Complete Guide to Demand Management for Business Owners
Virtually all businesses and organizations, regardless of industry, type, and niche, manage demand, including nonprofit and governmental organizations.
For instance, when a brand releases an advertisement for a product, its goal is to generate customer demand for the supply. Essentially, it is trying to get customers to want that product or service.
Although these concepts sound simple enough, managing demand is often a balancing act between having sufficient stock levels to meet demand and making sure customers know enough to want to purchase existing or new products and services.
This is precisely why multinational companies employ teams of demand managers and planners to create sales forecasts and use their predictions to make manufacturing and production decisions.
What is Demand Management?
At its simplest, demand management is the process of predicting demand for a product or service in the future and planning the company's manufacturing capacity and outputs to prevent gaps in supply and demand.
Generally speaking, the process of managing demand begins with a comprehensive analysis of the company's current requirements, historical sales records, and past customer behavior. This research can also include an analysis of product and service specifications, purchase orders, promotional activity, and business plans.
However, demand can also come from internal supply chain sources. These include requirements for raw materials to manufacture goods, components for sourcing products, and spare parts for repair and maintenance.
In other words, demand management is responsible for synthesizing a variety of business activities - from sales forecasting and supply chain management to inventory planning and supplier relationship management - to streamline the organization's many operations.
5 Key Components of Demand Management
With demand planning encompassing multiple functions, processes, and activities, it helps to understand its core components to fully grasp its importance in any organization.
1. Create a Demand Management Database
The first step of the demand management process is identifying the available data and creating a system for gathering and storing information in a database. These data sets typically include shipment history, previous demand forecasts, current orders, and current estimates.
Knowing what data to collect also requires knowing what demand forecasting methods will be used. This allows the company to create an iterative process for creating demand forecasts. To protect the integrity of projections, everyone in the organization must use the proper database as a data source.
2. Gather Data from the Sales Department
This is technically part of the data gathering process, but the nature of sales data makes it a separate component, as it is distinct from most supply chain data. This step allows sales teams to input and review their demand estimates independently from other departments in the business.
3. Manipulate and Analyze the Data
With the database in place, organizations can begin manipulating and analyzing the information to discover actionable intelligence. Examples of analysis techniques include filtering, comparisons, drill-downs, and monitoring changes over specific time-frames.
At this stage, it's usually a good idea for the organization to use demand management software that is designed to create reports from data analytics in real-time.
4. Develop a Method (or Methods) of Creating Demand Forecasts
A simple demand forecast can be geared towards a point estimate - an estimated value for a product or category over a given period (e.g., day, week, month, quarter, or year). Whatever the case, accurate forecasts are the product of a collaborative effort between managers and teams from different departments.
Each member of the organization plays a vital role in implementing a forecast value-add process that improves the quality of the demand estimate.
Demand management also requires a system for ongoing evaluation and improvement. Demand management software can make simple work of this task with automatic reporting and alerts.
Types of Demand Forecasting
Forecasting techniques can be broadly classified based on time, the scope of the market, and the level of detail required. Below are some of the more common types of demand forecasting.
- Passive Demand Forecasting
This type of demand forecasting is typically used by stable organizations with conservative growth targets. Estimates are usually simple and based on historical data with few assumptions. This type of forecasting is rare and is usually limited to risk-averse small and medium-sized enterprises (SMEs) and local businesses.
- Active Demand Forecasting
Active demand forecasting is ideal for businesses looking to scale and diversify with aggressive growth strategies, whether it's through marketing and sales activities, supply chain expansion, product development, or competitor analysis.
- Short-term Forecasting
Demand forecasting at this level often focuses on identifying patterns in seasonal demand based on metrics such as monthly sales volumes and inventory movement. This allows the business to make tactical decisions for manufacturing, sourcing, and distributing goods.
- Long-term Demand Forecasting
- Macro-level External Demand Forecasting
When assessing external demand factors, demand managers typically have strategic objectives in mind, such as expanding to new markets, targeting new customer segments, or creating a new product line.
