Demand Planning Aligns Sales and Supply Chain
Demand planning is a crucial component of the sales and operations planning process
. Specifically, it is the primary link between the sales forecast and the supply plan (or “Production Plan”). The demand planning process provides a forum in which the business informs supply chain what products to build to meet expected customer demand. This is a straightforward concept, but actually an incredibly hard process to get right.
In fact, most companies don’t recognize the complexity in demand planning, and simply fail to invest sufficient resources in this critical function. As a result, nearly every company has either excess inventory, routine customer stock outs, or both. In the below, I describe the challenges of demand planning, and I outline some of the best practices to develop an effective planning cycle in your organization. Finally, I identify some of the typical process gaps that prevent companies from truly excelling at demand planning.
Most companies don’t recognize the importance of demand planning, and fail to invest sufficient resources in this critical planning tool. This lack of focus results in both missed orders and excess inventory.
A Product-Specific Forecast
First, let’s define the outcome of demand planning: The goal is to generate an accurate product-level demand plan that informs the supply chain how much product to make, and at what time. For instance, if a company has 250 product variants, the demand plan will forecast the expected demand for all 250 products over a period of time, such as 12 to 18 months.
Supply Chain Management
Supply chain management then uses the demand plan to make sufficient products to meet future product demand. They may hire new workers to ensure they can make the volume the business will need at the right time. In some cases, they may modify production sites to produce the right mix products. If certain products require specific handling (such as cold storage), the supply chain leaders may elect to repurpose existing warehouse space to maintain ideal inventory levels.
Why is Demand Planning So Hard To Get Right?
The Multiplier Effect
First, imagine you are tasked with forecasting aggregate sales across an entire division. You don’t need to create for every product; you just need to predict one sales number for the entire division. You would likely start with prior period sales, and adjust for economic or industry factors. You may even model in prospects for your largest customers. If you are forecasting only at an aggregate level, these steps will yield a reasonable forecast. Now, imagine you are tasked with planning demand at the product level. If this same division has 500 products, then you are now tasked with creating 500 separate forecasts, one for each product. The task has just gotten quite a bit more challenging. It is now critically important that you consider promotion spend, and other nuances that could affect future demand for individual products. Given this level of detail, you would likely need to use a statistical forecasting method. To make the task even harder, let’s assume these 500 products are sold in five different geographic regions, each with its own supply chain. It’s expensive to ship products between regions, so you now need to predict demand for each product in each region. So, you are now creating 2,500 different forecasts (500 products times 5 regions). Now you get the idea. Demand planning is especially complex, even with only a modest-sized product portfolio.
Collaboration is Key
As I described above, demand planning is especially complex because of the granularity of supply chain planning. You aren’t just creating one prediction; demand planners create hundreds (likely thousands) of predictions, one for each product. So, what is the secret to creating an accurate demand planning function? Collaboration. It takes a ton of input data to yield an even modestly accurate forecasts, and demand planners cannot do it alone. They rely on a wealth of information from sales and marketing teams, and rely on business leaders to make prudent decisions on the size and scope of product portfolios.
Sales Team: Sales Pipeline
Sales associates should maintain data on near-term sales wins, and populate the CRM tool
with estimates of both the size of win and likely probability. Ideally, the sales team will maintain a sales pipeline with the following data:
- Size of likely wins from new customers
- Product(s) impacted by each win
- Stage of pipeline (prospect, proposed, negotiation, signed agreement)
- Measure of probability of win
The above details provide a good overview of likely new account wins, and this should be incorporated as a key input into the demand plan.
Best Practice: Accurate, Risk-Adjusted Pipeline
It is tempting for salespeople to build overly-optimistic pipelines. A healthy sales organization includes motivated leaders, and a natural competitive spirit among the associates. However, this frequently leads to overstated pipelines, which can wreak havoc in the demand planning cycle. Good practice is to develop rules for including wins from new customers in the pipeline. For instance, salespeople may include new wins only after a customer has signed an agreement. If the customer has not yet signed, the impact from this prospect should be discounted in the pipeline data to reflect the likelihood they will eventually become a customer.
Marketing: Long-Term Trends
The marketing team owns market research and product portfolios, and routinely measures the following items:
- Market size
- Market growth and industry trend data
- Product lifecycle
Since the marketing function typically has the best visibility into customer demand over a long time horizon, this team should contribute to the demand planning process. Their input may be more theoretical (“we think Product A sales may see a headwind due to competition from Company C”). Or, the marketing function may have more tactical input (“new construction starts are expected to drop 5% due to mortgage rates, and Product B is directly correlated with new starts”). Further, the marketers typically manage the product portfolio. They lead critical decisions on which products to add to the portfolio, and which to remove. It is crucial the planning team has real time data any time a product is either added or removed from the product portfolio.
Product Portfolios Should Reflect Impact on Demand Planning
Product portfolios grow over time. Customers want a new variant of an existing product, or the company solves a particular customer need through innovation. However, there is often little incentive to remove poorly performing products from the portfolio. A result, the number of products in the portfolio creeps higher each year, and eventually is burdened with a number of slow-moving products. Hundreds of dead (or nearly dead) SKUs represent a nightmare for any planning team. Slow-moving products are especially hard to predict, so the supply chain typically builds excess inventory for these products. A best practice is to identify an ideal size of the product set, and prune the portfolio any time a new product is added. While this isn’t a popular exercise (no one wants to kill products), the marketing team should enforce discipline in demand management to prevent excess inventory.
Demand Planners: Putting it all Together
The primary function of the demand planner
is to combine historical sales data with input from both sales and marketing teams to assemble a demand plan by product. Frequently, they will use planning software to predict future demand with sophisticated statistical forecasting methods. Larger organizations may even use artificial intelligence or machine learning. It is important to note the planning role is more than just consolidating inputs to build a demand plan. Rather, this role functions as a gatekeeper
for the demand planning function, and should be leading thoughtful conversations that lead to a reasonable approach for planning demand in near real time. For instance, the sales pipeline may yield exceptionally high demand for a product that historically hasn’t sold well. It is the responsibility of the demand planner to lead conversations to understand what is changing to drive new demand for the product.
The Demand Planner should be considered a Gatekeeper in the Demand Planning process. He/She should screen all inputs that impact prediction of future demand.
Demand Planning Review Meetings
In a perfect world, the demand planner leads periodic cross-functional demand planning meetings for purposes of communicating and approving the demand plan. Referred to as the Sales and Operations Planning (“S&OP”) process, these cross-functional discussions should seek consensus from sales, marketing, business leadership, and plant leaders prior to finalizing the plan. This is frankly where most organizations fall short in implementing an effective demand planning cadence. Organizations frequently operate in silos, and the demand planner often does not have the authority to force collaboration with both the salespeople and the marketing function. For this reason, it is especially important the business leaders encourage a strong management process, and support the planning team. Right or wrong, all these functions should feel ownership in the demand planning process, and are jointly responsible to provide input in this critical function.
Conclusion: Aligning Supply and Demand
Demand planning aligns the supply chain to business needs – By providing clear forecasts of future product demand, the supply chain is better equipped to meet customer demand in the future. Most companies do not recognize how an effective demand planning cycle can improve both their stock outs and inventory levels. It’s important for supply chain leaders to elevate the topic and ensure they obtain the resources and collaboration they need to develop accurate forecasts.