Managing Automation - December 2008 - (Page 19)

DEMAND PLANNING BY JEFF MOAD Five Ideas for As their businesses become more global and complex, manufacturers are struggling more than ever to come up with accurate, actionable demand forecasts. Here are five ideas that can help. et’s say you’re a large consumer goods manufacturer doing business in 160 different countries, selling your products to retail customers ranging from WalMart to small stores, each with its own stocking needs. The rising amount of point-of-sale and other demand data being passed to you, particularly by your largest customers, is beginning to overwhelm your people and systems. Meanwhile, the number of products and SKUs for which you must forecast and shape demand is soaring as your company attempts to satisfy the tastes of an increasingly global customer base. In fact, since 1998, your company has increased the number of SKUs it must manage by 4,000%. OK, now imagine coming up with an accurate, actionable demand plan for each of those products in each market. Welcome to David Mills’ world. “Complexity in the consumer products world has increased to the point where the growing amount of data to be analyzed causes demand planners to spend most of their time gathering data from each customer and getting all the inputs consolidated before they can even do the analysis,” says Mills, associate director of global business planning at consumer goods giant Procter & Gamble. “Instead of demand planners focusing on resolving specific issues or shaping demand, they’re dealing with the data. So we’re beginning to miss opportunities.” P&G isn’t the only manufacturer whose efforts to effectively forecast and plan demand are being undermined by an increasingly complex business environment. Manufacturers large and small are struggling with the fact that demand forecasting and planning, never a simple process, are today being made much more difficult by trends such as globalization, shortened product lifecycles, and customer demand for more product variety. In fact, many manufacturers are finding that, despite what they thought were their best efforts, forecasting error rates are actually rising. “There’s no doubt about it, demand planning has gotten more difficult today,” says John Simrose, a supply chain practice principal at Deloitte. “The fact is a lot of companies aren’t even treading water. They’re getting worse at forecasting.” At the same time, there’s never been a higher premium placed on demand forecasting accuracy and predictability. Customers are less tolerant than ever of out-of-stock situations. And, manufacturers say, suppliers are quick to favor manufacturers that are best in class at demand planning with things like priority ordering and even lower prices. And manufacturers that are better at demand planning are almost always able to operate more efficiently. According to a recent report by AMR Research, consumer products manufacturers that do the best job of shor t-term demand forecasting average 22% better plant utilization, 24% less raw material inventory, and 9% lower overall costs. So what’s behind increasing demand planning and forecasting complexity? For starters, global economic uncertainty has complicated matters. When unprecedented levels of economic uncertainty begin to affect buying patterns, long-term historical data — the kind most manufacturers traditionally use to forecast demand — loses some of its usefulness. Instead, such unpredictable times call for better realtime demand sensing and the ability to differentiate demand trends at the local level, experts say. December 19 2008 Photo: Karin Lau

Table of Contents Feed for the Digital Edition of Managing Automation - December 2008

Managing Automation - December 2008 Contents Take 1 Business Objects Chief Says Union with SAP Meets Objectives After One Year Yes, Emerson, Too, Is in the MES Market Infor Chief Puts Off IPO, Restarts Buying Plans Kronos Now Tracks Shop Floor Machines IQMS Rolls Out User Interace, Other Upgrades Notes Five Ideas for Demand Planning Building on the SOA Blueprint Innovation Now A Team Effort Lean %2B Technology = LEAN^2 Finding Flaws Before They Spread Product Scan Advertiser Index Next

Managing Automation - December 2008

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