Fluxx has helped organisations such as general insurance providers LV=, engineers Atkins, the Royal Opera House, retailer Argos and gaming providers William Hill create new services. As a leader in innovation services they will take part in the Innovation Leadership Summit challenger vendor presentations. All 100 attendees to the Innovation Leadership Summit, created and moderated by CIO editor Mark Chillingworth will receive the latest book by Fluxx: Unthinkable – the culture and politics of getting innovation wrong. The book guides business leaders through the challenges of creating an innovative culture and rethinking their products and services. In our lead up to the inaugural Innovation Leadership Summit, Fluxx share their thoughts on the principles for revolution.
1.Get the right idea before getting the idea right
Don’t let the potential execution of your genius idea trample over identifying your genius idea in the first place.
It’s tempting to have an idea, visualise how you think it would work as an end product, and get on with designing and building it, assuming that you have all the answers you need. However, by doing this, you may well not be capitalising on the opportunity or insight that led you to the idea in the first place. Or worse, your original insight might be completely invalid.
It is this homework that is so important to the success of new products – ensuring you understand the essence of the idea, that the problem you are trying to solve, or the opportunity you are trying to exploit actually exists – and then getting it into shape as a proposition that delivers on the promise of that idea. This means a proposition that meets the needs of customers, that is feasible to make, and viable to operate. Only then can you really think about the best possible execution.
The essence of a product is determined by unravelling a proposed solution until you get back to the core insight that led you to the idea in the first place. Once unravelled, you can clearly see the difference between idea and execution, and you can formulate that original idea as a hypothesis you can later test.
When you do this your ideas about the execution usually change dramatically as you discover more about the value that the proposition has to end consumers, and the feasibility and viability of the execution.
The desire to skip the proposition development phase and get straight into the production of that idea is a recipe for disaster. All of these things must be understood before you can decide on the execution and start building in earnest:
- Desirability – will customers want it?
- Feasibility – can it be made?
- Viability – can it make a profit?
The proposition must at this stage tell you who you believe you are going to sell the product to, and how you are going to sell it – what are the distribution networks, who are the partners, how will your product be presented? You must have convincing hypotheses on whether or not customers will buy it, and what their choices and motivations are when they do.
- Stop making predictions and start experimenting
Without a doubt, the number one cause of missed targets is the setting of targets.
The rule here is that if you’ve been asked by your boss to predict how successful your innovation will be, you are no longer in the innovation game.
You must avoid being pulled into predictive behaviour too early. Companies that require this sort of forecasting in the early stages of product development are doing nothing more sophisticated than asking to be lied to, albeit with complex-looking spreadsheets and graphs to support those lies.
We’re not averse to a litmus test of viability – a rough calculation where you work out what constitutes a significant product in the world of your normal business, and working back to see if it’s feasible to build it at the right cost, or reach enough of a consumer base. But we stop short at making grand predictions of future success.
- At Fluxx, we call this the “Numbers Game” – someone sets an arbitrary target of profit we want to achieve, and we work out how many sales or customers we would need to achieve this arbitrary, but compelling number.
- What this process does is not make any predictions, but rather, it highlights what we don’t know, and shows us what things would have to be true to make us successful – it also allows us to sanity check our customer or sales requirements against other known businesses .
- This exercise is not a business case or a predictive exercise, it is simply an activity that highlights the potential weak links in the chain we know we’ll have to look at in more detail later.
- We are always careful not to allow these numbers to turn into targets or predictions.
As described in The Other Side of Innovation (p. 146), there is an interesting cognitive bias when business targets are missed. It makes us assume that outcomes were too low, rather than the predictions too high.
What experimenting does is bring increasing levels of certainty to some of the numbers that underpin the calculations in our Numbers Game. A series of small experiments steadily evolves your understanding of what something will actually take to deliver, how customers will react to it, and therefore the likelihood of achieving the numbers you need to make the business stack up.
As our good friend Shed Simove says; “experiments don’t succeed or fail, they merely have outcomes”. Experiments will have hypotheses to test, for sure, but whether a hypothesis is validated or not should not be seen as a business target hit or missed, but rather simply as something you’ve learned that will improve the product you’re working on.
