January 25, 2011, 9:33 PM — Business analytics continues to be a hot target for acquisitions. This trend continues with the GE announcement that it would acquire advanced analytics vendor SmartSignal. Most of the acquisitions in recent years have been business intelligence analytics, built to handle financial metrics and provide dashboarding capabilities, such as IBM with Cognos and SPSS, Oracle with Hyperion and SAP with Business Objects. Now the analytics acquisitions are moving more into operational analytics. The attention to analytics makes sense now that energy companies are able to draw on more data due to the increase of sensors and monitoring devices on equipment in the field or plant. Energy companies have always had analytical tools that have been used by smart engineers, but with the "smart" aging out, there is room for templated algorithms that have been tested and tried in the field.
SmartSignal has gained a lot of traction in the energy industry over the course of its history. The company started by the University of Chicago based on technology developed at the U.S. Department of Energy's (DOE) Argonne National Laboratory. The company began with using analytics for the prediction of pump failure at nuclear facilities. The company got its big break monitoring aircraft engines "on the fly" and then later moved heavily into power generation and oil and gas. Customers of note include DTE Energy and Entergy for power generation. SmartSignal's customer base is primarily North American, but the company has been expanding into Asia Pacific.
The patented technology takes data from sensors that monitor equipment and conditions and analyzes it for outliers to predict potential equipment failures. The analysis is highly mathematical, rather than engineering based. This means that the algorithms identify departure from normal operating levels of a piece of equipment, rather than compare performance to expected performance levels for the equipment class. Recently, SmartSignal has moved into the realm of engineering with its service offering of asset management through performance center that monitors more than 4,000 assets. Based on performance center activities, the company has done historical analysis on equipment failure that will add the engineering dimension to its predictive models to establish a causal link to the root cause for failure.