Organizations can spend as much as 60 percent of revenue to acquire the goods and services necessary to conduct business. Procurement professionals are being asked to reduce the organization’s overall spend, while simultaneously improving supplier collaboration. Companies now realize more than ever the effect of procurement strategies on their profitability and viability.

All organizations have data on their products, inventory, parts and services – and most organizations have more product data than they have customer data. Increasingly, this information is becoming even more important to the overall health of a business. Yet this means that poor-quality product data is also becoming increasingly problematic. The unique challenges in the management of product data can inhibit the search for supply chain optimization, spend management and a more unified view of the enterprise.

The problems with product or item data stem from the wide variety of structure and conventions for this type of information. While customer data has a relatively small set of defined and universal attributes (name, address, email address, phone number), product data is much more complex. For example, a single company may have multiple definitions and descriptions of something as simple as a 60-watt light bulb within its product data.

Just imagine how complex, inconsistent and unreliable product data can be if it arrives from a dozen different suppliers in your trading network. Organizations are also grappling with the fact that enterprise resource planning (ERP), supply chain management (SCM) and other applications have done little to solve these issues. These applications can encapsulate the processes that drive a business every day, yet they typically have no integrated data quality capabilities to find and eliminate bad data. But creating additional ERP or SCM applications on top of existing applications to correct these issues essentially develops redundant silos of product information, and further complicates an already complex task.

Issues such as duplicate product numbers, obsolete product IDs and inconsistent item descriptions exist across all departments within every organization, impacting every level of the operation. An inability to understand the products that are being sold can affect the organization’s ability to plan for new products in the future. Similarly, a confused, disparate view of direct and indirect spending can foil the most well-intentioned spend management efforts.

The bottom line is that poor-quality product data creates difficulties in controlling the costs of production, promoting the productivity of the company, and the delivering finished goods. After all, the data within your applications drives every decision, from long-range strategic planning to day-to-day operations.