The Business Intelligence ROI Challenge

Calculating the ROI for data warehouse and business cleverness projects is a very complicated and perplexing task. Today’s decision manufacturers can no longer accept being struggling to calculate the ROI for data warehousing and business cleverness projects. This article provides a practical platform and process for calculating ROI for data warehouse and business cleverness projects.

In the first 1990s, mantras such as build it and they’ll come or creating a data warehouse is an excellent thing to do justified many data warehouses. Soft statements such as necessary to the business to stay competitive, improved access to data, and yields many intangible benefits are insufficient for the majority of today’s upper-level decision manufacturers. As a result, data warehouse and business cleverness tasks almost always require business justification through ROI analysis.

Companies now wish to know the business case, the worthiness proposition, and the potential ROI of the data warehouse project before funds are committed. Projects that are funded to deliver measurable, positive impact to the financial bottom line in either income generation or cost savings. There is hope for project managers, executive project sponsors, and CIOs facing the duty of assessing the advantages of data warehousing projects. One of the largest studies of data warehouse ROI, conducted by International Data Corp.

1996 touts an average 401 percent, three-year profits on return for 62 organizations with data warehouses. However, many companies haven’t any uniform, exhibited ROI processes. A TDWI study of 1 1,600 companies released in March 2001 demonstrated only 13 percent of respondents monitoring data warehousing ROI over the value string. Thirty-seven percent said they intend to begin tracking ROI and 27 percent said they aren’t tracking returns and have no plans to do so, underscoring that ongoing companies continue to struggle with the ROI concern. Calculating the ROI for a data warehouse is difficult because of the many qualitative or intangible benefits provided. Furthermore, the data warehouse is generally not associated with an action.

For example, the info warehouse may point out a location where sales can be increased through a mix selling a certain product but a sales representative still must make the sales call and close the sale to increase revenue. In reality, despite the actual tool vendors tell you, data warehousing and business intelligence don’t give an immediate, quantifiable financial return as an interest-paying Compact disc or connection does. The return on data warehouse investment can be produced from improved decision making and productivity because of this of having better information sooner, as well as the new or modified processes enabled by the data warehouse.

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Business cleverness leads to other new or modified processes that result in reduced costs and higher income. It really is still important to understand and quantify the benefits and costs necessary to make an informed decision. All data warehouse and business intelligence projects should have ROI justification prior to funding and each project or phase should be able to stand on the merits of the project ROI. Business intelligence efforts often can, and really should, be justified through a comparison of approximated ROI to other uses for the funds. ROI is calculated to provide an initial business value analysis evaluation that quantifies the financial rewards of a business intelligence task, allowing managers to judge and prioritize various IT initiatives within their organization.

As the area of the post-project review, recalculate the ROI and compare it to the initial ROI figure. Following is a step-by-step approach for determining the ROI for your data warehouse or business intelligence project. Define and document the business problem and business objective and identify the business goals had a need to solve the problem or meet the business objective. Begin by ensuring you have outlined the current situation, including identifying the main element business problems or “pain” the business is experiencing, combined with the overall dependence on the project.