#216: Is Your Innovation Strategic?
Innovation is not an act, it is an increasingly strategic organisational capability. Here's why you need both a strategy and an innovation operating model.
A Cruel World.
I don’t think I’m going to win any prizes for suggesting that we live in a high-change environment. In his excellent book ‘Range’, David Epstein calls it a ‘cruel world’. Its a world where your prior experience and knowledge becomes less useful, and in some cases completely irrelevant to the problems in front of you. Without a shadow of doubt the battering ram of change across businesses is Artificial Intelligence today. But consider the following multiple axes of change:
Geo Political Change:
We’ve had more major wars in the last 24 months than at any point since the second world war. The Russia / Ukraine war has, amongst other things, played havoc with manufacturing and food supply chains. The Israel/ Hamas/ Iran conflict is hitting trade routes. Many of the conflicts across the globe today are worsening. Businesses are impacted even when they are far from the epicentre of conflict. Last year when we were looking at changing our car, at least one major brand’s dealer told us that the earliest we could get a car would be in 12-15 months because a key component was manufactured in Ukraine and they were only able to operate one shift. Energy prices have been on a roller coaster. And not to forget, there is also the rolling aftershocks of Brexit in the UK - many businesses are still reporting worker shortages.
Pandemic, Health Tech And the Demographic Shift:
I’m combining a few things here but bear with me. The Pandemic was a black swan event - a one-off global catastrophe that threw everything off kilter. But we’re still feeling the longer term impacts of the changes - through hybrid work, long distance healthcare, and many aspects of workplace technology adoption. It also gave us a big jolting reminder about the fragility of our healthcare systems.
Health-tech is sweeping through our world, changing almost everything - this is largely a hugely positive thing. This includes everything from cancer cure via stem cell research or CRISPR, to genomics research, ectopic and artificial organs, digital twins of hearts and skin, and synthetic biology (which Mustapha Suleyman calls the second pillar shaping the world today, along with AI). Even seen through the commercial lens of any unrelated business, improvements in health-tech will lead to vast reclaiming of lost time and productivity. Or if you’re in the healthcare business, these are individual game changers.
Underlying all of this and possibly influenced by this is the increase in global longevity, drops in birth rates, and consequently the demographic shift to ageing populations. While this has a longer runway, the consequences are seismic - from shift of markets and consumers, to the societal challenges of care provision, and the shortage of (traditional) working age people.
Communications Transformation
It almost feels like a footnote, but there is a huge shift in communications technologies across the world. Many people see 5G as just the next serial increase from 3G or 4G. But beyond the bandwidth and speed, and the availability of the network, there are important differences with 5G which can make a huge difference. The primary amongst them is the intelligence and control of the network via software. The network can assign and constrict bandwidth across multiple scenarios as defined by software, which means that it can become hugely sensitive to specific situations, use cases, or edge scenarios. You can allocate more bandwidth in an emergency, to enable videos, geo-location, and other features, as a simple example. 6G will have AI enabled capabilities to do some of this intuitively.
Climate Change & Energy Transition
All of this is moot if we don’t have a planet, so the transition to a sustainable resource and environmental model is critical. The tide is turning very slowly and the commitments COP 27 may be too little too late, as the temperatures across the planet are still rising and becoming untenable. Sooner or later the change will have to come and the costs of change will just keep rising. One of the notable things this year at Davos was the lack of ESG conversations. It has long been my assertion that by expanding the goals to include all problems - such as education, and income inequality, it has actually diluted the sustainability challenge. But the central pillar of climate change and sustainability is still fundamental.
One of the areas where we are seeing the transition is the shift to renewable energy. The cost per unit of renewable energy - solar, wind etc. have fallen significantly. Fossil fuels have already dropped to 33% of the UK’s energy consumption, with renewables up to above 40%. In addition we are seeing the energy grid becoming smarter, with bi-directional movement of energy and more complex business models.
Technology:
This is the big one - and from where I live and work, a central driver. Within tech, AI is a primary change driver. And within AI, Gen AI gets a lot of the media coverage. So let me summarise this (because this alone could be the subject for many posts!)
