Demand Planning and Bottom Line – The Connection

Forecasting or demand planning is the lynchpin of supply chain management. Demand plans have an indelible impact on the entire supply chain, as they get consumed at every point of the value chain from planning to strategy, up to supply chain operations. Demand planning has a deep and spiraling effect. Errors in planning propagate down right up to the bottom line.

Why the Conventional Approach Does Not Make a Mark?

Typically, businesses take a piecemeal approach towards demand planning or forecasting. Short-sighted and standalone measures like adopting and implementing new forecasting models, or raising forecast accuracy targets are often taken without any consideration of how this will affect the business in the long run.

The level of forecast accuracy that can be achieved is usually a function of the nature of the product for which the demand plan is being charted out. When this important insight is overlooked, companies can set unrealistic targets without having a well-defined roadmap of how to reach these goals. Since forecast accuracy has a component of randomness to it, it is easy for organizations to lose their way in the maze of demand planning, when the results are not obvious. Instead, it is wiser to target improvements in maturity levels of the process. Sustained process improvement can only be achieved by looking at the entire process and the associated components that go into the demand planning process, and putting in place features that can sustain the improvements through the journey towards demand planning excellence.

The Importance of a Diagnostic Tool

Demand planning excellence can be achieved through long-term vision, a comprehensive process improvement framework, and an incremental approach.

Like any other business process, demand planning too has a life cycle with developmental stages that can be clearly defined, managed, measured, and controlled. A process maturity demand planning diagnostic tool is ideal for organizations trying to assess the status of their demand planning process and aiming to improve the process.

A Diagnostic Tool Can Be Used In Tandem with the Five Stages of Demand Planning

There are five stages in the demand planning process.

  • Stage 1: The creation of a crude 'sales forecasting process', without any attempts at forging a consensus across departments. The focus is on supporting operations over the very short term, typically for the next week or next month.
  • Stage 2: Organizations move over to a relatively evolved 'demand forecasting process' where advanced spreadsheets or specialized forecasting tools become the norm.
  • Stage 3: The 'integrated demand forecasting process' stage is where companies work on creating an integrated forecasting process that supports medium term tactical decisions in addition to routine operations.
  • Stage 4: 'Demand planning and management' is the next step, where the attention is completely focused on consensus demand planning and management.
  • Stage 5: This is where 'demand and supply orchestration' happens and the entire network is involved in the forecasting process.

Each stage in the planning process has its own functions and criteria, and using a diagnostic tool helps companies classify their maturity levels. The scoring of maturity levels on each salient feature of the demand planning process is done, based on the environment in which the organization is functioning. This leads to a prioritization of gaps unique to the organization's operating environment. A diagnostic tool thereby helps organizations to direct their efforts towards initiatives that present the best chance of profitability and long-term sustainability.

WNS Enables a Global Medical Manufacturing Major to Improve Forecast Accuracy by 10 Percent

A global medical manufacturing major,with multiple production facilities and distribution centers, was looking to improve the forecasting process. That's when the manufacturer partnered with WNS.

The medical equipment company needed forecasting for 4000+ Make-to-Stock (MTS) finished goods items under various product lines, with 25 percent low volume / high value parts with high volatility. The volatility in demand either led to lost sales due to dwindled stock or excess inventory due to errors in forecast. In a nutshell, business was getting impacted adversely, because there were gaps in the forecasting process.

By using the right diagnostic models, WNS helped the company identify critical gaps in the forecasting process, developed and executed a forecasting process improvement roadmap which included important aspects of demand planning such as forecastability analysis and demand segmentation, statistical forecast generation, exception alert generation, and review and revision process among others. WNS was able to help the company achieve sustained gains in forecast accuracy to the tune of 7-10 percent.

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