A Guide On Demand Planning: Definition, Importance And Steps
Updated 25 September 2022
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Marketing, sales and operations personnel use demand planning to keep the proper amount of inventory on hand that can ensure meeting the prevailing demand of a product or service. It maximises a company's capacity to satisfy client demand in the most effective manner. Knowing how to analyse past data and product trends to determine the demand for a product or service can help you plan the inventory accordingly. In this article, we define a demand plan, differentiate it from demand forecasting, explain its importance and share the steps to make demand predictions.
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What Is Demand Planning?
Customer demand planning, a cross-functional approach, enables companies to meet customer demand for products or services while minimising excess inventory and supply chain disruptions. It focuses on foreseeing consumer demand for a product as a business planning procedure. Having a well-stocked inventory without a surplus and a demand plan can be a fantastic approach to achieving this balance. Sales teams can use it to create demand projections, which they can utilise as input for processes like service planning, production planning, inventory planning and revenue forecasting.
Demand plans make use of information from both internal and external sources. This forecast then guides the business's sales and operational strategies, allowing it to determine how much product to produce or purchase to satisfy the demand. In short, demand plans combine inventory management, supply chain management and sales forecasting. A wide variety of factors can influence demand, including seasonal changes, labour shortage, economic shifts, competition, severe weather, natural disasters, location factors and global crisis events.
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Difference Between Demand Forecasting And Planning
The larger demand planning process includes the stage of demand forecasting. Demand forecasting analyses internal and external data to forecast sales, laying the groundwork for comprehensive planning. The business analyses historical data and project outcomes for the next 18 to 24 months while forecasting. The forecast duration varies depending on the product and industry, and businesses often constantly modify their forecasts after reviewing the most recent information and alterations to the market. This provides a future estimation of demand, which is useful in determining where to place the inventory and how to distribute the product.
Based on the demand forecast, the demand plan process begins, which determines the scope and action plan for fulfilling expected sales. It also includes demand shaping or affecting demand through price changes, promotions and product substitutions. A demand strategy aims to achieve and maintain an effective lean supply equilibrium, where store stocks the products per the demands of the market. Finding the ideal ratio of surplus and sufficiency is the goal of this strategy.
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Why It Is Important To Plan Demand?
Planning customer demand in advance has several benefits for companies. These are:
Production and labour scheduling: Predicting the timing and probability of sales, can help manufacturing organisations plan production scheduling, warehousing and shipping better. Simultaneously, accurately estimating how many employees can be necessary to complete orders on time can help organisations better allocate tasks and enhance productivity by utilising any excess resources that may be available.
Inventory management: Excess inventory restricts working capital, raises inventory carrying costs and necessitates more space for storage. Achieving the correct level of inventory to satisfy consumer demand prevents excess expenses in creating and storing excess inventory.
Supply chain and logistics: Planning carefully, helps reduce the bullwhip effect, which occurs when tiny changes in retail demand magnify demand from earlier participants in the supply chain, because of which, the supply chain can get disrupted, which can create an inventory shortage. Precisely anticipating product demand can also enable a company to ship products as required and minimise transportation expenditures.
Shortage: This can cause back orders, stock-outs or costly struggles for raw materials. Demand plans can help avoid inventory shortages and their possible unfavourable consequences.
Customer satisfaction: Delays in delivery and unavailability of favoured products may lead to dissatisfied customers. Similarly, reducing inventory-associated costs can help keep product costs low, which may deliver better customer satisfaction.
Profit: Demand plans can protect sales and ensure expected revenue generation. Meeting the market demands and ensuring there is a sufficient supply of a market-favoured product or service can also attract more customers because of its availability and popularity, which may increase the overall revenue.
Low waste: If there is a surplus, businesses may accumulate low value or obsolete inventory, which may cause additional expenses. Ensuring accurate stocking through a strong demand plan can help save both money and materials, which would otherwise get wasted.
Forecast accuracy: As companies create demand forecasts and review them against actual demand, the accuracy of the generated forecasts improves. This increases forecast accuracy, which may help improve production efficiency, optimise expenses and manage demand efficiently as the business grows.
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How To Carry Out A Demand Plan?
Organisations usually complete their process of planning demand by following these steps:
1. Create a team
The first step is to form a cross-functional team with people from the sales, marketing and operational departments, including finance, production and procurement. It is essential that everyone has clear roles and responsibilities.
For instance, members from the purchasing and supply chain departments may make sure that the company acquires enough inventory on time and a team or somebody might serve as a liaison with the IT department to address technical issues with the software, such as forecasting algorithms, data reporting and integration and representatives of the finance team may create the actual forecast. Teams occasionally include a specialist demand plan analyst to offer experience in data management and analytics.
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2. Organise and analyse data
Companies collect internal and external data from their inventory management software and point-of-sale (POS) terminal systems. Internal data includes historical sales data by channel and location, sales forecast, out-of-stock rates, lead times, production times, the business's order history and performance, market research, surveys, inventory turnover, obsolete inventory and other core metrics. External data refers to the business's industry, market trends, consumer behaviour patterns, the recent performance and delivery timelines of suppliers and distributors, and overall economic conditions that may impact sales.
It is also necessary to check with the sales, marketing and product teams regarding factors that can affect demand, such as new launches, price change timings, marketing campaigns, promotions, retirements and competitive offerings. The team then analyses this data with the analytics tools in the demand plan software. Finding connections between sales and inventory through this can enhance forecast accuracy.
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3. Choose a demand plan method
After considering the data, the team can decide which method of planning demand is best suited for their purposes. Here are some quantitative and qualitative methods:
Historical data method: This method includes obtaining a rough estimate or a baseline projection of demand using historical sales data and monitoring high and low demand times in the past. This also entails assessing the future demand for a new product by using the sales data of a similar product.
Delphi method: This process assembles the thoughts and assessments of a select group of advisers and specialists in the field and then summarises and presents them to the company. This can be useful when data is sparse and more viewpoints are necessary.
Demand sensing method: This method includes building a data-driven supply chain by employing machine learning to capture real-time fluctuations in consumer behaviour.
Predictive sales analytics method: This process combines machine learning (ML) algorithms with the latest Internet of Things (IoT) features to learn what factors influence sales, how customers are likely to respond under specific circumstances and how to develop a demand prediction accordingly.
Econometric model: This process includes assessing how economic factors relate to each other and combining that information with sales data to create a demand equation.
Trend projection method: This method utilises past sales data to make predictions for future sales by considering whether past sales trends may reoccur.
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4. Take action and keep adjusting
Following the forecast, teams can finally plan the inventory by figuring out how many products are required to satisfy the anticipated demand along with a buffer of safety stock, finding and selecting vendors who can meet this demand and setting up a transportation cycle that can manage the volume for moving goods between locations on schedule.
The team can add information and update the model and resulting forecasts per new data as it becomes available, such as actual sales of a product or sales of rival products. It is important to have forecasts that reflect the most current data to make the most informed decision. Re-examining the data can also involve holding review meetings with key personnel and staff to re-analyse the numbers and make sure that the teams can reconcile demand with supply.
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