Business Analytics is the process associated with the technologies and practices employed for continuous iterative exploration and investigation of past performance to gain insight and drive future process execution. Business analytics differs from business intelligence by focusing on raw performance data rather than consistent sets of metrics.
We provide business analytics largely inside the engineering design and engineering support functions in a large original equipment manufacturer. We have used private, internal corporate data as well as public data to determine ‘why are particular things happening’, ‘what likely will happen next if current trends continue’ and ‘what can do to produce optimum results’? These are associated with failure rates as well as reliability and availability measurements. These are used to drive action plans associated with equipment usage and spare parts provisioning. Predictive modeling is an outcome of business analytics. These impact outage planning and inventory management.
This effort encompasses data collection, data cleansing and data integration in conjunction with statistical analysis tools either available as third party tools or internally developed. Data accuracy and integrity are critical items to this process. Subject management experts develop rules to detect patterns or data anomalies that are of interest to the end user. Statistical tools utilizing innovative algorithms are combined with visualizations to provide rapid and continuous analysis of the data being consumed.
Industry has reported instances of revenue increases due to increase equipment availability and usage and decreased outage and maintenance cycles in excess of 10%. Productivity improvements in the high single digits are common as a result of improved focus and reduced labor waste as a result of improved planning driven by high quality analytics.