The sweet smell of pastries and the strong aroma of my steamy double espresso has become my morning highlight. I perform an acknowledging nod to myself as I leave the coffee shop. At that very moment, I run into the VP of one of the large OEMs in Europe, an innovator. No doubt. He’s not afraid to challenge the status quo and follow big visions.

He is successfully juggling with fascinating words from recent tech trends – Blockchain, Predictive Analytics, Machine Learning, and Artificial Intelligence. Words that I don’t even truly understand the nature of. However, being a Data Scientist, I love when people get excited about new technologies. What I love even more is to drill down and figure out how these technologies can bring value to businesses. This is unfortunately where the disappointment usually kicks in, and this conversation was no different from previous conversations on similar matters. However, this exact conversation made it perfectly clear to me that there must exist a systematic problem in the industry. The first OEM to solve this problem will win.

High on the wish-list, low on the grocery-list

Nearly every OEM I meet, at least everyone with a decent level of ambitions, sees data and analytics as key to superior performance in the future industry. Collecting and analysing data boost sales through entirely new revenue streams, cut costs on service and warranty, and provide greater visibility into the functionality and value of machines – allowing OEMs to make smarter decisions on difficult matters. What is more, OEMs can achieve product excellence by cross-selling profitable data-driven insights, which can solve their customers’ persistent problems with productivity.

It is therefore a paradox that OEMs choose not to become trailblazers. OEMs are based on that mentality stuck in a time warp regarding technological progress. I have not yet met an OEM that embed data and analytics into their strategy.

It’s like teenage sex – everyone talks about it, nobody really knows how to do it, and everyone thinks everyone else is doing it, so everyone claims they’re doing it.

To me, this signals a laggard mindset among OEMs with a firm belief that it is better to watch the competitions initial experiment with data and analytics so, when they fail, others can benefit from these mistakes. But what happens when they don’t fail and the competition snatches the appointed target you had your eye on but waited far too long to make a move on?

A Mexican standoff

When I think of the current industry I picture a Mexican standoff. The first OEM to draw the data-and-analytics-gun will not only survive, but dominate the industry. Data and analytics has matured in almost every other industry, which makes the adoption of data and analytics trivial in a global perspective. Moreover, the exact same pattern has happened in many other industries where the early-adopters of data and analytics are now ruling the market such as Amazon and Airbnb that put data into the heart of their business.

Productivity-enhancing technology is both cheap and accessible. This implies small chances of failure, which in turn will reward early adopters with an unparalleled growth potential.

Some OEMs have taken incremental approaches to adopting data and analytics practices by establishing small, discrete programs that run under the radar. Being in a laggard mindset, this is a natural way of testing technology innovations while minimizing risk. However, anchoring these programs into corporate strategy will mean the difference between barely surviving and successfully thriving in an industry that is on the verge of disruption.

Win or die

Do you want to win? Then you need to embed data and analytics in your corporate strategy. In addition, you need to acknowledge that great data and analytics programs do more than contribute to a single stakeholder within your company: it transforms the capacity of your company to recognize and seize business opportunities. Great data and analytics programs start with a strategic focus, which implies corporate-wide shared data assets. This wealth of data contains the seeds of digital innovation. The first OEM to grow these seeds and harvest their data will become the industry leader. The critical missing link is to marry that early-adopter mindset that sparks innovation and experimentation – one that reimagines the future by encouraging instead of prescribing.