Struggling with inaccurate forecasts, stockouts, or overstocking, and costly working capital? In today’s unstable world economy, companies constantly fight to find the perfect balance of supply and demand. That is where demand planning can be a rescuer. With the building of information, analysis, and strategic skills, demand planning allows companies to anticipate customer needs better, optimise supply chain management, and steer clear of inefficient and costly pitfalls.
Moreover, research has indicated that firms employing sophisticated demand planning solutions can decrease inventory expenses by 20% and boost revenue by 10%. Furthermore, efficient demand planning optimises service levels, decreases waste, and enables executives to be more responsive to fluctuations in the marketplace.
This article provides a complete guide to demand planning, outlining its key components, benefits, and how organizations can leverage it to optimize their supply chains. So, let us begin!
What is Demand Planning?
Demand planning is one of the key functions of supply chain management. Its objective is to obtain a balanced inventory, whereby product supply equals customer demand precisely without overstocking. Demand planning techniques are the basis for all other supply chain operations, such as procurement, production, order fulfilment, and distribution.
Demand planning for an Australian retailer means investigating previous sales, considering consumers’ seasonal buying habits, and monitoring promotion activity to forecast future demand precisely.
Why is Demand Planning Important?
Demand planning is crucial because it is necessary for operational efficiency and bottom-line results. It addresses the dual issues of stockouts and overstocking in the following ways:
Stockout Prevention
If a product is out of stock, the sale is lost, and customers become dissatisfied. In Australia, where online sales remain increasing, a single stockout can lead customers to switch permanently to the competition. Demand planning keeps products available, protecting revenue and customer loyalty while reducing the risk of poor delivery lead times.
Prevention of Overstocking
The cost of holding inventory, insurance, and possible obsolescence can be a considerable burden. For instance, the average cost of holding inventory in Australia can be as high as 20% to 30% of its value annually. Good demand planning, supply planning, and stock control minimize this risk, releasing capital for other business opportunities.
Through the optimal management of this balance, demand and supply planning optimise profit and enhance market position.
Key Components of Demand Planning
A sound process for demand planning is constructed from a few interrelated and dynamic components that collaborate to develop a good forecast. These include:
Data Collection and Analysis
The cornerstone of any sound forecast is quality data. It involves aggregating detailed data sets, not only the ones that are internally sourced, such as historical sales, product lifecycles, and marketing plans, but also externally sourced, like market trends, economic indicators, and rival moves. To manage this large amount of data, they apply complex data modeling and analytics, which help them find the small patterns and correlations that are very important to the forecast. This thorough examination changes the basic data into measurable insight.
Forecasting in Demand Planning
Forecasting is the quantitative process whereby the information that has been gathered is utilised to forecast demand in the future. Here, many demand planning methods, from simple statistical methodologies such as moving averages to sophisticated statistical models, enter into action. To a company anticipating the summer months, a forecast model could look at historical sales of refrigerating goods, correlate this with weather conditions, and estimate the precise peak demand for products like bottled water and sunscreen. The quality of the technique used will depend on the type of product and data quality.
Inventory Management Strategies
After forecasting demand, inventory control is the second step. This entails establishing optimum inventory levels, e.g., safety stock, a buffer for increased unpredicted demand, or a supply chain breakdown. The general aim is to harmonize demand planning and inventory control so that products are available at the time required with as low a holding cost as possible. This entails establishing definite reorder levels and using just-in-time inventory systems wherever feasible. This can also include aligning with suitable packaging boxes and logistics practices to reduce waste and costs.
Supply Chain Synchronisation
Demand planning does not occur in isolation; it must be synchronised throughout the supply chain. More specifically, the departments at the organization’s helm, such as sales, marketing, production, and logistics, must communicate effectively and openly to reach that kind of synchronization. A typical demand plan is the foundation for all departments to be on the same page, hence, a more coordinated and efficient supply chain. Such cooperation leads to fewer disputes, eliminating choke points, and the assurance that the whole company is moving forward to the same target at the same pace. This includes streamlining warehouse logistics for efficiency.
Demand Planning Methods and Techniques
Demand planning methods have traditionally been classed as quantitative and qualitative methods.
Quantitative methods use past data and mathematical models to make their projections. These techniques, like time-series and regression analyses, are best used with products with stable sales histories.
Qualitative methods rely on expert opinion and market awareness. They are best applied in new product launches or where historical data is unavailable.
Demand planning techniques vary depending on the product type, market, and data availability.
