Data Warehouse economics
 


Economics refer to feasibility of the product or service. In business, profitability occurs when revenue exceeds expenses. Using the total cost of a product to calculate expenses gives you a more accurate picture of profitability. The total cost of a product takes into account a wide range of expenses, including all fixed and variable costs associated with producing the product.

Operational feasibility– a measure of how well a solution meets the system requirements.
Cultural (or political) feasibility- a measure of how well a solution will be accepted in an organizational climate.
Technical feasibility– a measure of the practicality of a technical solution and the availability of technical resources and expertise.
Schedule feasibility– a measure of how reasonable the project timetable is.
Economic feasibility- a measure of the cost-effectiveness of a project or solution.
Legal feasibility- a measure of how well a solution can be implemented within existing legal/contractual obligations.
Operational feasibility– a measure of how well a solution meets the system requirements.
Cultural (or political) feasibility- a measure of how well a solution will be accepted in an organizational climate.
Technical feasibility– a measure of the practicality of a technical solution and the availability of technical resources and expertise.
Schedule feasibility– a measure of how reasonable the project timetable is.
Economic feasibility- a measure of the cost-effectiveness of a project or solution.
Legal feasibility- a measure of how well a solution can be implemented within existing legal/contractual obligations.
 
 

Economic Feasibility of Data Warehouse 

Just as any computer system must be justified in financial terms, the data warehouse project must also demonstrate an ability to add a positive cash flow to the company that undertakes to create the warehouse. Economic feasibility considerations include (but are not limited to) development costs, warehouse benefits, and ROI (return on investment).

DEVELOPMENT COSTS

As we know, it’s fairly simple to calculate the hardware and software costs for creating the data warehouse. All of a data warehouse’s basic costs, such as the cost of the processor and disk, are known in advance and are fully quantifiable. But, there are other hidden, intangible costs which may be quite real, but are more difficult to quantify. For example, using a nascent technology may provide a competitive advantage, but there is a very real cost associated with the risk in using a new technology. Some managers have resorted to a probabilistic method for attempting to quantify the costs of risk, just as actuaries have developed very sophisticated methods for assessing the costs associated with risks. However, risk costs are rarely factored into the development costs of a data warehouse project because they cannot be precisely measured. But does this mean that the cost does not exist? Of course not. The costs associated with risk will become tangible during the development of the data warehouse, when increasing human and technical resources are required to fix problems that crop up during the implementation phase of the warehouse. While development costs may not be factored into development costs, the costs should not catch developers by surprise. Developers should keep hidden risk costs in mind, especially when conducting a feasibility study.

WAREHOUSE BENEFITS

The benefits from a data warehouse are far less easy to measure than development costs. Benefits for a data warehouse project fall into two categories: tangible benefits and intangible benefits. Of course, it is important to have a very concrete idea about the benefits that will accrue from a data warehouse project, especially because the expenditures of human resources and computer equipment is a substantial investment.