Demand Forecasting

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There are two ways of predicting future sales.

You can take your chances gazing through a crystal ball. Or you can use demand forecasting.

Demand forecasting is the process of predicting future sales by using historical sales data to estimate the amount of goods and services that customers are likely to require in the foreseeable future.

Due to the volatile nature of business, no one can claim 100% accuracy in forecasting future demand for products or services.

However, any organization that expects to turn a tidy profit cannot afford to rely on speculation or "guesstimates" -- especially if you are eyeing consistent growth.

5 steps in demand forecasting

Demand forecasting can only be effective when the process is conducted in a systematic and scientific process. To facilitate an efficient and methodical estimation of future demand for products and services, five basic steps should be observed:

1. Setting the objective

Demand forecasting necessitates clarity in objectives as this will set the direction for the entire research process. Managers should never lose sight of the main purpose of demand forecasting, which is to effectively predict what particular products or services are customers likely to purchase within a given time frame, when they would need these, and how much of these they will require within the predetermined period. In setting the objective, it is also necessary to identify which specific product/ service you want to focus on, then decide whether you will be forecasting customer demand for the entire market or just a particular section of consumers.

2. Determining the time period

Based on your objective, the demand can be forecasted to cover a short period (typically less than 12 months) or a long period (a year or more). Understandably, the determining factors of demand can be assumed to remain constant or not change significantly within a short period, as compared to a longer timeframe. The variables in the behavior of determinants have to be taken into account, which makes the definition of a time perspective critical to the research process.

3. Choosing a forecasting method

There are several methods that can be applied to demand forecasting, depending on the needs of the organization. Generally, these methods would fall under two categories: survey methods and statistical methods. As the name suggests, survey methods rely mainly on market research strategies such as customer surveys and consumer polls. On the other hand, statistical methods would include trend projection, barometric and econometric methods, which all rely on sales data and external economic factors.

From this variety of approaches, choose the one that best serves your specific purpose, timeframe, and data requirements. Selecting the most appropriate method will help ensure the accuracy and reliability of the resulting data.

4. Collecting the data

Available data is gathered and integrated to provide a cohesive view of the actual product demand. Using historical sales data and other information sources such as market conditions, you can forecast growth on a more granular level and look back to see how your previous forecasts compare to the actual year-end figures. Collected data can be classified as primary data (raw data collected from source or first-hand information) or secondary data (published data or processed information gathered in the past).

5. Estimating and interpreting the results

Once the requisite data has been gathered and processed using the forecasting method of choice, the final step is to arrive at the estimated demand for your particular products or services over your predetermined time period. Usually, these estimates will appear in the form of mathematical equations, which makes it necessary to interpret and present the figures in usable form that can be easily understood by whoever will be using the data, particularly the key decision makers.

To be consistent, you need a repeatable process of data analysis. Whether you continue to rely on manual methods or have upgraded to automated solutions, you should be able to compare the figures you projected against the actual sales, to serve as reference for your next forecast.

Factors that affect demand forecasting

Demand forecasting is a proactive process where the supply chain side of business aligns with the sales and marketing groups in determining what products will be needed where, when, in what quantities. This process is typically influenced by several factors that affect demand forecasting.

