Demand Planning

Demand planning is a business process that predicts future customer demand for a company's products or services. It involves analyzing historical sales data, market trends, and other relevant factors to estimate the likely demand for a product over a specified period. It aims to ensure that a company has the right products in the right quantities.

It helps companies avoid overstocking or stock shortages, which can result in lost sales and increased costs. Therefore, it is a critical component of supply chain management and is often integrated with production planning, inventory management, and other related processes.

• Demand planning is a critical aspect of supply chain management, as it helps companies to ensure that they have sufficient resources and capabilities to meet customer demand.
• Its process involves analyzing historical and current demand data to forecast future demand and developing and implementing strategies to meet this demand.
• Effective planning requires a deep understanding of customer behavior, market trends, and the competitive environment.

The demand planning process estimates future demand for a company's products or services. It aims to align a company's supply with customer demand to minimize the associated risks. As a result, it helps companies to manage their inventory better, reduce costs, improve customer satisfaction, and increase profitability.

Some of the essential considerations in it include:

1. Accuracy: Forecasting demand accurately is difficult due to the unpredictable nature of consumer behavior and the impact of external factors such as economic conditions and market trends.
2. Data quality: The data used in the process is critical to forecasting accuracy. Quality data can lead to correct demand predictions, resulting in overstocking or stock shortages.
3. Collaboration: Effective planning requires cooperation and communication among different departments within a company. The lack of coordination between departments can lead to conflicting demand forecasts and inefficient supply chain management.
4. Adaptability: The process must be flexible and adaptable to changes in demand in real-time.

There are several methods used for such planning, including:

1. Statistical forecasting: This method uses statistical techniques such as time-series analysis, regression analysis, and exponential smoothing to forecast future demand based on historical data. Statistical forecasting is appropriate for products or services with a stable demand pattern and significant historical data.
2. Judgmental forecasting: This method uses expert judgment and intuition to forecast demand. Critical forecasting is often used when there is limited historical data or an uncertain demand pattern.
3. Combined forecasting: This method combines statistical and judgmental results to generate a more accurate demand forecast. This method is proper when the demand pattern is complex, and a combination of statistical and critical methods is required to create a precise prediction.
4. Delphi method: It involves a structured process where a panel of experts provides their forecasts, which are then consolidated and refined through a series of iterations. The goal of the Delphi method is to arrive at a consensus forecast that considers the views of multiple experts.
5. Simulation modeling: This method involves creating a mathematical model representing the demand for a product or service and simulating different scenarios to forecast the market. Simulation modeling is appropriate for products or services with complex demand patterns or situations where multiple factors impact demand.
6. Promotional forecasting: This method involves forecasting demand for a product or service during a promotion or advertising campaign. Promotional forecasting considers the impact of promotions and advertising on the market and helps companies plan for increased demand during these periods.

Its elements can be broadly categorized into three main components:

1. Data collection and analysis: This involves gathering and analyzing historical sales data, market trends, customer demographics, and other relevant information to develop a baseline for forecasting future demand. The data collected and analyzed in this stage forms the basis for the demand forecast.
2. Forecasting: It involves the use of statistical models, judgmental methods, or a combination of both to estimate future demand for a company's products or services. The demand forecast considers the impact of various factors, such as seasonality, promotions, and market trends, on future demand.
3. Demand planning in the supply chain: It involves the development of a plan to ensure that the necessary products or materials are available in the right quantities at the right time to meet customer demand. It may include adjusting production schedules, inventory levels, and transportation plans.

In addition to these three main components, it also includes:

1. Performance monitoring: This involves continuously monitoring actual demand against the forecast to promptly identify and respond to changes in direction. Performance monitoring helps companies improve their demand forecasts' accuracy over time.
2. Consensus building: This involves reviewing and validating the demand forecast with relevant organizational stakeholders to ensure that all relevant departments understand the demand forecast and its underlying assumptions.
3. Collaboration: It requires cooperation and communication among departments within a company, including sales, marketing, finance, and production teams. The lack of coordination between departments can lead to conflicting demand forecasts and inefficient supply chain management.
4. Adaptability: Its process must be flexible and adaptable to changes in demand in real-time.

Let us understand it in the following ways.

Example #1

Suppose a clothing retailer, Amacon Ltd., wants to improve its process. The company has different departments, such as sales, marketing, finance, and production, generating its forecast of expected demand for other products. The process aims to align these forecasts into a single, unified demand plan that can inform decision-making and guide the development of supply chain strategies.

