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Data Warehousing Horizons:
Return on Investment Via Cost Savings

  Column published in DM Review Magazine
July 1999 Issue
 
  By Russell Mallay

Russell Mallay is a managing consultant and west region business intelligence practice leader for james martin + co. Mallay can be reached at rmallay@jamesmartin.com.

Return on investment (ROI) is the definitive metric of a project's value. Most businesses are expanding, and projects are justified based on revenue growth and obtaining competitive advantage. Yet we see many public, private and government organizations where the ROI is based on cost savings and improving efficiencies. Competition, downsizing, mergers and deregulation highlight the need for a lean and mean business.

Your data warehouse budget is best sustained through continual ROI measurement. This "lesson learned" outlines the business case approach and highlights examples to quantify the return on investment via cost savings.

The business case phase of an enterprise data warehouse project is focused on defining and prioritizing the data warehouse iterations based on cost/benefit analysis. The data warehouse business case stage is normally conducted in a four-to-six-week time frame with the essential activities being individual interviews and small group focus sessions with the business community. The business case development results include: high-level work breakdown structure for the entire project; cost/benefit analysis including ROI; critical success factors and inhibitors, project assumptions, and sponsorship (sponsor's approval and budget).

Soft ROI is fairly generic and less compelling than hard ROI. Typical data delivery benefits include timely, accurate, consistent, accessible, integrated, quality cleansed data. Typical productivity enhancements include improved staff utilization, empowerment, work smarter, ability to respond to changing business environment, pro-active vs. reactive, etc.

Hard ROI is your mission. Common cost savings are related to making efficient use of resources such as labor, materials, capital assets and overall throughput. The supply chain market segment targets similar cost savings. Here is a selection of actual data warehouse derived cost savings:

  • $500,000 per year savings in materials costs for processing.
  • $250,000 per year savings from volume discounts on materials purchases together with scheduled deliveries and cross- verification of delivered goods.
  • $120,000 per year savings in inventory holding costs due to the just-in-time scheduling and verification of deliveries.
  • $500,000 per year savings in capital improvement projects due to predictive replacement and predictive improvements to facilities.
  • $175,000 per year savings by avoiding regulatory fines.
  • $200,000 per year saved by incurring maintenance expenses based on actual usage instead of scheduled intervals that are not necessary.
  • $1,000,000 per year saved in extended useful life of capital assets by spending money on usage- or event-triggered preventative maintenance to avoid near end-of-life high maintenance costs, emergency fixes and down time.
  • $650,000 labor savings per year due to cross-training, scheduling and optimization of the operational labor force.
  • $2,500,000 cost avoidance by optimizing current facilities to avoid building additional facilities.

Costing analysis includes hardware, software, maintenance fees, maintenance labor, business users time, in-house development costs and consulting services. Technology costs are driven down by the maturity of data warehouse technology, new Web-enabled technology and cost-competitive data warehouse vendors such as Microsoft. These technologies also drive down development costs which encourages the practitioners to focus on the business results rather than technical feasibility.

Figure 1
FIGURE 1: ROI FOR THREE BUSINESS CASES

Figure 1 shows the results of three business cases achieved through three data warehouse iterations delivered at four-month intervals. The total ROI is achieved at 20 months when the cumulative benefits exceed the cumulative costs.

Project success must be measured in business results. Cost savings, cost avoidance and operational efficiency are profitable business case justifications. Cost savings are obtained by utilizing the analysis capability of the warehouse to derive actionable insight for business process improvements. Measure the value by tracking the derived insight, the related actions taken and the resulting benefits. Share the wealth with the extended project team by offering prizes for the best substantiated ROI example on a quarterly basis. Success is seeing the profit trend increase with the roll out of your data warehouse.

...............................................................................

For more information on related topics visit the following related portals...
Business Intelligence and Strategic Intelligence.

Russell Mallay is a managing consultant and west region business intelligence practice leader for james martin + co. Mallay can be reached at rmallay@jamesmartin.com.

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