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What are the major risk factors in a data warehouse project implementation?

By
  • Joe Oates, Sid Adelman, Chuck Kelley, Clay Rehm, Les Barbusinski
Published
  • December 09 2003, 1:00am EST

Q:

What are the major risk factors in a data warehouse project implementation? Do you have any case studies for these risk factors?

A:

Sid Adelman’s Answer: Major risk factors:

  • Unrealistic user expectations
  • No management commitment
  • Unrealistic schedules
  • Budget too small
  • Untrained staff
  • Staff not available when you need them
  • Poor project management
  • Not properly architected
  • Exceeding platform capabilities
  • Inappropriate organization structure
  • Scope creep
  • Changing requirements
  • Changing priorities
  • Sponsor leaves the project
  • Database too big
  • Data cleansing underestimated
  • Vendors out of control
  • New technology not understood
  • Users not available when you need them
  • No procedure to settle disputes

Les Barbusinski’s Answer: Most of the fatal risks for a data warehouse project are organizational rather than technical (i.e., building a data warehouse that doesn’t address a relevant business need, for example).That said, Chapter 4 of Data Warehouse Project Management (by Sid Adelman and Larissa Moss) provides a pretty succinct list of the major risks that can confront a DW project.

Chuck Kelley’s Answer: Risks factors include, but not limited to a) not having a corporate sponsor high enough up the corporate ladder, b) project management that has never built a data warehouse and insists that it is done like a transaction system, c) in-fighting within your team, d) designing the database to be transaction- oriented vs. aggregation-oriented, and e) not having your user community involved in the requirements and development process.

Joe Oates’ Answer: There are many risk factors for data warehouse implementation. I do not have any case studies to cite but have been involved in more than 30 data warehouse implementation projects and can only cite experience. I will cover the risks that I have seen to be the most important. By the way, they have nothing to do with tools. Here is my list of most important risk factors:

  • Lack of strong sponsor or sponsor not at high enough level to get people motivated.
  • Lack of proper skills and experience. Most people have to go through at least one failure before they understand how different a data warehouse is from a transaction processing system or small data mart. You can have wonderful logical models, but turning those into an efficient, integrated, enterprise-wide physical design is a most difficult task.
  • Not understanding what the organization needs from a data warehouse and how the data warehouse helps achieve the strategic objectives of the organization.
  • Lack of a data quality project as an integral part of the data warehouse implementation. If users don’t have confidence in the answers they get from the data warehouse, they won’t use it.
  • Inadequate funding.
  • Political squabbles among and within organizational units.
  • Not having people who really understand the source system provided on a timely basis and for an adequate amount of time.
  • Poor project management.

There are many other risks, but these are the ones that I have seen, either singly or in combination, hurt data warehouse projects the most.

Clay Rehm’s Answer: There are more major risk factors than this column has space for! A good place for these is in the book by Sid Adelman and Larissa Moss called Data Warehouse Project Management. Some of the risk factors that come to mind are unsupportive/absent sponsors, a project with a "if we build it they will come" mentality, a technical environment already established waiting for a project.

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