Submitted by Erik Udstuen, CEO & Co-Founder at TwinThread
An aspect worth discussing, when it comes to leveraging predictive analytics in the name of profit, is a platform’s ability to easily connect and interface with a variety of data sources. There’s no need to wait for the “intergalactic” data lake to be built. Draw on the diverse data you already have.
Whether your organization deals in SCADA Systems, Historians, MES Systems, CMMS, IoT devices and sensors, or some other information apparatus – your predictive analysis center of choice should not only be compatible with the apparatus you make use of (because that’s just the bare minimum, of course), it should integrate painlessly.
The solution you choose should connect up with your in-house system so well that you don’t even pass a thought regarding its implementation. Don’t even consider adapting your machine learning loadout to accommodate a solution. That’s a one-way ticket to losing money. And, for those solutions that will interface with your systems, build confidence with your provider that they are certain their platform can be connected up easily and quickly.
Time is of the essence when attempting to prove the value of a particular predictive operations center. Getting started needs to be fast so it doesn’t serve as a barrier to moving the proving process along.
So, any given platform’s ability to connect (and fast) to whatever information apparatus you currently have in place is really a prerequisite to accomplishing profitability through the application of predictive analytics.
Profit (when it comes to predictive operations) is garnered through meaningful insights that can be operationalized by your domain experts. The more condensed you can make the time between implementation and insight, conceptually, the greater your chance at increasing profit margins.
To see how fast TwinThread can connect to your data and deliver insight,get started here.