The first step in defining a common narrative and providing consistent analytics is to define a common starting point: a single version of the truth. Referential Data encompasses all data that is needed to harmonize multiple systems’ key business information including customers, products, materials, suppliers and the like.
The source system (e.g., a Product Information Master or PIM) for any given set of data should be the starting point for all analytics. While the same data can reside in multiple systems, only the source should be used when producing analytics. For example, an Item or SKU may reside in many different systems (Finance, Supply Chain, Marketing, etc.), but in most cases these subscribing systems will have only a subset of the total Item/SKU population and attributes that the Item’/SKUs source system will have. When this type of data is aggregated, data issues and disparity of results only get compounded. When referential data is not in sync across systems, seemingly straightforward reporting of key metrics such as sales can become the most daunting of tasks. When Items are missing or associated incorrectly to a hierarchy, sales numbers will never match between systems. Having an agreed upon starting point is the only way to not only consistently deliver the same results, but also speak a common language.