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One of the key components of an ecosystem for innovation is setting up a separate system to allow for the search for new business models in an otherwise executing environment. There is a need for different processes, innovation KPI’s and ways of working to allow for disruptive innovation to succeed in an environment that is made specifically for optimizing current business models. The current ‘core’ system is there to sustain and execute on the existing models. It can by its nature never allow ‘high-risk, high opportunity’ projects simply because the processes are set up to exclude risk in the first place. Professionalizing or scaling your internal innovation efforts is dependant on a new system for these kinds of initiatives. Building and more importantly embedding a professional second system for disruptive innovation in your organization will make innovation less dependant on the opinion of a single leader, but rather a company-wide capability. Ensuring continuity and thus more chances of success over time.

Building this new system is hard and a lot of work. Therefore, I’d like to share five conditions that you need to have met in order to build this new system. 

1. A clear understanding of what kind of innovation falls under what system in the company

Incremental innovation versus Disruptive innovation. Since the business goals are different, we need a different way of managing as well.
Recognise what innovation belongs to what system

The first and most important condition is having a clear definition of innovation within your company. 

Innovation is a catch-all phrase for lots of different things. Digital transformation, customer centricity, culture change. These are all answers to the question; “what does innovation mean in your company?” If it is all these different things at once, how do you know who is responsible or who should be involved? More importantly, how do you know what to do, or when it is successful?

Your company is governed by a system of processes, rules, and KPIs. The innovation that contributes to or adheres to the current business goals of the organization can be dealt with from within the current system. Digital transformation for instance, or improving current services into more customer-centric ones. 

But there is one type of innovation that cannot succeed under the current system and needs a new system of processes, rules, and KPIs: The innovation that has a high risk and high uncertainty factor and does not directly contribute to the current business goals but rather tries to find new businesses in the near future, needs a new system.

It is important that your company recognizes there is a need for two separate systems and that there is a clear understanding within the company what initiative falls under what system. So that everyone, from stakeholder to innovation team member, actually knows what to do and what to expect once they interact with these initiatives. 

2. Agreement on a ‘company-wide’ product lifecycle or framework

A lifecycle framework for innovation helps teams understand where their focus should lie, it helps stakeholders understand what questions to ask.
From idea to scale

A lifecycle framework is an important step in setting up your new system. Because of the uncertainty of initiatives, it makes sense to break the journey from a great idea to a validated business model up into phases. These steps or stages help identify the risk level of the initiatives and the different needs in each of the stages. We usually identify 4 stages (or 5 if you count the stage where the initiative has become business as usual and can be governed by the existing core system).

At GroundControl we’d like to call these four stages by there focus areas:

  1. Problem: Prove there is a problem
  2. Solution: Prove your solution solves that problem.
  3. Revenue: Prove your customer will pay.
  4. Scale: Prove your business model can scale.

3. A unified way of working or a systematic approach to innovation 

Systematic innovation with continuous learning. The Lean Startup approach.
Continuous learning

In addition to this framework, you have to create a new way of working. A unified systematic approach to innovation. Searching for and de-risking new business models is something that we see works best with an approach that is focussed on learning and testing.

Although innovation is a creative and entrepreneurial process, providing a structure helps to focus on progress, both for the team as well as managers. A structure will also prevent teams from falling back into their old ways of working.

A systematic and unified way of working also allows for teams to be compared to one another. Once you have more initiatives running this is something that will become more and more important. If you want to start making decisions in a portfolio of initiatives, comparability becomes a necessity.

4. A new set of KPI’s that reflect the search rather than financial outcome

Innovation Accounting and innovation management. new kPIs for new ways of working
Are we still learning?

If you have determined a unified way of working you can start implementing new and more relevant KPIs than those used in the current system. These KPIs from the current system are rooted in financials. For the new system, the KPIs should reflect the search journey of the initiatives. “Are the teams learning?” “Can we say with confidence that they are de-risking their business model?” These are the questions you need answers to, to judge if progress is being made. Instead of Accounting, as we do in the core system, we call this Innovation Accounting.

Innovation Accounting consists of different layers of interconnected data. There are innovation KPIs that the teams need to understand if they are moving forward with their idea. There are KPIs for the manager to see if the teams are focussed on learning and de-risking. Lastly, there are KPIs to compare initiatives over the different stages. These layers of KPIs are passing on information from one layer to the other.

It is therefore important to start with the teams, without teams there is nothing to look at in the first place. So ask yourself what it is that you need to steer on to improve the success of the teams and go from there.

