Data mining, predictive analytics, and statistical engines are examples of tools that have been embedded in BI software packages to leverage the benefits of performance management. If BI is backward looking, and data mining identifies the here and now, predictive analytics and their use within performance management is the looking glass into the future. This forward-looking view helps organizations drive their decision making. BI is known for its consolidation of data from disparate business units, and for its analysis capabilities based on that consolidated data. Performance management goes one step further by leveraging the BI framework (such as the data warehousing structure and extract, transform, and load [ETL] capabilities) to monitor performance, identify trends, and allow decision makers the ability to set appropriate metrics and monitor results on an ongoing basis.
With predictive analytics embedded within the above processes, the metrics set and business rules identified by organizations can be used to identify the predictors that need to be evaluated. These predictors can then be used to shift towards a forward-looking approach in decision making by using the strengths from the areas identified above. Scorecards are one example of a performance management tool that can leverage predictive analytics. The identification of sales performance by region, product type, and demographics can be used to define what new products should be introduced into the market, and where. In general, scorecards can graphically reflect the selected sales information and create what-if scenarios based on the data identified to verify the right combinations of new product distribution.
What-if scenarios can be used within the different visualization tools to create business models that anticipate what might happen within an organization based on changes in defined variables. What-if analysis gives organizations the tools to identify how profits will be affected based on changes in inflation and pricing patterns as well as the impact of increasing the number of employees throughout the organization. Online analytical processing (OLAP) cubes can be created to identify dimensional data, and patterns within changing dimensions can be compared over time to contrast scenarios using a cube structure to automatically view the outcome of the what-if scenarios.
With predictive analytics embedded within the above processes, the metrics set and business rules identified by organizations can be used to identify the predictors that need to be evaluated. These predictors can then be used to shift towards a forward-looking approach in decision making by using the strengths from the areas identified above. Scorecards are one example of a performance management tool that can leverage predictive analytics. The identification of sales performance by region, product type, and demographics can be used to define what new products should be introduced into the market, and where. In general, scorecards can graphically reflect the selected sales information and create what-if scenarios based on the data identified to verify the right combinations of new product distribution.
What-if scenarios can be used within the different visualization tools to create business models that anticipate what might happen within an organization based on changes in defined variables. What-if analysis gives organizations the tools to identify how profits will be affected based on changes in inflation and pricing patterns as well as the impact of increasing the number of employees throughout the organization. Online analytical processing (OLAP) cubes can be created to identify dimensional data, and patterns within changing dimensions can be compared over time to contrast scenarios using a cube structure to automatically view the outcome of the what-if scenarios.
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