In the past, business intelligence (BI) was intended solely to help senior management understand financial performance to make informed strategic decisions. Over time, the scope of business intelligence increased to also support decision-making at the operational level. However, those decisions are still commonly based on data collected and stored days or weeks previously. This ARC Advisory Group Insight considers the changes that must occur to successfully analyze data generated by the Industrial Internet of Things (IIoT), which alters the BI paradigm to a considerable degree.
Historically, business intelligence has its roots in helping senior executives understand financial performance. By accumulating many individual data points - sales transactions, material costs, staffing costs, overheads - executives could gauge recent performance. Further, if those data points were retained for a long period, historical comparisons could be made. That historical perspective gave rise to what we now call a data warehouse. Back then, BI was used to help inform strategic decisions that were not time critical. Or, to put it another way, they had a big decision window - decisions were made using data long after those data were generated.
