External Insights Critical to Effective Supply Chain Performance

There is a better way to anticipate supply chain demands that improves projections and decreases discrepancies

Rich Wagner
Rich Wagner

Traditional forecasting models that leverage historical data to predict future performance are the tools used by most supply chain executives to plan critical functions, yet these predictions are frequently inaccurate. In fact, research from KPMG International, in cooperation with the Economist Intelligence Unit, shows that most quarterly forecasts are off by 13 percent—meaning that supply chain managers are basing their decisions for ordering materials and scheduling distribution on erroneous projections. The result can mean surpluses or shortages, potentially costing companies millions either way.

There is a better way to anticipate supply chain demands—one that can vastly improve projections, and decrease the discrepancies between forecasting and reality, therefore helping supply chain executives perform their jobs more effectively. Few companies take into account macroeconomic factors, global manufacturing activity, consumer behavior, online traffic, weather data, etc. when making business projections. Yet companies that do identify leading performance indicators using such external data earn more than a 5 percent higher return on equity than those that use only internal metrics. Leveraging external factors, in addition to internal performance measures, is proven to result in more accurate, effective forecasts. Not to mention that improving forecast accuracy can represent huge bottom-line benefits. For a billion dollar manufacturing company, for example, improving forecast accuracy and overall return on equity even 1 percent can equal a $3 million increase in net income.

Forecasting accuracy, improved through external factors, benefits multiple business functions—from financial operations (shareholder value) to human resources (adequate staffing) to marketing (product innovation)—but is especially impactful on the supply chain management function.

Improves Inventory Management

Improved forecast accuracy using external drivers equates to reduced inventory management costs, ultimately improving bottom-line profit. By accounting for external factors, companies can see a 10 to 15 percent improvement in forecast accuracy, significantly decreasing the cost of excess inventory. By ordering raw materials based on correct projections, supply chain managers no longer have to worry about discounts necessary to move excess inventory or the cost of warehousing excess materials because they are ordering accurately from the start.

Provides Insight on Supplier Stability

Taking the entire global market into account, as well as hidden external factors affecting operations and demands, supply chain executives gain a more complete picture of their full supply chains, including the stability of their suppliers. For example, a manufacturing company that sources most of its raw materials from Brazil may want to keep a close eye on the market there and begin to source potential new suppliers if early indicators point to increased volatility in the Latin American region. Likewise, if early indicators point to an upcoming industry boon, companies may want to shore up suppliers and inventory as increased production industry-wide may lead to material shortages.

Reduces Supply Chain Risks

The foresight that comes from using external factors to improve company projections helps supply chain managers to minimize risks because they can better anticipate fluctuating markets, demand spikes, supply shortfalls and decreasing interest. With this knowledge, supply chain executives can tailor orders for raw materials, storage and shipping accordingly, reducing the need for rush orders, transshipments to an intermediary destination and disposal of obsolete products.

Answers What-If Scenarios

Supply chain managers who can accurately answer what-if questions and are nimble enough to respond as those what-if scenarios start to play out are at a huge competitive advantage. How do fluctuations in gas prices affect demand? How does the financial crisis in Greece impact my supply chain? As gross domestic product (GDP) rises, do our sales rise, too? Those that can answer questions such as these can adequately plan for potential scenarios—both adverse and advantageous—so that they are prepared with proper resources, storage and transportation.

Maximizes Investment in Supply Chain Planning Software

Companies invest heavily in supply chain planning solutions, yet this software is only as good as the factors input to predict future supply and demand. Integrating external data makes supply chain planning solutions more accurate, and therefore, more effective in anticipating demand.

While it’s clear that using external insights to improve forecast accuracy is crucial to improving supply chain performance, companies often struggle with just how to gather and leverage these external insights. It would take multiple researchers to gather all available data, then countless hours to mold that data into effective projection models, only to have the original data become obsolete before the models can even be completed. This laborious process is the reason that many companies still rely on the antiquated model of relying solely on internal historical data.

However, new technologies are eliminating this barrier. Big data predictive analytics solutions put millions of data points in the hands of companies and update them in real time, creating accurate, effective and real-time models that allow for improved forecasting—increasing profitability and effectiveness across business units and particularly improving the effectiveness of supply chain executives.

As president and chief executive officer at Prevedére, Rich Wagner empowers companies to look beyond their own walls for key external drivers of financial performance. In his role, Wagner is leading the initiative to close the gap in inaccurate forecasting by utilizing millions of global metrics, including macroeconomic factors, global manufacturing activity, consumer behavior, online traffic and weather data. Wagner uniquely positioned Prevedére as a complimentary solution to existing forecasting platforms on the market due to its application of external economic factors that are often left out of traditional forecasting. Under his leadership, Prevedére was named a Cool Vendor in Information Innovation by Gartner and one of IDG Research’s Five Startups to Watch. To learn more, please visit prevederesoftware.com and follow @Prevedere on Twitter. 

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