Measuring forecast accuracy and supplier performance is still a hit-or-miss proposition. Supply chains are growing increasingly complex, from linear arrangements to synchronized, multi-echelon, outward-facing networks of distributed servers. There's much more information that needs to be monitored than there was just a few years ago. Most companies lack the tools that can quickly sift through and present data coming from supply chain partners and systems.

Gartner, Inc., a leading IT consultancy, estimates that less than one percent of companies today are actually capable of monitoring and measuring online supplier performance. A study conducted by the University of Texas for Dell Computer Corp. found that only 11 percent of 1,000 companies studied have any form of online transactional and information-sharing capabilities with their suppliers. Building an information sharing and analysis capability will be critical to sustaining critical competitive advantage over the next few years.

"The movement of supply chains in the 1990s was powered by optimization, but as we move into the 2000s, the trend is toward workflow and analytics," says Lora Cecere, analyst with Gartner.

The types of questions confronting enterprise managers today include:

  • How can we develop short-range forecasts to respond more quickly to market changes?
  • How can we monitor the performance of our top five suppliers?
  • What will it cost to shift to a new supplier in a particular product line?

To get at this information, managers and analysts too often must spend days, or even weeks, cobbling together aging or obsolete information on spreadsheets. Achieving visibility across the supply chain means not only being able to track the performance of a supplier, but that of the supplier's suppliers as well. Such visibility enables a more agile level of demand planning in which production and quality issues can be addressed within days, or even hours.

The Analytics Approach

Supply chain analytics form the foundation of such an effort. Supply chain analytics is the process of extracting and presenting supply chain information to provide measurement, monitoring, forecasting and management of the chain. An analogy is the role of the network administrator who needs to monitor, in real time, a company's servers, networks and interfaces. The administrator needs to be alerted when bottlenecks appear or if a system is underutilized or stressed. He or she also needs to be able to run and review reports to spot developing trends in system usage and be able to plan for acquisitions or upgrades of future system resources. If a network administrator was kept in the dark about the performance of a corporate computer system, that system would be in sad shape.

Likewise, a business manager trying to optimize a large supply chain network needs to be able to monitor the system on an end-to-end basis. All it takes is one bottleneck to disrupt the performance of an entire supply chain. A supply chain analytics system will enable a company's analysts and executives to view the performance of the supply chain over a secure extranet and alert them to problems. Predefined thresholds, fed into the system by business users, trigger these alerts.

For example, if the percentage of on-time deliveries by transportation providers drops below a predetermined level of 95 percent, managers would be alerted and could take action to address any bottlenecks. A new generation of monitoring tools not only provides such monitoring and alert capabilities, but also enables end users to drill down, visualize and analyze trends in real time. Processes that can be tracked by a supply chain analytics system include production, materials management, procurement, manufacturing, warehousing, transportation, inventory, supplier management, fulfillment, customer relationship management, demand management, order fulfillment, product development and returns management.

Business Drivers: It's All About Collaboration

Once implemented, supply chain analytics can help companies achieve more surplus – or economic profit – from their supply chains. Analytics can also help drive down costs, increase productivity and increase market opportunities across the supply chain.

The formal return on investment for a supply chain analytics effort is significant – Gartner calculates the potential return on investment for supply chain analytics at approximately 40 percent after five years. However, supply chain analytics can deliver value in a more profound and immediate way – actually increasing cash flow – by helping companies reduce their inventory levels. This means they'll have more cash on hand, rather than tied up in inventories. Typically, manufacturers are forced to overproduce inventories to meet unpredictable demand, only to be followed by forced markdowns of excess items. A company holds inventory to take care of these spikes in demand, which ties up working capital. For some industries, such as electronics, where there's a huge obsolescence factor, this can make a big difference.

The most likely end users of analytics tools are those involved in key processes in the supply chain such as transportation or procurement, or manufacturing managers and analysts. At one major food distributor, for example, procurement managers are charged with looking at product sales information coming in from retail partners and monitoring the suppliers that are helping to fulfill those orders. Ideally, a group comprised of representatives for each affected process should be installed to determine what metrics make sense in this new supply chain. They should also be able to look at continuous improvements toward their goals.

As analytics capabilities mature, the end-user base will also include managers from supplier and trading partner firms. In fact, this information sharing is where the value of an analytical infrastructure can first be seen. Because the analytics involve monitoring and measuring data from suppliers, manufacturers, planners, sales and marketing, logistics, and customers, this information needs to be shared with these partners.

Historically, businesses have been reluctant to share such information, even with their most trusted partners. However, there's a growing recognition that by sharing analysis of business process data across the supply chain, the overall profit "pie" will grow as partners become more responsive to the market. A number of companies in vertical industries are already collaborating online with initiatives such as vendor-managed inventory and collaborative planning, forecasting and replenishment (CPFR). Supply chain analytics enhance these initiatives as well.

It is not necessary to build an elaborate network that reaches every single trading partner. Most likely, it will only be necessary to run analytics against data from the top 20 percent of partners that handle 80 percent of the business.

The Technology: Tying It All Together

Information from supply chain management processes must be collected, measured, analyzed and continuously monitored. This requires integration of data coming out of ERP, CRM and all other systems supporting these business processes. Increasingly, applications supporting these processes are supporting common standards such a XML, UDDI and WDSL; therefore, new releases are moving closer to the interoperability required to support collaboration between trading partners.

