Innovation Accounting: A way to measure R&D performance
If you read Lean Startup by Eric Ries, one topic you’ll find difficult to comprehend is of Innovative Accounting. The reason of incomprehensibility and importance of the term has been explained by Eric itself in one of his answers on Quora:
I don’t find this especially surprising. People love the parts of Lean Startup that can fit on a bumper sticker or t-shirt. Slogans like “get out of the building” or “minimum viable product” are way more fun than the dry drudgery of accounting. And yet, there’s absolutely no way for us to make the massive changes as a movement that we are striving for if we don’t make reforms to accounting and the accountability systems it drives in most corporations.
The essential problem is: during the long, flat part of the hockey stick, how do we know if we are making progress? How do we keep from deluding ourselves? And how to convince key allies – like our funders – that we are moving in the right direction?
Simply put, innovation accounting helps in:
- Finding and assigning metrics of growth
- Measuring progress without using revenue as KPI
- Making sure you are on the right track
At that time, I wondered is a concept for a startup can be implemented in an Enterprise? Recently I came across an article by Dan where he explained how the concept could be used in an organization. You can read his take by clicking here which I’ve compiled in the concise form below.
As per Dan, one mistake most of the organization make is that they don’t separate the innovation dept KPI from their regular KPIs. Rather than the regular KPIs which are detrimental to individual motivation and overall innovation goal of an R&D team and a complete organization, the below three KPIs should be followed.
- Reporting KPIs
- Governance KPIs
- Global KPIs
Let’s discuss these KPIs in detail.
It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.
— Mark Twain
Reporting KPIs are focused to check the progress made from an ideation stage to prototype and finally to the product-market fit. Under these KPIs metrics like the number of hypotheses validated/invalidate, a number of experiments conducted, the number of prototypes built, the number of MVPs, etc., are considered.
Dan further suggests that some of these KPIs could be a vanity metric and may not provide any actionable insights at all. Hence, he suggests the use of actionable KPIs like Cost Per Learning, Time-Cost Per learning, and Validation Velocity under Reporting KPIs. Below is a succinct overview of why to use these KPIs:
Cost Per Learning
Cost per learning is a better KPI than the number of MVPs built or prototypes built as focusing on cost per learning will inspire the R&D team to conduct more experiments. For example, if you allocate a budget of $100k to a team and their build one prototype which fails, their cost per learning would be $100k. However, under the number of prototypes built/failed, a team may look good as they failed at only one prototype.
The number of MVPs/Prototypes KPI discourage a team to create multiple prototypes as their performance sheet look bad when there are 10 failed products. On the other hand, if the cost per learning would be a KPI, a team would be more inclined to build more prototypes. And with each prototype, say if 10 got to build on the same budget of $100k, the cost per learning would be less and a subsequent prototype would be better than the last one.
Time-Cost Per Learning
This KPI focuses on how fast a learning cycle got completed and is directly related to the KPI above. If a Time-Cost per Learning is small, moving from ideation to the final product stage will be quicker.
It is the KPI that measures the speed with which assumptions and hypothesis were validated/invalidated while moving from ideation to prototype and finally to product-market fit.
Governing KPIs are instrumental in the selection of new ideas for funding or for continuing fund supplies to already funded ideas. These KPIs also are conducive to an idea of moving from the ideation to market-fit stage than revenue. Depending upon different stages, below KPIs could be used:
This is the stage where an organization makes funding decisions when a team displays that they have located a problem as well a solution that has a considerable market.
Product Market Fit
Under this KPI, a team has to prove it has built a prototype with a right product-market fit and has a sustainable business model. If a team proves so, further funding decisions are made by management.
Knowledge to Assumption Ratio
Knowledge to Assumption ratio is governance KPI which gives intel on how close a team they are about to fund is close to having a product market fit. Close a team’s knowledge to assumption ration is to 1, higher are its chances of having a product market fit.
Barebones Net Present Value (NPV) is a concept given by Prof. Rita McGrath which Dan describes as an art of pulling the plug. This KPI gives you a few parameters on the basis of which you can make a funding decision. You can explore the Barebones NPV in detail from these links: Link1, Link2.
Governance and Operational KPIs alone are not enough for Corporate C-Suite to evaluate the performance of the innovation department, writes Dan. Global KPIs with a focus on ROI help C-suite to find whether their innovation department is successful or not.
These KPIs stem from the idea that overall investment made on innovation dept. should lead to an increase in the wealth of an organization. Following metrics fall under the global KPIs:
Innovation Contribution: This KPI measures the % contribution in revenue coming from the products launched by the innovation team.
Cohort Performance: Under this KPI, the innovation dept of an organization should be performing better than the cohort of the last quarter.
Innovation Conversion: Under this KPI, the number of old customers adopting new products is measured. These new products could or couldn’t be a replacement of an old product by the same organization.