

Lastly, we have to integrate uncertainty.

Although the basic hypothesis-driven financial model allows us to play around and try out different scenarios, it doesn’t actually tell us what is going to happen or the likelihood of success. But we can do this if we get a little data and integrate uncertainty.

Statisticians have a few tricks we can adopt here. Hurricane forecasts, baseball games, and even startups can use a technique called the Monte Carlo Method to predict outcomes based on uncertainty.

Instead of entering a single number into each of our variables, we enter two numbers to represent the range and a distribution curve which tells us the likelihood of any individual outcome within that range. This is not easy.

For example, I may not know the outcome of rolling two six-sided dice and adding the numbers, but I know for certain that it is between 2 and 12. It’s most likely that it’s 7, but 50% of the time the number will be between X & Y.

We can make the same estimations with our business model variables. We may not know what price the customer is willing to pay, but we should be able to say that they will pay between $10 and $100. That’s all the information we need to start building a Monte Carlo simulation.

The math behind choosing the right distribution curve is tricky, and the art of choosing the right range requires a bit of training. But both can be accomplished with a little effort. Building the right spreadsheet is even more complicated, but more and more tools are being created that allow teams to run Monte Carlo simulations right in their spreadsheet or in a specialized application.

Here is a Monte Carlo simulation example if you would like to try it out.

In practice, this means that innovation teams and executives can create go / no go criteria for their pivot / persevere decisions. You want your project to be at least 10% likely to reach 1B in revenue? The Monte Carlo simulation can tell you if your project has reached that threshold. If not, you can stop the project with confidence that it would not achieve your goals and move on to test the next idea.

The output of the Monte Carlo simulation is a chart that shows a range of possible outcomes at any given point in the future and allows you to calculate the likelihood of any individual outcome.

Lessons Learned

This process is repeatable and is applicable to all types of business models. It doesn’t matter if it’s B2B, B2C, B2G, a network, a platform, or anything else not yet invented. Building a model from Day One allows innovation projects to make better decisions, make useful predictions, and demonstrate real progress to stakeholders.

Start by:

  • Identifying assumptions
  • Constructing a visual model
  • Building a hypothesis-driven financial model
  • Integrating uncertainty

Building High-Performing Innovation Teams: Commitment vs. Consensus

Mike's Notes

Jeremiah Gardner on commitment vs consensus. I have seen the problem he is describing many times.

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Last Updated

26/03/2025

Building High-Performing Innovation Teams: Commitment vs. Consensus

By: Jeremiah Gardner
jeremiahgardner.com: 26/03/2025

Let's be honest about something – working on an innovation team is hard. Really hard.

Anyone telling you differently is either selling something or hasn't actually done it.

Here's why: Not only are you trying to find answers to questions nobody's asked before (that's challenge number one), but you're doing it with a group of humans who each bring their own perspectives, biases, and ways of working. That's your one-two punch right there.

And what do most teams do when faced with this complexity? They chase consensus like it's the holy grail of innovation.

You know how it goes. The endless meetings. The careful tiptoeing around disagreements. The diplomatic dance of making sure everyone feels heard. The desperate pursuit of harmony at all costs.

Sounds nice, right? Almost utopian.

But here's the thing – while we're all sitting in our comfy meeting rooms, nodding along and "building consensus," something critical is happening: absolutely nothing.

Let me paint you a picture of what consensus actually looks like in practice:

Three-hour meetings that could've been 30-minute decisions

"Let's circle back" becoming your team's unofficial motto

Death by a thousand tiny compromises

That gnawing feeling that you're moving at the speed of bureaucracy

Meanwhile, your customers – you know, the people you're supposedly innovating for – are out there, waiting for solutions while you're debating the finer points of your project timeline in meeting room B.

This is where great innovation teams zag while others zig. They understand a fundamental truth:

Consensus is the enemy of progress. Commitment is the ally of innovation.

What do I mean by commitment? It's not about blind agreement or hierarchical mandate. It's about:

  • Crystal clear priorities that everyone understands
  • Quick, informed decisions that keep momentum alive
  • Forward movement without the paralysis of second-guessing
  • Actual accountability (yes, with real names attached to real tasks)

I've seen this play out countless times in my work with Fortune 500 innovation teams. The most successful ones aren't the ones with perfect harmony – they're the ones who've mastered the art of commitment.

Take Netflix's approach to innovation teams. They famously operate on what they call "informed captains" – team leaders who are expected to make clear decisions after gathering input, rather than seeking consensus. As former Netflix executive Patty McCord puts it, "Good teams don't wait for consensus. They listen, debate, and then commit to a course of action."

Want to shift your team from consensus-seeking to commitment-driving? Start with these four questions in your next meeting:

  • "What specifically do we need to learn next?"
  • "How exactly will we learn it?"
  • "Who's taking point on this?" (Yes, actual names)
  • "When do we regroup to share learnings?"
  • Then – and this is crucial – get out of the building and go learn something from your actual customers.

Remember: Innovation isn't a committee sport. It's a commitment game. The teams that win aren't the ones who agree on everything – they're the ones who commit to learning fast and moving forward together.

Ready to ditch consensus and embrace commitment? Your customers are waiting.