If you’ve read recent lists of manufacturing trends, you’ll have seen that complex event processing is scoring…

Sign in for existing members

Step 2 of 2:

By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time. Contact TechTarget at 275 Grove Street, Newton, MA.

You also agree that your personal information may be transferred and processed in the United States, and that you have read and agree to the Terms of Use and the Privacy Policy.

a top spot — and for good reason.

The term complex event processing is used to describe analytical software that processes information from multiple sources about events and develops conclusions or predictions based on those events. CEP looks at patterns on which it can infer the likelihood of future occurrences. The goal of CEP is to identify opportunities or threats early enough to allow the user to prepare for or avoid their occurrence.

In a way, all forecasting can be considered “event processing” if you consider sales transactions to be events. Forecasting that encompasses additional sources of input, extrinsic factors like demographics, economic data, product lifecycles or leading indicators can be considered “complex” event processing. But that’s splitting hairs.

The CEP that is making recent lists of manufacturing trends is a subset — or perhaps a renaming — of analytics that manufacturers are using in conjunction with big data and the Industrial Internet of Things (IIoT), which are two other manufacturing trends business leaders would do well to research. The old executive information dashboards and business intelligence systems are morphing into increasingly sophisticated analytical engines on the way to predictive analytics, i.e., complex event processing.

The real questions are whether CEP is finding its way into manufacturing organizations and whether it has value. The answer to both is a resounding “yes”. To address the second question first, anything that can provide advance warning — or at least a probabilistic forecast — of market trends, demographic shifts, or any future threats or opportunities is certainly of great value to any business leader.

As far as the evolution and adoption of CEP, that is well underway, but not yet at the point where CEP use is anywhere near widespread. As with any new technology, there are barriers to early adoption, primarily complexity and price. Sophisticated analytics are quite technical and early adopters have needed data scientists and other technical resources to implement and operate the systems.

But as with most other technologies, these systems are becoming more affordable as the number of users increases and as they are packaged into analytics modules designed to integrate with commonly used ERP systems. This evolution is also “commercializing” the tools so that a wider range of people can employ them — i.e., business users with a little help from IT — no data scientists required.

You can expect to see more CEP and predictive analytics capabilities migrating into existing business intelligence applications, resulting in a new wave of packaged, user-friendly and affordable add-on modules for use with the major installed ERP systems in the market.

This entry passed through the Full-Text RSS service – if this is your content and you’re reading it on someone else’s site, please read the FAQ at fivefilters.org/content-only/faq.php#publishers.

SearchBusinessAnalytics: BI, CPM and analytics news, tips and resources