You bought new enterprise apps to get more data about your supply chain and its processes, but now the data is piling up and you're at a loss as to what to do with it all. Here's a look at the enterprise performance management approach and how it could help you turn your data into actionable information
What's the difference between data and information?
Manufacturing, retail and distribution businesses today produce mountains of data through a dizzying array of enterprise processes and applications with much it coming out of disparate, unconnected systems. But how much of that data is actually leveraged into information that provides a competitive edge in the marketplace? Honestly, very little. That's because data alone cannot provide corporate executives and managers with the actionable information on the performance of their companies that they need to stay ahead of the competition.
An enterprise performance management (EPM) approach, using operational analytics, can change that. EPM provide a means for businesses to bridge the gap between raw data and actionable information. As a result, many manufacturers, distributors and retailers are adopting EPM to help them tie execution to strategy while controlling and managing the full lifecycle of business decision making.
The following is an overview of EPM, exploring the performance management issues specific to supply chain businesses, and describing how they can be overcome with EPM solutions.
During the technology boom, supply chain-reliant businesses held a vision of an all-encompassing information system that managed day-to-day business processes while providing the analytic insight necessary to make timely, informed, proactive decisions. Many implemented enterprise resource planning (ERP) applications to achieve that goal. However, these applications had little, if any, decision support.
The adoption of customer relationship management (CRM), supply chain management (SCM) and other applications added even more data to the mix, but again they had little impact on performance management. Individual departments continued to plan and analyze their own areas of the business, in silos, with no connection to each other. Often these plans conflicted, as when sales bases its plans on having a ready stock of products to meet peak customer demand and manufacturing bases its plans on a just-in-time (JIT) strategy. These applications also yielded little, if any, visibility to sell-through, stockouts, forecast variability, promotional waste and other business variables.
Business intelligence (or online data analysis) was the first attempt to convert data into information, and it remains a critical component of EPM. However, EPM extends BI's analytical value with business planning, forecasting, optimization and alerting capabilities to enable business performance management (e.g., having the ability to accurately forecast demand, sales and inventory levels and subsequently react to variances that may occur along the way).
EPM also crosses departmental boundaries to include supply chain, customer management and production-based performance management. It drives operational changes and performance improvements through business planning, real-time performance analysis against objectives (presenting performance indicators to managers in scorecards or dashboards), guidance on what should be done when performance variances occur, and continuous response to changing business conditions. These functions are driven from a corporate-wide repository of key business data that can be accessed and used by the entire organization.
The ultimate goal of EPM is better performance, such as higher returns on invested capital, lower product and overhead costs, better asset utilization, faster delivery, greater customer retention, higher perfect order rates, reduced working capital needs, faster product innovation, and greater sales and marketing productivity.
Trends Driving the Shift