Success factors for a BI solution
The success factors those are essential for Business Intelligence projects, in addition to the technical issues and challenges are:
• Scope the project to be able to deliver within at least six months
• Select a specific business subject area; do not try to solve all business requirements within one project.
• Find a sponsor from the upper management of the business side of the company
• Involve the sponsor throughout the project
• Establish a sound information and communication structure that includes business and technical staff inside and outside the project
• Define the contents and type of the deliverables of the project as early and in as much detail as possible
• Together with the end users validate the results of the analysis phase (the initial dimensional models) against the deliverables definition
• Deploy the solution quickly to a limited audience and iterate development
• Establish commonly agreed on business definitions for all items within the scope of the project
• Validate the quality and correctness of the information before making it available to the end user community
• Keep the end users involved and informed throughout the project
• Be prepared for political and cultural obstacles between business departments or between business and IT departments
There are a number of examples of success indicators. Let us take a look, below, at some measures of success.
1. Return on investment (ROI). A ROI can be achieved in a number of ways, such as:
• Lower cost - Costs could be lowered through better inventory management, fewer dollars spent on unproductive measures, product promotions, and so on
• Improved productivity - Greater productivity could be expected from both IT and the user. Today user analysts may spend 80 percent of their time gathering data and only 20 percent analyzing the data. The data warehouse should reverse those numbers. IT will still be responsible for developing complex reports, as well as writing reports for production systems. The data warehouse can provide reporting tools with a well documented, clean and easily accessible database. This capability should significantly improve IT productivity
• Increased revenue - This could be a result of greater market share and increased sales as marketing is able to more effectively target customers and provide the right products at the right time to the right market. The effects of costs and revenues may be difficult to assign to the impact of the data warehouse. As the data warehouse is being implemented, the organization is not standing still. There are both internal and external factors that impact costs and revenues, so the actual benefits of the data warehouse may be difficult to determine
2. The data warehouse is used. One of the easiest categories to understand can be measured by the number of users and the total number of queries and reports generated. If queries and reports are run regularly, it is a good indication that the users are achieving some benefit.
3. The data warehouse is useful. The data warehouse may be used, but the users may find the benefits to be marginal and illusive. It is important to ask the users what they see as the benefits of the data warehouse, how it has changed the way they do business, how it may have improved their productivity and how it may have improved the quality of their decisions.
4. The project is delivered on time. This measure is problematic, as schedules are often set without an understanding of what is involved and how long each project task will take. “On time” is only relevant if a realistic schedule is the base for comparison.
5. The project is delivered within budget. This criterion may be difficult to achieve since the total costs of a data warehouse are difficult to determine. Initially, you may not have known how many users to expect, how many queries and reports they would be generating and the complexity and resources used by the queries and reports. You did not know how large the data warehouse would be or how many indexes and summary tables would be required and desired. You may not have anticipated needing a larger CPU. You may not have known that the software was more difficult than the vendors represented, resulting in teams of software consultants being required. You may not have anticipated needing to upgrade your network to support the increased line traffic. You may not have anticipated needing to raise the salaries of the data warehouse team, nor the increased cost of recruiting the talent required to make the project a success. All these factors will contribute to severely underestimating the budget. “Within budget” is only relevant if a realistic budget is the basis for comparison.
6. There is improved user satisfaction. Users may be internal, external, or both. In all cases, the goal is to have users who are happy with the features and capabilities, performance, quality of the data, and level of support.
7. There are additional requests for data warehouse functions and data. You will know you were successful if other user departments are beating down your door with requests for access to the data warehouse, and current users are requesting new data and functions to be added to the existing data warehouse.
8. Business performance-based benchmarks. This is the most subjective of all the measures and will become the most controversial. Most industries have sets of industry averages, as well as to benchmark (the best) companies against which they make comparisons. For example, the industry average for quality, represented by the number of defects for a new car, may be three, while the best is one. With better information, a car manufacturer in the middle of the pack may have a goal to manufacture a mid-size sedan using eight worker days. The data warehouse may be able to provide improved, more complete and timelier information, and, with this information, the auto manufacturer may be able to achieve their productivity goals.
9. Goals and objectives are met. On the assumption that you have developed goals and objectives, success will be defined by how well these goals and objectives were met. No doubt, not all were met or were only partially met. A scorecard will give you an initial - and then an ongoing - measure of your project’s success.
10. Business problems are solved. The data warehouse was developed for some specific reason. Perhaps marketing was unable to identify customer demographics for target marketing. If the data warehouse now provides this capability, it should be considered a success.
11. Business opportunity is realized. The identified opportunity might have been the ability to provide information to suppliers through the Web, so they would be able to respond more quickly to your demands for components that you need for your manufacturing process. If the supplier now has fewer stock-outs, the project is successful.
12. The data warehouse has become an agent of change. The world is changing, and the rate of change is accelerating dramatically. Successful organizations must be able to respond and respond quickly.
Decisions must be made more quickly, but this can only happen with better and more timely information. There can be some fundamental changes to the business in the manner and speed in which decisions are made and the data warehouse can be the vehicle for that change.
Posted on September 29th, 2008 by Sanjay Mehta
Filed under: Business Intelligence
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