5. A VC-approach to investment in innovation

It is a numbers game. A lot of small bets in the beginning. High risk. double down when there is enough evidence to keep going.
Venture Capital Mindset

If you want to start investing more in innovation, you have to adopt a VC-mentality to investing in innovation in your company. This means treating these investments as high-risk investments. Venture Capitalists invest only a little money in the first, highly risky stages, and invest more in those initiatives that have proven their business model enough to move ahead into less risky stages. Starting with a lot of little bets and ending up, over time, with a few less risky, high potentials that you can double down on. 

Another important aspect of Venture Capitalist investment is timelines. Where a Corporate Board is used to make decisions and want to see a return in a year, the timelines for a return on a VC fund are around 12 years. Reaching product/market fit for one initiative may already take up to 24 months.

Invest in people that understand how to manage this, and know what questions you can ask in each of the stages of the framework. 

Laying the groundwork

All of these conditions are interconnected. It depends on your company what makes sense to set up first, but being able to identify which initiatives need what system to succeed is usually a good first step. At least for the most important stakeholder. Keep in mind that sometimes you have to implement parts of these conditions in unison to test the interaction in parts of the organization, rather than implementing them separately one by one company-wide. Building and embedding these elements within your organization takes time. It is a transformation in itself, but the more stakeholders are involved in setting up the system, the better. Implementation starts with actually doing things and showing results. Over and over again.

Here at GroundControl, we’ve seen that some managers don’t (initially) like to add startups to their portfolios when trying our product. Instead we see them taking a lot of time figuring out on their own how they should structure and measure their innovation program. While it’s completely understandable that they don’t want to throw their startups into deep with the risk of wasting their time, we do think that it’s important that startups get involved as soon as possible. 

Our platform is heavily built around the principles of innovation accounting to measure innovation success. Applying innovation accounting is a vital step towards professionalizing innovation. Yet, it is only possible to measure aspects that are actually happening. Thus, these KPIs only work if startups are actively learning by running experiments, and if they’re kept track of in a structured fashion. 

This problem doesn’t just apply to our platform, but applies to how innovation managers try to professionalize innovation as a whole. It is easier to overthink how we might structure and improve our program than it is to actually take (small) incremental steps to reach that point. If we give in to this tendency, we risk spending months (if not years) without moving innovation forward. 

Let’s use an analogy for the sake of argument: When building and testing a solution, you’ll only gain relevant data and learn if it works the way you’ve intended, once you let your users engage with it. The same applies to measuring innovation. You want to learn as fast as possible how your innovation program performs and how startups (your users) are interacting with it. Where does it do well and where does it require improvement? 

When we consider it as such, it seems obvious that the only way to gather and analyze data is to facilitate and structure interactions that generate it in the first place. Yet many of us would rather overthink what we’re going to measure and how we’re going to do so. If we were to run into a startup that would spend weeks thinking about how they would measure an experiment before actually running it, wouldn’t we be concerned? Precisely. 

From the perspective of startups, Tristan Kromer appropriately calls this the Rudder Fallacy. It’s based on the idea that the rudder of a boat only works when you’re moving. If you try to steer without moving at all, you’re going nowhere. Yes, chances are that you’re heading the wrong way initially. But you’ll only know by doing so, and you’ll only be able to correct your steering if you’re moving somewhere in the first place. The same logic applies to managing innovation. 

So our question becomes: how can we sail this ship in an unknown direction without the risk of sinking it? Or: how can we start structuring and measuring innovation without the risk of wasting the time of those involved?

The latter question is tough to answer. You’ll only learn the true answer for your company by doing. However, there are a few ‘rules’ that we believe should always be applied in ‘sailing your ship’:

Applying these ‘rules’ consistently should contribute to ‘smooth sailing’. In conclusion, professionalizing innovation as a manager is no simple task, but the only way to get there is to involve your startups and measure their progress in a way that gathers relevant and comparable data, without letting them worry about it. 

Fortunately, as you might’ve already noticed, our platform helps you in applying all of these ‘rules’. If you have any additional questions or concerns regarding this, feel free to contact us. We’ll be more than happy to help you through this and set up GroundControl to guide your moonshots. 

Learn how to measure innovation, at Innov8ters Connect Unconference

We struggle to iterate quickly – I’d like to identify metrics to demonstrate that innovations are moving forward?

This challenge from the first Group Call at Innov8ers really caught my eye. It is a struggle that we’ve seen a lot with both our own startups and the corporate startup teams that we’ve coached over the years. Especially if the team does not have an active user-base or revenue stream yet, it is hard to see progress. The metrics we use in scaling, like annual revenue or daily active users do not apply.

One of the first things we did, now almost six years ago, was to start dividing our startups into different stages. We saw that startups go through the same 4 stages: First, prove there is a problem, then prove your solution solves that problem, prove your customer will pay and the hardest (and often overlooked) stage: prove you can scale.

