Making innovation count

john bessant
11 min readFeb 3, 2022

Why measuring innovation matters

The great management writer W. Edwards Deming had a powerful introduction to his talks on quality management. Pulling out a dollar bill and waving it in front of the audience he would point out the wording: ‘In God we trust’ — and then go on to comment that in business life the same principle could be applied, but with the afterthought ‘…everything else we should measure’. His argument was simple; if we want to control something we need to make sure we measure it.

And that’s as true of innovation as any other business process. Although it can appear to be about inspiration, intuition and risk-taking the fact is that it’s a process and needs managing as such. That’s a point driven home by countless studies and it underpins the ISO standard (56000) for thinking about innovation as a manageable activity. And if we want to manage the process the first question we need to ask is can we measure it?

The good news is, of course, ‘yes’ but that begs a second question about what we can measure. Part of the problem with trying to manage innovation by the numbers is that there are so many different views on what can be measured and the relative importance of these. Certainly we can look at inputs — spending on R&D for example. And we can look at outputs — number of patents, percentage of sales derived from new products, number of ideas suggested by employees, etc. But the real challenge lies in finding ways to monitor and measure the process itself.

Let’s take an analogy — driving a car. Clearly there are important things we’d like to measure before we set off to ensure we’ve got a good chance of reaching our destination– have we got enough fuel in the tank (or battery), is there sufficient oil to stop the engine overheating, ditto water for the radiator, are the brakes and other safety systems in good condition? These days car manufacturers helpfully provide sensors which can display the status of all of these and warn us if there’s a problem before we let off the handbrake. They are all examples of input measures, reminding us of what we ought to put in place if we want to go travelling.

At the other end of our journey we can apply various ‘output’ measures — most importantly, did we reach our destination safely? But we can also measure other things which might help us in the future when we next choose to travel — for example, how long did it take us, how much fuel did we use, was it a comfortable journey, etc?

Image: Mike from Pexels

But the measurements we really rely on are those which give us information while we’re driving — and that hopefully give us warning if we need to make any corrections. If we’re going too fast, if the engine is too hot, if the tyre pressures are too low we need to do something about it.

The dashboard/driver display is the nerve centre of the whole process, and these days it’s moved on from the simple speedometer and rev counter to give us a wealth of real-time information. We can tell the status of all sorts of systems with a glance and even if we aren’t actively looking there are verbal and other warnings to attract our attention built in. The range of information available to us has grown and it is no longer confined to the performance of the vehicle itself; we now have access to a rich source of information about the wider context.

Navigation aids like GPS tell us not only where we are but what different routes are available should problems emerge on the road ahead. They take into account weather and accidents and road works to give us updated real time information about the wider world; importantly they also offer advice and guidance to assist our own decision making about course correction, speed and style of driving. With novel sensors built in we have access to predictive information, warning us of dangerous situations which might develop — carrying out a kind of forecasting operation on our behalf. In fact the biggest problem in control may be the sheer volume of information available to us and the competing demands it makes on our attention and decision-making capacity.

Of course managing innovation is a lot more complex than a simple car journey — not least because there is so much more uncertainty involved. A closer analogy might be to flying a plane where you are trying to navigate in 3D space, maintaining a healthy distance from other aircraft, dealing with changing weather conditions, keeping 400 tons of metal on a reasonably straight and level course and eventually landing it safely. Not for nothing do modern airliners have cockpits resembling Las Vegas in terms of the number of lights, dials, digital displays and other measurement indicators!

Image: Rafael Cosquiere from Pexels

From measurement to control

So innovation measurement is critical — and its absence shows up in pretty graphic fashion. Trying to run a start-up without keeping an eye on key variables like cash flow is a good recipe for quickly becoming an ‘end-up’. Project managers who don’t keep a sharp eye on key milestones and progress towards them may find themselves in trouble for overrunning budgets, falling behind timescales or missing key delivery dates or marketing windows. So far, so obvious; we need to monitor something as uncertain as innovation carefully.

But the real value of measurement isn’t that it tells us that we’re off course or running late — it’s that it gives us a chance to react, to change direction. Process control involves loops, not simply status monitoring. Sensors detect what’s going on, controllers work out what the implications are and decide on corrective action and actuators effect change to bring the system back under control. The earlier we detect drift away from our desired set point the sooner we can try to correct the situation;

Image:Dmitry Demidov from Pexels

Today’s emphasis on agile innovation reflects this, building in high frequency loops which allow for measurement and correction — pivoting. Importantly there’s also an element of learning; it’s not simply a matter of bringing things back under control but also learning for the future. Whether in a lean start-up or a major software project the same principle applies — a learning cycle. We can build into our controller a memory of what control action worked so as to improve its effectiveness over time.

It’s not just about the individual project; we can also deploy control loops at the strategic level reviewing progress across a portfolio of product, service and process innovation. The power of stage gates and other tools is that they monitor at a system level, looking at the big picture. Even if performance on some key process measures is adequate there may be questions about whether or not this is still the right thing to do in a rapidly changing environment. Sometimes it needs an unpopular decision — the kill/stop choice is a hard one to make but without it, (especially in public sector projects driven by strong political forces) we are likely to hear the lumbering sound of white elephants.

Image: Mike from Pexels

Sometimes this meta-level strategic control system intervenes to perform a course correction; sometimes it will involve a complete innovation system reset.

