Demand forecasting is an essential part of informed decision-making when operating any business. It helps stores determine how to manage inventory or schedule their staff effectively. Manufacturers can anticipate busy seasons and adjust their production accordingly. Warehouses can plan for increased volume or product movement during certain times of year. Understanding how to forecast your business properly helps save money, improve data compilation, and enhance inventory management, ultimately leading to satisfied customers.
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Forecasting uses data to estimate or predict future outcomes. Demand forecasting is no different. Businesses across various industries utilize historical data to estimate their needs regarding inventory, staffing, facilities, logistics, and more. To fully define demand forecasting, it’s the process of estimating future customer demand for a product or service. Without demand forecasting, you’ll have unhappy customers who don’t have the products they want or the personnel in place to serve them when they need them. Demand management typically involves using data from the past several years to identify trends in customer needs, allowing you to be prepared to meet them.
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Why Is It important?
Cost Savings
Part of keeping costs down is producing, shipping, and stocking the right amount of inventory. Demand forecasting helps project the need for replenishing inventory, determining production levels, and deciding on backstock. For instance, a company selling seasonal widgets requires historical data to effectively forecast sales and predict when sales are likely to increase. Forecasting ensures that your company orders sufficient inventory to meet customer demand throughout the season. When the peak season is over, you might be left with overstock that’s sold at a reduced price or sent back to a warehouse, where it incurs costs to hold until the next widget season rolls around again. Furthermore, transporting widgets through your supply chain costs you money. Efficient inventory management reduces forward and reverse logistics costs.
Data Management
It’s said that those who don’t study the past are doomed to repeat it. Maintaining quality data ensures you have a clear picture of where your company has been and makes it easier to see where you’re headed in the future. Quality data is essential in supply chain management. By ensuring your company maintains robust records, you can more effectively understand the past and predict the future with greater accuracy. GS1 Standards ensure your company has processes in place to help manage data to analyze past trends for effective supply chain planning.
Inventory Management
Understanding customer trends makes inventory management much easier. You typically know when to increase or decrease your stock on certain items. Demand forecasting creates efficiencies in inventory management by preventing overstock and shortages. Overstock often leads to revenue losses, as items are sold at a reduced price or not sold at all. Shortages can result in long-term revenue losses by eroding customer trust. Effective supply chain demand planning ensures your customers are always served.
Demand Forecasting Techniques
Demand forecasting traditionally incorporates six approaches that contrast in three dimensions. The most common forecasting techniques include:
- Passive demand forecasting
- Active demand forecasting
- Short-term demand forecasting
- Long-term demand forecasting
- Macro and micro demand forecasting
Each can be used to create useful projections within your business operations. Whether you’re planning to use software to automate projections or rely on the hand of an expert, different demand forecasting methods and techniques can be used within your company to provide robust projections to help you plan for the future.
Passive demand forecasting enables a company to automate the process, allowing it to be completed efficiently and accurately. Using software or AI, projections are created based on historical data. The more data you can provide to the software, the more accurate your projections will be. For instance, a company can feed demand forecasting software years of data showing customer trends over a calendar year. The software will then analyze the data and display trends for your chosen period, whether it be daily, weekly, monthly, quarterly, or otherwise.
While passive demand forecasting is an effective method for identifying basic trends, the software generally can’t give a reason for certain trends or predict anomalies. However, having an expert in place who can interpret the data is a great way to ensure that these gaps are filled. This approach, however, begins to involve active forecasting. You may encounter additional limitations with passive forecasting in a rapidly growing company or a market experiencing significant disruption. It can be challenging to identify trends when data shows marked changes year over year.
Active demand forecasting leverages the human element to analyze statistical data and create customized projections based on historical data. In contrast to passive demand forecasting, active forecasting is ideal for fast-growing businesses and dynamic or seasonal marketplaces, as previous data might not be sufficient to project future activity accurately. Having an expert analyze data, you can paint a complete picture of trends and why they happen, and your business can respond to them. For example, a restaurant might show a spike in takeout orders every year during a special sporting event. An analyst can look at this data and fully understand why, but analysis software might see this as an anomaly and overlook it.
While active demand forecasting can offer more robust insights to data, it takes more time than using software that can process the information in a matter of seconds. Having a person comb through years of data to analyze it and identify trends that predict future results can be incredibly time-consuming.
