The Industrial IoT brings new promises to the plant floor: lower operating cost, better visibility, and improved Overall Equipment Effectiveness. These results are all in the pot of gold at the end of the IIoT rainbow, but that pot is sometimes hard to find.
Here are the top 7 reasons why I believe IIoT projects fail:
1. Starting too big too fast
If you focus on your entire plant, you will be making success much less likely. Try starting with a smaller project, in a key focus area – perhaps an area that has the most downtime, the most maintenance, the most energy consumption, etc. Keep the project manageable. Make sure you contemplate how to scale – if you are successful, what’s next?
2. Lack of a clear objective
I continue to be surprised by the number of companies diving headfirst into an IIoT journey with no clear goal, objective, or a full understanding of ROI. What is success? Determine what you are trying to achieve and measure it before and after any IIoT implementation. For example, what’s your unplanned downtime today? Where do you want it to be? By when?
3. Lack of internal company alignment
The days where operations can implement networking projects without IT are gone, or at least close to extinction. You can only find the pot of gold together. For example, data analysis might bring new compute requirements where IT can help. IIoT can also bring new security risks – a key area where IT can help, but only by fully understanding operational requirements. You also need executive buy in. Not only can this help you with driving support across your organization, but it may help “grease the skids” for approval by aligning with corporate objectives like Sustainability or Security.
To bring IT and OT together, view our page here.
4. Not understanding and addressing security risks
Connecting to data from the Enterprise or opening up remote access all the way down to the plant floor can potentially open up security risks. With any IIoT project, your attack surface is likely to expand. This is where operations and IT collaborating can bring big value to your organization. Carefully evaluate the potential risks and impact of those risks, then focus on the most serious. Many companies like Cisco can perform assessments to help you evaluate and prioritize those risks. Your entire organization’s IIoT effort may come to a grinding halt if a hacker wreaks havoc in your facility – it’s game over.
Understand potential security challenges by taking our holistic security assessment.
5. Siloed or disparate networks
Make sure you fully understand the different networks in play all the way down to the data you want to capture for analysis. There’s no disputing that Industrial Ethernet is the de Facto standard today for nearly all control applications. Do you have Controlnet, Devicenet, CAN, or other networks? Do you want to install a “Shmozzle” (technical term, meaning “Varied”!) of different gateways to translate that data to Industrial Ethernet? Or do you want to overlay new equipment to gather data for analysis?
This can create quite a spaghetti of networks and hardware (extra failure points) on your plant floor. You may decide that extra complexity and risk is not worth it, set a plant floor standard, and explore changing out all controls to a robust standard Industrial Ethernet. With more than 80% of industrial facilities over 20 years old, I’d propose that changing to newer controls with Industrial Ethernet communications is worth the spend. In the long term, it may be more cost effective to replace old machine controls with new ones instead of other options to gather data.
6. Lack of automated analytics
I heard a great quote recently: “Sure you can connect your toaster to the internet, but do you really need to??” Let’s say you are interested in looking at product quality on one of your lines. Although it would be great to correlate the earth’s rotation and hundreds of other potential variables to quality, you don’t want to suffer from data overload. Keep your data set manageable and use basic statistical analysis to look for outlier data. You might consider using edge analytics (fog computing) to reduce the overall data set for later analysis. Work with a partner who has experience with automated analytic software packages designed to look at manufacturing data and glean actionable results from that data.
7. Spiraling cost
Adding gateways, converters, extra wiring, piggy backing extra sensors to get at data, multiple vendors, adding wifi or cellular, adding security, data storage & computational horsepower might all add cost to your IIoT project. In the immortal words of one of my favorite movies, Office Space: “Plan to plan.”
The better you plan out the potential pitfalls to your IIoT project, the more prepared you will be to mitigate surprises later. Companies will either do it right or they will do it over…. which one do you want to be?
Very good blog. I believe that these recommendations apply not only for IoT projects but to any Digital Transformation project.
Thanks, Oscar – Absolutely right on any DT project.