The 2011 Moneyball movie starring Brad Pitt as coach Billy Beane of the Oakland Athletics is probably one of the most talked about movies in the lean startup community.

Based on real life events, the movie tells the story of a small budget baseball team turning the table on more financially potent rivals, using numbers. Numerous parallels have been drawn between the movie and lean innovation. This is mainly because lean startup methodology values evidence over faith when it comes to new business development.

It’s no surprise that enterprises are fast to adopt new trends, especially ones that might offer them a competitive advantage, and lean innovation is no different. Promoting speed over aesthetics and facts over opinions, is easy to see why numerous organizations were quick to embrace lean.

Unfortunately large organizations don’t have a good track record when it comes to adopting new methodologies. In some cases, some of the adopted methodologies never made it past the buzzwords. For some, lean will be no different.

For all it’s emphasis on validation and numbers it seems that the corporate adoption of lean follows the well established, faith based path. Read some blog posts, read some books, attend some conferences, pay for some workshops, ask some experts to come over for a keynote than take 6 months to make a well-detailed 5-years faith-based plan on how to end 5-years plans.

In somewhat of an anti-pattern fashion detailed lean transformation plans are put together with total disregard for measures and experiments.

AARRR Metrics Funnel DiagramHypocritically many lean transformation initiatives – promoting the use of numbers and evidence in decision making – are not created using the methods they promote. And that’s in spite of the fact that almost any action point of a lean transformation can be tracked and measured in a scientific manner.

Playing Moneyball in a corporate ecosystem implies the use of a measurable framework. A widely used metric framework in the lean startup community is the pirate metric system, AARRR. This is an acronym for the stages of the funnel users go through: acquisition, activation, retention, referral and revenue. Much in the same way, elements of a lean transformation (trainings, accelerators etc.) can be assigned to different stages of a funnel of an ecosystem. The benefits of doing this are that:

  • progress can be tracked,
  • impact can be measured,
  • expectation can be managed and
  • improvements can be implemented.

Following the mantra: if you can measure it you can manage it, the right type of initiatives for the company’s ecosystem can be selected by looking at numbers.

Investing in initiatives can and should be tied to measurable outcomes if the company is serious about being evidence driven (Moneyball). To this point, throughout 2013 to 2015 in a me-too frenzy wave many blue-chips created labs and accelerators. But, as expected, some were short lived. The point here is not that internal accelerators are bad for corporations and they shouldn’t be promoted. The point is that there needs to be clear reason for that decision other than the media buzz. A reason to take specific action or go down a certain path needs to consider the other elements of the ecosystem, as well as the other stages in the funnel.

Same can be said about venture arms or training programs – they need to fit the ecosystem’s need. And the only way to understand what the ecosystem needs is to measure its every stage.

Trying to plot an innovation ecosystem on a AARRR funnel is no easy feat. I’ll try doing in the following part but bare in mind it’s only an oversimplified version, intended to inspire you to do it for your own ecosystem in more detail.


The biggest question that needs to be answered at this stage of an innovation ecosystem funnel is: how many ideas are being generated by the ecosystem or enter the ecosystem?

One of the most trivial measurements of this stage would be the ‘numbers or idea generated or entering the ecosystem’. But other measurements can touch on the HR aspect of the ecosystem too.

If in an ecosystem not enough ideas are being generates the following initiatives can alleviate the problem:

  • hackatons
  • idea challenges
  • ideation training
  • design thinking training
  • university collaborations
  • startup collaborations
  • M&A

Activation: how many ideas are being worked on?


  • number of team being formed around ideas
  • number of ideas financed

Ecosystem initiatives for this stage:

  • management training
  • train the trainers program

Retention: how many ideas make it in the market?


  • percentage from the generated ideas adopted by business units
  • percentage from the generated ideas launched in the market
  • number of external companies invested in
  • number of spinoffs
  • number of experiments created

Ecosystem initiatives for this stage:

  • innovation lab
  • internal accelerator program
  • venture arm

Revenue: how much are the generated ideas worth?


  • percentage of revenue generated from ideas launched in the past 3 year
  • cost saved from ideas generated
  • overall cost of innovation

Ecosystem initiatives for this stage:

  • M&A (Internal and external)
  • Investments in startups
  • Joint ventures

Referral: is the ecosystem an evergreen one?


  • Number of new projects started from existing ones
  • Drop in hiring cost

Ecosystem initiatives for this stage:

  • Internal conferences
  • External conferences
  • Case studies
  • Entries in competitions

Designing an innovation ecosystem or adding new elements to an existing one are complex tasks requiring a preliminary understanding. All the moving parts need to be considered. If the ecosystem’s output is expected to be fact-based and numbers driven so should its design. Only by understanding how an innovation ecosystem works can it be continuously and systemically improved. And what better way than with numbers?