Creating projections for the next weekend, week, month, quarter, or year is considered short-term demand forecasting. Companies can use data from the last several years to project earnings or inventory demands for upcoming dates, fiscal periods, or holidays. Companies can easily create multiple short-term forecasts to track month-to-month or year-to-year data, creating more data for future projections.
Short-term forecasting can be an effective way to meet customer demand. However, it’s important to consider the current economic environment when using data from previous years. Even if you’ve had relatively consistent data to show what to expect each year, a recession could cause a sharp drop in sales, leading to overstock. In contrast, a flourishing economy might bring more customers than you’re used to and cause shortages in a product. Take into consideration the current climate when making short-term projections.
In contrast to short-term forecasting, long-term demand forecasting is measured in years, making it less likely to be accurate in the short term. While the projections may not be as accurate in the short term, they can help prepare for a variety of scenarios. Long-term demand forecasting is a great way to create “what if” scenarios, making it easier to plan for several contingencies and providing a road map to long-term success based on assumptions about market trends. Despite the large margin of error with long-term projections, the demand for accuracy is low for effective planning.
Micro versus macro demand forecasting is like focusing on the trees versus the forest. At the micro level, or internal, forecasting analyzes company data, considering customer demand, your products and services, and financial metrics. Macro demand forecasting focuses on the current state and direction of the entire industry. You’ll need to consider what your competitors and industry leaders are doing with the current market. As part of market analysis for creating macro forecasts, you’ll need to understand the current economic climate. Are customers spending or feeling more frugal? Ultimately, utilizing micro and macro demand forecasting strategies can help companies make informed decisions in areas such as expansion and contraction.
What Factors Impact Forecasting and Planning?
Demand forecasting relies on several factors within your company and industry. Many businesses go through seasonal sales periods. Whether you’re running a large grocery store or a small sporting goods store, there will be periods of feast and famine. A grocery store won’t have as significant peaks and valleys in sales as a small sporting goods store, but they’ll still exist. Understanding your seasonality is a crucial part of effective planning.
Your competition will often dictate some of your decisions. For instance, if you see a store down the street bringing in a hot new item that’s selling well, you’re probably going to want to find out how you can get the same item for your customers. This requires planning with your supply chain partners and will affect your current plans.
The quality of your data determines how well your team can project future needs. Some data can help you get the job done and forecast some of your needs. However, the more data you have, the better you can understand historical trends and account for similar activity in the future.
Demand Forecasting Across Industries
Demand forecasting plays a crucial role in every industry. Each of the following industries can effectively use demand forecasting to help run and grow their business.
- Retail: Inventory and staff management to serve customers
- Manufacturing: Projecting material needs and delivery to meet client needs
- Healthcare: Serving patients with sufficient medication, supplies, and facilities
- Logistics: Creating efficient routes and delivery to save on costs throughout the supply chain
Retail
Demand forecasting is essential to running a successful retail operation. From inventory management to staffing, your company will utilize historical data to plan and ensure it has the right products to meet customer demand and the personnel to serve them. Effective supply chain demand planning incorporates historical data to plan for seasonal sales peaks and valleys as well as day-to-day operations.
Manufacturing
Busy seasons in manufacturing don’t often come as a surprise, thanks to demand forecasting. Using high-quality data to create projections for manufacturing schedules is an effective way to ensure your company is sourcing the right amount of materials when you need them to meet your clients’ needs.
Healthcare
Demand forecasting is used across the healthcare industry to ensure patients receive sufficient care. Historical and patient data are tracked to predict seasonal illnesses, such as colds or flu, and to inform the availability of medications, medical supplies, staffing allocation at a facility, and bed management. Planning supports informed decision-making to meet patients' needs and expand provider capacity.
Logistics
Without demand forecasting in logistics, you could find yourself without a sufficient number of vehicles, spending more money on fuel due to inefficient routes and missing delivery deadlines. Projecting needs makes it easier to manage capacity for transporting goods throughout the supply chain. Continuous forecasting can help create more efficient routes and schedules, facilitate the adoption of new technologies, and provide up-to-date feedback on necessary adjustments that need to be made to the system.
GS1 US Can Help
Using demand forecasting models and techniques ensures operational efficiencies and cost savings, helping you determine when it’s time to grow or hold the line within your business. Get help from our team to create effective demand forecasts for your business. Our team of experts can assist you in establishing GS1 Standards to ensure you capture quality data across your supply chain, enabling more effective demand forecasting. Request more information to get started improving your supply chain solutions today.