- Internal Demand Forecasting
Methods of Demand Forecasting
There is no single best approach to forecasting demand, as different goals and situations can require specific methods. Regardless of the approach, however, most forecasting methods will fall under two main categories - qualitative demand forecasting and quantitative demand forecasting.
Qualitative Demand Forecasting Methods
Qualitative methods predict demand by using the opinions of key stakeholders and experts in the organization and outside of it. Data can be gathered using focus groups, surveys, and one-on-one interviews. The insights from these data-gathering activities can then be used to predict potential quantities of future demand.
- Delphi Method
The Delphi method involves tapping a panel of demand forecasting experts outside the company to get their opinions on the company's market forecast. Multiple rounds of questionnaires are sent to the group, whose responses are aggregated and presented anonymously. This process is repeated multiple times, with the panel being able to adjust their responses based on the previous round's pool of answers.
The idea of the Delphi method is to encourage the group to arrive at a consensus as to what the proper demand forecast is. Because each panelist's answers are anonymous, the group can be candid about their views.
- Market Research
In the context of demand forecasting, market research typically involves conducting customer surveys, one-on-one interviews, and focus groups with customers. When done correctly, market research can provide a wealth of insights about an organization's customers that management simply would not find in their internal sales data.
Companies can perform market research on an ongoing basis or at scheduled times of the year, such as during the last quarter of a financial year to prepare for the next.
- Sales Force Composite
The sales force composite method stands out for putting a company's sales team in control of creating the demand forecast. It rests on the idea that, due to their proximity to customers, sales teams have intimate knowledge of their desires, challenges, pain points, and feedback. The nature of their work also means that salespeople are aware of what the company's competitors are doing.
Quantitative Demand Forecasting Methods
Quantitative demand forecasting methods leverage current and historical statistical data to predict future outcomes. By using verifiable facts and figures, quantitative methods are considered to be more objective than qualitative methods. However, quantitative data still has to be contextualized to be of real use to a business.
- Trend Projection
Trend projections use historical sales data to predict future sales volumes. It's a simple but effective forecasting method that draws conclusions only from verifiable data sources. However, it's imperative that future trend projections also take historical anomalies into account.
For instance, the company's primary offering may have had unusually weak sales in the previous year. However, closer inspection shows that this was due to the eCommerce site experiencing problems during peak seasons. These isolated anomalies need to be considered when using this demand forecasting technique.
Econometric demand forecasting uses complex mathematical models to establish relationships between sales data and external forces that influence customer demand.
This method aims to derive and fine-tune an equation to establish a reliable historical correlation. The projected values of the variables that influence demand are then plugged into the equation to produce a demand forecast.
Demand Forecasting - 4 Best Practices
Demand management and forecasting will always be an imperfect science. But there are tried and proven ways to make forecasts as accurate as possible.
1. Establish an Iterative Process
Improving the accuracy of a demand forecast often boils down to having a repeatable and consistent process for comparing previous forecasts with actual market outcomes. Ideally, this process should be repeated every month, which makes it easier to identify deviations and use them to minimize future errors.
2. Measure the Right Data Points
Measuring everything in the organization tends to do more harm than good. Demand managers should instead focus on measuring data points that are most relevant to the company's business goals. These include-
- Point of sale (POS) data
- Stockout frequency
- Competitor sale data
Next, demand managers should decide how often to measure these data points. This largely depends on the industry and inventory turnover rate.
3. Leverage Sales Data
Businesses with multiple sales channels will have to gather and aggregate data from each sales channel for every product in their inventory into one data set. Again, this should be done for all SKUs - this makes it possible to identify which channels have the highest ROI for every product, as well as their individual shipping requirements.
4. Gather Real-time Data
To generate accurate demand forecasts, businesses should invest in automated demand forecasting solutions that provide real-time visibility of sales, inventory, raw materials, and procurement data among others. Automated platforms also make it possible to forecast demand on a weekly, monthly, and yearly basis with little to no human intervention.
Demand management serves as the bridge between a company's internal operations and the marketplace consumers occupy. While sales and marketing teams interact with customers themselves, it's demand management that consolidates those interactions and other business activities, allowing the organization to understand and leverage demand insights during production.
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