  • Seasonal trends - Volumes of orders are likely to change over a specific period of time, as people either increase or decrease their demand for certain products or services as affected by a specific period, event, or season.
  • Competition - Demand is affected when the customers have more options to choose from, especially if your organization belongs to a highly competitive industry.
  • Types of goods - The type of goods or services you offer plays an important factor in demand forecasting as they are subject to different conditions, whether they are perishable goods (like fresh produce, for instance), consumer goods, or professional services. Aside from these classifications, goods are also grouped into "established goods" (or those already in the market) or "new goods" which are yet to be introduced. To help in predicting the demand for different types of goods, it is necessary to tap into historical data and know the total purchases your customers have bought from you over time, how much they were spending each time, and the combinations of products they’ve ordered.
  • Economic factors - Changes in pricing policies greatly affect demand forecasts, as does the prevailing business climate. For instance, an economic uptrend or increase in investment would likely yield positive demand forecasts, while an economic slowdown or a downtrend in a particular industry would have the opposite effect.
  • Geography - Where your customers reside and the location of where you manufacture and shop orders determine your inventory management and the speed of delivery. Geography is vital to strategic supply chain management. For professional services that can be fulfilled remotely, however, this is less of a concern.
  • Level of Technology - Are your goods or services "future-proof" or are they susceptible to rapid changes in technology and are at risk of obsolescence? Being aware of new or upcoming trends in technology and services will keep you of the game by anticipating how much of your products will still be needed as you work out future demands.
  • Time Period - Determining the time period covered by the research is crucial to demand planning as variables change when you are doing projections for a short term, a long term, or a very long term. Your time period defines what you determine as your "foreseeable future" so it impacts your predictions to a large extent

6 types of demand forecasting

There are different ways to organize demand forecasting based on the time period, scope, and capacity of your market. Expert opinions lean towards using multiple demand forecasts as one of the best practices for obtaining better quality of data and a more comprehensive insight into your future sales.

The six major types of demand forecasting are:

1. Passive demand forecasting

Passive demand forecasting is ideal for stable businesses with conservative growth plans, particularly small and local businesses. It simply extrapolates historical sales data in order to project future demands. Passive forecasting will work well only if you have solid sales data to work on. While it is easier to use than other types, this approach assumes that the demands of the current year will be approximately the same as the year before, which we know is no longer feasible as the market continues to be affected by many unforeseen forces. Last year’s passive forecasting users would not have been able to accurately forecast this year’s losses due to the COVID-19 pandemic.

2. Active demand forecasting

Highly recommended for start-ups or for organizations that are diversifying and have aggressive expansion plans, active forecasting focuses on externals and is a good choice for businesses that don’t have a lot of historical data to draw on. Active demand forecasting puts into play your company’s marketing research, marketing campaigns, product portfolio expansion, growth projections from your market sector, economic trends, as well what your competitors have been up to.

3. Short-term projections

Short-term projects are usually carried out in a period of the next three to 12 months and allows you to adjust your projections quickly if there are changes in demand based on real time sales trends.

4. Medium to long-term projections

A medium to long-term forecast can span anywhere from one year to several years into the future. Among the forecasting models, this is most effective for organizations that are trying to create a roadmap for their growth trajectory. Long-term forecasting is aspirational and can be used to drive strategic planning, sales and marketing, financial planning, capital investments, supply chain operations, and other considerations for business growth based on future demand.

5. External macro-level forecasting

External macro-level forecasting looks at how broader economic trends are likely to affect your business goals and provides insights on how to deal with them. For professional services in particular, external macro-level forecasting helps evaluate the strategic objectives of a business in areas that affect product portfolio expansion, expanding to or entering new markets, changes in consumer behavior, disruptions in technology, risk management and mitigation, and so on.

6. Internal business forecasting

This forecasting type deals with internal operations and is used to identify the factors that could be hindering your business from realizing its full growth potential. It can also reveal areas of opportunity that can be maximized to support your expansion plans. In making projections, internal forecasting will include items such as cash flow, profit margins, annual sales forecast, business financing, supply chain operations, and resources.

Stay on top of demand

Seeing how crucial demand forecasting is to growing your business, it pays to look into the advantages of implementing an agile and dynamic resource management and planning software that can help take much of the forecasting guesswork out, and yield sound business data and insights you can rely on.

If you want a holistic and comprehensive approach to demand forecasting, check out Mavenlink’s Full Cycle Resource Management Solution, which enables full cycle resource management with all the forecasting tools, insights and granular control you need for predictable business growth.

With its robust forecasting capabilities, Mavenlink combines sales pipeline and backlog with active projects to help your business make informed and confident decisions for today and the foreseeable future. With resource-centric insights and powerful reporting, you get the real-time data you need for making faster decisions and getting better results – all in one spot.

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