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Who Loves Ya?? Demand Planning or Supply Planning? (Part 1)

A few of us were sitting around discussing possible article topics for future issues of “View From The Ridge” when I was challenged by a fellow Blue Ridger to write something about the differences between Demand Planning and Supply Planning.

He was right about one thing, there is a lot of stuff to write about. In fact, there is so much to say that it quickly became obvious why this topic is so confusing. I knew it wasn’t going to be easy to concisely describe the differences between Demand Planning and Supply Planning.
With that said, welcome to part one of a multi-part series: “Who Loves Ya??  Demand Planning or Supply Planning?”


At its most basic level, Demand Planning is all about managing and planning for customer demand. Supply Planning is about managing and planning the inventory supply to meet customer demand.

Simply put, it’s all about Customer Forecast versus Inventory Supply.

Of course, nothing is ever that simple is it? The same holds true for Demand and Supply Management. There are a few pieces of the puzzle that make successful Demand and Supply Management possible.

First, let’s discuss Demand Planning

Demand Planning is the management of the relationships between retailers/distributors and your customers to deliver the best value at the least cost to the demand chain. Demand management is conducted with special regard for the customers. Demand Planning is comprised of several components, all necessary when managing that ‘customer component’.  Let’s look at the first component- forecasting.

Demand Forecasting – the ability to produce precise, segmented projections of upcoming customer demand. Notice I said customer demand… not item demand.

The biggest awakening you can have is to understand that in
forecasting you're trying to predict how customers (and a few
thieves, clumsy folks, etc.) will act on your items.

To truly understand the customer actions that drive demand, you must start by analyzing every customer transaction to develop an understanding of patterns, trends and even fads. The connection between the transaction and the distributor/retailer makes it possible for you to understand demand at that deeper level of detail.

To help you truly understand demand, rather than just analyzing raw statistics without knowing the cause of demand, a distribution/retail forecasting and planning solution needs to be geared toward an environment that captures customer purchasing activity.  This exposes influences, events, and causal factors to predict customer demand more precisely. This level of precision is key to assuring product availability and eliminating stockouts in the supply chain. It’s important to recognize that the forecast consists of multiple segments that today’s distributors and retailers should be taking advantage of:

  • Causal Forecasting: demand that occurs either due to retailer/distributor action (example: sales push, spiffs, promotions), market influences (example: news, social media, supplier advertising), or other conditions (example: events, weather, etc.)
  • Deterministic Forecasting: demand that occurs in a known, or pre-determined way, such as order schedules, committed or booked orders.
  • Stochastic Forecasting: demand for which the cause cannot be identified requires statistical techniques be applied to generate a forecast.

Causal Forecasting is worth a shout out all its own – Truth be told, all demand is causal. Meaning, something or some combination of things caused the customer to buy. Stochastic/Statistical forecasting was only invented because the data and processing power didn’t exist to allow companies to know the “cause” for demand.

Most distributors and retailers have a common business problem: they are unable to accurately predict events that affect sales and their attributes (e.g. spiffs to sales reps, price promotion in a circular, in-store promotion, etc.).

The solution is quite simple: collect the attributes of past causal events that enable the creation of an event forecast. When the impact of causal events create the forecast for similar upcoming events, the totality of the forecast is much more accurate, enabling better event in-stocks.

Aggregate Forecast Management – Today’s planners are inundated with a multitude of responsibilities. Arguably, the most important of those responsibilities is assuring that the different forecast inputs for an ever increasing number of SKU/locations is as complete as possible. To manage these forecasts effectively, planners must be able to:

  1. Aggregate forecast inputs in order to make forecasts more accurately reflect upcoming demand
  2. Segment and compile forecast inputs
  3. Apply forecasts to the appropriate products and locations

By spending the time on the front end to gather forecast inputs, the forecast is more accurate prior to demand occurring, demand fulfillment is more effective, inventories are more aligned with demand, and the need for demand exception analysis is reduced.

In our next article, we will discuss the next elements needed for superior Demand and Supply Planning. Let us know your thoughts on which of these two important components of Supply Chain Management is best for you.