Gartner Highlights Best Practices for Supply Chain Leaders to Improve Their Overall Demand-Planning Processes to Deliver Against Business Goals

Analysts to discuss effective demand planning at the Gartner Supply Chain Executive Conference

Egham, UK—Aug. 29, 2012—A functioning demand-planning process is a key enabler for supply chain organizations, and getting the process right is fundamental to improving demand-planning effectiveness, according to Gartner, Inc. Gartner analysts have identified some best practices to help supply chain leaders improve their overall demand-planning processes to deliver against business goals.

To better understand the state of demand planning, Gartner surveyed 240 respondents during the fourth quarter of 2011 in Brazil, China, Europe and the U.S., spanning seven industries: consumer products, aerospace and defense, healthcare, consumer electronics, chemical, apparel, and footwear.

The survey found that the primary influences on demand variation were increased customer requirements followed by new product launch and the state of the economy. Fifty-seven per cent of respondents also said that erosion in profitability had the greatest effect on their organizations.

"It is critical that organizations develop the right demand-planning process to improve effectiveness," said Steven Steutermann, research vice president at Gartner. "Without a functioning process, obtaining a consensus-driven demand plan will prove extremely challenging."

"Organizations are struggling to find the process that fully utilizes the alignment of organization resources," said Steutermann. "The balance between bottom-up collaborative approaches versus top-down statistical modeling is challenging, and the ability to understand baseline volumes from promotional volumes—as well as mix and shift within portfolios—is an equally daunting task."

Gartner has identified a number of best practices to help supply chain leaders improve their overall demand-planning processes. You can also view Gartner’s demand-driven maturity model on Flickr at / 

Finding 1. Defining the balance between statistical modeling and collaborative forecasting improves accountability for the forecast, and enables continuous improvement across the organization

Companies can benefit from clearly defining the balance between statistical modeling and collaborative forecasting methods to improve accountability for the forecast and put in place continuous improvement plans to improve the forecast. When asked what the challenges are when improving demand planning, respondents indicated the "lack of accountability for the accuracy of the forecast" and "lack of communications between commercial and demand planning" as the two biggest.

"Determine the best method, or methods, to optimize forecast accuracy," Steutermann said. "The company should be able to address what items should be statistically modeled, what items are reliant on a collaborative process, or both. The demand-planning organization should play a central role in identifying accountabilities across the organization."

Finding 2. Companies that utilize demand sensing and shaping capabilities realize higher forecast accuracy

Gartner research found that those companies that utilize demand sensing and shaping as part of their demand-planning processes significantly improve their forecast accuracy.

"To fully realize the benefits of demand sensing and shaping, organizations must first mature their demand-planning processes," Steutermann said. "A rigorous process and discipline must be supported by organizational balance, metrics, sponsorship, ownership and accountability. Organizations must recognize that the demand plan is not a sales or marketing forecast, nor is it a budget. It is a process by which organizations determine the most profitable mix of items that could be sold, balanced by constraints and demand risks."

Finding 3. Demand-planning process best practices include measurement, planning hierarchies and new product launch forecasting

Despite the focus on customer collaboration and customer inputs, only 17 percent of respondents indicated that they forecast at the stock keeping unit (SKU), location and customer planning level. Given that a primary driver of demand volatility is increased customer requirements, Gartner analysts found it surprising that companies do not measure demand error down to the customer level as a means to better understand the sources of error — so that process and accountabilities can be improved. They also said that new product launch forecasting is overly reliant on sales and marketing for demand inputs. Opportunities exist to remove forecast bias by utilizing attribute modeling techniques and solutions that use similar product introductions to understand consumer/customer trial and repeat, as well as volume-build assumptions, to improve the forecast.

"Organizations should measure forecast accuracy at the item, location and customer level for forecast error understanding," Steutermann said. "Customer or sales forecast accuracy should be measured for continuous improvement and accountability. The appropriate place to measure for continuous improvement is in the sales and operations planning (S&OP) review process."

Additional information is available in the report: "Building an Effective Demand-Planning Process," which is available on Gartner's web site at

Steutermann will examine the state of demand management across industries at the Gartner Supply Chain Executive Conference 2012, taking place from September 17 to 18 in London, please visit