In today’s business scenario, different business decisions are aimed at satisfying various needs and desires of society by determining future demand. Also, there is a necessity for the right decision-making in a dynamic and competitive market. These are only possible if the right planning is done for business activities and decisions are taken based on the accuracy of future demand. So, demand is considered an important element to fulfill business goals. Optimum utilization of available resources to meet such demands is only possible once the proper understanding of the demand is there and it is predicted with the required accuracy level.
So, we can say that to initiate any business activity, prediction, or forecasting of the demand (demand forecasting) is considered the first stage and further, plans are made to meet the demand. This demand forecasting acts as an input for other business activities such as production planning, manpower planning, capacity planning, and overall planning, etc.
Meaning and Definition
A process of estimating or predicting future demand through past and present events is considered Forecasting. Information on potential future events and their effect on the business can be obtained from forecasting. Though forecasting may not reduce future uncertainty and complexities, still, management becomes confident to make any important futuristic decisions. In other words, forecasting is both a decision-making and planning tool because, through its support, businesses can examine historical data and thus, they can deal with the effect of uncertainty of future; also, businesses can plan their further actions and make budgets to cover such uncertainties that may occur in the future.
1. As per Heizer and Render (2010), “Forecasting is considered art and science of estimating future events”. It is defined as an art because to improve the correctness of forecasts, it is required to have subjective assessment along with a contemporary and historical judgment. It is also considered a science because lots of scientific methods are used to have different numbers and further analysis is done through mathematical models to determine the correctness of the forecast.
2. According to Louis Allen, forecasting is considered “a systematic attempt to probing the future through inference from facts that are already known”.
Example of Forecasting
One simple example of forecasting can be when a manufacturer does forecasting to decide the appropriate time to purchase raw material for producing goods in the future. There are two choices in front of the manufacturer i.e. either to buy raw material and store it in its inventory or stock to use later or to postpone the purchasing of raw material till future production. In this, inventory costs are stable and already known and the issue of forecasting is related to the forecasting of raw material cost in the future.
In other words, if the future cost forecast of raw material is much higher than its current cost, then it is feasible to buy the stock of raw material to store it as an inventory for future use. On the other hand, if the forecast cost is less than or equal to the current cost of raw material, then to buy the raw material later is more feasible.
The Strategic Importance of Forecasting
From a strategy perspective, the importance of forecasting is very high for any type of business because of the essence of having inventory (material or final product) at the right place and the right time for earning profits. The purchase of raw material in the right amount is required for producing goods for customers in the right quantity. In absence of the forecasting, the situation of less or high inventory may occur that will create an adverse effect on the business in terms of the extra cost or inability to meet the demand of customers.
So, it’s really important for organizations to understand the importance of forecasting as the presence of the right resources within the right timeframe is required for the effective functioning of business processes. Also, forecasting is considered one of the great sources to save cost in business as it helps in predicting future demand and to manage available resources accordingly. If forecasting is not done properly, then it may result in a huge loss.
Forecasting is used in all large organizations i.e. both in the manufacturing and service sectors for strategy formulation. Until the actual demand is not known, the forecast is the only way to predict demand. So, lots of business areas depend on the forecast to make decisions.
Below three main activities of an organization are influenced by the forecast:
Supply Chain Management
All those activities that allow the right kind of product at the right price and the right place are termed as supply chain management. So, it is required to carry on-demand forecasting in a careful manner in order to identify choices in pricing, vendors, material alternates. The proper demand forecasting provides the privilege to plan logistics, suppliers, and other beneficiaries or mediators. This also ensures product delivery in a timely manner. So, an accurate forecast decides the market speed, good relations with suppliers, and the advantages in cost, product, etc.
