02 Jul

EAM transforms industrial businesses into data-driven organizations

If asked to mention some companies whose business is based on data, we would probably have Google, Facebook or Amazon top of our minds. But organizations relying on data to take mission-critical decisions are more than those, as the value of data is now widely acknowledged, and most decision makers are fond of evidence. They may not understand algorithms behind data analysis, but the idea of mirroring business choices with facts and figures is surely appealing for any executive.

From finance to manufacturing, from retail to healthcare, data-driven organizations outperform competitors in terms of financial results, and this was confirmed by several independent surveys. Best performing companies have in most cases adopted what the experts call the DataOps approach, the equivalent of DevOps for data. It is a new way of managing data requiring the integration of formerly siloed data, teams and systems. DataOps allows businesses to build a sort of continuum from people who collect and prepare data to those who analyze them, up to those who leverage information to take business decisions.

This can be intuitively applied to customer-related data, using advanced business intelligence and predictive analytics tools to take advantage of more accurate forecasts. How did sales perform last quarter, what are they going to be like next month? Which customers are more likely to subscribe to our service? Does this feature make sense for our heavy users?

In manufacturing companies, the same principle is valid for data generated by production assets and equipment. As industrial businesses are pushed to maximize plant performance while ensuring efficiency and cost control, a stricter monitoring of operations is needed – and it depends on data collection, information reporting, key parameters and indicators tracking.

Companies are well aware of the intrinsic value of data lying in their assets: they store relevant information, which can provide significant insights and feed decisions to prevent production downtimes or disruptions, but also encourage innovation. That’s why demand for Enterprise Asset Management (EAM) solutions is rapidly increasing, supporting the evolution of traditional manufacturing businesses into smart, data-driven organizations.

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