Supply chain business intelligence is still in its infancy. Most BI platforms and supply chain management applications fall short in capturing and modeling the intricacies of global supply chain networks. Reconciling disparate data definitions, establishing a common business process reference model and providing managers with meaningful, forward-looking metrics offer even more challenges for these vendors. Business users will have to augment their BI tools and platforms with complementary applications to support the growing complexity of managing supply chain performance.
In the 1980s, finance and telecommunications companies pioneered the use of business intelligence (BI) technology to support financial and market analysis of the large volumes of electronic data they had begun to accumulate. The need for BI capabilities grew in the ‘80s and ‘90s in other industries, as companies began capturing data electronically across the full range of their business activities. This need was further compounded by the growing interest in real-time access to data, which required effective tools to mine and analyze dramatically increasing volumes of data. In the last few years, the desire for better operational BI has grown even more. Going beyond static data snapshots to enable users to identify and analyze ongoing business trends and patterns is at the top of the requirement lists for supply chain managers. Driven to improve operational performance and responsiveness to customer demand, supply chain managers know that better information about the state of their operations and processes will lead to better decisions and outcomes. Supply chain managers use BI with many goals in mind. One is to reduce inventory levels by improving visibility of data. Another is to identify specific problem areas by analyzing customer service levels. A third is to improve accuracy of forecasting through better understanding of the sources of variability in customer demand. Managers also are using BI to analyze variables in production and identify where to take corrective measures. Some analyze transport performance to reduce costs by finding the most efficient transport providers. Still others use BI to augment their supply chain planning applications so they can understand where and how they deviate from plan objectives. No matter what the specific goal, most senior managers know that the wider their visibility into plans and supporting data, the more they will improve business performance. But getting broader intelligence about supply chain performance is not easy. Virtually all companies operate with two or more software applications from different vendors to tackle the functions of supply chain management (SCM). Most have at least one enterprise resource planning (ERP) system to do the basic order management, purchasing and accounting functions, and often they augment it with a specific best-of-breed (BoB) application to provide connections across supply chain processes, such as linking inventory replenishment and transportation management. Many BoB SCM vendors are adding BI or performance management capabilities to their applications. It is not unusual to find a dashboard, an activity monitor or an integrated event management tool within a suite of applications that handle supply chain planning, manufacturing execution, warehouse management, transportation management or supplier relationship management. While each of these systems provides a valuable piece of the supply chain performance puzzle and functional views of specific supply chain subprocesses, they do little to give managers a broad and connected view of supply chain operations or performance. To get the big picture, at the request of their IT departments, many companies have rushed to adopt large-scale BI application platforms. These platforms create or tap into an enterprise data warehouse (DW) or operational data store (ODS) and sit outside the main ERP and SCM systems, capturing the essential transactional data. BI platforms do a good job of collecting and homogenizing all the disparate data. The cost saving in having one platform (instead of many) that serves all functional areas of business with a standardized set of BI applications is self-evident. The problem with this strategy is that it often fails to broaden business intelligence about the supply chain. Simply put, there are unique information needs for managing complex supply chain networks and processes that most BI tools do not address. These needs include support for distributed decision-making, master data management (MDM), visibility of trading partners and predictive performance management analytics that evaluate supply chain “what if” option planning scenarios.
The need for better supply chain intelligence has created challenges for established vendors of BI platforms and SCM applications. Some have made progress. Business Objects, Cognos, Oracle (PeopleSoft EPM) and SAP now incorporate prepackaged supply chain-centric analytical applications. Cognos supports distributed decision-making with business event management alerts. Hyperion provides master data management services. However, no BI vendor supports trading partner visibility and detailed supply and demand scenario planning. This requires the integration of trading partner data and the mixing of planning information with transaction information. For these needs business users must turn to players like IBM, Kalido, SAQQARA and Tibco for trading partner MDM; Interlace, Kinaxis or SymphonyRPM for scenario planning; and RiverOne, seeCommerce or Viewlocity for trading partner visibility.
Ventana Research recommends that senior supply chain managers and executives take the lead in establishing their supply chain business intelligence assessment efforts. Their aim should be to identify the operational intelligence requirements that are critical to support the business and manage performance of the supply chain. Start by defining the business goals of the BI initiative. Select the supply chain processes that you want to target first. Then build a business case to demonstrate the value and results that the project will deliver. The business case will require clear definitions of both program cost and potential benefits, as well as compelling productivity and financial reasons for pursuing the unique requirements. Also, to ensure support for your initiative, address cultural, business and technology barriers forthrightly as well.