In an effort to separate hype from reality the Rainmaker Group has been documenting the top reasons our clients used in their decision making process when evaluating decision support technology. This is part one of a multiple part series reporting our discussions with middle market CEO’s.

One Version of the Truth
Most organizations have many silos of disconnected data and dozens or even hundreds of spreadsheets. Marketing has campaign data, finance has AR/AP and budgeting data, sales produces a weekly forecast in Excel. Because the data exists in multiple formats with contradictory definitions, and unexplainable gaps in quality it is not easily assembled together to form a coherent consolidated picture. A decision support system helps to alleviate this problem by consolidating all data into a centralized repository (data warehouse) and by providing users with tools to access, analyze and visualize the data. Common business logic like “top customers” can be defined within the tools and used across the organization establishing one version of the truth.

Reduced Reporting Costs
The steps necessary to build a report with or without a data warehouse are essentially the same. One must find the data needed for the report, access the data, integrate the data, merge data, and build the report. This process is repeated for each new report. Research indicates reports built in a traditional fashion against an operational data store (ODS) cost between $25,000 and $1,000,000 to build. Although the steps remain the same when building a report with a data warehouse in place the time and complexity is shifted from each individual report to a one-time up front investment where a cube is built which can serve large numbers of unique reports. And the actual report building can be accomplished by a non-technical end-user as opposed to IT. Studies consistently show the cost to build a report using a data warehouse is between $500 and $10,000. The return on investment opportunity is huge and immediately quantifiable. As examples Verizon reports more than a 50% reduction in the time and effort to create a new report, and InFocus calculates more than $10,000 per week in cost reduction.

Historical Data
Most organizations have invested heavily in installing and optimizing operational data systems (ODS). These ODS follow traditional database design techniques based on snowflake design and normalized data. They are built for speed of transaction processing which requires them to dump historical data very fast. Typically within 60-90 days. If your business or the environment in which you operate did not change, this would be acceptable. The problem of course is that your business does change. For example what if one of your top customers moves business addresses 4 times in the next three years as they grow? If you run a 5 year sales history by sales territory will you see an accurate picture of sales and how that customer fit into the mix? Without specific intervention to piece together their data outside the ODS the answer is almost certainly no. A data warehouse is specifically structured to handle the unique challenges of storing and reporting on historical data. Everything about your business changes from pricing, to customers, products, suppliers, and business locations; a data warehouse is specifically designed to handle changes in business conditions without degrading the quality of data and still providing an accurate historical view.

Ongoing Compliance for Sarbanes-Oxley

Now that your organization has addressed the initial SOX reporting regulations it’s time to turn your attention to ongoing compliance. Ongoing compliance means dealing with issues like email communication, and other documents which are very hard to manage. The Rainmaker Group has a solution to help with “unstructured data” on an enterprise-wide basis.

Contact us to learn more today! sales@rainmakerworks.com