Demand planning is a process just about every consumer goods company performs to keep their supply chain operation running smoothly. This necessary function can take on many forms, require numerous contributors from different departments, and be a key driver for the success of teams outside of the supply chain like sales and marketing. After all, if the demand plan is wildly inaccurate, there will likely be lost revenue either from empty store shelves or lost revenue due to overproduction.
Most of us feel that we have a grasp of what demand planning involves. We believe that, at its core, demand planning breaks down into historical data being funneled through a statistical model with various inputs such as promotions, seasonality and expected sales lift, all to form a prediction, right? The answer – partially.
While historical data on what retailers order, seasonality and the other company-known inputs are important when formulating a reliable demand plan, traditional plans are still missing one crucial ingredient. Real-time POS data.
This data gives consumer goods companies a leg up on the competition and allows them to more proactively plan for what their retailers will order.
The importance of POS data in demand planning
Point of Sale (POS) systems make a record that includes date, location, and SKU every time a retailer makes a sale. This occurs either at a physical register in a store or on an e-commerce platform in the cloud. The data captured here is what retailers themselves use for their own internal demand forecasting processes and how they determine how much product to order. Retailers can see exactly how empty their store shelves are and marry that information up with inventory on hand in their distribution centers to understand what they need from their suppliers.
When a manufacturer or distributor for these retailers tries to predict demand based on what they think the retailer will order, they’re really trying to determine what the retailer thinks their end consumers will buy based on the emptiness of their shelves and how fast product is selling.
Therefore, incorporating real-time POS data into a demand plan as the packaged goods company will create a forecast that is more closely aligned with the retailer’s reality. Today’s empowered consumer is making demand highly volatile, especially as brand loyalty ebbs and SKU proliferation results in numerous options for consumers. All of this compounds the problem of aligning forecasts with a retailer’s reality.
Think of traditional demand planning like a game of Telephone.
- The customer initiates the “game” by buying a product and that purchase information is transferred to the retailer.
- The retailer formulates orders based on what they “heard” from their customers (POS data) and transfers that in the form of orders to their suppliers.
- The consumer goods companies receive those orders and use that historical information to plan demand.
In this scenario, much like a game of Telephone, the manufacturer or distributor of the product is “hearing” about the end customers’ buying patterns through the filter of their retailers’ orders. By adding POS data directly into demand plans in addition to historical information regarding retailer orders, consumer goods companies can improve their demand plans.
Leveraging technology to incorporate POS data
The ability to use POS data in demand planning used to be reserved only for the largest, most advanced companies looking to generate complex forecasts. This is because POS information breaks down into massive datasets of SKUs, locations and dates. The sheer quantity of data has traditionally been too large for SMB and mid-market consumer goods companies to wrangle in their demand models.
What is required is an intuitive, fast and connected demand planning platform that connects real-time, granular POS data with advanced analytics and statistical models to generate complete demand plans all in one place. With the right technology, consumer goods companies can become more proactive and compete with larger enterprises for the best on-shelf availability.
Adding POS data into the demand planning process via technology has numerous benefits. These include:
- Better reaction speed to market and supply chain disruptions that can lead to unnecessary stock-outs or excess inventory
- More aligned team processes as all teams work off of a single set of information that aligns with retailer planning
- Less wasted time and fewer missed opportunities when real-time, granular data is leveraged for exception management
- Improved retailer trust as on-time, in-full (OTIF) rates and service levels increase and recommendations for order changes prove more reliable
- Enhanced ability to scale the business with more SKUs, doors, or retailers without sacrificing accuracy
The market volatility of the last two years has shined a spotlight on the supply chain industry as a whole.
With so many aspects of the supply chain outside of individual companies’ control, areas such as demand planning which can be controlled need to be given higher priority.
By incorporating the “secret ingredient” of POS-data into demand planning with the help of technology, companies can connect planning and execution together to generate the most actionable and accurate demand plans.
