How to Overcome the Challenge of Demonstrating ROI for Demand Plan Management

By: Greg Spira and Todd Ferguson

A new regional operations leader discovered an issue with his company’s demand plans: they were initially structured to optimize the demand plan for the factories. While the accuracy of the plan nationally was good, when measured geographically at distribution centers (DC), the accuracy was a nightmare. Unfortunately, the organization’s decision-makers did not share the leader’s concern about the criticality of reliable demand plans at the factories and DCs. No one had established the linkage between unreliable demand plans and business and financial performance, which meant they did not see the value of investing in improvements.

Making changes

Because of the commonly held belief that “all forecasts are wrong,” many executives think their business is too unique and unpredictable to be forecasted. Sales and marketing plans will never be 100 percent accurate, but striving to improve their accuracy drives companies to improve plan execution. When plans are well executed, companies are top performers in their industries. The challenge is demonstrating the return on investment in concrete terms directly related to business performance.

Creating the case for change—and investment—starts with determining what needs improvement. Organizations that believe that improved forecast accuracy alone is the goal of demand planning initiatives fail to consider that every statistical forecast has an upper and lower confidence range. Effective planning involves combining documentation of what is and is not known and controllable with forecasting and supporting the numbers and timing of demand projections with clearly documented assumptions.

Four considerations for improvement

Improvements to a demand management process generally address the following four areas. A lapse in one area impacts the effectiveness of the other three.

1 – People. Top-rate demand planning teams help convey the thinking that underpins business goals and objectives. The correct caliber of demand managers should primarily focus on accurate and valid plans and be concerned with how the plan compares to stated business objectives.

2 – Analytics. Incorporating planning assumptions and drivers that go beyond simple trends and seasonality requires advanced predictive analytics methods. These demand drivers include price, sales promotions, in-store merchandising, store distribution, advertising, epidemiological data, and regional economic information. Advanced predictive methods help identify the cause-and-effect relationship of these drivers to demand.

3 – Process. The demand planning process should consistently drive to the “what,” “so what,” and “now what,” regarding sales, marketing, and product plans and activities. Communication of this information utilizes impactful visuals, creating effective storytelling and the understanding required for discussion and decisions.

4 – Tools and technology. As companies adapt their processes and data management for the digital economy, they seek cloud-based, open-source technology with strong data processing and analytical functionality. Digitalization helps supply chain partners respond faster—and more intelligently—and better connect with customers and consumers.

Quantifying and documentation

An honest approach involves a holistic understanding of three important topics.

  • First, it defines why a demand plan is needed.
  • Next, it explains how the demand plan impacts the way other business functions perform.
  • And lastly, it establishes how the demand plan drives decision-making that affects business performance.

It is liberating to know the goal is not simply to improve a lone key performance indicator, like forecast accuracy. It helps business leaders shift their thought processes to how to use the demand plan information to make better decisions. This includes quantifying and documenting the financial benefits of improvement and evaluating how the demand plan affects business performance by gathering data and making calculations. For many companies, this could include inventory turns and reduction, sales and marketing activities, and execution issues.

Business leaders need to consider the implications of demand plan accuracy on decisions made by various business functions, considering the magnitude of error (accuracy) and direction (bias). Documentation regarding these impacts assists in this area. With the costs of failure outlined, a link or causal relationship can be established between the incidence of failure (frequency of overselling or underselling) and the magnitude of the cost. Some links and costs will be easier to identify than others. Where there is uncertainty, clearly highlighting the assumptions in both the written documentation and verbal presentations is critical to a solid business case for improving demand planning.

Improving inadequate demand plan performance is a business imperative. Oliver Wight has developed templates that guide the process of linking demand planning to decision-making, documenting the impact of the demand plan, identifying the cost of failure, and calculating the return on investment from the improvement initiative.

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