Using Analytic Hierarchy Process (AHP) for BI Tool Evaluation

Posted by Karthikeyan Sankaran
Comments (3)
April 15th, 2008

Enterprise wide BI architecture utilizes a multitude of tools within its landscape, each serving a specific functionality – Extract, Transform and Load (ETL), Data Cleansing, Metadata Management, Databases (both relational and multidimensional), Reporting and Analytics (OLAP), Data Mining etc. For example, just taking the OLAP area alone, there are more than 40 different products that can potentially solve a customer problem. You can imagine the number of combinations possible when all the tool options are combined across the overall landscape. This establishes the fact that one of the most challenging and vexing problems in Business Intelligence domain is Tool Evaluation.

Tool Evaluation and selection has become strategic to the implementation of enterprise wide Business Intelligence. Traditionally, tool selection involved comparing the technical features of the tools, looking at demos by product vendors, reading up industry reports, get word-of-mouth referrals and then taking a final decision. In my humble opinion – that is not sufficient any more.

Technical features, though important, cannot be the definitive criteria for selecting a particular tool. More crucial than technical features is what I term as the “Business Fitment Index”. The selected tool should fit with the characteristics of the business process prevalent in the organization and should take into account the requirements of different classes of users. The concept of Business Fitment can be classified as a Multi Criteria Decision Making (MCDM) problem and one of the powerful tools in this category is the Analytic Hierarchy Process (AHP).

AHP is a systematic procedure that helps to:

  1. Represent the elements of any problem, breaking it down into smaller constituents
  2. Assign weightages to each constituent by following a pairwise comparison technique
  3. Leverage expert judgment and intuitive feel into a coherent framework for problem solving

Though AHP can be used in many situations, Hexaware’s BI practice has perfected the art of leveraging its power in the realm of “BI Tools Evaluation”. There are 3 steps to calculating the Business Fitment Index using AHP.

Step 1 – Pair-wise comparison of business parameters by customer stakeholders is done in this step. The parameters can be things like – Real Time Data Integration, Data Volumes, Data Quality, Business Rules Flexibility etc.

Step 2 – Relative ranking of Business Parameters based on the AHP (Analytic Hierarchy Process) technique

Step 3 – Each of the short-listed tools are evaluated against the business parameters and a final rating is arrived at taking into account the organization readiness factors

Bottom-line is that the technical features of the tools have to be taken in conjunction with the fitment level of tool to the characteristics of the business. That alone would ensure the success of the tool for enterprise wide BI initiatives.

AHP is a simple yet powerful way of arriving at a decision by consensus. There are wide ranging applications of AHP in BI and this is a great area for practitioners to get interested. If you have some thoughts on other applications of AHP in the BI world, please do share it with us. Thanks for reading!

Comments (3)

Tom S. - July 23rd, 2008

What about rank reversal?

Karthikeyan Sankaran - July 12th, 2008

Thanks for your insight, Bharatheesh. I completely agree with you - AHP can be used to prioritize functional needs. Thinking from a Agile development standpoint, AHP can be used in combination with a SCRUM based agile approach to prioritize the "requirements backlog" (functional requirements) for each sprint. Thanks once again and do keep reading.

Bharatheesh Jaysimha - July 11th, 2008

Another area which we have successfully used AHP is in prioritizing the deliverables in a BI project. In a phased delivery approach, what has to be delivered to engage the user community to entice them to ask for more BI is very difficult. It should not be based on 'the highly paid person in the organization'. Rather the objective approach will be to evaluate different functional needs with respect to complexity and usefulness(in terms of profitable/actionable information!!) to the organization.

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