In your bid to run an effective supply chain management system, there are quite several actions you will take, and one of them is setting up an effective demand planning and forecasting system (DPFS). In this article, we will review the essentials, explore its elements, and discuss how to set up a robust demand forecasting system.
“Every effective enterprise has a vision, and in your supply chain management system, Demand planning and forecasting serve as the guide to achieving the vision of your supply chain.”
What is Demand Planning and Forecasting in Supply Chain Management?
Every effective supply chain piggybacks off the demand of customers. For that reason, demand planning and forecasting in the supply chain is vital. DPFS estimates or predicts customers’ demand on the supply chain, then uses that demand forecast to plan and run the supply chain while giving allowance for margins of error.
So many factors go into DPFS, including market acceptance of the product, historical data on demand, seasons, pandemics, natural disasters, and economic variations.
Importance of a Demand Planning and Forecasting System in Supply Chain Management
The main aim of DPFS in any supply chain is to manage resources to satisfy customers’ demands effectively while reducing the cost of the supply chain. This section will review some of the importance of any demand planning and forecasting system to your supply chain.
- Optimize Inventory
- Effective resource allocation
- Improve Production efficiency
- Minimize risk
- Enhance supply chain collaboration
1. Optimize Inventory
Inventory management is a key aspect of your supply chain but is also one of its most expensive aspects. Supply chains have to hold inventory which could cost a lot of money due to storage, insurance, and security.
Implementing a DPFS allows you to plan your inventory effectively, allowing you to hold only necessary inventory, ultimately reducing storage, insurance, and security costs.
When planning for inventory, you should remember that different types of inventory work differently for every supply chain. Therefore, always try to ensure you plan your inventory according to your supply chain type.
2. Effective Resource Allocation
Supply chain management systems are increasingly complex, with many parts moving simultaneously and needing different resources. This simultaneous movement makes the effective allocation of resources very essential.
A robust demand planning and forecasting system will help allocate resources, ensuring your supply chain runs smoothly.
3. Improve Production Efficiency
Demand planning and forecasting give the production arm of your supply chain a schedule which allows the production team to work more effectively.
When your supply chain knows what demand to expect, it allows for production planning and finishing around that demand. This way, your production bottlenecks are greatly minimized. It will also optimize the process and reduce lead times.
4. Minimize Risk
Supply chain risk can be detrimental to the survival of any supply chain, including yours. Similarly, during the pandemic, there was very high uncertainty in the demands of customers, which led many supply chains to fail. The ones that succeeded relied greatly on demand planning and forecasting tools.
As mentioned earlier, several factors affect your supply chain’s demand planning and forecasting. Using these factors to plan will enable the supply chain to identify potential risks such as low demand, market downturns, or supply chain disruptions.
Using the demand planning and forecasting system, you can prevent these issues and optimize the supply chain to make the most of any circumstance.
5. Enhance Supply Chain Collaboration
Supply chain collaboration is the parts of the supply chain, including stakeholders ( internal and external) working together to achieve the primary objective of the supply chain.
Through demand planning and forecasting, these parts and stakeholders will understand what is expected of them, enabling them effectively work to ensure the success of the supply chain. The alternative is working blindly and expecting a great result.
Elements of a Demand Planning and Forecasting System
To make the most out of your supply chain planning efforts for accuracy and effective production, many elements go into setting up the right DPFS.
- Data Collection and Analysis
- Market Research and Insights
- Demand Modelling and Scenario Planning
- Collaboration with relevant Supply Chain Stakeholders
1. Data Collection and Analysis
This entails collecting and analysing historical and current data. It draws insight into customer behaviours over time, allowing your supply chain to predict their future behaviour.
2. Market Research and Insight
Market research helps you understand market trends and how customers interact with competitive and complementary goods.
This broadens your insights on customer behaviours, including what they like or dislike about you and your competitors’ products, allowing your supply chain to make the necessary changes.
3. Demand Modelling and Scenario Planning
Drawing up a demand model and scenario planning allows your supply chain to use gathered data to navigate potential scenarios in the demand and supply of your supply chain products. This helps mitigate the risk of your supply chain.
4. Collaboration with Relevant Supply Chain Stakeholders
Relevant stakeholders in the supply chain also help facilitate demand planning and forecasting. You do this to gather all necessary information that could impact the demand negatively. Examples could be production delays or logistic disruptions.
Demand Planning and Forecasting System Methodologies for Supply Chain
Several methodologies exist in implementing DPFS for supply chains. Finding the right methodology for your supply chain varies and depends on factors such as the data available, the type of supply chain, and historical demand patterns.
