The seven steps of adoption for Industrial IoT

Industrial IoT is reaching a maturity point where organizations can get real benefits from it. There is, however, some (a lot?) of hype around IIoT.
The following seven steps are what we think is the best approach to IIoT.


1. Use what you have now

We all love new toys, and everyone wants to buy new and shiny hardware. However, take a close look at what you have now, it may be a simple GPS-based fleet management system or PLC-based automation. A couple of years ago these things were called Machine-to-Machine (M2M), and this means most companies already have IIoT infrastructure in place, if you look closely.
Don’t spend money yet on new toys, leverage what you have now.

2. Find problems to solve

Look at your organization from a distance and start small. Don’t try to change the whole company, start with your department or business unit.


3. Involve people

IoT will not replace people. Write that a hundred times in your whiteboard.
People play the most important role in this new way of operating. IoT is all about helping people to make the right decisions, at the right time, using what machines don’t have: emotional intelligence, empathy, domain knowledge.

Get people on-board, from getting C-level buy-in to involving rank-and-file workers in the process. People directly connected to Operations or Manufacturing are going to be the most impacted by IoT, start with them.


4. Test concepts as quickly as possible

There will be failures, don’t doubt it, so skip long and expensive software development projects. Use ready-made frameworks and tools that minimize your risk and let you quickly test and deploy new processes (Atomize Spin can help you with that).


5. Identify and measure hard business benefits

Not “we are more efficient” or “we are so cool, we have IoT” type of benefits, but hard benefits like “John increases his successful job rate by 12%” or “customer satisfaction went up 15%”.


6. No Big Data

At this point you don’t have a Big Data problem, don’t worry about it for now.


7. Re-analyze

The last step is where you will see if it makes business sense to buy best-of-breed sensors, actuators and edge computing devices.
This is also where you should start to think about Big Data and if you need specialized tools for it (Hadoop, Spark, Kafka, etc.)