Gen AI is all about language, context, meaning, and ‘generation’ - of words, pictures, and video. So Gen AI will continue to revolutionise how we use create and use language and images, which when you think about it is all communication and interaction. Gen AI will change (and become the default) human to machine interaction, and then even human to human interaction. Oh and along the way it will probably take over software development.
Other forms of AI, more broadly, are changing how we make decisions. All decisions are about categorisation, prediction, and optimisation. AI can do these things better, and at scale. While most businesses are thinking about use-cases, a top down view will emerge. Remember what Sam Altman said recently - a one person billion dollar business is possible.
Beyond AI, I believe Robotics will have a blowout year, and around the edges we’ll hear about mixed reality (Apple’s vision pro), neuromorpic computing, quantum, blockchain, drones and autonomous vehicles, and IoT & digital twins. Collectively they will transform almost every part of your business.
One ironic point that I always like to mention here is that these changes, as they apply cumulatively, can be seen as a tsunami of change. It feels like we’ve never seen this kind of simultaneous transformations in business, technology, health, energy, and communications before. But lest we forget, you could have had exactly this feeling 200 years ago looking around at the industrial revolution, with steam and electricity, telegraph and telephones, and huge spurts in life expectancy. It’s only now, looking back, that it all seems very glacial. And maybe a hundred years later, todays changes will also feel glacially slow!
Innovation: Your Change Muscle:
If you’re a CEO facing into all of this change, the one thing you’re going to want is an ability for the organisation to deal with change. And fundamentally, this is what innovation is. It’s your ability to deal with change effectively, consistently, and efficiently. When people ask me to define innovation, this is the definition I use - the ability to do new things in the business and do them well. We are used to the idea of working in your core areas of expertise and competence. But working in new areas, away from your competence is where innovation often lives.
Every company wants to be innovative. And as we’ve seen in the list of change drivers, every company needs to be as well. And in all the work we do for dozens of clients across industries, I don’t see a single business that lacks innovation ideas. But innovation is not about ideas, but rather, about outcomes.
Because most companies will tell you that their innovation efforts don’t deliver at the level that they need to. Occasional successes can be found, and many a PoC may have been built. But real innovation and change, measured by the number of PoCs and pilots that scale is still very small. The gap between ideas and outcomes is typically the domain of the innovation operating model.
The Innovation Operating Model
Historically, innovation was something some people did because they had some time or interest, and if it worked the business might pick it up. Almost as often, they would ignore it or pass on the option. History has record of many such instances - for every one Post It at 3M, there is an example of digital photography at Kodak. Companies like 3M and Google have been known for letting employees devote time to these experiments. But this is still at an individual level. Companies that are good at innovation are good at going from ‘people with ideas’ to ‘new business and operating models’. Broadly speaking there are a few established innovation patterns which we can see around us:
The industrial research complex - mastered by AT&T’s Bell Labs which gave us long distance telecommunication, but also radar, the silicon chip, satellite communications, and led indirectly to the creation of Silicon Valley as we know it.
The masters of adjacency - such as Amazon - who slice off the next layer to their existing business model - from ecommerce to logistics, and cloud services, for example.
Moonshot companies - such as Lego and pharma giants that have historically bet big on ideas, make and lose millions on them, and rely on winning more than losing in the long term.
Tech Plays - such as Octopus Energy, who have stormed the market with their tech platform Kraken. This is where companies create technology businesses out of their core industries with a combination of tech expertise and industry knowledge. You could say Amazon’s cloud business is similar, or Bosch’s IoT business.
All companies also of course have to keep doing marginal innovation which is the everyday, ongoing improvements that can and probably should actually be done by existing teams alongside their day jobs. But some of the other types need new skills, new risks, new funding models and new org structures. This is where your innovation operating model comes in.
Most organisations have some elements of this in place, but not all. And as the Anna Karenina model suggests, there are many ways to fail. Lacking a couple of the key pieces may cause you problems even if you have many others. This by the way is a core area of our work in the TCS Pace team. Aka the day job!