The benefit for the startup team is that they know what to focus on and more importantly what to not focus on at the moment. Validating acquisition channels when you haven’t validated what your customer segment is doesn’t make a lot of sense, but is often done. We put these stages, along-side the stage relevant assumptions, together in our NEXT Canvas.

To show that innovations are moving forward, you can start tracking how long it takes for startups to go through each stage. You can setup stage gates to make that transition “smart” or even data-driven. For example by asking: “Has the team validated a clear problem for at least one customer segment?” or “Has the team validated a repeatable revenue model?

This journey through the stages of a startup is however rather slow, compared to quicker iterations. To tackle that we started running innovation sprints with our teams. Sprints very similar to the Scrum sprints, determining what is currently most risky and how can we test that? We divide the tasks for that experiment between the team members and in the next 2 or 4 weeks, the team will execute that experiment. At the end of the sprint, we ask what the team has learned and how that affects their assumptions on the canvas. We then look at what is currently most risky, how can we test that, rinse and repeat.

This structured way of working makes it possible to start measuring how fast a startup is innovating, by looking at the number of experiments per quarter for example. We call that the experiment velocity. How well a team is innovating is measured via the learning ratio: The number of successful experiments, divided by the total number of experiments in a quarter. Fast-moving teams without any learnings are still failing.

After a month or two, you should already see which teams are working hard and which are learning fast. It will also become clear why some teams make more progress than others. When you have these team innovation metrics in place and make them actionable, you can continue by looking at how long each of your startup teams takes to progress through your gates.

Which stages and stage gates have you defined to measure progress?

Relevant links:

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Innovation accounting metrics

Most of us run experiments as part of the validated learning principle. Even more (corporate) startups use the pirate metrics to measure customer engagement. But how can we effectively measure the performance of our innovation activities? How can we compare one corporate startup to another? Is that even possible?

While working with hundreds of startups and corporate innovation labs in the last few years, we started to develop our own innovation accounting framework. Because we started to see patterns and felt the need to make the progress of startups measurable and transparent. We use this framework, for example, as the basis for GroundControl, our software platform to help corporate startups to innovate in a structured and measurable way.

In this article, we dive into how you could start with innovation accounting in practice today.

Levels of Innovation KPIs

What we learned is that there are three types of key performance indicators (or KPIs) each company should be tracking to measure innovation performance:

Reporting KPIs are connected to Innovation Practice. These focus on startup teams, the ideas they are generating, the experiments they are running and the progress they are making from a great idea to scale. The questions these KPIs answer are: How fast and how well are my startups innovating?

Governance KPIs are connected to Innovation Management. The focus here is on helping the company make informed investment decisions based on evidence and innovation stages as part of Portfolio Management. This answers: How well is my Innovation Lab, program, or Accelerator doing?

Global KPIs are connected to Innovation Strategy. The focus here is on helping the company examine the overall performance of their investments in innovation in the context of the larger business. What is the impact of our innovation on the overall strategy?

The Reporting KPIs (or startup team KPIs) are the innovation metrics that fuel the whole innovation accounting framework. Without teams, there is no accounting possible. Just like there is no financial accounting possible, without selling anything.

So to start with innovation accounting, it is important to have teams on the ground, running experiments and interacting with customers. We’ve seen too many corporates that started to develop an innovation accounting framework first, without any teams and it just doesn’t work. You are building a theoretical framework with no way of testing your assumptions. (Sounds a lot like waterfall product development, right?).

3 Reporting KPIs to start with

How to start with innovation accounting? We start with measuring the following three innovation KPIs from corporate startups:

1. Experiment Velocity

The experiment velocity tells you how fast a team is able to run experiments. We measure the number of experiments a team is running per quarter and divide that by the number of experiments the team could have performed. Usually, this is one experiment per 2 weeks, so 6 per quarter. This rate tells us the relative and comparable execution speed of the team.

Example
If the team has run 4 experiments in the last quarter, their experiment velocity is 4 out of 6 or 67%.

The experiment velocity only tells you how fast a team is innovating, not how well they are doing it. It is, therefore, an activity metric. The impact metric counterpart is the learning velocity.

2. Learning Velocity

The learning velocity tells you how fast the team is learning.
We measure the number of successful experiments and divide that by the number of experiments the team could have performed.

Example
If the team has run 4 experiments in the last quarter, but only 1 was successful, the learning velocity is 1/6 or 17%.

The big difference with the experiment velocity is that we look at the number of successful experiments. An experiment is successful when it has clear learnings within the learning goal that we set upfront. The outcome of the experiment can be both a validation or an invalidation of a hypothesis. An experiment is only a failure if the team hasn’t learned anything. They then basically wasted their time by either doing the experiment wrong or by doing the wrong experiment.