Take the case of ABC Electronics — a thriving player in the good old days of pre-liberalised telecoms in the UK. One major customer, the General Post Office and one new product development project every three years, replacing and upgrading the phones in the iconic red telephone kiosks. But fast forward to the days when they were riding the incredible growth wave around mobile phones. Their core expertise of acoustics, electronics and plastics moulding meant there were drowning in opportunities — with the result that they were taking on more and more projects but still trying to control them via the same old process. They were soon locked in a dangerous spiral of increasing costs, time overruns, unhappy customers and an accelerating crisis. It took a major reset to bring them out of this spin, changing the innovation management system to bring in key elements like portfolio management, stage gate controls and product management.

Experienced companies are not immune. For decades 3M were regular residents of the top echelons of league tables listing the world’s most innovative companies. But in the early years of the new millennium they began to slip down the rankings; by 2007 a Business Week cover feature was talking about ‘3M’s Innovation Crisis — How Six Sigma almost smothered its idea culture”. Careful reflection highlighted a problem with their control system; the enthusiastic adoption of six sigma principles had led to a tightening up of performance but in the process had squeezed out their capacity for radical breakthrough thinking. Once again a reset was needed to adjust the innovation control system to allow more freedom and flexibility back into their corporate innovation approach.

Perhaps one of the most significant shifts was that carried out at Procter and Gamble as it wrestled with the move towards ‘open innovation’. For nearly two centuries they had built and operated an effective innovation model based around R&D, generating all the technical and market knowledge they needed to deliver a steady stream of consumer product innovations. But an internal strategic review team sensed that they were increasingly missing out on opportunities being offered by an outside world rich in different and complementary knowledge. This culminated in the shift to ‘Connect and develop’, the banner beneath which they re-engineered their whole innovation system. Led from the top by new CEO Alan Lafley and with a clear (but for its time very ambitious) target of sourcing half its innovations from outside the programme was launched in 1999.

Close to a quarter of a century later and they are still adapting, putting in place new routines for external collaboration, letting go of others which had served them well over many years. The learning process has paid off; breakthrough innovations resulting from C&D include Olay Regenerist, Swiffer Dusters, the Crest SpinBrush and Glad ForceFlex refuse bags.

P&G’s continued growth has come in large measure from external ideas which now account for well over the targeted 50%.

Image:Andrea Piacquadio from Pexels

Innovation accounting

Whether course correction or full system reboot innovation management is about creativity and control. Which puts the measurement system at the heart of things. From the operational improvement loops typified by the ‘plan-do-check-act’ (PDCA) cycles which underpin shop-floor process innovation through to project-level control, innovation measurement not only gives us better control but also offers an opportunity to learn. PDCA tools continue to drive the kaizen approach (little improvements from everyone) which make lean and six sigma such powerful approaches; companies like Toyota can point to half a century or more of successful growth on the back of this. And what we’ve learned about innovation management at system level (embedded now in the ISO standard) has come in large measure from careful analysis of success and failure at the project level and building operating routines out of that.

In their excellent book on ‘Innovation accounting’ Dan Toma and Esther Gons argue this point strongly, placing particular emphasis on building a hierarchy of control based not only on a clear ‘dashboard’ of measures to manage the operational side but also developing measures around the long term strategic development of the organization. They focus on things like the building up of the knowledge base and the training and human resource systems designed to create and maintain a culture of innovation.

The timescale involved in such measurement systems need to be long; we’re talking about years before the effect of strategic investments into new knowledge or human resources might pay off. Take the case of the German company Hella, for much of the twentieth century a key supplier of lighting systems to the automobile industry. Back in the 1980s they thought long and hard about making the (then) risky move into micro-electronics. They had some experience in simple solid-state devices like flashers and brake lights but the move into a whole new field would be expensive and disruptive. They had to compete in a very tight labour market for the scarce skills involved, they had to find ways to house and equip a completely new development team and most important, they had to redesign their organization to integrate the new knowledge architecture involved in the shift.

Not surprisingly there were critics but the longer view prevailed. This proved fortunate for the business since the division which the small team grew into now accounts for around 60% of the company’s business and is their growth engine for the future, embedded in the increasingly intelligent and autonomous vehicles now moving from concept design to the streets outside.

Apart from the direct value of this investment it also helps reinforce the long-cycle strategic control system in the business. From its early days as a start-up back in the 19th century it has been faced with similar strategic choices about building capability and technical competence and it has learned to take a long view. Innovation strategy involves difficult decisions and they need a measurement system able to reflect these long term intangible benefits as much as the shorter-term returns on investment and other operational performance indicators.

Double loop learning

Another way of looking at this challenge comes from the work of Chris Argyris and Donald Schon and their concept of double loop learning. They argue that organizations not only need a control loop but also the capacity to step back and review and reset that control system — what they term ‘double loop learning’. In a highly simplified analogy it’s like a central heating or air conditioning system; the thermostat is a single loop control which makes sure the room temperature is maintained at the level we set it to. But changes in the environment — a sudden cold snap or heatwave- might mean we need to rethink our needs and step in to reset the controller.

It’s the same in organizations managing their innovation systems; they need this meta-level capacity to reflect and reset — dynamic capability. Which was something else which W. Edwards Deming was keen on. Outlining his famous ‘14 points for management’ in his book ‘Out of the crisis’ he laid particular emphasis on the role of strategic leadership to help ensure that the organization was able to ‘improve constantly and forever’. And he was pretty clear that doing this would involve much more than a slogan….

If you’d like more around the innovation theme please visit my website here

Or listen to my podcast here



john bessant

Innovation teacher/coach/researcher and these days trying to write songs, sketches and explore other ways to tell stories