- Time Series Analysis
- Regression Analysis
- Delphi Method
- Predictive Analysis and Machine Learning
- Market research and Surveys
1. Time Series Analysis
This method relies solely on historical data to predict future demands. This method implies that the historical data will continue into the future.
Although this method is very popular, its challenge is that other external factors, such as economic downturns and policies, can significantly impact customer demand. Without considering them, you leave your supply chain exposed to numerous risks.
2. Regression Analysis
Every demand planning and forecasting analysis has the demand variable and any other independent variable. The regression analysis studies the relationship between the demand variable and at least one independent variable.
Some examples of independent variables are price, government policies, level of competition, and season. The regression analysis studies or determines the impact of these variables on the demand and can be used to predict future demands.
3. Delphi Method
This methodology entails collecting the opinion of experts in the product field and aggregating it to make demand forecasting or planning decisions.
4. Predictive Analysis and Machine Learning
This technique relies on collecting large and broad data and then feeding it to an algorithm for analysis and making predictions based on identified patterns, demand segmentation, and other patterns.
5. Market Surveys and Analysis
This method deals with the customer directly. It helps you collect data on customers’ preferences, challenges, and anticipated demands, giving you valuable insights into their state of mind.
How to Implement an Effective Demand Planning and Forecasting System in Your Supply Chain
To successfully implement a DPFS, you will need careful planning and execution. The following steps will guide you.
Step 1: Define the Goals and Objectives for Your Demand Planning and Forecasting System
Before implementing the system, identify the objectives and goals you want to achieve with the demand and forecasting system. Determine key metrics and outcomes you aim to improve, such as forecast accuracy, inventory optimization, or customer service levels.
Step 2: Identify Data Sources for Your Demand Planning and Forecasting System
Identify the relevant data sources you wish to rely on for your DPFS. This includes historical sales data, customer orders, market data, economic indicators, and other data sources that can provide insights into demand patterns.
These relevant data sources will feed into your demand and forecasting system.
Step 3: Select Forecasting Methodology for Your Demand Planning and Forecasting System
Common forecasting techniques include time series analysis, regression analysis, and the Delphi method. It would help if you considered combining techniques or methodologies for your supply chain to improve accuracy.
Choose the appropriate forecasting methodology based on your supply chain requirements and the nature of available data.
Step 4: Implement Forecasting Software in Your Demand Planning and Forecasting System
Invest in forecasting software or tools that align with your supply chain needs. These tools automate data analysis, forecasting calculations, and reporting, saving time and enhancing accuracy.
Choose a user-friendly system to integrate with your existing systems for seamless data flow.
Step 5: Set Forecasting Parameters in Your Demand Planning and Forecasting System
Configure the forecasting system by setting parameters such as time horizons, forecast intervals, and aggregation levels. Define the level of detail required for accurate forecasting, whether at the product, customer, or geographical level.
Step 6: Monitor and Review Your Demand Planning and Forecasting System
Continuously monitor and review the performance of the DPFS. Measure forecast accuracy, track forecast errors, and assess the impact of forecasts on key supply metrics. Regularly review and refine the forecasting model to adapt to changing market conditions.
Step 7: Continuous Improvement of Your Demand Planning and Forecasting System
DPFS require ongoing improvement and refinement. Incorporate feedback from users and stakeholders to drive continuous improvement in your forecasting process.
Stay updated on the latest forecasting techniques, industry trends, and technological advancements.
Frequently Asked Questions on Demand Planning and Forecasting System
1. What is the difference between Demand Planning and Demand Forecasting?
They are mostly similar but differ in that forecasting is predictive action while planning is corrective action taken to meet the demand.
2. What are Demand Planning tools in Supply Chain Management?
They are computer software and algorithms that help your supply chain plan, manage, and prepare for future customer demands and inventory, ensuring effective supply chain management.
3. What are the components of Demand Forecasting
There are generally six components. They are auto-correlation, random variation, average demand, trends, and seasonal and cyclical elements.
4. What are the Relevant KPIs of a Demand Planning and Forecasting System?
There are six of them. Forecast accuracy, forecast bias, mean absolute percentage error, weighted mean absolute percentage errors, inventory turnovers, and stock out rate.
Conclusion
Demand planning and forecasting systems are essential for the success of any modern supply chain. Conversely, implementing a robust DPFS would significantly benefit your supply chain. However, getting the most out of it is another matter, although they have been completely addressed in this article.
Obinabo Tochukwu Tabansi is a supply chain mastro and writer with a decade of experience working in different facets of the supply chain. Today he is living his passion for writing on all things supply chain. His blog, Supply Chain Nuggets, is Africa’s fastest-rising supply chain blog, helping professionals, business owners, and curious minds navigate the supply chain complexities on the continent.