The Learning Velocity is an impact metric since it tells you how well the team is innovating.

3. Team Happiness

The final KPI we keep track of is Team Happiness. We track the Team Happiness at the end of each innovation sprint, as part of the Retrospective.

The Team Happiness score is a “culture metric” and is a subjective measurement: the teams themselves decide how happy they are with their work of the past two weeks. It is a clear leading indicator of how well the team is performing. It shows you rather quickly when things go downhill, much fast than the Experiment or Learning Velocity. Usually, first the team Happiness drops, after which the experiment and learning velocity starts to drop as well.

Summary

After a month or two, you should already see which teams are working hard and which are learning fast. It will also become clear why some teams make more progress than others. When you have these team metrics in place and make them actionable, you can continue by looking at how long each of your startup teams takes to progress through your stage gates.

GroundControl offers an automated way to track these innovation KPIs over time. It is a great tool for startup teams to create and execute their experiments and track their learnings afterwards. For innovation managers, it offers a transparent way to compare innovation performance accross teams and report both Reporting KPIs and Governance KPIs to the board.

Interested in trying out GroundControl?

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To properly manage innovation, we need a new way to identify the different types of innovation.

When looking at the innovation maturity within a company, the existence of different definitions for innovation is an important criterion. The acknowledgement that there are multiple types of innovation and we should treat these types differently. Because we all agree that innovation is no longer to be treated as a ‘catch-all’ phrase.

There are several reasons to identify different types of innovation. One is to be able to pursue different types of opportunities. Another is to be able to create a balanced portfolio and innovation strategy. And a third reason is to be able to manage innovation.

Since there are different reasons to identify different types of innovations, there are also different matrixes to define these different types of innovation.

The problem is that we regularly use these different matrixes interchangeably. And no matrix exists to define the different management systems needed. To make innovation work, that is precisely what we need.

Innovation matrixes currently in use

One of the well-known matrixes is the 10 types of innovation model. This model identifies types of innovation and groups them around themes. It is used by students and companies across the world to pursue new opportunities. Or as they say themselves “It provides a way to identify new opportunities beyond products and develop viable innovations”. It is a framework used for pursuing innovation

For years companies have used the horizon model to create a balanced portfolio and innovation strategy. Recently there is a switch to different matrixes since time seems to have caught up with the McKinsey model. One of the newer models that is used widely in building an innovation strategy is the one Gary Pisano describes in this article. This matrix helps you to consider the different types of innovation regarded from the current business model of your company and the technologies that your company has capabilities in. It gives a clear framework on how to consider the different types for your company from the perspective of creating an effective innovation strategy.

But what if we look at it from a management or governance perspective. Within a company, every procedure, process, compliance rules, legal processes and financial processes are rooted in the principle of enhancing and optimizing the current core business models. A very logical thing, because this is how money is made. New projects and endeavours are judged from the risk they pose, the financial cost of development and the financial return it will add to the company. All governance is there to enable growth, optimisation and cost-effectiveness of existing business models. It is based on improving operational excellence. Any risk can be accounted for with reasonable accuracy, and managed. 

Identifying innovation types for the purpose of properly managing them.

The matrix by Greg Satell
This matrix by Greg Satell is one used to map innovation around whether or not a problem is clearly defined and in what market they exist. Its purpose is around strategy and where to solve these problems, but looking at the definitions helped me consider how to map types of innovation in a way that would fit management purposes.

There are several types of innovation that work very well within the core governance of operational excellence. All innovation that adds to, improves, or makes the current models of your company more efficient, or what Greg calls sustaining innovation fits. This innovation can be managed from within the current governance and accountancy models of ‘operational excellence’. Even though for some innovation you would like to adjust timeframes or optimise processes (think of digitalisation) it does work quite well with the current system since it is perfectly aligned with the goal of growing and optimising the current model(s). 

With innovation that is pursued through basic research, or R&D, companies already have different governance in place. They agree that future benefits are uncertain and expenditures cannot be capitalised directly. Timelines and management are different and very often these labs are set outside of the company, or not even part of the company altogether (Universities, research facilities etc. for example) The goal of basic research is oriented towards new discoveries in technology or science. 

There is another reason why some types of innovation need a different form of governance, however.

What innovation falls under what set of rules?

There is one type of innovation that does not work well with the companies core processes and rules. The Innovation that is looking into completely new markets, the innovation that pursues new business models. In Greg’s matrix, these would be the types of both disruptive and breakthrough innovation. These two types of innovation cannot be managed by known systems in the organisation.

Just as with basic research, they are risky investments with an unclear outcome and long timelines, but with a clear purpose to create new revenue streams. We ideally want these initiatives to be part of the company rather than moving them away from the resources they need along the way.

