The Present! Understanding Innovation Accounting – a historical perspective – Part 2


The Present

Accounting is not the problem, but accounting has a problem

In this age of big data, extracting information is simple and cheap. The accounting tools we have available today are designed and work very well if we have historical data available. But when it comes to innovation you have little to no data – you have little to nothing you can use to make informed decisions.

The lack of relevant data is the very reason it is so risky to invest in innovative projects and indeed those initiatives and Startups are very likely to fail because traditional accounting methods are not efficient in handling this.

Another problem with standard accounting in the early stages of a risky project is the accounting department’s well-intended risk management is to not waste organisational resources. Early-stage innovation projects are very risky and management discounts it accordingly. Whoever pitches knows this and in order to demonstrate a high Internal Rate of Return (IRR) that justifies funding, they ramp up predictions to the maximum of rationalisation. This process tends to hide assumptions in the plan, rather than unearthing and tackling them. The need to ‘prove’ IRR so early on also gives very innovative projects little chance as they often don’t draw on existing assets but want to create them. Using existing assets of course makes IRR look a lot better. If at least in this specific case, IRR is the key metric for picking a project, it works against the very reason to fund the project in the first place. It makes breakthrough innovation that can future proof the company indeed less likely to come about.

Further, today’s accounting tools, especially when combined with a business plan projecting far into the future, leave insufficient room for adaptation. Especially for innovation projects, this can create an incentive to execute a plan on time and on budget that creates no value and only burns organisational resources even though teams and managers knew this a long time ago. This is because we can’t really measure innovation processes and produce reports to inform about the past present and future of a project or portfolio with today’s methods.

This is just an example of how accounting can be a systemic problem for innovation.

The effectiveness of today’s R&D budgets

According to Strategy&, a business unit within PWC, the problem with innovation budgets is so big that after analysing the 1000 most innovative companies in the world for over 12 years they found – ‘no statistically significant relationship between how much a company spends on its innovation efforts and its sustained financial performance’. There are several reasons for this but what is certain, is that simply spending more while still using a traditional approach, is likely not to pay off. 

Funding decisions are often made on the common belief in fiction, not facts (as there are very little knowns). The communication abilities and political talent of individuals are more important than the truth. What is always easy though, is to retrospectively rationalise a denial of responsibility.

‘Without data, you’re just another person with an opinion’

Thanks, W. Edwards Deming

A system that doesn’t honour managers and teams clearly stating the known unknowns of an emerging business model and a clever way to tackle those, is very likely to return nothing. It should not be too surprising that the question ‘whether to invest and if so, how much’ for a project with no significant traction, can hardly be determined based on a Net Present Value (NPV) calculated for years into the future. One thing is certain, the calculation will be wrong. 

How is it helpful to predict Cost Per Unit (CPU) when we are not even sure if the solution, we are envisioning really solves a customer problem and won’t change anymore? At worst it holds people accountable towards building something that nobody wants.


Accounting should assist in assessing the past, present and future performance of a company/project and subsequently, inform investment and management decisions. As predicting the future is very hard, we need a system that enables us to test the maximum amount of ideas to find the best ones.

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