The old adage of "build it and they will come" doesn't work for today's business intelligence users. Users today have unique, complex questions and issues that must be clearly understood before embarking on a data warehouse-generated business intelligence project. Users require that the data warehouse provide a solution to their business needs. Employing the approach described in this column, users recognize from project inception that their business needs are being addressed through initiation of the business case development phase of the project.
To further complicate matters, users generally require tangible results (such as reports and analysis information) within three to six months of project inception. How should you approach a data warehouse project in which you want to ensure that you are going to deliver a functional system providing users with business value and consistent, reliable releases on a timely basis? Simple. Use a proven methodology, or approach, that facilitates this process.
This is the first of a three-part series outlining an approach that can work for you and your organization.
The data warehouse develop-ment approach illustrated in Figure 1 provides an outline for the project approach. As you can see, certain aspects will be performed once with an enterprise-wide focus, and others will be performed in an iterative manner. This iterative-release approach provides the quick three-to-six-month releases that most users need.
This month I will focus on two of the most important structures of the data warehouse project project management and business case development. In Figure 1, these sections are highlighted in red.
Before starting the project it is important that everyone on the project understands that an overall project management rigor will be applied to all aspects of the project and that this project management approach is results oriented plan to activate, control to end. An easy way to remember and communicate this rigor is to consider setting the PACE of your project.
Plan. The initial planning phase should start by establishing the scope, standards, project objectives, risks and list of deliverables for the project. Once completed, the plan must be finalized and approved by both the business and IT managers. A solid plan will set the foundation for a successful project.
Activate. The most important aspects of activating the project are establishing adequate publicity, providing appropriate training and getting the project up and running. Because the data warehouse project will impact both the business users and technical developers, it is important to hold a kick-off meeting to educate the developers and users of the overall goals and objectives of the project and how it will impact them. Also, providing adequate training is essential to both business users and IT staff. The key to a successful activation is that all business stakeholders and participants are ready, willing and able to make the project a success.
Control. Control of the project is an ongoing process and is primarily one of constant communication, both within and outside the team. The project manager must assess not only status against the plan but also must be sensitive to the needs of the stakeholders and how to manage those expectations. Focusing (and often refocusing!) the participants on the core objectives of the project is key.
End. At the end of the project, the team should capture the lessons learned during design, implementation and testing; archive the project materials; report on the project's performance; turn over the project results to the operations and support staff; and release project resources for use on other projects. Never underestimate the importance of formally bringing the project to closure.
The business case specifies and supports the justification for a data warehouse, estimates the costs, identifies the project's executive sponsor(s) and gets their approval so that development can begin. As part of this phase, the team should document the following:
High-Level Work Breakdown Structure. This should contain summary-level tasks that reflect major efforts. This helps management understand the project better and helps the team create budgets (time and cost) more accurately. Specifying these tasks is critical to the success of the project.
Cost/Benefit Analysis (including ROI). This phase consists of working with the key business users to identify costs and to assign relative weights to the high-level business benefits of the data warehouse. In order to do this, you should document all the expected costs associated with the project such as software, hardware, internal resources and consulting costs. Then review the expected benefits of the project. Examples include reduced costs, increased revenue, ability to perform target marketing and ability to respond to marketplace shifts. This comparison of the costs and benefits will allow you to see the cause and effect of developing your data warehouse.
Critical Success Factors (CSFs) / Inhibitors (CSIs). Utilizing focus sessions is the best approach for gathering CSFs and CSIs. Some possible CSFs include sound architecture design, realistic project scope, dedicated staff, and approved and available budget. Some possible CSIs include unrealistic schedules and expectations, lack of involvement by business and IT users, lack of commitment by executive sponsors and impact of other strategic technology projects.
Project Assumptions. The project assumptions must be in place for the project to be conducted as planned. These are based on detailed analysis of the specific project. Examples include:
- Scope of project will be limited to X and will begin no later than X date.
- Defined resources will be available on X date.
- Appropriate resources will be available for interviews and strategy sessions.
The Completed Business Case Document. Once completed, you should present the business case document to management for approval. This document serves as the foundation for the rest of the project and provides a point of reference as project team members join the project.
You now have "made the case" for implementing the data warehouse. Next month, I will provide information on how to collect business requirements to support the business case utilizing the "business question assessment" as well as how to establish the data warehouse technology strategy employing the "architecture design and tool selection" technique.
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