As a manager, I always felt incredible pressure to innovate. Yet it was hard to know how to go about it. There were plenty of books about high flying companies, but those same organizations seemed to sputter out almost as soon as the ink was dry. I wanted to know how to innovate consistently, not just fly high and then flame out.
That’s what started me on the journey that led to my book, Mapping Innovation. Over the last decade, I’ve talked to hundreds of executives, entrepreneurs and scientists looking for what they had in common. What I found surprised me and has changed the way I look at innovation ever since.
The organizations I studied were all very different. Some were hard-charging, others fairly conservative. Some were centralized, others decentralized. Some innovators were charismatic, but others were soft-spoken and introspective. Yet the one thing they all had in common was their willingness to explore and that, it seems, is what makes all the difference.
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Early digital computers weren’t very useful. Sure, they were far more powerful than the punch card tabulating machines that they replaced, but they were devilishly hard to program. Instructions needed to be written in assembly code, which was time consuming and difficult.
That began to change when John Backus developed FORTRAN in the early 1950s, which replaced assembly language into command statements that compiled the lower level code into something that roughly resembled English. Later languages built on that basic logic, compiling commands of low level code into something simpler still.
Today, there’s a similar movement underway to transform code into visual interfaces by companies like Quick Base, Mendix and Zudy. Much like the shift from assembly code to FORTRAN, the underlying code is still there, but it can be represented more simply. These low-code/no-code platforms are beginning to disrupt how software powers enterprises.
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“Culture isn’t just one aspect of the game,” Lou Gerstner wrote in the memoir of his historic turnaround at IBM, Who Says Elephants Can’t Dance? “It is the game. What does the culture reward and punish – individual achievement or team play, risk taking or consensus building?” Culture is, in many ways, is how an enterprise honors its mission.
Yet all too often, culture becomes an excuse for uniformity. Managers hire people like themselves and encourage their people to see things the same way, which can hinder a team’s ability to take on new ideas. On the other hand, studies have shown that diversity can create discord that can make it hard to get things done.
Clearly, we need to balance diversity with cohesion, but that not as easy as it would seem. It takes more than just putting people of diverse backgrounds and perspectives together and seeing what happens, you need a strategy to help them to work together. So while building a diverse team is a worthy goal, we need to put some thought into how to make it work.
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Go to any conference these days and innovation is almost sure to come up. When it does, you can be just as sure you will see something Steve Jobs said, something Elon Musk did (or plans to do) and some doomsday scenario about how robots will make us all obsolete (if they haven’t already).
There are good reasons for this. Our world is changing faster than ever and companies don’t last nearly as long as they used to. In some cases, entire industries are swept away by the rising tide of new technology. We’re not only creating machines that think, but editing genes and manipulating materials on the molecular level.
These are exciting, but confusing times. Unfortunately, that leaves a lot of room for hucksters selling gimmicks and every conference has its share of them as well. They tend to be long on buzzwords and short on any real experience or track record of accomplishment. Nevertheless, they can be incredibly convincing. Here are four ideas you should be looking to avoid:
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Ideas fuel business. They drive how we respond to customer problems and leverage market opportunities. The right idea can make a business work and, over time, our successes become ingrained in our mental models. The opposite is also true. If we begin with the wrong mental model, important problems become impossible to solve.
Consider the labor participation rate for prime working adults, which despite the recovery is still three points below where it was in the 1990s. Some believe that people aren’t working because they lack incentives. But the evidence shows that the problem is more rooted in the opioid crisis and high incarceration rates.
Clearly, if you believe that a lack of incentives is the root of the problem, you’d want to adopt “tough love” policies like making cuts to the safety net. However, once you understand that incarceration rates and opioids are to blame, you can begin to make an impact. It’s the same in business. The right mental model can push you forward, the wrong one will end badly.
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The recent scandal involving Facebook and Cambridge Analytical was different than most other breeches, because it wasn’t a breech at all. Cambridge Analytica simply walked through the front door, took the data it wanted and then moved it back to its own servers to be used for a completely different purpose than was intended.
We derive enormous benefits from having our data shared. As Sheryl Sandberg pointed out, without data, Facebook would have to be a paid service. The same goes for Google and every other ad supported business on the web. Yet there is a dark side of technology and data sharing is its greatest vulnerability.
Data sharing goes far beyond social media. We want doctors to share our data so that we can get medical treatment. Banks needs information about us so that they can extend credit. Law enforcement needs access to data to keep us safe. Yet each one of these activities exposes us. It’s not just Facebook, the Internet is broken, but new technologies may be able to fix it
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One of the most interesting things I discuss in my book Mapping Innovation is what I call the new era of innovation, which will create profoundly new technologies, classes of data and business models. It is likely to be the most important shift we’ve seen in at least 50 years and perhaps in a century.
To understand the size of the shift, imagine yourself as the CEO of a Dow component company in 1918. The impacts of the major technological forces that will shape the 20th century are not yet clear, but their capacity for disruption will be so great that your company has only roughly 50% chance of surviving the next decade.
The nascent forces at work today may be just as profound and it’s critically important to begin to explore and understand them because they will shape business models for decades to come. Much like a century ago, it will not be enough to simply wait to see their impact and adapt. If you want to win the future, you have to prepare to shape it — or someone else will.
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In Mindset, psychologist Carol Dweck argues, based on decades of research, that how we see ourselves is a major factor in what we can achieve. Whether it is children in school or executives in a boardroom, the mindset people adopt has a significant influence on how they perform.
Yet what she doesn’t say is that we need different mindsets for different jobs. A successful mindset for one set of tasks may hinder our performance in another. For example, aggression and competitiveness may work great for a professional athlete on the field, but not so great for building a productive home life.
Most of the changes in mindset we need to make, however, are far more subtle. They lack the social and environmental cues of the delineation between work and home life. So we always need to be looking for when best practices in one area lead to poor performance in another and shift our mental models accordingly. In an age of disruption, we need to learn to adapt.
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We all have a change we want to see happen. For some of us, it is something in our organization or industry. Other times, it is something in our community or throughout society as a whole. That’s why people start companies or join groups at church and school. Sometimes groups connect with other groups and the call for change becomes a movement.
Creating true change is never easy. Most startups fail. Most community groups never get beyond small local actions and, even when a spark catches fire, as in the case of the Occupy movement, it often seems to fizzle out almost as fast. The status quo is, almost by definition, well-entrenched and never gives up without a fight.
Yet the kids from Stoneman Douglas High School seem to be succeeding where so many others have failed. Their “March for our Lives” protest was one of the biggest since the Vietnam War and they seem to be getting real results. Their home state of Florida has already passed new gun legislation and other states plan to do the same. Here’s why they’re winning:
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We were told that “data is the new oil.” The Internet of Things combined with the ability to store massive amounts of data and powerful new analytical techniques like machine learning would help derive important new insights, automate processes and transform business models. It seemed like a massive opportunity.
Yet Gartner analyst Nick Heudecker estimates as many as 85% of big data projects fail, due to a lack of data skills, poor internal coordination between departments and lack of integration with line managers and staff. Implementing a big data project, it seems, is far more challenging than installing a new email system.
The news isn’t all bad. A survey by Deloitte of “aggressive adopters” of cognitive technologies found 76% believe that they will “substantially transform” their companies within the next three years. So while big data and cognitive technologies are no panacea, they can deliver value, if pursued wisely. Here’s how you can keep your data project from going off the rails.
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