Want To Get Smart With Data? Get Out Of The Echo Chamber Posted on : Dec 14 - 2018

It is no secret that many industries are looking to developments in artificial intelligence (AI) and the internet of things (IoT) to reduce the cost and risk of identifying new opportunities. The oil and gas sector continues to drive down the cost of exploration, while pharmaceutical companies are battling with the fact that nine out of every 10 clinical drug candidates fail approval.

In many cases, the introduction of these emerging technologies is helping. The large legacy companies that dominate these traditional industries have been around for a long time and have a wealth of data at their fingertips, making it the perfect opportunity to take advantage of new technical developments to speed up and simplify processes. Pharmaceutical giant Sanofi has dedicated significant funds to the development of end-to-end analytics, whilst Merck announced plans to connect “smart factories.”

(Full disclosure: My company, Altran, worked with Sanofi on its innovation and collaboration strategy.)

However, some companies are finding the journey to digital transformation an uphill battle, or are left wondering why their efforts are not leading to any clear return on investment (ROI).

The Industry Myopia

One reason traditional industries are struggling to transition to AI and the IoT is that these companies have previously existed as isolated islands of expertise and have operated in their own “silos” of knowledge, only looking to the experts within their field to solve complex problems.

The reason these silos exist is that the sectors have developed separately from other industries, and thus, they have become reluctant to trust experts in other fields. Oil and gas companies previously assumed that the best people to design efficient and cost-effective methods of oil exploration are geologists or petroleum engineers. Pharmaceutical companies would have assumed that the best people to work out how to identify new drug molecules for treatments were analytical chemists.

As such, these legacy industries have evolved to accommodate only forms of expertise from within their own verticals, assuming that other sectors will not experience the same problems that they do. They developed a “vertical mindset” with preconceived ideas about how to solve issues rather than thinking bigger.

However, as industries such as health care and energy begin adopting digital technologies, they need to draw on expertise from other digital native sectors. The oil industry needs expert knowledge of oil exploration, but it does not necessarily have expert knowledge of machine learning or smart data. As the IT and software industries converge with legacy industries such as health care, firms need to be prepared to open themselves to outside expertise. An image-recognition algorithm designed for driverless car cameras might have applications for autonomously analyzing brain scans to diagnose disease. View More