How to calculate market forecast and why is it important in strategic business decision
Demand forecasting is the act of developing models that help estimate future customer demand for specific items over a set period of time by utilising historical data and other analytical information. It also helps with the formulation of product roadmaps, inventory production, and inventory allocation.
Demand forecasting is a rigorous process for estimating how much of a specific product will be in demand in the future. Simply put, it allows you to precisely anticipate sales for the coming weeks, months, or even years, ensuring that you always know how much inventory to order and maintain on hand.
There are several methods for accomplishing this, ranging from human calculations to automated inventory forecasting tools, but inventory forecasting is primarily a combination of market knowledge and data from recent sales.
Types of demand forecasting
Demand forecasting can be done in a variety of ways, and your forecast may alter depending on whatever forecasting model you employ. The best way is to do many demand predictions to obtain a more thorough view of your prospective sales. Here are the several types of demand forecasting.
Active forecasting
This sort of demand forecasting is ideal if your firm is new or expanding. An active demand forecasting model considers your expansion strategies, market research, and advertising campaigns. It also considers external variables such as the status of the economy, growth projections for your industry, and anticipated cost savings from improved supply chain effectiveness.
Passive forecasting
Passive demand forecasting makes use of existing sales data to predict future demand. It's a plan that assumes this year's sales will be roughly equivalent to the prior one. Because it does not need the use of statistical tools or the examination of economic trends, this sort of demand forecasting is simpler than others. This is an effective strategy for firms that choose stability over growth.
Internal forecasting
This sort of demand forecasting studies your operations to discover potential hurdles to growth or to highlight the company's untapped potential. Internal business demand forecasting considers your company's funding, available cash, profit margins, supply chain operations, and workers.
External forecasting
External demand forecasting takes into account broader economic trends and how they may affect your company's aims. In addition, this type of forecasting can provide guidance on how to attain your objectives. It may also contain aspects that have a direct impact on your supply chain, such as raw material availability.
Long-term forecasts
The purpose of this demand forecasting model is to affect your company's growth trajectory by generating projections one to four years ahead, based in part on sales data and market analysis. This forecasting method can help you organise your supply chain operations, capital investments, and marketing strategy to prepare for prospective demand.
Short-term forecasts
Short-term estimates focus on the next three to twelve months. Looking at short-term demand allows you to update your predictions using current sales data and respond quickly to changes in client demand. Understanding short-term demand is useful if you manage a product line that frequently changes, but for most businesses, it is just one component of a larger picture.
Forecasting methods
There are numerous ways of demand forecasting, which can be categorised into two categories: quantitative and qualitative.
Quantitative forecasting methods
Quantitative demand forecasting is based on previously collected data on consumer demand, seasonal demand, supply chain efficiency, and other data-driven parameters.
- The most popular quantitative forecasting methodology is trend projection. The trend projection approach uses previous data to provide a sales forecast. Although this can provide an accurate demand estimate for the near future, relying entirely on sales history without considering other factors may not be prudent, particularly if you need to establish a long-term demand strategy for your supply chain.
- Barometric forecasting: this form of demand forecasting uses current data to anticipate future demand. It forecasts demand by statistical analysis.
- Econometric forecasting. This methodology creates a demand plan by combining demand data with knowledge of external factors that can influence demand. Compared to other methods, econometric forecasting requires more complex statistical forecasting methodologies, but it has the potential to deliver more accurate demand estimates.
- Exponential smoothing. This demand forecasting method combines seasonal sales changes into the result while also utilising previous data as input. Because demand planning with exponential smoothing is based on a small dataset, it might be a useful quantitative tool for startups and new firms.
Qualitative forecasting methodologies
Qualitative forecasting methods rely less on data and more on human input. A qualitative forecasting system uses both your company's internal and external data sources. The following are some of the most prevalent methodologies for qualitative demand forecasting.
- Salesforce composite: This approach of demand forecasting brings together sales team members, supply chain managers, and other demand forecasting stakeholders. The salespeople rely on their experience and take the lead in sales forecasting.
- The Delphi method: The Delphi methodology, also known as the expert method, includes a demand planner gathering a group of subject matter experts and soliciting their feedback on a series of prospective demand-related topics. The planner then develops a summary based on the responses and presents it to the panel. The experts reword the questions based on the summary of the first round of responses. The demand planner repeats this approach until the expert panel finds a consensus.
- Trend and opportunity research: This forecasting method makes a demand projection based on market trends and opportunities. When forecasting the market, consider plans for promotion and expansion, as well as facts on the supply chain's capacity and limits. Startups without the historical data required for sales forecasting can benefit from it.
Both quantitative and qualitative methodologies have their advantages and disadvantages. For an astute demand forecaster, a combination of both may be the best solution.
Author's Detail:
Nisha Deore /
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I am a well-organized, conscientious, and professional Research Analyst with two plus years of experience. In my current role, I conduct in-depth secondary research, data mining, competitive analysis, DRO's, PR, and Collateral writing. Whilst I enjoy working as part of a team, researching information, analyzing data, and producing results that help my organization to achieve its commercial and financial objectives.
I am committed to continuous professional development, regularly engaging in workshops, seminars, and staying attuned to the latest industry trends. This commitment reflects my dedication to providing cutting-edge insights and staying ahead in the ever-evolving field of research. I led research initiatives aimed at uncovering market opportunities and enhancing competitive positioning. My responsibilities spanned the entire research lifecycle, from designing methodologies to presenting findings. Through collaborative efforts, I facilitated data-driven decision-making processes that contributed to the overall success of key projects.
