Topic #2, Post #2 “Systems Development” will focus on Business Intelligence products. We will examine their role, functionality, and address some questions regarding their implementation between business and IT teams.
Summary: Business Intelligence (BI). The term business intelligence refers to data and information organized and presented to enable decision-making. “BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business.” The distinction between business intelligence and business analytics is that BI communicates how the business currently operates – the “is”, and analytics attempt to predict the future (‘predictive analytics’) – “will be” – or how the business should operate (“prescriptive analytics”) – “should be”. BI examines the current state of the enterprise and can be tailored to focus on various metrics or categories.
Considerations. How enterprises implement and leverage BI depends on factors such as size of the enterprise, level of IT complexity, and chosen/desired metrics. Considerations for executives, managers, and analysts include:
a. The Art of Selecting Metrics. The selection and presentation of metrics is an art – not a science. With millions or billions of data points and hundreds or thousands of individual metrics to consider, selecting those which enable strategic value is the primary driver of success. Similar to statistics, which can be manipulated to tell a desired story, metrics and BI must focus on the true drivers of value to genuinely enable improved strategic decisions.
b. Personnel Applications in BI. Business Intelligence is requires a link between production/operations, IT, external data sources, and analysts. Data points must be gathered both externally and internally. IT enables the transmitting, storage, and display of the information. At the back-end, analysts must attach assessments to the information to form knowledge which enables executive decision-making. As each enterprise’s size and scope differs, there is no generic equation for success in BI. However, several key takeaways include:
(b.1) The Role of Information Technology (IT) in BI. The IT department generally does not have the analytical capability to assess information; therefore, a cross-functional team including business analysts and internal production representatives, and those representing external data sources, improve the BI function. Leaving IT to manage the entire BI function could lead to sub-optimal assessments.
(b.2) Non-IT Involvement in BI. Business analysts often require assistance from IT to compile and summarize data. Synergy between technical and analytical departments is required for the best BI product. Likewise, operations representatives (i.e., manufacturing or production managers, or sales managers) are helpful when crafting BI metrics structures or analyzing data, because they often provide a more intimate knowledge of operations.
c. Recommendation: Recurring Re-evaluation of Metrics. BI metrics should be re-evaluated cyclically to ensure that changes in the operating environment are incorporated in analysis. For example, as new technologies are introduced to market, dynamics can change; a new type of fuel or a new energy-production source can change entirely the metrics window. Cyclical re-evaluation should be time-bound and will depend on the scope of the enterprise, but yearly evaluations is a good starting point.
SOURCE: https://www.cio.com/article/272364/business-intelligence-definition-and-solutions.html