By Jorie Fox | Manager, Integrated Demand and Supply Planning | Chainalytics
You’ve heard it from sales before: “My forecast accuracy is 98%, so why should I use your forecast?” Or better yet: “My customers aren’t going to get their products if I use your forecast.”
Sales and Operations have always been at odds. Operations is tasked with reducing inventory and costs, while maintaining service levels. Sales wants more inventory to support higher sales. Unfortunately, there’s a common misconception that higher sales can’t be supported through reduced inventory. So how do you get sales involved in the S&OP process and believe in the forecast that comes out of the collaboration?
It’s all in how you phrase it
Approach the conversation with an attitude of helpfulness. Demand Planning can’t take an adversarial role, or an “us” versus “them” stance. Without sales’ input, it’s easy to miss promotions, new customers, etc. that will result in lost sales and a decrease in forecast accuracy. We need the sales team as much as they need us. The whole point of S&OP is to collaborate with sales on a forecast that makes sense from a business standpoint; while supporting revenue.
Try this approach instead: Demand Planning continually supports sales by providing a statistically accurate forecast. It remains imperative that sales be a part of the process to call out any anomalies, promotions, or new customers that aren’t captured with a statistical process. This will allow the sales team to focus on what they are best at, selling! If the sales team has more time to focus on selling, then revenue (and commission) will go up. It’s a win-win for everyone in the company.
Prove forecast accuracy – and associated forecast metrics – through deep analytics
You’ve all heard of MAPE (Mean Absolute Percent Error) and weighted MAPE when it comes to forecast accuracy, but it is often measured infrequently and incorrectly. Make sure you’re measuring forecast accuracy in a way that is suitable to your business. For example, if you’re forecasting weekly, then you should be measuring MAPE at a weekly level. If you’re forecasting monthly, then make sure to measure MAPE at the monthly level.
Also, at what level of the product hierarchy are you forecasting? If you’re forecasting at a family, or product group level, you probably shouldn’t hold yourself to forecast accuracy at the individual SKU level. This can also ring true from a geography perspective. Forecasting by country requires metrics at the country level, especially in situations where your KPIs and performance are measured on forecasting metrics. Do you really want to be measured against a forecast you didn’t manage?
Forecast Value Add (FVA) should be one of the primary metrics Demand Planning uses to help justify which forecast is used as the consensus. Forecast Value Add is exactly as the name describes: what is a particular step or participant contributing to the forecast? Is the statistical process adding value? Is the sales team’s input adding value? Inversely, are any of these participants actually degrading the forecast accuracy? This metric is not intended to “beat up” on the sales team, or any other participant for that matter. The intention is to see where value is being added, and where value isn’t. Energy can then be focused on the SKUs or product families where value is being added, and the statistical forecast can be applied to SKUs or product families where the forecast is being degraded. Forecast Value Add provides a great metric to show the sales team how their input affects the forecast, and it drives the conversation towards optimizing energy expenditure.
Exception based management
This goes back to allowing the sales team to focus on selling. One of the biggest complaints we hear from clients is that the S&OP meetings take too long. Having consensus review meetings shouldn’t be so labor intensive that your stakeholders don’t show up. In the beginning of implementing S&OP, the demand consensus review meeting can take up to 2 hours as the kinks are worked out, and the sales team adjusts to the new process.
However, once S&OP is established, review meetings should focus on exceptions only and last an hour, at the most. Exceptions to focus on include; revenue variances between statistical forecast and sales forecast, percent variances between statistical forecast and sales’ forecast, new products, discontinuing products, and any product (or group) that has planned promotions or new customers.
These tips are not exhaustive, and there are many creative ways to involve the sales team in the S&OP process. Remember that although S&OP is a standardized process, every company’s uniqueness requires a bit of finesse to the standard.
Jorie Fox, CPIM, MBA, PMP, is a Manager in the Integrated Demand and Supply Planning Practice at Chainalytics with a focus in demand planning process improvement, S&OP implementation and optimization, and planning technology assessments. With nearly eight years of supply chain experience in both industry and consulting, Jorie brings a great blend of supply chain education with real world expertise.
Read more about how better S&OP supports better businesses:
- (BLOG) Is Statistical Forecasting Making Your Demand Plan Better or Worse?
- (BLOG) Four S&OP Pitfalls to Avoid for Supply Chain Success