Hence the need for a separate system, one that dictates how to specifically deal with these types of innovation. A company-wide system for investing, managing, and innovation accounting that fits these types of innovation. I call this the startup rulebook.

To create such a rulebook, we also need to be able to clearly identify these types so that every stakeholder in the company understands what type of innovation falls under which system. 

Managing innovation: the types we need to differentiate

For this reason, I would like to propose a new matrix to define innovation types. One that will allow for a unified and company-wide understanding of how to manage each type of innovation. One that tells every employee in the company which system applies when dealing with innovation. 

With sustaining innovation, even if we set up more efficient processes, the current system works in terms of management. Since the goal of this innovation is to contribute to the current model

With startup innovation, we need to adhere to the startup workbook. For there are alternative rules in managing and accounting necessary to successfully deal with these. They need a system that deals with their specific risk, longer timelines and a new way of working. Their goal is to find new models something that does not align with the current system. 

Let’s start using innovation types for the purpose they were designed for. Some are tools to let you think about innovation to pursue new opportunities. Some are there to help create or reconsider a strategy. This new matrix is here to help create company-wide clarity on what people should DO when interacting with innovation. To explain which system of management applies to which innovation initiative. Innovation is not a catch-all phrase, innovation matrixes shouldn’t be used for catch-all purposes either.

Setting up a dedicated management system for startup innovation is something that can be only done if there is a clear way of deciding what is what. Ultimately this is one of the necessary steps in professionalising innovation within your company.

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What is the Business Model Canvas?

The Business Model Canvas (BMC) is a strategic management and lean startup template for developing new or documenting existing business models. It is a visual chart with elements describing a firm’s or product’s value proposition, infrastructure, customers, and finances.

In other words, the BMC is a design tool for the creation or renewing of business models. The BMC is often used during ideation sessions and to regularly check the viability and feasibility of business models.

What is the NEXT Canvas?

The NEXT Canvas, however, is a product lifecycle framework used to test business models and track the progress of an idea turning into a validated and profitable business model.

The NEXT Canvas visualizes the four types of proof an idea needs: First, the team needs to prove there is a problem to solve, then that a solution can be created to solve that problem. After there is a proven solution, there needs to be proof that customers will pay and finally, the team needs to prove that the business model can scale.

The 4 steps from idea to proven business model

This is not a linear process. When proving the solution, the problem might need some zooming in and when the team is ready to prove the business model can scale, the whole NEXT Canvas needs to be reconsidered, to make the business model fit the larger customer segment. It is interesting to observe that it actually becomes harder to prove a business model the further the idea moves towards scale and not easier. The team is juggling with more and more puzzle pieces that have to fit together to make a business model work. The BMC is regularly used in this process to keep checking the viability and feasibility of the envisioned business model.

What is the difference?

The BMC is primarily used to design business models, where the NEXT Canvas is used to track the progress of teams from great idea to scale. The NEXT Canvas is also used for stage gates and portfolio management. When we map multiple teams onto the 4 stages we create a great funnel of all our innovation initiatives.

The NEXT Canvas and the BMC are thus not mutually exclusive but work well together as tools to create, test and renew ideas.

Our Innovation Manager offers a digital version of the NEXT Canvas both for teams as for portfolio management. Teams can use the Innovation manager to determine what is currently most risky and create, design and execute experiments. For innovation managers, it is a great tool to get insights into where each startup is in their maturity, and how fast they are moving towards scale.

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In our book The Corporate Startup, we describe what an innovation ecosystem is and how you can build an innovation ecosystem within your company. An ecosystem is needed to foster innovation company-wide, with the right governance in the right places, and multiple ways to do innovation. Where everyone knows how to do innovation, how to manage innovation, and how to look at innovation strategically. Asking the right questions at the right time.

We also describe the twelve building blocks of innovation that are needed to develop an ideal ecosystem for innovation. Implementing these one by one, however, is not necessarily a proven path to a successful ecosystem. I have seen many organizations trying to implement the blocks step by step only to see it fail halfway through. Transformation and innovation is not something that can be built with a roadmap. it needs exploring, testing and iterations. It is a process that will keep changing, just as the world around us is changing all the time.

So, what is a good way to start? That is where we introduce the MVE. A Minimal Viable Ecosystem from where you can start iterating and building out a thriving ecosystem for innovation. 
This sounds easy, but in practice, it is hard to see or understand what is needed in a Minimum Viable Ecosystem. I have seen companies building out a process and a set of innovation KPI’s and criteria for innovation accounting before having any teams or ideas going through it. There are companies that start with fully capable teams but no board members to ask them the right questions. Both routes are hard to pursue, how do you build out on one block when the other is dependant on it?

