Decision Support Systems, Part 2 – Business Performance Analysis

Decision Support Systems, Part 2 – Business Performance Analysis

In part 1, we described the approach to capture detailed information on ‘how successful the business was’ for a given time interval. The next step is to analyze the performance “why has the business been successful” or in lower level of detail “why didn’t product A sell as expected”.Factors which have contributed to the given business results are analyzed. Some analysis methods may be predetermined. However, as analysis proceeds, a need to apply ad-hoc analysis may arise.

The availability of detailed performance facts, captured in their full ‘dimensionality’ (e.g. time, geography, product, Customer or Customer group, Business unit involved), upgrades the analytical capability and allows complex fact processing in order to analyse complicates issues.

Analysis may involve specific issues, like:

  • Why is revenue on a specific product or customer group, below expectations ?
  • Profitability of a specific product or service – profitability comparison of various products or customer groups
  • Why productivity of a specific product is lower than planned
  • Analysis on the Customer profile to build customer insight
  • Analysis on Customer defection characteristics
  • Analysis on production quality on a specific product
  • Analysis on a product introduction
  • Analysis on a marketing campaign execution result

Analysis may help identify deviations from expected measurement values and alert the Business. For example:

  • Reduction in the consumption of services by a Customer, may be an indication that this Customer is about to defect.
  • Revenue reduction of a Branch unit, may lead to actionable decisions

Analysis needs change dynamically, as the internal and external business environment change. The captured data level of detail, should strike a balance between allowing in depth analysis and keeping overhead cost related to data capture under control. The exclusive use of predefined reports or queries, is not the best practice. A decision support system can contribute to the identification of trends, can enrich the view of facts (with richer dimensional data) and support the development of innovative strategy. The capability evolution, from simple capture of facts to the ability to analyze them in order to identify trends, is of particular value to the Business.

Copyright 2006 – Kostis Panayotakis

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