How to Justify an IIOT Investment
How do I put together an Industrial Internet of Things (IIOT) strategy? How do I define success? These are questions that I'm often asked. People believe that implementing IIOT is a must do, but aren't always clear to the "why". The choice is made to implement a thing, and then the benefits are loosely identified. When the solution is implemented, the value does not deliver and the culture loses confidence in technology investments.
For example, in 2016, a large industrial company invested in connecting machines to get data from them. Metrics were established to count the machines connected. Data was collected. People were not given the tools or the training to actually extract value from the data. The cost never provided value and people lost motivation towards digital investments. I have to say that this approach is just wrong. You should start with the problem statement first.
Upfront problem definition is the key to creating a robust return on investment story for any technology investment. Ideally, the problem should start with the business strategy. Where is the company trying to go? What are the biggest challenges with making that happen? In large organizations, the problems can come from within the functions, and still have a sizeable return on investment. How much can be saved by improving the problem? The justification should start here.
Once the problem is defined, get an understanding of what data is required to solve that problem. Let's say a company's objective is to save money by rejecting false warranty claims. What data is needed to make that decision? Perhaps, the company needs to see a visual image of the part to determine if the claim is legitimate. The image is not captured in a system and is not accessible to the key decision makers. The technology investment in this case may be to invest in a mobile application that requires images to be uploaded prior to requesting a replacement part under warranty.
Finding applications to solve these problems is getting easier. For many years, the solutions have been dominated by large technology companies. Now, many startups, including Leverage4Data, exist to make software and technology more accessible. After all, why should smaller companies pay for lavish conferences and giant city buildings? Remember to keep the IT team involved in the search for solutions. They have a better understanding of risks and resources required to maintain the systems.
Once a solution is selected, revisit the initial benefits identified with the problem statement. Compare the cost of the solution to the benefits and timing. Does this solution meet the companies return on investment expectations? Does the IT team support the solution? If so, then go for it. Remember to track the improvement after the change and communicate it throughout the organization. One small win may help drive a more data driven culture.