Justifying Your Data Warehouse

Justifying Your Data Warehouse
Even if your company. is a medium-sized company, when everything is accounted for, the total investment in your data warehouse could run to a few million dollars. A. rough hi breakdown of the costs is as follows: hardware – 31%; software including the DBMS— 24% staff and system integrators-35%; administration-10%. How do you justify the total cost by balancing the risks against the benefits, both tangible and intangible? llow can you calculate the ROI and ROA? How can you make a business case?

It is not easy. Real benefits may not be known until alter your data warehouse is built and put to use fully. Your data warehouse will allow users to run queries and analyze the variables in so many different ways. Your users can run what-if analysis by moving into several hypothetical scenarios and make strategic decisions. They will not be limited in the ways in which they can query and analyze. Who can predict what queries and analysis they might run, what significant decisions they will be able to make, and how beneficially these decisions will impact the bottom line?

Many companies are able to introduce data warehousing without a full cost justification analysis. Here the justification is based mainly on intuition and potential competitive pressures. In these companies, the top management is able to readily recognize the benefits of data integration, improved data quality, user autonomy in running queries and analyses, and the ease of information accessibility. If your company is such a company, good luck to you. Do some basic justification and jump into the project with both feet in.

Not every company's top management is so easy to please. In many companies, some type of formal justification is required. We want to present the typical approaches taken for justifying the data warehouse project. Review these examples and pick the approach that is closest to what will work in your organization. Here are Milne sample approaches for preparing the justification:

1. Calculate the current technology costs to produce the applications and reports sup-porting strategic decision making. Compare this with the  ' mated costs for the data warehouse and find the ratio between the current costs and proposed costs. See if this ratio is acceptable to senior management.
2. Calculate the business value of the proposed data Warehouse with time estimated dollar values for profits. Dividends, earnings growth, revenue growth, and market share growth. Review this business value expressed in dollars against the data warehouse costs and come up with the justification.
3.  Do the full-fledged exorcise. Identify all the components that will be affected by the proposed data warehouse and those that will affect the data warehouse. Start with the cost. Items, one by one, including hardware purchase or lease, vendor software in-house software, installation and conversion, ongoing support, and maintenance cost. Then put a dollar value on each of the tangible and intangible benefits including cost reduction, revenue enhancement, and effectiveness in the business community. Go further to do it cash flow analysis and calculate the ROI.

Top Management Support

Top Management Support
No major initiative in a company cao succeeds without the support from senior management. This is very true in the case of the company's data warehouse project. The project must have the kill support of the top management right from day one.

No other vender unifies the information view of the entire corporation as the corporation's data warehouse does. The entire organization is involved and positioned for strategic advantage. No one department or group can sponsor the data warehousing initiative in coil party.

Make sure you have a sponsor from the highest levels of management to keep the focus. The data warehouse MUM often satisfies conflicting requirements. The sponsor must wield his or her influence to arbitrate and to mediate. In most companies that, launch data warehouses, the CEO. Is also directly interested in its success. In some companies, a senior executive outside of IT becomes the primary sponsor. This person, in turn, nominates sonic of the senior Managers to be actively involved in the day-to-day progress of the project. Whenever the project encounters serious setbacks, the sponsor jumps in to resolve the issues.

Business Requirements Not Technology

Business Requirements Not Technology
Let business requirements drive your data warehouse, not technology. Although this seems SO obvious, you would not believe how many data warehouse projects grossly vio-late this maxim. So many data warehouse developers are interested in putting pretty pictures on the user's screen and pay little attention to the real requirements. They like to build snappy systems exploiting the depths of technology and demonstrate their prowess in harnessing the power of technology.

Remember, data warehousing is not about technology, it is about solving users need for strategic information. Do not plan to build the data warehouse before understanding the requirements. Start by focusing on what information is needed and not on how to provide the information. Do not emphasize the tools. Tools and products come and go. The basic structure and the architecture to support the user requirements are more important.

So before making the overall plan, conduct a preliminary survey of requirements. I low do you do that? No details are necessary at this stage. No in-depth probing is needed. Just try to understand the overall requirements of the users. Your intention is too vain a broad understanding of the business. The outcome of this preliminary survey will help you formulate the overall plan. It will be crucial to set the scope of the project. Also, it will assist you in prioritizing and determining the rollout plan for individual data marts. For example, you may have to plan on rolling out the marketing data mart first, the finance mart next, and only then consider the human resources one.

What types of information must you gather in the preliminary survey? At a minimum, obtain general information nit the following from each group of users:

• Mission and functions of each user group
• Computer systems used by the group
• Key performance indicators
• Factors affecting success of the user group
• Who the customers are and how they are classified
• Types of data tracked for the customers, individually and groups
• Products manufactured or sold
• Categorization of products and services
• Locations where business is conducted
• Levels at which profits arc measured---per customer, per product, per district.
• Levels of cost details and revenue
• Current queries and reports for strategic information

As part of the preliminary survey, include a source system audit, liven at this stage, you must have a fairly good idea from where the data is going to be extracted for the data warehouse. Review the architecture of the source systems. Find out about the relation-ships among the data structures. What is the quality of the data? What documentation is available? What are the possible mechanisms for extracting the data from the source systems? Your overall plan must contain information about the source systems.