What is really slowing IoT adoption in manufacturing?

There was an article published in HBR titled “The Biggest Challenges of Data-Driven Manufacturing” in which they pointed out that IoT is at its peak for hype.  It cites the following 4 real challenges manufacturing faces with adopting IoT technologies to see true productivity gains:

1. Going from “time-triggered” to “event-triggered”
2. Transitioning to a shared data model (not just data exchange)
3. Integrating legacy systems
4. Uncovering security challenges that were never initially conceived 

While I agree with these challenges, I think this article misses a fifth key challenge that is also crucial to IoT technology adoption within manufacturing, and it’s a harder one to list because it’s harder to define.  What this article misses is the organizational impact IoT technology has on manufacturing. You know, the human aspect of Things. The fifth challenge is the cultural shift away from organizing responsibility by the “top floor” of the plant (where IT systems tend to live) and its “shop floor” (where the machines are programed and manufacturing execution systems live). 

Think about the impact this division of responsibility has within manufacturing.  For example, the IT systems that control the orders for a plant’s output are typically setup and maintained by a completely different group of people than the people who program the machines to produce that output. So what happens if an enterprise wants to go to demand driven manufacturing?  Or what if they want to adjust downstream processes based on upstream waste measures? Or what if they want to halt batches based on live quality test results?  These are all powerful “event-driven” examples of what IoT technology can do for manufacturing.  Now what group of people are ultimately responsible for designing, implementing, and maintaining the technology responsible for these new processes? 

The answer is that there are different groups that need to share this responsibility, but are they ready to?  A wiser manufacturing lead at SAP told me that when he gets these different factions into one room (which is rare) he likes to break the ice by introducing the groups to each other with the provocative suggestion that the groups also don’t generally like each other.  This suggestion always generates laughs but also nods.  Each group has existed up until now implementing systems without the others help (or sometimes knowledge of) because they could. 

Within IoT we talk about IT (Information Technology) and OT (Operational Technology) convergence, but the focus needs to extend from the data and systems convergence to the actual people who are ultimately responsible for doing.  At SAP, we can use Design Thinking to help overcome these organizational barriers.  First, we bring people from diverse backgrounds together to work as one multi-disciplinary team.  Then we work together to clearly define the real business problem that we wish to solve (i.e. not a faster horse).  Lastly, we ideate as one team, bringing our diverse experiences and backgrounds together to solve the problem.  We can easily munge data and systems together, however in my experience munging people is always harder.   

>> Sarah McMullin is a Director for Emerging Technologies at SAP Waterloo.  Working for a big company does not stop her from running simple like a startup.  Successful creator of junior honey badgers and applications that create new markets.  Fascinated by biogenomics and food fraud.  Follow me on twitter @Sarah_Sugoi