Analyst Insight: Sherman's Law of Forecast Accuracy states that forecast accuracy improves in direct correlation to its distance from usefulness. It's time to stop being driven crazy by demand variability. Don't be driven by demand; sense, shape and respond to demand. Your company can better predict and respond to demand variability through integrating forecasting techniques with demand planning techniques; in a word, collaboration! - Rich Sherman, Principal Essentialist, Trissential

The Defense Logistics Agency tasked partner LMI with helping to develop a more efficient system for managing items with infrequent demands through an innovative system that accounts for need and risk, without sacrificing mission-readiness.

The Defense Logistics Agency tasked partner LMI with helping to develop a more efficient system for managing items with infrequent demands through an innovative system that accounts for need and risk, without sacrificing mission-readiness.

Winning the game in demand management is a yard-by-yard gain. There may be some super long passes and some genius calls, but by and large, making progress requires granular visibility of the market, and software that can understand the data and, like a great quarterback, call the shots in a timely way.

One of the new buzzwords in the demand planning arena is demand sensing. Developed around 2003, demand sensing has slowly been grabbing the interest of the CPG, energy, food, beverage, and chemical industries. Often viewed as an alternative to demand management, demand sensing is anything but. Let's compare the two.

Surrounded by an explosion of data, most forecasting systems have no way to leverage or take advantage of it.

Supply chain is the largest expense for any product company and generally accounts for 60 percent to 90 percent of all costs. Controlling such a substantial expense demands continuous performance improvement and high operational efficiency. Research suggests the existence of a statistically significant relationship between analytical capabilities and supply chain performance. In other words, data analysis can assist in controlling supply chain costs. Further, an analysis of 310 companies from different industries in the USA, Europe, Canada, Brazil and China indicates that analytics of the supply chain plan has the second-biggest influence on supply chain performance.

Analytics companies are popping up everywhere as Big Data starts to work its way into more executive conversations. We've been down this road before; analytics isn't a new concept. However, new related technologies and a better understanding of what's at stake for businesses may make this wave a different one. The key is for everyone to get comfortable with the idea of using the new tools to roll their own analytics.

A recent Deloitte survey of 600 executives at manufacturing and retail companies found that 63 percent were highly concerned about risks within the extended supply chain comprising vendors and customers, ranking it among their top-two concerns. The executives surveyed also cited "lack of acceptable cross-functional collaboration" as the number one obstacle to managing risk effectively. While these survey results indicating a serious lack of collaboration and coordination among trading partners are certainly worrisome, should they really come as a surprise?