Business GrowthCRM Best Practices

Sales Forecasting for Manufacturers

Accurate sales forecasting in manufacturing has always been critical, but can sometimes be tricky. For a manufacturer, sales forecast data integrity is even more critical since it is used to generate plans in all aspects of the business including manufacturing schedules inventory management, product positioning and placement, and production planning. This data is even used when planning budgets, cash flow, expansion, investments for capital equipment, and raw materials purchases.

The reality is supply chain management must have the correct amount of raw materials in order to manufacture an assumed amount of finished goods to fulfill the predicted sales forecast. Then the product will be marketed and distributed based on the forecasting.

The problem comes when your forecast is too gregarious, you’re burdened with units you must carry/inventory instead of selling. Unfortunately, you are still stuck with the raw materials that you already paid for that were required to produce this overstock. Conversely, if your forecast is too conservative, you won’t produce enough units resulting in a backorder situation and possibly having sales orders cancelled or even worse, having your customer drop you as a vendor. Obviously, this scenario creates an “organic rub” between sales and supply chain/demand planning, especially when confidence/ trust in the forecast accuracy is low. The solution is having a more accurate and timely forecast whereby sales will be able to hit their revenue targets and the factory can build the correct product mix, lower on-hand inventory levels, reduce unfulfilled backlog, reduce inventory obsolescence, and improve lead times of finished goods and its components.

Some sales forecasting best practices include:

  • Communicating through all fields. The information of how much customers have purchased, how many they plan on purchasing soon from those closest to the customers, the manufacturing team with how much raw material they already have, warehouses that are storing your good, all of these need to communicate to know how much you already have and need so you can adjust quickly.
  • Best practices demand planning forecasting. You need to know how the forecast is going to be made and when.
  • Make more than one sales forecast. It is helpful to make a forecast for multiple time frames and to double check that these forecasts together, this will also help in knowing when you might need to adjust a larger forecast or catch an error faster.
  • Use the sales forecast in your manufacturing forecasting. You can’t have the correct inventory without knowing how many you expect to sell and thus how many more you should need. Anytime either of these forecasts need to be adjusted, the a=other should be checked and most likely adjusted accordingly.

 

CRM and Forecasting

 

By now, you should be getting the message that forecast accuracy is key and CRM systems can help with this. Having a forecast module in a CRM system is a must for manufacturers. Since it is used daily, CRMs allow sales reps to review the buying behavior and precise/accurate analytics on each account to provide a real-time dimension to the historical data resulting in more concrete and reliable sales forecasts. Incorporating info generated by the CRM can give the forecast a more accurate perspective of true demand as you’re getting as close to the customer as possible. Statistical forecasts based on analytics such as “average closing ratios” and “average time for a sale at a particular stage of the sales process” (allowing a much more precise calculation of risk-versus-reward for each sale) tend to be more accurate than methods based solely on an educated guess.

Marketing and sales organizations prefer to plan forecasts in dollars (revenue) and conversely, production needs to plan in units. Ultimately, for products to be available when the customer needs them, you need to develop a forecast by product in units. However, your sales forecasting system should be flexible enough so that it can aggregate demand to different levels of details in units and in dollars to satisfy company-wide needs.

Forecasting in CRMs enables:

  • Automation of a role-base data entry process by linking the opportunity pipeline to the forecast increasing accuracy. Sales reps can better evaluate what customers may purchase as they cultivate real-time opportunities. These sales forecasts are available by customer account and can be viewed via a Sales Dashboard.
  • With organization-wide usage, it will allow Sales and Demand Teams to collaborate in real-time on forecasts. It also enables the option for end-user customers and sales partners to view/input forecasts via a self-service portal.
  • Reporting provides a clearer picture to senior management as to how actual results compare to the sales forecast.
  • Since CRM usage is daily, it allows the forecast to be measured and reviewed frequently, which in turn, fosters better accuracy, which is necessary.

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