DATA WAREHOUSING
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Department DSR vs. Enterprise DSR: Understanding the Difference
The demand signal repository (DSR) is not just a database of point-of-sale data that allows one or two functional teams to be more effective. The DSR, instead, is an ongoing process built on a solid foundation to enable the consumer products enterprise to truly achieve increased sales and reduced costs.
In the DSR strategy for your organization, it is important to recognize the difference between Department or Team DSR, versus a true Enterprise DSR. Relational Solutions has spearheaded the distinction between the two since the DSR acronym was coined. The company used the Enterprise DSR distinction to point out the vast differences in the options available. Vendors providing completely different solutions were all thrown into the same DSR category simply because reports contained sales data. But the solutions available are vastly different and more and more, these differences are being understood and embraced as the industry matures.
A Team DSR is one focused on traditional category reporting for a specific retailer team. This is a non-integrated, silo approach. Financial returns are limited without the ability to expand the solution easily into other areas of the enterprise.
Architecturally, the Team DSR solutions are vastly different than the Enterprise DSR. The former solutions are point applications designed to produce buyer reports. They were not designed from the ground up for multi-retailer reporting or for long-term scalability and seamless integration of internal and other third party data. Expansion of data sources can be very painful, if not impossible.
The Enterprise DSR was built from the ground up to support multiple retailers and multiple internal and external data sources. It was designed with the full enterprise in mind. There are many different groups within an organization that can leverage POS data. Category teams are just one of many teams that can provide value to the business. Extrapolating the positive results across the enterprise is crucial to show substantial financial return.
Even a small or incremental improvement in one area or retailer can often yield a significant company return when extended across the entire retail landscape. The ability to take an analysis -- for example, on shelf availability -- from one retailer, and extend that capability across all retailer accounts will enable the organization to achieve true competitive advantage. Once considered a luxury, an Enterprise DSR is quickly becoming a necessity for companies. Retailers are demanding more insight. Streamlining internal efficiencies is a necessity.
In this process, it is very important that the organization has a solution in place that can start with perhaps one to two retailers, and quickly expand and scale to deploy additional retailers. A solution is needed that can integrate all POS information provided by the many retail chains, including retail chains across the globe. Leveraging international downstream sources is becoming imperative in many organizations.
Whether supplied via Electronic Data Interchange (EDI), txt or a proprietary application such as Walmart’s Retail Link, the retail information requires a proper integration and data architecture solution, with abilities to consolidate, harmonize, and align the data into a common environment. This capability requires inclusion of shipments, ERP/SAP data, forecasts, and other internal data sources, in addition
to the POS, syndicated, and other outside data. The end result enables cross-retailer views, but also allows for cross-functional capability that enables new insights not available for the organization in their current environment.
Meanwhile, the effectively-built Enterprise DSR foundation will allow an organization to see tangible ROI in supply chain, new product introduction, trade promotion effectiveness, consumer understanding, and others areas. This will be achieved through faster, more effective, forward-thinking insights. The insights are built on a strong marriage of the downstream POS data with internal operational data, yielding the highest possible return on investment.
It is important to recognize that additional data sources will continue to be made available with time. Just several years ago, loyalty card data was hardly heard of. Now it is quite widespread. Additionally, social media data is rapidly becoming important for consumer understanding. An Enterprise DSR provides companies with a long-term strategy that makes use of every data source available to gain competitive edge. The Enterprise DSR will enable support and management of cross-organization analytics with these new sources for financial success.
There are a few other areas worth thinking about as consumer products companies plans their Enterprise DSR strategy. Here are a few:
The importance of change management for the organization itself While deploying a strategy to enable demand-driven insights, it is important not to underestimate the importance of process change management as part of the initiative. With POS data, for example, the company is using data for new purposes. As a result, process changes will need to be managed. The conversion of an organization to use more downstream demand data, in addition to data such as orders and shipments (for example), will not happen overnight.
Evolution and data changes as part of the process Ensure that the organization realizes that ongoing evolution of the DSR will take place. This will come in multiple forms, including retailer consolidation, UPC changes, re-statements of data, new application inclusion, and new data sources. Varying 3rd party data is constant, and is to be expected. This evolution is a sign of success as it leads to enhancements of the Enterprise DSR. Enhancements support different groups within the organization and on-growing needs of the business including new products, mergers, acquisitions, new markets, etc.
Rapid deployment, and importance of short-term ROI for long-term success Getting a short-term ROI established through rapid deployment of an initial demand data project for one to two organizations will help sell a longer-term phased approach internally to senior management. One important ingredient to success will be ensuring your solution involves the right hardware, software, ETL, ELT, and data models.
Speed of analytics and optimization - choosing the right hardware Understanding how the most challenging analytics will perform for end users is important. Analytics that involve complex algorithms
or vast amounts of data should be looked at closely to ensure optimal performance. (for example,
multi-year trend analysis, shopping basket analysis, etc.). This will help you understand ‘before and after’ performance and ensure you run the DSR analytics on the best hardware / appliance possible for your needs.
In summary, the DSR is the hub, the foundation, to enable the right analytics approach for the CP organization. The demand signal repository, properly managed, can be as transforming to the CP enterprise as SAP/ERP deployments were years ago. The long-term result is a demand-driven, near real-time, forward thinking business. With the enterprise approach, the return on investment is maximized as companies realize increased profits, reduced costs across multiple functional areas, and improved customer service.
This article was co-authored by Kevin Abele, Consumer Products Global Solutions Manager, IBM Corporation (kwabele@us.ibm.com,), 513-826-1774, and Janet Dorenkott, Chief Operating Officer, Relational Solutions (info@shoppertech.org), Westlake, Ohio, 440-899-3296 (ext 25).
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