Introduction to Sales Forecasting

What is sales forecasting?

Involves projecting achievable sales revenue, based on historical sales data, analysis of market surveys and trends, and salespersons' estimates.

Sales forecasting methods can be catergorised into what 2 factors?

1. Quantitative techniques

2. Qualitative techniques

What are quantitative sales forecasting techniques?

Quantitative forecasting methods are used when there is historical data available. A number of different models can be used to forecast future events and predict likely revenue. Quantitative methods rely heavily on data and are objective. These methods include:

• time series analysis

• use of market research data.

What is extrapolation?

• Involves using past experience or past business data to forecast future sales.

• Extrapolation involves making statistical forecasts by using historical trends that are projected for a specified period of time into the future. It is only used for time-series forecasts.

What are qualitative sales forecasting techniques?

Qualitative forecasting methods are used when historical data is not available to carry out quantitative methods. Qualitative methods involve the use of opinions to predict future events and are subjective. These methods include:

• the Delphi technique

• brainstorming

• intuition

• expert opinion.

What are the benefits of sales forecasting?

• Financial planning: business can estimate future revenue, plan cash flow, help set budgets etc.

• Businesses can organise staffing levels and create HR plans for when demand increases / decreases.

• Businesses can plan the required level of production in order to meet demand.

What are the difficulties involved with sales forecasting?

• Sales forecasting usually involves the use of past data to predict the future.

• In the short-term, sales forecasts are likely to reflect the recent past.

• Longer-term sales forecasting is often more problematic as several factors affect its reliability.

• Effective sales forecasting requires skill, time and the accurate use of timely data

  • Smaller businesses in particular may lack the experience or specialised personnel to construct, analyse and interpret sales forecasts

    • It is difficult to avoid experience bias (e.g. opinions of the future based on experiences in the past) 

    • Businesses may face problems in constructing sales forecasts that ignore the priorities of key stakeholders
      
      

• The future seldom repeats the occurrences of the past

  • Sales forecasts will rarely reflect the full range of external influences that can affect future inflows such as fashions, trends, the actions of competitors 
    
    

• There is a significant amount of data available for businesses to consider when constructing sales forecasts

  • Internal data such as previous sales figures will be a key source of information when constructing forecasts

  • Selecting the most appropriate external data to support sales forecasts is extremely challenging and will require careful evaluation

State some circumstances where the sales forecast is likely to be inaccurate.

• Business is new – a startup (notoriously difficult to forecast sales)

• Market subject to significant disruption from technological change

• Demand is highly sensitive to changes in price and income (elasticity)

• Product is a fashion item

• Significant changes in market share (e.g. new market entrants)

• Management have demonstrated poor sales forecasting ability in the past