Business Cases Weren't Designed for Innovation

Innovation is a key driver of growth and is only going to increase in importance for organisations and the world as we look to come out of this economic downturn. Yet innovation is hard, risky and rarely successful.

In a study cited by Robert G. Copper in his book Winning at New Products he reveals that ‘for every seven new product ideas only one succeeds.’ And “most startups fail” says startup guru and author of the Lean Startup, Eric Ries.

Why is this? One reason is that our traditional approach to managing business as usual projects isn’t suited to innovation. Where the traditional business case and business plan rely on certainty, clear facts and data, and little change, when innovating we are dealing with uncertainty, complexity, and ambiguity. The solutions that we are creating are new and don’t exist yet, so there is little to no data on them to build an accurate and realistic business case. Furthermore, the business case is very time intensive and costly, and in innovation speed is of the essence and we’re often innovating on a tight budget.

So how do you validate innovation ideas when there is high uncertainty and ambiguity, and little data or hard evidence?

The Experimentation Method

A faster, less expensive, and more accurate approach for innovation and managing in volatility, uncertainty, complexity, and ambiguity (VUCA) is to take an experimentation method to choosing which ideas to take into development and commercialisation.

Experimentation is a process of continually generating a broad range of hypotheses, prototyping and testing them in fast small-scale experiments, and feeding the more successful concepts while pruning the failed ones.

Here are seven steps for running business experiments:

Start With Desirability

By the time you get to a short-list of solutions that you want to validate, you've most probably been 'workshopping' internally with little feedback from customers and potential customers for a wee while. Now it is time to get out into the real world and quickly and cheaply test if your target customers are equally excited about these ideas.

Your first phase of testing is not about finding whether you can feasibly build the solution. You want to find out whether, if you did build it, would it matter to the target customers.

The question is, 'Is it desirable?' Remember, the number one reason innovations and startups fail is because they don't have a market - they're not desirable. If we prove it is desirable, then we can move on to running experiments to explore other aspects of desirability (like pricing, customer relationships, and channels) and feasibility and viability.

Map The Business Model

The next step is to map out your solution into a Business Model or Lean Canvas. I like using the Business Model Canvas (with a few tweaks) because it helps you look at your solution at a business model level and capture the four main areas of developing a new business or innovation – customers, offer, infrastructure and financial viability. At this stage you won’t have all the answers; you’ll have to make some informed guesses. More on these guesses soon.

I've seen many experts and teams start their innovation projects with the Business Model or Lean Canvas: they have an idea and immediately start to fill out the canvas. In my view, based on my experience, there is no point completing a Business Model or Lean Canvas for a solution if you don't know yet it's desirable. This is just waste.

Identify Risks

In Steve Blank’s book The Startup Owner’s Manual, he states:

‘Every business model has a degree of uncertainty. Whether it is a new product, market or technology, each adds risk.’

The focus on this step is to efficiently identify which of our assumptions (guesses) pose the greatest risk, so we can then systematically de-risk the business model through experiments.

To identify the riskiest assumptions I use a Risk Matrix, which plots assumptions from low to high uncertainty versus low to high importance. The riskiest assumptions, which should be tested first, are those that are both highly uncertain and highly important to your idea. It’s then important to write them up as hypotheses that can be tested as true or false.

Design Experiments

Now we can start designing experiments to prove or disprove our hypotheses, de-risk our business model and validate the desirability, feasibility and viability of our ideas.

To design experiments I use an Experiment Brief which helps teams articulate: what they want to learn, what type of prototype and test is required, who the customer is, success criteria, duration of testing and action you will take if it passes or fails.

The key is to identify the most efficient way to test the riskiest assumptions and gain validated learning.

Prototype and Test

The next step is to build the prototype in the minimal form required to test your hypothesis and then run the test as expediently as possible. You test your prototype with the target customers identified in the Experiment Brief. The type of experiment your run will depend on what you want to learn. At the start of the innovation journey uncertainty for your idea is high, so your experiments should be low-fidelity and low-cost, keeping the cost of failure low. A prototype doesn’t usually have to be very complex in order to learn what you need to know. In fact, you’ll be surprised at how much quality feedback a customer can give you on a storyboard sketch that is far from perfect. As you progress and certainty increases you can spend more on higher fidelity experiments.

Capture Learnings

Following your tests you need to analyse the results to see if you’ve validated or invalidated your hypotheses and to identify key learnings. The more vivid and understandable your results, the more definitive they’ll be for you and the more convincing they’ll be for stakeholders.

In addition to validation of your hypotheses you want to capture the following: what the customers (or respondent) liked and disliked about your solution, any suggested improvements, and new questions, hypotheses and ideas to explore in the next iteration.

You can then make an informed decision on how best to proceed – whether you should progress, pivot or perish the idea. Success also includes walking away from ideas that aren’t going to fly.

Iterate

The next step is to update your Business Model or Lean Canvas and repeat the experimentation cycle.

At the end of this process you’ll have a short list of validated, robust and desirable solutions with de-risked business models that are feasible and viable, as well as some that have been justifiably perished.

Happy innovating,

Nathan

P.S. Thank you for reading, and if you enjoyed it, please like and/or reshare, and add your thoughts and questions into the comments or DM me.