Vanguard Blogs
FinanceMay 04, 2021

Steps to Better Demand Forecast Accuracy

By: CCH® Tagetik

Read this blog to discover the seven steps to improve demand forecast accuracy for increased operational efficiency and profit.

There is no crystal ball that can allow planners to perfectly predict product demand by giving insight on everything happening in the market. However, there are quite a few ways to improve demand forecast accuracy. 

Here are seven ways to improve demand forecast accuracy for increased operational efficiency and profit

Question and Communicate Assumptions

The first step in the forecast process is to determine assumptions, or starting values. Take care to derive these values statistically, analyze them, and communicate them; they are the basis of your forecast quality. Communicating them to team members provides context for generating the initial forecasting model. 

Some basic assumptions might include: 

  • Number of buyers in the target market
  • Percentage of consumers in the target market that will purchase 
  • The timing of their purchase, taking economic cycles and holidays or seasonal events into account
  • Pattern or frequency of repeat or replacement purchases 

It’s important to leverage the collective knowledge and expertise of the various teams involved to validate these assumptions before you start the forecasting process.

Use a granular model 

Your forecasting models, especially those used for predicting short-term demand, need to be detailed and granular. 

A granular model can inform: 

  • When customers will make a purchase 
  • The different purchasing behaviors exhibited by markets in different locations 
  • The optimal price point to help maximize revenue
     

Keep in mind that even though a high-level or aggregated demand plan is easier to create, and in some cases helpful, it may not have sufficient granular detail to address consumer behaviors or purchasing patterns. 

For example, a car manufacturer may be able to predict accurately the number of SUVs they sell in a year. However, if the demand planning team does not take into account regional preferences, the company may fail to produce the correct number of models in the sub-SKU level and distribute them to the right locations. 

Produce a range of forecasts

It is also possible to achieve a broader perspective for demand plans by producing a range of forecasts that can be re-calculated frequently to reflect market conditions, changing assumptions, and probabilities. 

Besides historical data, the demand sensing approach enables a more accurate, daily demand plan for the short-term horizon (4-6 weeks) so planners can respond quickly to immediate changes on both the supply and demand side. 

A Range of forecast models can be easily generated by using an AI-based, cloud-native platform, such as CCH® Tagetik Supply Chain Planning, that pulls in real-time data into pre-determined models. With Vanguard, planners can create forecasts to share with all relevant departments within an organization through customized dashboard and reports.

Minimize delays

Delays happen when market demands are not reflected in the supply chain with minimal lapse time and they can severely impact the demand forecast accuracy. To minimize the impact of such delays, use fully integrated supply and demand forecasting models to increase adaptability and operational efficiency. 

These models should preclude delay and shorten the renewal cycle by allowing planners to compare stock across all locations and generate a detailed replenishment report for each product. Such reports help prevent stock-outs from occurring, especially during new product launches and global disruptions. 

An integrated demand-supply planning process also gives businesses the opportunity to respond to market trends in a nimble manner (for which some fast fashion retailers such as Zara, Topshop, H&M, etc. are well-known for), which wouldn’t be possible without the software and technologies that utilize connected data to make short lead times possible.

Employ a variety of forecasting methods

While the most common and essential models are based on purchasing intentions, there are other models that can be used to consider different angles and perspectives. 

By applying different forecasting methods to different phases of a product life cycle, planners are able to leverage the most appropriate historical data and market knowledge. The key is to choose the most effective and flexible models for your market, blend their best features, and shift between them to generate the most accurate forecast. 

For example, historical demand is a great starting point for forecasting mature products with plenty of history. But for new products with little or no history, consider advanced techniques such as comparable forecasting to make use of historical data from similar products. 

Continuously check forecasts

Regular checks on actual sales against forecasts based on quantitative and qualitative data should be performed as soon as data becomes available. Use any discrepancies to fine-tune future forecasts to ensure that they are grounded in real market conditions. 

These reality checks should also involve assessing competitors’ sales and performance in the market. If entering an emerging market, also consider how your market share will be impacted as competitors enter the space and the market expands. 

Conduct these reality checks regularly and more frequently for a newly launched product or under rapidly changing market conditions. Monitor sales and qualitative feedback diligently and re-forecast whenever necessary. 

Improve planning with integrated supply-demand forecasting ontinuously check forecasts

Accurate forecasting is fundamental to supply chain management, as well as to sales and operations planning for the entire organization. Improve demand forecast accuracy by employing different models and drawing data from a variety of sources. The faster data is pulled and shared within an organization, the more valuable the information will be for everyone involved. 

This can be done effectively by using software such as CCH® Tagetik Supply Chain Planning. Our application allows demand and procurement teams to model and integrate data, forecast, collaborate, and report to maximize the impact of critical information and knowledge. CCH® Tagetik integrates supply chain management and demand planning so planners can immediately share any update and prediction with all aspects of business to ensure the organization is equipped to respond to the market in a nimble manner, increasing profitability and the operational efficiency of the entire organization.

For further reading, download our case study on Fountain Tire to learn how they improved their forecast accuracy by 15% with CCH® Tagetik.

 

CCH® Tagetik
TAA - CCH® Tagetik

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