Demand Planning vs. Supply Planning
While occasionally they are mentioned together, demand planning and supply planning are different processes. The following table highlights the key differences between the two methods:
| Aspect | Demand Planning | Supply Planning |
| Primary Focus | Planning what customers are going to buy and when. | Deciding how to fulfill that demand. |
| Objective | Develop a credible estimate of future customer needs. | Have the correct products in supply at the correct time. |
| Key Activities | Data analysis, statistical forecasting, market research, and collaboration with sales and marketing teams. | Production scheduling, raw material buying, inventory control, and logistics planning. |
| Key Question | “What do we think our customers will want?” | “How do we make and get the product out to satisfy that demand?” |
| Role | The starting point for the entire supply chain. | An execution-based plan to satisfy the forecasted demand. |
| Risk Mitigation | Tackles the risk of over-forecasting or under-forecasting what the customers will require. | Manages threats such as production shutdown, material scarcity, and distribution bottlenecks. |
Effective planning can also reduce reliance on a single central distribution centre, spreading stock across multiple hubs for resilience.
Demand Planning Software
The sophistication of today’s global supply chains makes strong demand planning software desirable and necessary. Strong demand planning software is light-years ahead of simple spreadsheet calculations, automating data analysis, executing advanced forecasting algorithms, and giving stakeholders a single source of truth. The latest demand and supply planning software impacts forecast accuracy and business performance.
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Studies have proven that forecasting through AI lowers forecast errors by 50%, resulting in considerable cost reduction in operations and inventories. These organizations also save 10-15% or even higher holding costs for inventories, which frees up capital and increases profitability. Such software packages play a significant role in introducing competitiveness with data-based, quick decision-making.
Explore more of iSend’s features to see how it helps retailers optimise their supply chains.
Demand Planning Methodology
There has to be a well-defined demand planning process to provide consistency and accuracy within the company. Although the particulars may be different, the overall demand planning methodology typically includes several steps that are defined below:
Data Consolidation
Step one is gathering and cleaning data from internal systems (such as ERPs and CRMs) and external sources (such as market data and economic reports) to obtain a consolidated data set.
Initial Forecast Development
An initial statistical forecast is generated using total data and a demand planning tool. It depicts a starting point for the planning process.
Coordinated Replenishment
Stakeholders from sales, marketing, finance, and operations review and approve the initial forecast. They also implement the qualitative feedback, which depends on their market knowledge, future promotions, and strategic plans, and use it to adjust the estimations accordingly.
Consensus Finalisation
The forecast that will be finalized is the one created by departments jointly. Being consensus-based guarantees that every party is working under one plan and is loyal to it; thus, the potential for departmental differences is eliminated.
Performance Feedback
The process does not stop once the plan is completed. Planners monitor closely forecast-to-actual sales to discover any variations and determine the reason for the variance, making continuous improvement possible.
This iterative and collaborative process guarantees not only that the forecast is data-driven but also that it is strategically motivated and broadly accepted.
Future of Demand Planning
Disruptive technologies such as machine learning (ML) and artificial intelligence (AI) are shaping the future of demand planning. The demand and supply planning software can manage enormous and complex data sets, such as unstructured weather, news feeds, and social media sentiment data, to accurately predict demand like never before.
For instance, McKinsey & Company states that companies adopting AI within their supply chains have streamlined their inventories significantly, reducing them by as much as 35% in some cases. This is testimony to AI’s significant potential to streamline inventory, releasing capital that would otherwise be tied up in stagnant stock.
How iSend Supports Demand and Supply Planning
iSend is a top cloud-based demand planning software provider supporting end-to-end supply chain process streamlining. The solution provides an all-inclusive suite of tools that support organisations in making data-driven decisions.
Automated Forecasting
Harnessing powerful AI and ML capabilities, iSend’s demand planning methodology makes precise predictions, reducing the manual work planners need to do and thus giving them time for strategic thinking.
Improved Collaboration
The combined platform is an integrated source of truth where all departments can talk and agree in real time, from sales to production, accounting, and marketing.
Inventory Optimisation
iSend allows companies to hold stock at its best by connecting the demand plan directly to stock management.
By utilising iSend demand and supply planning software, companies can shift demand planning from a highly time-consuming and manual process into a growth driver and an efficiency-based strategy.
Conclusion
Demand planning is a crucial and constantly changing science for companies today. When a company has a clearly defined demand planning process, good tools for demand planning, and truly cross-functional relationships, it can build a strong supply chain that is also customer-focused. The demand and supply planning process is, however, not just an option anymore; it is a must to deal with today’s volatile markets and maintain sustainable growth in the long run.