The first step in its process is to collect data on historical demand and relevant market trends, as well as forecasts and projections generated by different departments.

The next step is reconciling the different forecasts and projections to develop a consensus view of expected demand. This may involve adjusting individual forecasts to account for any discrepancies or outliers.

Once a consensus view of expected demand has been developed, all relevant stakeholders must agree on the demand plan, and any necessary adjustments must be made. The consensus demand plan is then communicated to all relevant departments and stakeholders, and the company works together to ensure that the project is implemented effectively.

Example #2

As per recent reports, with a spike in demand for luxury goods like sports vehicles and models with many features, Hyundai Motor India is trying to capitalize on growth prospects in rural areas. With more retail locations and initiatives like mobile service vans, the second-largest automaker in the nation hopes to increase its footprint in small towns and rural areas. The carmaker has over 5,000 employees working in rural areas, and its sales locations have already surpassed 600. Last year, Hyundai sales in rural areas reached one lakh.

It is essential for several reasons:

1. Improved customer satisfaction: By accurately forecasting demand, companies can ensure sufficient quantities of products or services to meet customer demand. It helps to minimize stock shortages and reduces the risk of disappointing customers.
2. Increased efficiency: It enables companies to optimize their supply chain processes, reducing waste and maximizing the use of resources. It helps to reduce costs and improve overall efficiency.
3. Better inventory management: By continuously monitoring actual demand against the demand forecast, companies can adjust their inventory levels to minimize the risks associated with overstocking or stock shortages. It helps to ensure that the right products are available at the right time, improving customer satisfaction and reducing costs.
4. Improved decision-making: It provides companies with valuable information about future demand for their products or services. This information can inform strategic decision-making, such as product development and marketing initiatives.
5. Better resource allocation: By forecasting demand, companies can make informed decisions about resource allocation, such as raw materials and production capacity.
6. Enhanced collaboration: It involves collaboration between different departments within a company, such as sales, marketing, finance, and production. It helps ensure that all relevant departments understand the demand forecast and its underlying assumptions, improving communication and collaboration.
7. Increased competitiveness: It helps companies stay ahead of the competition by ensuring they have the right products or services available at the right time. It helps to increase market share and improve overall competitiveness.

The demand planning job is a broader concept encompassing demand forecasting and developing and implementing strategies to meet customer demand. Supply planning ensures that a company has the resources to meet customer demand. In contrast, demand forecasting focuses on estimating future demand based on historical data and other relevant information.

Here are some other differences between demand planning, supply planning, and demand forecasting:

1. Objectives: It is focused on meeting customer demand by ensuring that a company has sufficient resources and capabilities. Supply planning is focused on optimizing the supply chain to minimize waste and maximize efficiency. Finally, demand planning tools estimate future demand as accurately as possible.
2. Inputs: It considers various information, including historical demand data, market trends, and customer behavior. Supply planning thinks the availability of raw materials, components, finished goods, production capacity, and delivery schedules. Demand forecasting relies on the statistical analysis of historical demand data and relevant market information.
3. Outputs: The output is a demand plan outlining the strategies and tactics a company will use to meet customer demand. The production of supply planning is a supply plan that outlines the strategy and tactics a company will use to optimize its supply chain. Finally, the demand forecasting output is a forecast that estimates future demand for a company's products or services.
4. Time Horizon: It typically covers a longer time horizon, such as several months or a year. Supply planning often covers a shorter time horizon, such as weeks or months. Demand forecasting typically covers the most concise time horizon, such as several weeks or months.
5. Degree of Detail: It involves a high level of detail, including product-level forecasts, sales targets, and inventory management strategies. Supply planning also involves a high level of detail, including production schedules, delivery schedules, and inventory management strategies. On the other hand, demand forecasting could be more detailed, providing an aggregate estimate of future demand.
6. Level of Accuracy: Its accuracy is critical, as it directly impacts customer satisfaction and the efficient use of resources. The accuracy of supply planning is also essential, as it affects the efficiency of the supply chain and the ability to meet customer demand.
7. Collaboration: It involves collaboration between different departments within a company, such as sales, marketing, finance, and production.

This has been a guide to what is Demand Planning. We compare it with supply planning and know its methods, elements, examples, and importance. You can learn more about accounting from the following articles –

• Law of Supply and Demand
• Material Requirements Planning
• Business Continuity Planning