The model which visualizes the ingredients for an innovation ecoystem.

Working with so many companies and talking to even more, has made it clear that for an MVE to really work, it needs to be compromised of elements of the twelve building blocks. But those elements need to be evenly distributed across the three pillars of the ecosystem; Innovation Practice, Innovation Management, and Innovation Strategy. As soon as there are enough elements to form the Build-Measure-Learn loop and start interacting, is when the first version of your Ecosystem is ready to start iterating and growing.

If you want to start out with internal innovation teams with enough capabilities to run lean teams to show some early successes, you could start with teams that have help from outside coaches. Make sure, however, that they all work according to the first draft of an innovation framework and some initial key metrics to start testing the loop. From there, you can build out on an innovation model, and a framework that is suited for your organization. You can start improving the metrics and build out on portfolio management. And you can start educating on the right way of working and methodologies.

It is important to make sure that after every ‘learning’ you look at the bigger picture and evaluate what needs attention the most at that point. You cannot do innovation accounting if there are no teams running. You cannot test your process if nobody is really doing it. The board cannot develop an innovation thesis if there is no understanding of what that entails for the company and its strategy. Only a combination of the elements that interact with each other across the organization, is a good way to start testing. Get all the wheels turning to give you results to build on.

A combination of top-down and bottom-up hands-on innovation is where you should start. No matter how you organized innovation, you need the cogs to interact to be able to start the learning loop going.

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Apart from the well-known adagium, it is the most common answer I get when talking to companies about their most urgent reasons to innovate. “We need to! Our industry is being overtaken by startups left and right”. “We need to! How else are we going to survive when everything around us is changing so fast”. For most companies, it is that pain of realizing that the product lifecycle also has an end (or renew phase).

The need for innovation

According to Gijs van Wulffen, there are sweet spots for innovation
One is on the ‘up’ curve of your product lifecycle when the exploitation of the product is still in the growing phase. This moment has the advantage of having enough money to invest in innovation. There is also a higher chance of being able to have a longer-term vision since there is no real pain yet. It ensures you the time needed for ideas to come to life and mature, a process that often takes around 3 to 7 years.

The innovation sweet spots during the product life cycle.

The other sweet spot is on the downside of the curve when there are immediate urgency and pain. Most often this pain acts as a motivator. There is a ‘need’ to innovate rather than a ‘want’. It also, however, oftentimes prevents companies to dare and invest in risky and longer-term projects.

Once there is an immediate need to innovate, this urge is delegated by the board to all the employees in the company. Hoping that ‘innovation’ in general will make the company more future proof as a whole. Becoming more customer-centric as a company, or starting digital transformation within the company are often starting points for ‘innovation’ in general. Often overlooking the obvious question, what is it that needs innovating and what can we use to do that?

What does innovation mean in your company?

Innovation is a ‘big’ word. It makes sense to start defining what ‘innovation’ means in your company. Innovation can be several things, for different purposes. This is not a bad thing, as long as everyone agrees on these definitions and purposes. Once this is clear it makes sense to start asking how and by what means you can achieve this.

Why do you innovate?

Now if the reason for innovation was, “Otherwise we’d die!” the ‘what’ of innovation most probably will need to be a new business model to renew or replace the product lifecycle of the current one. The cause of the immediate pain and diminishing returns. However, from the companies that I have worked with over the years the ‘how’ almost always ended up being nothing more than an innovation lab that works on the companies operational excellence rather than its innovation excellence.

Product lifecycles

If we use the following matrix to plot innovation, dividing innovation into innovation of processes, innovation of products and innovation of technology. And divide these between improving current and creating new ones. Where does the new app go that optimizes conversation and communication of customer support and the back office? Or the machine learning tool that reduces the time that analysts need in a process? These all are excellent examples of innovation. But they both fit in the box process. An innovation on current processes, yes, but still only contributing to operational excellence.

The 3 horizons of innovation. Commit to risk and long-term. Innovate or die!

Commit to risks and long-term

This is not surprising if you realize that most companies have structures and processes in place that do not allow for risk. Or, when there is risk involved, demand for some sort of return within the time span of a year.
This process is often driven by years of cost-cutting and diminishing returns. This in itself is not a bad thing because these processes mean the survival of the current company. It is needed to be able to adjust to people’s demands. The core is the source of your resources for survival and those needed for innovation as well. But if your ultimate aim to innovate was to create new business models, it makes sense to purposefully commit to high risk and have a long-term vision towards innovation. Otherwise, all innovation that is attempted within a company, no matter how lean or customer-centric, will have a hard time moving past improving operational excellence.

