Innovation and the Paradox of the Information Age
[This is the third article in a series on innovation — the previous post can be found here]
It’s a new year and no doubt many of you have devised or received an annual goal related to innovation. I can picture some of you scratching your heads wondering what you can do — or, worse, I picture others sitting in off-site meetings discussing what innovation means and how to make it happen.
In my last post, I noted how many companies struggle with innovation and would benefit from a rigorous, scientific approach. Innovation in this instance means the introduction of new products, processes and other developments that solve problems, derive from analysis and create economic value for customers. Much like a science, innovation can be broken down into a systematic approach that comprises three building blocks, which I define as the Who, the What and the How.
In this post, I’ll focus on the How block of that framework where I recommend organizations move from qualitative to quantitative feedback. I’ll highlight a few examples of data-driven companies that use a variety of sources to deliver innovative solutions.
The lesson is that innovative businesses have a clear understanding of their customer, know what information matters and combine data from multiple sources to make informed decisions.
Every Cloud has a Dreamliner
Boeing’s 787 Dreamliner program has been my go-to case study on the good, the bad and the ugly of innovation. I can’t think of a starker example of where two competitors had such opposing views of the future and such divergent outcomes. During the 1990s, both Airbus and Boeing were planning for their next big idea. Airbus envisioned a future where the then-emerging “hub and spoke” model of air travel would prevail. Boeing, on the other hand, developed a vision where “user experience” that didn’t involve connecting flights would be core to its success.
The first commercial flight of Airbus’ A380 jumbo jet took place in 2007; since then, Airbus has delivered 210 planes to 17 customers and has a backlog of 315 to deliver. Airbus has already announced that it will ramp down production of this model in 2018 and, if recent news articles are accurate, may exit the program entirely — just 10 years after its first commercial flight. In comparison, the first commercial flight of Boeing’s 787 took place in 2011; since then, Boeing has delivered 500 planes to 65+ customers and has a backlog of 700 that will keep its production facilities in South Carolina and Washington busy for the foreseeable future.
Marketplace insight was at the core of Boeing’s product development strategy to build the next generation aircraft for its users — including crew, mechanics and passengers. The design of the 787 was based on more than 50 focus groups and scientific studies, held over multiple years, where Boeing engineers educated themselves on what users wanted. Complementing these focus groups was a social research element that recognized users aren’t always able to articulate what they need, so different techniques were used to find out what customers really wanted[1].
Boeing executives were able to prioritize the features that mattered most to users.
As one executive recalled, “What is more important, drinking or breathing? Well, both are important, but you can go some time without drinking, but you can’t last very long if you don’t breathe.” Their approach led to features such as better air quality, greater fuel efficiency and even bigger luggage bins on the Dreamliner.
What did Boeing do right? It recognized that product differentiation and decisions based on data from multiple sources would be crucial to the success of its very expensive new endeavor. The A380/ Dreamliner story is so useful because of the extremes — the successes and the failures; the immense upfront investment; and, the lengthy product lifecycle. It also illustrates the importance of (a) having a clear understanding of your customer; (b) complementing qualitative feedback with quantitative and (c) taking your time to get it right.
Man and the Machine
The paradox of the information age is that we produce so much of it and use so little of it. You have heard statistics that 90%+ of the world’s data was generated in the last few years. Another statistic is that companies analyze only 12% of the information they have available[2]. While these are overwhelming figures, they represent an opportunity.
Direct customer feedback has to be the starting point. Boeing employed focus groups as part of its development process — an approach that was pioneered 100 years ago by sociologist Paul Lazarsfeld — but there many other sources of information today.
You need to identify the right sources that enable you to understand your customer: break information out of its silos, link it up, store and analyze it on an ongoing basis.
Whether information is derived from market research or financial reports, in a machine, on the factory floor or in a team — when you link it together you’ll start to notice trends that reflect real-world experiences. Let’s look at a few examples of each.
A crucial component of the 787 — its GE (or Rolls Royce) engines — presents a great example of where product usage directly informs operational and strategic decisions. Both GE and Rolls Royce use remote monitoring systems to track the health of thousands of engines operating worldwide, using on-board sensors and live satellite feeds. This is analogous to Apple, Bloomberg or Facebook monitoring feature usage of their products. Usage offers a feedback loop that measures how customers are interacting with your solution and reacting to specific features.
Operational processes are the next logical source. You probably know about advanced manufacturing techniques where information collected from a factory is used to improve a solution. Samsung Electronics, for instance, uses these techniques in a facility in Texas that produces chips for iPhones while Komatsu of Japan does the same in its manufacturing of excavation equipment[3]. Similarly, the sales and marketing process as well as client support are additional sources. Here it’s important to identify those processes that link directly to the customer experience.
Finally, direct observation of market activity is an untapped source. Observing actual experiences in the markets rather than abstracts has been part of decision making for centuries. Economists, for instance, assess the strength of the economy by counting construction cranes in the skyline.
Today, the proliferation of mobile devices, low-cost sensors, and technologies like image processing have led to an explosion of new and potential data sources. These alternative sources of highly unique insight are becoming integral to decision making in many fields with providers such as Alpha Eagle and Quandl leading a path. It is also an area that I will cover in more detail in a future post.
In Summary
As you roll into a new year, recognize that your innovation objective is within reach. Process and technology can enable you to approach innovation rigorously and scientifically. Starting with a very clear understanding of your customer, a combination of logic and emotion should inform your strategy. Complement decisions based on qualitative evidence, often captured from a meeting with an important client, with decisions based on quantitative evidence, captured from multiple sources in your organization.
[1] How Boeing Put the Dream in Dreamliner, by Douglas Gantenbein; Air & Space Magazine, September 2007
[2] The Forrester Wave; Forrester Research, February 2014
[3] How U.S. Manufacturing Is About to Get Smarter by Christopher Mims; The Wall Street Journal, Nov 13, 2016
