How can I convince management to buy a solution when the team I have is inadequate (either not enough manpower
or lack of experience, or both) and there is a hiring freeze?
First you start with capabilities. Regardless of financial resources available to support the DW/BI solution, does your company have the "chops" to be successful at such a thing? And I don't just mean the technical skills and experience.
We use an multi-part evaluation template with our clients that we developed over the past 10 years specifically to help with the planning and development of DWs. Part 1 focuses on organizational history in building systems; demonstrated abilities in the company in project management, communications, transition and relationship management; an inventory of tech, business and soft skills critical to developing, executing and maintaining a data warehouse; and the history of senior management, the business unit and the IT department support for various IT-enabled initiatives. We compare the results of this evaluation to a collection of better/best practices that we've developed from years of expert analysis and consulting. We do, in fact, split our analyses between back-end processes and front-end decision support pieces.
Part 2 of the evaluation uses job descriptions for DW/BI initiatives that I originally developed in 1994 as an analyst with META Group. They are, in fact, the industry's first comprehensive organizational view of the data warehouse and have been updated and revised several times since then. We have been regularly updating and tracking salaries and skills pay for 19 data warehousing/business intelligence positions four times a year since 1995. We usually do a human capital evaluation using these as a baseline. From this we can judge in-house staffing capabilities, identifying strengths and weaknesses and areas where outside assistance (or new hiring) would be necessary.
The rest of our evaluation is outlined around the following criteria and success factors.
- Why a data warehouse
- Goals and objectives
- Desired characteristics
- OLTP vs. data warehouse
- Tangible benefits
- Intangible benefits
- Cost elements
- Budget issues
- User buy-in
- Examples of failures
- Challenges to DW quality
- Risks inherent in DW projects
- Risk mitigation
- Hardware platform
- Tools, software
- Selection of first project
- User expectations
- User responsibilities
- Service-level agreements
- Developing the project plan
- Work breakdown structure
- Evaluating products
- Evaluating vendors
- Reference checks
- Getting the most from your vendor
- Critical success factors/bare essentials for success
- Success criteria
- Measuring results/measures of success
- Promoting and marketing the data warehouse
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