FREE DM Review Site Registration!
Sign-up today and access DM Review on the Web!

Your FREE registration entitles you to:
FREE email newsletters

FREE access to all DM Review content

FREE access to web seminars, resource portals, our white paper library and more!

   

Are there any templates, checklists or questions to consider that would assist in prioritizing the various projects/initiatives required by data warehouse clients?

Question: Are there any templates, checklists or questions to consider that would assist in prioritizing the various projects/initiatives required by data warehouse clients?  I am looking for a logical analysis that could justify to clients why we are proceeding with one project first versus another.

Joe Oates’ Answer: I don't really know of any checklist for prioritizing various projects/initiatives.  I can, however, share with you an approach that has worked very well.

 

This is a variation of the Kepner-Tregoe decision analysis approach.  First, create a matrix with the following columns: criteria, weighting factor, weighting score for Project 1, weighted score for Project 2 and weighted score for Project N.  Some typical criteria include: ROI, resources, elapsed time and alignment with strategic goals.

 

First, you must come up with weights from one to ten for each of the criteria. Normally, ROI is rated highly.  I would suggest you work with team members and management to come up with the respective weights.  Next, you must calculate a weighted score for each of the candidate projects.  The weighted score for ROI is usually the ROI times the weighting factor.  Next, summarize the individual weighted scores for each project.

 

However, you can't stop there.  You must evaluate the possible adverse consequences of not doing each of the projects - that the customer will go to the CFO and have you transferred to the South Pole for example.  Then list these in a matrix below the original matrix.  The columns in this matrix are: adverse consequence, impact (of not doing the project) on the department and the probability of happening.  For each adverse consequence, in the impact on the department column enter an H, M or L for high, medium or low.  Assess the probability of the adverse consequence happening as a result of not doing the project.  Those adverse consequences that have a high-high, high-medium or medium-high adverse consequence probability may cause you to change the ranking based on the weighted score.

 

Of course, there may be a policy, such as a cutoff for ROI or other criteria, that will prevent the project from being initiated. 

 

Larissa Moss' Answer: Data warehousing (DW) projects or business intelligence(BI) applications should be prioritized by the BI steering committee, which is an advisory body of senior business executives who meet on a regular basis to discuss, plan, staff and fund DW and BI projects. Together, the executives provide collective sponsorship to the BI/DW program. They must carefully prioritize the BI applications (DW projects) and decide which ones have the highest business value. Since all BI applications share the same BI/DW infrastructure, the same pool of resources, much of the same data and many of the same processes, very strong interdependencies exist.

Because of these interdependencies, fewer BI applications can be scheduled and coordinated at the same time. Therefore, it is up to the business executives on the BI steering committee to prioritize the projects based on these constraints and based on their knowledge of where the biggest business pain is in the organization and what BI application would provide the highest payback. If you do not have a BI steering committee, it is still up to the business executives to negotiate BI/DW priorities amongst each other. It is not up to the DW team to set BI/DW priorities (with or without templates and checklists).

 

Sid Adelman's Answer: These are some questions to consider:

 

  1. Who is asking for this project? If it is the CEO or some other big dog, the project goes to the top of the heap.
  2. Is there a regulatory requirement for this initiative? Even with a mandatory regulatory requirement, the priority should be based on when the requirement kicks in. Some regulations get changed, killed, or deferred so don’t jump the gun.
  3. What’s the return on investment (ROI) on this project (assuming you cost justify each of the projects)?
  4. Is there a logical progression where one project should be the precursor of another?
  5. Do not choose one where the source data is dependent on a project not yet complete.
  6. In addition to the questions above, if you have a choice, start off with:
    • The smallest     
    • The least complex
    • The one with the cleanest source data
    • The one with the fewest sponsors to satisfy
    • The one with the most powerful and reasonable business sponsor
    • The one that is the least contentious

Sid Adelman is a principal in Sid Adelman & Associates, an organization specializing in planning and implementing data warehouses, in data warehouse and BI assessments, and in establishing effective data architectures and strategies. He is a regular speaker at DW conferences. Adelman chairs the "Ask the Experts" column on www.dmreview.com. He is a frequent contributor to journals that focus on data warehousing. He co-authored Data Warehouse Project Management and is the principal author on Impossible Data Warehouse Situations with Solutions from the Experts and Data Strategy. He can be reached at (818) 783-9634 or sid@sidadelman.com. Visit his Web site at www.sidadelman.com.

Larissa Moss is founder and president of Method Focus Inc., a company specializing in improving the quality of business information systems. She has more than 20 years of IT experience with information asset management. Moss is coauthor of three books: Data Warehouse Project Management (Addison-Wesley, 2000), Impossible Data Warehouse Situations (Addison-Wesley, 2002) and Business Intelligence Roadmap: The Complete Project Lifecycle for Decision- Support Applications (Addison-Wesley, 2003). Moss can be reached at methodfocus@earthlink.net.

Joe Oates is an internationally known speaker, author and consultant on data warehousing. Oates has more than 30 years of experience in the successful management and technical development of business, real-time and data warehouse applications for industry and government clients. He has designed or helped design and implement more than 30 successful data warehouse projects.

For more information on related topics, visit the following channels:



Industry Vendors