Things at Predikto are going well. We have been growing our team, primarily sales, after closing our Series A round 3 months ago. I was asked to run a webinar with a partner company, eMaint, in March. eMaint has a large following to their monthly webinars primarily consisting of Operations and Maintenance folks from asset intensive industries. The topic was the Industrial IoT.

In putting together the content for the webinar, I realized that many of our customers do not fully understand the exact expected results and success criteria prior embarking on a Predictive Analytics initiative. In a traditional enterprise software purchase, customers are fully aware of what they need and they shop around to compare the features and capabilities that would best fit into their checklist. When customers are purchasing Predictive Analytics solutions, there is no punch list, they just take the plunge.

Predictive Analytics technologies are not new. But operations and plants have not been early adopters until now. The use of machine learning and statistical algorithms to predict an event that will likely take place in the future by utilizing historical data is very new in asset intensive industries. Predictions could be focused to improve yield, reduce asset downtimes, and increase overall plant reliability and operations.

So, next time you are trying to evaluate how to operationalize Predictive Analytics in your plant or with your assets, do not worry about having all the answers before you start. Engage with a low risk pilot that would allow your organization to test different areas of your plant or different pieces of equipment. Early wins will result in a lot of light bulbs going off across the organization and enabling you to layout in more detail the next areas of your company where Predictive Analytics can have a big impact.