For innovation excellence, the company needs to commit to risk and a longer-term vision of the future. They need to build a different process and structure that allows for exploration. Because a new and working business model is not built by one team doing a couple of design sprints. It takes several teams trying multiple initiatives to find out what works and what doesn’t. “Be patient and build an innovation process.” For the secret to success lies within the number of opportunities tried and learned from.

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Download the Canvas

Another canvas? Yes, but this one is different.

We all know the Business Model Canvas. The Business Model Canvas is a great design tool for creating and renewing business models.

The NEXT Canvas, however, is a product-lifecycle framework created to test ideas and track the progress from idea to a profitable business model.

The NEXT Canvas visualizes the four types of proof an idea needs to become a profitable business model: First, the team needs to prove there is an actual problem to solve. With a clear problem in mind, there is proof needed that a solution can be created to solve that problem. After there is a proven solution, there needs to be proof that customers will pay and finally, the team needs to prove that the business model can scale.

The 4 steps from idea to proven business model in the NEXT Canvas

1. Prove there is a problem

The most important part of any business model is the question what problem are you solving for which customer? The first stage of the canvas focusses on finding proof there is an actual problem. It helps you define an early customer segment and zoom in on the problem.

2. Prove your solution solves that problem

After you have defined the problem of your customer, it is important to understand why they would hire your solution. What job are they trying to get done? Only if you know that you can start thinking of a solution.

Of course, most corporate startup teams and even startup founders start with a solution in mind. A vision of a brighter future. It is important however to start at the beginning and define a clear problem. Otherwise, you won’t be able to create the perfect solution to solve that problem.

While working on your solution, you might notice that you are targeting the wrong customers or haven’t really nailed down the problem. It helps to make an iteration back to the Problem stage to revisit your assumptions and proof, to be able to build a product or service your customers want to use.

3. Prove they will pay

After building a solution that your customers want, it is important to prove this by first setting up the right metrics and then by proving your customers are actually willing to pay. There can be no profitable business model, without customers taking out their wallet and transferring money to yours.

At this stage, it regularly happens that it turns out the envisioned perfect customer segment is not willing to pay or not pay enough and you have to make a pivot. Making a pivot means you have to revisit all previous stages. From Problem to Solution and Revenue.

4. Prove you can scale

The hardest stage towards a profitable business model is proving you can scale. You have to be able to grow from an early evangelist customer segment to a much larger and broader segment that can help you scale. This broader customer segment has (slightly) other problems, has another job to be done, might need a different solution and might not want to pay the same or in the same way as your customer segment. You are now juggling all eight puzzle pieces from the canvas, to prove the final stage.

Origin of the NEXT Canvas

Credits where credits are due: The NEXT Canvas is based on the segments of the Business Model Canvas and took further inspiration from the Lean Canvas. We incorporated segments from Ash’s canvas because the Lean Canvas focusses on problem and solution, rather than key partners and key recourses.

We were using the Business Model Canvas and the Lean Canvas with both corporates and startups but were looking for a way to track the progress of the journey from idea to a working business model.

We realized that certain segments are tackled together: you really need to understand the problem of a specific customer segment, to be able to produce a value proposition on which you can base a solution. With this knowledge we reordered segments joining up related ones. Customer on the top row, the product on the bottom. Moving from left to right in way of time and the order in which these become important moving towards a profitable business model.

A lot of organizations we work with today recognize the innovation rhythm and the difference between searching and executing. The rhythm of innovation is different and less linear than that of other corporate processes. Innovation is the search for a business model of which we do not know if it will work, whereas corporates are used to execute a model that is already proven. The necessity to start with a framework and some form of process or unique governance for this innovation, however, is almost always looked upon as being counterintuitive.

Innovation is something that needs free reign, something you cannot control or measure, so why do we need a new process? It is an argument I frequently encounter. Although we agree with the fact that innovation is not something you can control, it is not true that it needs to live in a void.

Corporates have processes ingrained in them. Decisions are made by processes and governance that have existed for a long time. Sometimes we do not even realize that these processes throughout the company define culture and way of working. It is what is needed to scale certain ideas and agreements across a company. Without it, how would people know what decisions to make and why? Purposely not putting a process or governance in place will result in people interpreting how to deal with innovation on their own. Most will look to other processes or governances in place. Reverting to a process or governance that might not be relevant is always easier than not knowing how to deal with something. Not creating a common understanding of innovation will create a void that will only lead to confusion and misunderstanding. Voids are not possible within an organization. Automatically, existing governance will fill the space even if it is not suited for the occasion.

There needs to be a common understanding of not only why a company is innovating in certain areas, but also on how to deal with this and with what form of governance, thus creating clarity rather than confusion. Ensuring a sustainable environment for innovation throughout the company, with a clear framework and common governance. Aligning this with the business strategy will make it possible to effectively scale innovation across the entire organization.