The ‘big bets’ culture has businesses agonising over say, a £2m investment for a new product based on no actual evidence. Rather than take this one huge bet, the experimenting method proposes we take a series of much smaller bets, say twenty £100,000 bets, or even two hundred £2,000 bets, and in the process learn a massive amount about the market, theproduct and what is likely to work, and we then of course have the ability to stop at any time without losing face.
- With these much smaller budgets, we free up more investment to explore more areas of opportunity, and also reduce the level of predictive promises that business teams require from each other in return for releasing that capital.
- Remember, the smaller the “I”, the less we care about the “R” in ROI…
- Learn from what people do, not what they say they will do
We know that we are bad at predicting how other people will behave. Why then would our customers be any better than us at predicting how they themselves will behave?
There is a fiction persisted by researchers that we can find out what people will do in the future, or indeed discover why they did something in the past, by simply asking them.
What these methods don’t account for is simply that people lie. They don’t do it maliciously, but they craft responses to market research based on a complex set of very human considerations:
- How will my answer affect someone’s perception of me?
- Will my answer prejudice some benefit to me or to my fellow humans at some point in the future?
- How would other people want me to answer?
- How can I look clever to the rest of the group?
- How does the researcher who paid me money and put a glass of wine in my hand want me to respond?
We need to find new ways to find out what customers care about, and how they will actually react to the products we are developing.
- Build a team to learn, not to ‘succeed’
Probably best Jeremy Clark quote in Pretotyping@work is: “Wake up, Pollyanna: MOST NEW IDEAS FAIL”. Clark and his colleague Alberto Savoia also coin the brilliantly reversed catchphrase “Failure is an option”.
When you are in the incubation phase, the results of any experiments or studies should not impact the wellbeing of individuals, or the team itself. The reality is that this can be very difficult to do.
Left to their own devices, teams are very likely to become emotionally attached to the ideas on which they are working, and they are likely to make a connection between this idea and advancement in their careers. However, outcomes must impact on the idea itself and not on the team that learned of the outcomes – in other words, we must thank the messenger, not shoot them.
The measure of success, and therefore the basis of rewards and advancement for the team, must be their ability to learn, and to generate learning. We must reward our staff’s own behaviours, and not the behaviour of the markets. If we incentivise our people to produce results, then they will bias themselves to find positive outcomes – regardless of what they have learned in the process about the suitability of the idea for our business.
We should reward responsible, honest behaviour, as that’s the only way we will know when it’s right to start, or shut down a project.
Get people used to moving on quickly with no stigma attached. As much discipline should be felt in de-funding projects as went into funding them in the first place.
- When shutting down a larger initiative, you need to spend time to ensure the learnings are understood and retained, and that the team involved see it as the right thing to do – not a reflection on their abilities.
- The advantage of having a centralised function that deals with new product development is that they can retain the knowledge and learnings from everything, regardless of whether or not it went to market – and also that they see every outcome as acceptable, not as a personal failure.
Don’t keep failure a secret. The innovation team must get used to giving bad news as well as good. And the board (or whatever executive exists) must get used to receiving it.
- Unless you’re incredibly lucky, there’s going to be more bad news than good news coming.
- Attempts to conceal the bad news or magically transform it into good news are futile.
Regular grown-up conversations are critical to a sane innovation process. They also provide a platform for the innovation team’s work to be shared with the business – which may of course make for some quite unexpected successes, through other parts of the business making use of what has been learned.
- Do something
As you will discover very early on in any innovation programme you launch, the lists of reasons not to do something will always be longer than the list of reasons to do it. But to not even attempt doing something is to admit defeat from the outset.
The number one characteristic of successful innovators is an on-going enthusiasm and tenacity.Without any success or failure, there is nothing to learn from, just a void – a total lack of knowledge or information.
Doing something will start to fill that void with evidence rather than opinions – and increase your confidence about what to do next. Leaving the void empty will paralyse you.
To meet Fluxx and join 100 peers and secure the last places at the 2016 Innovation Leadership Summit request a ticket at: http://horizoncio.network/2016-innovation-leadership-summit/