The Innovation Charter & Goals
One level above the operating model is the innovation vision and charter. If you ask a dozen companies ‘why do you want to innovate?’ You’ll get some common generic answers, such as improving CSAT and adding new revenues. But if you were to ask what specific goals or milestones exist for innovation efforts, you may find there is a wide range of answers even within each organisation, depending on who you ask. I believe every business should seek to articulate in 2 pages or less what they seek from their innovation efforts. It could be any or all of the following (or something else totally):
New revenues
New products
Uplift in customer experience / satisfaction / NPS
Reduction of costs
Improving the workplace and employee satisfaction
New business models
Support and accelerate transformation
This articulation is important because while everybody implicitly supports innovation, they may not all be clear about what innovation should deliver for the firm, especially in the short to medium term and with what relative priority. This charter will be critical as a mechanism to evaluate ideas that come through the business.
The Innovation Big Picture
In sum, the innovation big picture therefore involves scanning the environment, and picking the key trends that matter, being clear about the goals of your innovation function, and putting in place the right methodology and operating model to support this ambition. A financial services company who want innovation to drive new products, might look at the volatility and energy price spike and evaluate a new savings account that helps customers manage future financial shocks. The innovation function, when it works, is able to pick these kinds of signals, identify opportunities, help to evaluate them, and build the methodology and models for executing them. The operating model would enable the right tools, platforms, funding models, methodologies, and governance.
Remember successful innovation companies don’t do this once. It’s a repeatable, dependable model for them. This is why we call it an innovation muscle. It’s a function, or a capability, not an act. And in the cruel world we live in, it absolutely needs to be a strategic capability.
AI Reading
ACI - Capable AI: A very interesting take on the evolution of AI, as it goes from narrow AI to AGI, we are getting to the interim phase of ‘Capable AI’ or ACI - another phrase coined by Mustapha Suleyman. In a nutshell, it’s the stage where AI has ‘dog-like’ intelligence before it gets to human intelligence (AGI), and beyond to super intelligence (ASI). We might be at the ACI for a while, given the various limitations of technology, business, and public policy which will all create drags on the adoption of AI.
Open AI Sora: as you might have noticed, Open AI have announced Sora (only available to a select few people) which allows the generation of rich video from a few lines of descriptive text. No doubt Google, Meta, and others will follow. And in an election year, AI generated video will no doubt raise significant concerns.
News AI: Meanwhile Microsoft has tied up with Semafor to create an AI generated newsfeed called ‘Signals’. This may be the first of many. And given that the NYT is suing OpenAI, it makes for a full circle of Generative AI taking from and returning to news media. (Reuters)
Voices Lost: This is haunting / creepy/ disturbing - all depending on your point of view. the activists campaigning against guns are using AI to bring back the voices of school shooting victims, with the permission of their parents. (WSJ)
Other Reading
Robots - Big in Japan: Japan has a huge labour shortage, which is not surprising given that 30% of the population is above 65. For instance, construction industry workers total declined by 30% from 1997. There is a projected shortage of 11m workers by 2040. As a consequence, many sectors, including construction, retail, agriculture are turning to tech and will soon be reliant on robots, drones, avatars, and even autonomous ducks! (FT)
Davos Summary: Reflecting back on Davos again, it turns out that some of the key themes that captured the consciousness of the worlds leaders included: ensuring AI has a strong diversity and inclusion agenda, managing a regulatory tipping point, driving digitisation for good, and ensuring we have the right models for critical minerals, and noticeably, not much about ESG.
The Town that Ozempic Built: this is a fascinating story about the impact that the success of Ozempic and Wegovy have had on the home town of Novo Nordisk and the surge in wealth and lifestyles there.
PayTM challenges: we’ve been big fans of the payments revolution in India but one of the major players has run into trouble over its ‘persistent non-compliance’. Their banking licenses have been suspended and PayTM are having to scramble to keep parts of their businesses running. (Bloomberg)
Neurons and Learning: Last week I wrote about neuromorphic computing, so its quite a nice follow on to see this piece in my feed which talks in some detail about the learning models and AI.
Fixing San Francisco: As somebody who has agonised about the decline of San Francisco, I love this piece about the attempt to fix the city’s problems.
Thanks for reading and see you next week!