When Marc Andreesen famously declared almost a decade ago that “software will eat the world”, he fired a warning shot across the bow of companies in a variety of industries that their life was going to change, in many ways irreversibly. Some sectors moved faster than others, e.g. consumer commerce, financial services, etc. But there were plenty of others that simply haven’t made the transition as fast as they could or should – or maybe they didn’t need to. One of them is the Industrial OEM sector that by all accounts lags behind most for technology adoption.
However, times are changing and many large companies like GE, Honeywell, Schneider, Siemens, etc. have invested heavily in software and platforms. The most famous one was GE’s Predix, but Honeywell with Forge and Siemens with Mindsphere is not too far behind. Additionally, there are independent companies like Uptake, C3, and a few others that are attempting to create a digital-first, OEM agnostic platform for end-users. Most of the focus of these efforts has been on serving very large end-users, e.g. refineries, process plants, airlines, utility companies, etc.
But there are only a few thousand of these globally. What about the other millions of businesses that buy and use equipment that could and should be monitored? What about a “platform for the rest”? How will OEMs engage with these users? And equally importantly, will OEMs engage with all their customers, or only their top 15% as they are wont to do?
The latter is a really important question for OEMs to address in the upcoming years. As digitization becomes the norm, not the exception, every customer is going to expect a digital experience in their interactions with their suppliers. This means that OEMs will need to develop applications that allow every user to interact with them, from eCommerce websites to customer portals, to IIoT applications. This means that OEMs are going to be awash in data from every touchpoint with their customers. They will be generating and consuming data through multiple channels and countless more interactions. And unless they do something about it soon, this explosion of data will become unmanageable and create catastrophic consequences for the OEM.
So how will they deal with this changing world? Industrial manufacturers have perfected the art and science of supply chain management, manufacturing, building complex electromechanical machines, and distributing and servicing these globally. But building enterprise-grade software? Not so much.
The very strengths that made OEMs successful may now get in the way of their future success. In a resource-starved environment, investing ahead of growth and operating margin has never been a luxury they could afford. Now, not only will they have to maintain their existing business and related systems, but they will have to invest in new applications, new capabilities, and new business models without the luxury of knowing if these will pay off. A tough place to be.
So how should an OEM handle this transition? How much should they invest in building capabilities themselves vs. partnering with subject matter experts? Should they follow the lead of the likes of GE, Siemens, etc? Build their own Predix? Or forget a different path forward? This is a hard decision and a very hard transition for most OEMs to make.
After all, data is in their blood – most of these are engineering-oriented companies, with strong operations capabilities. Very quantitative, very analytical, and very data-driven. But building KPI dashboards with an army of analysts is very different from building enterprise-grade, data-driven software applications.
Our experience suggests that the old adage of “invest in your core competencies, outsource the rest” applies to this matter as well. Specifically, OEMs can and should leverage their knowledge and capabilities about the equipment they manufacture, its behavior under various environments, their ability to decode IIoT signals into diagnostics, etc. In other words, “the physics and chemistry” of their equipment that the OEM is the expert on and needs to ensure no other party gets between them and their customer. But they should partner with third parties with relevant knowledge on handling and managing data as well as building and supporting enterprise-class software.
All of the above means a change of mindsets, approaches, and capabilities within an OEM. It is not for the faint of heart but creates an opportunity for the pragmatically bold leader. It means giving up the Not Invented Here (NIH) syndrome that is so prevalent in these companies. It means finding leaders who are pragmatic partners to a large ecosystem that can help them fulfill their aspirations. It means nurturing an ecosystem of partners with different capabilities, each of whom plays a unique role in the success of their customers.
It means building AND buying to win AND partnering to win.
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