About the PodcastThe Innovation Metrics podcast provides insights on measuring innovation, innovation accounting and managing the uncertain process of developing new, sustainable and profitable business models.About the EpisodeTristan Kromer speaks with us about the pitfalls of early-stage predictions in startups and corporate innovation initiatives, and how to drastically improve them. “It’s ok to ask innovators how a business is going to make money and how much. The problem is the way we traditionally expect them to produce the answer. The way we frame it can’t be answered effectively.”An emerging concept, enabling effective Innovation accounting, is to express variables as a range of likelihood not as single numbers. Subsequently, the outcome of the financial or mission impact model can be expressed as a range of likelihood rather than a wildly optimistic estimation of a single number. This enables innovators to quantify the uncertainty of each variable and the entire project. The innovation team’s job is to gather new insights and reduce uncertainty. Innovation accounting enables them to feed this back into the model by changing the estimated ranges and quantify what they have learned. By narrowing down the ranges based on a new insight teams gain the ability to demonstrate progress in a quantifiable way even before a product is launched.Topics and Insights (03:15) Nobody in innovation is happy with the way predictions are made.  (07:00) Business cases tend not to be terrible when there is enough historical data available. (10:15) Human behaviour usually causes the most uncertainty. (12:00) There are legitimate reasons not to invest in innovation.(16:00) Asking if and how a startup will eventually make money is a fair question but the way the question is usually framed can’t be answered effectively. (18:00) Even businesses with a 10 year trading history have mostly terrible business cases. Warren Buffet who is known to only invest in companies with a long track record does not listen to forecasters when allocating resources. (“There is no business so lousy it can’t get a wonderful projection” – Charlie Munger.)(20:30) Typical business cases don’t inform about uncertainty effectively. (21:30) Asking for best case, worst case estimation and dividing them by two is hardly an improvement. The solution to understanding uncertainty better is to allow for ranges. (24:30) Allowing for ranges is great for any type of project, not just innovation.(25:40) Expressing things in ranges has many benefits, amongst them, that it makes predictions more honest and more accurate. It also increases the sense of psychological safety and is simply easier.  (28:00) If innovation accounting can assist in solving the problem of biases and favouring talented storytellers in securing funding. (29:30) Methods to battle certain biases during resource allocation. (31:15) On the usefulness of templates for auditioning.(33:00) Innovation accounting can measure and demonstrate progress by narrowing down the ranges. (36:40) In a state of extreme uncertainty, a little bit of...

Ver todos los episodios