The Corporate Startup

The best way to innovate is for a large company to view itself as an innovation ecosystem. Because of its core business, an established company cannot be as flexible as a startup, which can focus itself on creating one single product. Instead, established companies need to increase their innovation capabilities from within, without endangering their core business. This requires a big change in the organizational structure, which should ultimately lead to a company that can both search for new business models and execute existing ones.

The transition to an ambidextrous organization starts with a strategic recalibration and a new form of management. The organization has to create an innovation thesis, in which the organization predicts in a convincing way where their sector is heading and how innovation can be used to stay relevant.

Established companies need to stop thinking and acting like they are single monolithic organizations with one business model. Every contemporary company needs to build a balanced portfolio, a mix of established cash cow products and new products that are currently searching for profitable business models.

An innovation framework is necessary to analyze and manage the innovation portfolio. Beyond the three types of innovation (core, adjacent, and transformational), the framework is used to map the products in terms of where they are on their innovation journey. Mapping the portfolio across these two dimensions allows a company to not only get a sense of how balanced the portfolio is but also where products are on their innovation journey.

To measure how well innovation teams are doing in their search for profitable business models, it is not possible to use traditional financial KPIs. A new form of accountability is needed, called innovation accounting. A form of bookkeeping that uses alternative metrics, like the number of new ideas an organization generates, the percentage of innovations with a proven product/market fit or the speed of learning.

Innovation Practice is the cutting-edge face of an innovation ecosystem. This is where the rubber meets the road. It is where ideas are generated, tested and taken to scale. The other elements of the ecosystem cannot thrive without a great innovation practice in place. For example, a company cannot evolve its innovation thesis or balance its portfolio, if product teams are not testing new product ideas with customers.

How to implement a successful innovation ecosystem can be read in the second half of The Corporate Startup, or have a look at how our GroundControl software platform can help you with our best practices.

The topic of how to structure the perfect corporate innovation lab comes up regularly when talking to innovation managers.

Some corporates have one big central lab where all innovation happens. It’s a separate department or business unit with its own resources and budget. The down-side of this is that innovation happens far away from the day-to-day business. It is sometimes perceived as the playground where the cool guys go to have fun. But when a team is disbanded, it is also often hard to get the team members back into the “normal” business. They moved out of their business unit and are now working at a different department and often have to re-apply for their old jobs.

Other corporates have an innovation lab per business unit. That brings innovation closer to the business, but it also makes it harder to get enough resources out of the business units into the lab. Sharing learnings is also much harder if your labs are distributed among the company.

In the last couple of weeks, I have been thinking a lot about the startup studio model and how to apply that to corporate innovation.

startup studio, also known as a startup factory, or a venture builder, is a studio-like company that aims at building several companies in succession. (Source: Wikipedia) Just like a movie studio that creates multiple movies in succession, using shared resources and learnings to be successful. One of the best-known startup studios is Betaworks from New York, responsible for building companies like Bitly, Giphy, Dots, and Chartbeat. The studio takes internal or external founders and together with a team of shared experienced startup employees bring new ideas to life.

The great thing about the studio model is that you can have idea owners from the business that have an intrinsic motivation to bring their idea to a success, combined with a corporate startup team that becomes more experienced with every initiative they help bring to scale. When a corporate startup fails, or as we prefer to call it: gets invalidated, the idea owner can return to the business bringing with him valuable knowledge about corporate innovation to apply to the core business. The studio team can move on to the next corporate startup and help a new idea owner with a new corporate startup. That way you get studio teams that become more and more experienced combined with fresh minds that have an intrinsic motivation.

What I also like about this setup is that you can apply different types of innovation accounting as well. A regularly used metric for a startup studio is the number of startups that are founded in a year. When a studio startup has a meeting with their investment board, the board can then question whether they want to continue with an idea and invest more money and time, or free up the team and resources to try out a new idea. Because at the end of the year, the “startups founded”-metric needs to be met with a fixed amount of resources. Of course, there could be the luxury problem of too few, but really successful startups, but we have never encountered this. Labs that do not try out enough ideas, however, are much more common.

At NEXT Amsterdam we see that HR capabilities for innovation are in high demand but often in low supply. The great thing about the studio model is that the idea owners can help spread these innovation capabilities throughout the entire company. At the same time, the innovation lab is creating expert startup teams that learn by doing and act as coaches to expand the HR capabilities even more. This will slowly transform the company into a corporate innovation powerhouse.

If you’d like to learn more about the startup studio model and how to apply that to your innovation lab, we’d be happy to have a chat.

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