Accurate demand planning is essential, as it ensures that you always have the right products on your shelves.
Correctly predicting customer demand also means that stores don’t have lots of unsold inventory that ties up valuable capital.
In this post, you’ll learn how demand planning contributes to better supply chain management.
What is demand planning?
The term “demand planning” is part of the supply chain management cycle. As a retailer, you are forecasting a product’s demand so there are always enough items on the shelves for customers to buy.
You also want to avoid a surplus of products. Excessively high inventory levels reduce your capital and impact your profitability.
Factors that influence product demand
Several factors can influence a specific product’s customer demand, including:
- The economic performance of your country, region, market, etc.
- Weather conditions
- Seasonal fluctuations
- Political disruptions
- Pop culture and trends
- and more
It’s important to obtain demand-related information from all possible sources. Analyzing consumer trends and past sales data can often prove useful. Together, these factors enable you to improve your forecast accuracy and match those numbers with your supply forecast.
Why is demand planning important?
Skilled demand planners know the importance of making accurate forecasts. First, you’ll avoid undesirable stock-outs that increase the chances of customers switching to a competitor. Obtaining accurate demand information also simplifies inventory management and operations planning functions.
When to conduct demand planning
Ideally, you’ll perform demand planning tasks on an almost real-time basis rather than relying on historical data. As a starting point, pay attention to the demand signals you receive during your daily operations. This nuts-and-bolts information comes from actual retail sales and product order information.
Demand sensing activities are also useful for enhancing near-future forecasts for the next few hours or days. This method uses demand data sourced from short-term activities.
Enhance these two types of data with targeted demand planning applications. More timely data acquisition enables better decision-making and more accurate product performance metrics. In turn, this leads to more efficient supply chain management.
If you don’t regularly perform these demand management tasks, you may encounter significant product shortages. You could also be burdened with excess and/or obsolete inventory that customers won’t buy at any price.
Demand planning vs. demand forecasting
Demand planning refers to the entire process of predicting a product’s sales. Within this larger context, demand forecasting covers a longer-term period such as the next 18 to 24 months. However, the forecast timeframe often varies by industry and type of product.
Reviewing sales data, and monitoring changing market conditions, will help you to better forecast demand for a specific product. Using the service levels concept provides an indication of the chances of having sufficient stock to satisfy customer demand. Based on this information, you can refine the forecasting process accordingly.
7 steps for effective demand planning
When you implement a workable demand planning process, you’ll find that sales and operations planning (or S&op) are also much easier. In turn, this sets the stage for more productive business planning.
Let’s say you can successfully predict demand for a certain product (or SKU, short for “stock keeping unit”). Then, you’ll have an indication of which product lines will be profitable for your business. This knowledge can drive your product portfolio and subsequent new product introductions.
Demand planning in action
The demand planning management process involves internal stakeholders and external partners such as product vendors. Participants will review varied forecasting methods and choose the one deemed most appropriate for the business’ needs.
1. Assemble a cross-functional team
Gather team members from every department involved in the product lifecycle. Supply chain planning and purchasing team members should be dedicated to ensuring sufficient inventory to fulfill the demand forecast. Finance department team members will create the demand forecast. Each participant should have well-defined roles and related responsibilities.
2. Obtain agreement on relevant details
All team members should decide on the data needed for a high-value forecast. Common data metrics include sales data, inventory turnover, out-of-stock frequency, and production lead times.
To enable informed decision making, product teams will provide new product and product retirement details. Sales and marketing team members will present information on price adjustments, promotions, and marketing campaigns that could impact demand.
3. Add relevant external data
Varied external factors will likely affect the demand forecast. Examples include supplier/distributor delivery performance and key customer buying habits. Large-scale economic trends, significant market shifts, and changes in demand for specific products are other factors.
4. Produce your demand forecast
Team members should select the most relevant statistical forecasting model for the retailer’s needs. Although some retailers still use relatively laborious Excel spreadsheets, most companies have opted for powerful demand planning software.
Depending on the forecasting model, artificial intelligence, machine learning, and/or algorithms may also be involved. These forecasting methods easily automate the processing of huge datasets.
These sophisticated forecasting models can also identify obscure patterns and trends. Demand planners can utilize this data to make near real-time adjustments.
Larger retailers may use enterprise resource planning (or ERP) software that integrates varied aspects of the business’ operations. If necessary, conduct a webinar to familiarize all team members with the chosen forecasting method.
5. Review the draft demand forecast
Convene the team members, and verify all relevant forecast information. Consider removing unusual data that could unnaturally skew the forecast.
Add recently available data to determine whether it significantly affects the predictions. Finally, ensure that the demand forecast syncs with the company’s larger-scale financial forecasts.
6. Compare forecasts vs inventory
Identify the amount of inventory necessary to meet the projected demand (including some extra “buffer inventory”). Ensure that specified vendors can meet the demand on time. Confirm that transportation contractors can meet your schedule and volume demands.
7. Implement specific measurement criteria
Define key performance indicators (or KPIs) that enable effective demand planning evaluation and optimization. Assign target levels for factors such as sales forecasting accuracy and order fulfillment lead time, among others.
Methodically review actual performance vs the targets, and implement adjustments as needed. This “bottom-up” approach evaluates a specific process or function. Then, the retailer can incorporate those results into larger-scale company operations.
Looking ahead: the future of demand planning
Technology advances have led to the development of powerful demand planning software that improves forecast accuracy. Machine learning, artificial intelligence, and/or algorithms may be integrated into the software program.
Companies may utilize Internet of Things (or IoT)-enabled devices to receive real-time data on inventory or raw materials. IoT technology also enables real-time sales monitoring that drives faster replenishing of store inventories.
Communications and collaborative skills are also important in this digital business landscape. Working effectively with internal and external stakeholders helps to ensure that everyone’s goals will be met.
Combined digital technologies will continue to improve a retailer’s ability to predict customer demand for their products. To satisfy this demand, the retailer orders more products through their established supply chain.
Ideally, suppliers deliver the merchandise in time to avoid potentially costly stock-outs. Over time, this successful demand strategy will help the business to grow.
About Francesca Nicasio
Francesca Nicasio is Vend's Retail Expert and Content Strategist. She writes about trends, tips, and other cool things that enable retailers to increase sales, serve customers better, and be more awesome overall. She's also the author of Retail Survival of the Fittest, a free eBook to help retailers future-proof their stores. Connect with her on LinkedIn, Twitter, or Google+.