Demand for demand planning has been on the rise for two years and our prediction is it will continue to be a strong career option for analytical experts. The combination of public policy encouraging more domestic manufacturing and the quickly evolving fully digitized business processes means building a precise demand-driven supply chain is critical to the success of any product-driven organization.
Demand planning focuses on sales forecasting, supply chain management and inventory management. While expertise in all three can be acquired over time any successful demand planning group will have experts in each area. Striking the right balance between sufficient inventory levels and customer demand is the goal of every demand planning team.
This is the most important step in the demand planning process. It requires the most input from the greatest variety of internal stakeholders and has the greatest chance of error or missing the mark. The best sales forecasting starts with historical data taking into account marketing changes and inventory shortages that might have impacted that history. Industry trends are then added to the analysis including consumer behavior and business operations changes. Competitor activity has to be added to any good sales forecasting model, as does any large customer risk or reward. Including plans for new products or services has to be incorporated.
Common models for creating a sales forecast as part of demand planning include:
- Moving Average Demand: Assumes that future demand will be the rolling average of the last few sales periods.
- Linear Regression: Processes previous demand levels through a least-squares regression model. Often called a “line of best fit” that is a curve based on previous demand extended to predict future demand.
- Seasonal Trends: Predicting future demand based on historical sales during particular months or seasons.
- Sales Forecast: Predicting demand based on particular sales opportunities that are expected to happen in an upcoming period.
An article by Demand-Planning.com makes the case that using Excel when working with the sales stakeholders reaps additional benefits more sophisticated packages don’t. Because most employees who don’t work with statistics on a daily basis still have a strong understanding of Excel and familiarity with it, presenting sales information via Excel makes them more comfortable and more participatory. Input by senior management, marketing and sales is critical to the success of any sales forecast. They are the ones defining upcoming promotions, pricing changes, campaigns and events that impact sales. They can provide insight on volatile SKUs and their agreement on final figures is critical to the process.
Supply Chain Management
A sales forecast that includes what goods will be demanded, how much of each item will be demanded, when the goods will be demanded and where the items need to be at the time they are demanded will lead to the best supply chain management. Poor forecasting results in avoidable supply chain disruptions and can leave a company short of products which results in backorders, stock outs or costly scrambles for raw materials. The digital transformation is connecting more supply chain participants, from the consumer to the manufacturer to the raw materials supplier and providing finer-tuned control over the movement of goods. This creates a demand-driven supply chain where supply is more responsive to actual consumer demand and not primarily the product of an educated guess.
Successful demand planning without efficient, accurate inventory management is not possible. Striking the right balance between sufficient inventory levels and customer demand frees up working capital, reduces inventory carrying costs and decreases the potential that there will be obsolete or low-value inventory. The integration of the sales forecast with supply chain data to determine inventory levels will insure supply does not exceed demand and directly impact the profitability of the product line and the company.
Interested in discussing a career in demand planning? Contact Smith Hanley Associates’ Data Science and Analytics Executive Recruiter, Nancy Darian at email@example.com.