Representative End User Clients
Representative Automation Clients
Representative Software Clients
For the past few years, executives at industrial organizations have been exploring how to best leverage analytics to improve operational and business performance. At their disposal are vast amounts of data that can help address business challenges in new, innovative ways. By embracing data analytics to help drive better decisions across all areas, organizations have an opportunity to transform all facets of the business.
Analytics is hardly a new thing, as many industrial businesses have been employing historic performance monitoring and describe/discover analysis (also known as “business intelligence”), for some time. However, many industrial sectors are quite a bit behind in the learning curve for newer, predictive analytics.
The difference now is that many organizations are looking to integrate more sources of new, complex, and often real-time data for analytics. They are also looking to combine that information with performance data they have been gathering for decades. The data is structured and un-structured, and is a dizzying array of information in many formats—assets, historians, logs, paper, pdfs, backbone operating systems, financials, spreadsheets, pictures and video, audio, weather, social media, etc.
Despite the complexity and volume of this data, executive expectations remain that it can be used to deliver transformational business value. Executives expect that by integrating and analyzing multiple data sources to enhance decision support, they will be able to improve operational efficiency, asset performance, and, in some cases, deliver new, value-based services.
Business executives expect data analytics vendors to help them collect, transform, and analyze their data to provide previously unavailable in-sights. They want vendors to make analytics easy for people to use. What they don’t want is to have to hire a bunch of data scientists.
Executing this vision of harnessing data to gain transformation insights is proving to be far from simple. A major reason is that the highly sophisticated analytics needed for this type of data-driven insight are new to most industrial organizations.
Table of Contents
- Executive Overview
- Confusion in the Market
- Filtering the Noise
- Understanding Solution Types
- Navigating the Buying Process
- Recommendations
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Keywords: Data Analytics, Industrial Organizations, Business Intelligence, Predictive Analytics,, ARC Advisory Group.