Each process has its own set of metrics that can be analyzed. Information streaming in from various points on the supply chain ­ from back- end mainframes to Web servers ­ is consolidated in a centralized database, data warehouse or a data mart-type environment. Data from transactional systems is summarized into an analytical database, which should be able to scale to large sizes and be continually updated. Because most organizations have wide arrays of packaged or custom-built applications, a data warehouse approach ­ which can store information from these various data silos in one place ­ is often the best choice.

"Enabling seamless navigation of data requires a common, unified data model that ensures a 'single version of the truth' about the business," according to Henry Morris, analyst with IDC.

A key component of an analytical database is a rules engine that links to agents running within key applications. The rules engine activates alerts based on predefined tolerance parameters and sends these alerts to appropriate managers. The information contained in this database must also be easily accessible to the partners in the network in a cost-efficient manner ­ any time, any place, via any device. Typically, a Web browser interface through a supply chain extranet is the most cost-effective and rapidly deployable approach. However, alerts should also be deployable to mobile devices such as cell phones, pagers and hand-held PCs.

The front end of an analytics system needs to be speedy, accessible and user friendly. While supply chain analytic systems may employ sophisticated tools running against data stored on high-end systems, it's important that the end results are user friendly and accessible either through PCs or browsers. Alerts, for example, should be presented in a familiar format, such as a grid or checklist. Historical data should be rendered in a graphical format, such as a bar or line chart. If end users have difficulty using a system, or cannot pull up the data they need within a few seconds and navigate down through the information toward a solution, they will abandon the application and its benefits will not be realized. Final presentations to end users need to be in the form of a graphic presentation that can quickly illustrate the business implications of the trend being measured. Whether the results are made available on a thin-client browser or as a Windows PC application depends on the way the data will be used. For some companies, it pays to support "power users," who are typically analysts who can access and conduct custom analysis from their workstations. For users from the operational side of the business, a browser that accesses predefined reports is sufficient.

Transportation Company Accelerates Data Delivery

To pull supply chain logistics reports for customers, end users at a major transportation and logistics company had to pull down numerous reports from back-end mainframes and load them into spreadsheets. Often, it took three-and-a- half to four days to get an answer to a customer's question. As the company sought to grow its supply chain management business, it knew it had to speed up its process. The company's business goal was to support, on an outsourced basis, customers' supply chains, including product movement between manufacturers, distributors and retailers.

The solution was a supply chain analytics system that ran against an operational data warehouse that mirrors its mainframe database. The company opened its online systems to customers over an extranet, including analytical tools to help them track shipping and logistics transactions. As a result, the three-day lag time was reduced to almost instantaneous feedback to inquiries. Information is sent between the company's data center and its vehicles by satellite, providing faster response times for customers. Shipping bottlenecks or other issues can be fixed quickly. Customers also are provided an interface to view historical data.

Internet-Based Financial Service Takes Full Account of Customer Payments

One area of the supply chain process that is still mired in manual processes is payments. Error rates are high, and discrepancies and other issues in the supply chain are often not uncovered until payments fall past due. An Internet-based financial management service sought to address this gap by extending online analytical capabilities to its client companies. The company established a framework to provide customers with Web-based secure access to track, highlight exceptions and document their entire trade receivables process from purchase through delivery to settlement in real time.

The service pulls data from customers' ERP systems, logistics providers and financial institutions, tracking and monitoring the logistics and the financial processes associated with any given order. Reports are sent to customers in PDF formats or as CSV data that can be incorporated into spreadsheets. By identifying exceptions and providing meaningful alerts, the information service is enabling customers to resolve financial process problems, take steps to improve the efficiency of their physical supply chain and reduce outstanding receivables. As a result, discrepancies are discovered early in the process, when they can be quickly resolved. In addition, executives at client companies can look up day-to-day sales data to see how they are matching up to projections.

What's Ahead

Supply chains are rapidly evolving from linear arrangements to real-time, customer facing networks. With analytics, companies that share information about their supply chain management processes up and down this supply network will be able to capture more surplus than companies that do not share the information.

"The world of supply chains is probably changing the most around latency, time to market and agility," says Gartner's Cecere. "Being able to carve out the key metrics in these areas is essential."

In the years to come, analytical capabilities will increasingly be facilitated by continuing improvements in application and user interface design, particularly as enterprise information portals become the leading gateways to relevant applications and content. Real-time monitoring capabilities will increasingly play a greater role in analytics. Such capabilities are already necessary for internal operations such as manufacturing. An analytical tool that sits on top of a manufacturing execution or ERP system can monitor real-time events as they happen. For example, a manager in the consumer products industry can monitor daily data to see which products were sold at the end of the day and replenish these products the following day. An e-commerce firm can monitor sales from hour to hour to gauge spikes in demand.

These are still the early days of supply chain analytics, and most companies have only begun leveraging information from inside their company, let alone outside the firewall. The challenge is identifying key processes for measurement among top suppliers or trading partners. Over the next few years, companies will increasingly be developing these capabilities and bringing this visibility to trading partners as well.

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