Below are a few examples of different organizations that do forecasting for effective supply chain management:
Apple Inc., a U.S.-based multinational technology company has developed an effective and efficient global system through which it is easy to control mostly all aspects of the supply chain i.e. from designing products to retail stores. Apple is able to enhance innovations, reduce the inventory cost, and improve the market speed through effective communication and accurate data which is shared both upwards and downwards in the supply chain system. Production forecasts are adjusted on daily basis during the product is in the market for sale. The same is done by tracking the demand of each store on an hourly basis. So, forecasts are considered a strategic weapon in a technology giant like Apple.
Toyota which is a multinational automotive manufacturing company forecasts sophisticated cars by taking input from different sources. Their dealers are also part of such sources for obtaining inputs. On the other hand, it is difficult to forecast the demand related to accessories like custom wheels, navigation systems, etc. because it contains more than 1000 items and that too vary according to color and model.
So, Toyota reviews the available data of vehicles that have been manufactured and also, considers vehicle forecasts in detail to decide the demand for a future accessory. The accurate forecast results in an effective supply chain for the company.
Human Resources (HR)
A process, through which an organization estimates the future requirement of human resource or manpower in the right number and right quality, is termed as HR demand forecasting. Different HR functions such as hiring, training, promotions, transfer, lay-offs, etc. are based on future demand.
For example, a restaurant is required to do staff forecasting as it has to meet the anticipated demand for bookings, late-night big parties, bookings during festival seasons, and other arrangements at night when a couple of diners look for reservations. To meet this, the restaurant manager forecasts the requirement for the bar staff, kitchen staff, and waitstaff.
Capacity from an organizational point of view refers to all those elements such as physical resources, ideas, people, etc. that an organization requires fulfilling its mission and to meet the demand. In other words, an organization’s ability to fulfill the demand with regard to resources and the readiness on its part is termed as capacity. In the case of well recognized and increasing pattern of demand, capacity enhances. Wherein, if the demand pattern decreases, then it indicates a downfall in the capacity as well. Inadequate capacity results in shortages and may lead to loss of both market share and customers. So, demand forecasting is necessary for making decisions of lag capacity (capacity enhancement only in case of 100% capacity due to the rise of demand) and lead capacity (adding or subtracting capacity according to the future market demand).
Benefits of Forecasting
Forecasting facilitates reducing the demand related uncertainty by providing a practical workable solution. Below are the major benefits that forecasting offers:
Inventory or Material Management
Predicting demand or orders of products may lead to achieving an optimum level of inventories by reducing the shortage or surplus inventory of both raw material and finished goods. Through forecasting, manufacturing organizations can get clarity of situations related to supply and this further helps them in evaluating the customer demand level in more accurate form according to the volume of components required to fill orders in a successful way. The reduction in inventory results in reducing warehousing and helps organizations smooth their operations by removing losses that are costly by reducing the time in which the unused inventory is kept in the warehouse.
Improve Employee Relations
Forecasting promotes active participation and coordination of staff members in the process of forecasting. So, it initiates better employee relations through teamwork and unity. Different data and information is required in forecasting from various internal and external sources and employees at different levels collect such information through different resources. This demands all verticals and functions of an organization to participate in the forecasting process and thus, allowing improved coordination and communication between employees.
Better Utilization of Available Resources
Using forecasting, organizations ensure optimum utilization of their available resources such as capital, manpower, material, and other resources by identifying the weak areas and giving required information related to the future. This helps the management of the organization to focus on and control critical areas.
Improve Customer Satisfaction
Better customer service leads to customer satisfaction which demands offering customers the right products/ services in the right quantity and at the right time. Using forecasting to enhance, refine, and streamline different functions of an organization such as operations, logistics, and production; helps in increasing customer satisfaction level.
Cost Implications of Forecasting
Special efforts and the opinion of experts are required in forecasting which involves a lot of costs that an organization has to bear. Both in-house and external forecasting demands appropriate investments. So, we can say that cost of forecasting is directly proportionate with forecasting efforts i.e. more forecasting efforts mean more cost involved in forecasting. Due to better judgment and improved accuracy, there can be a decrease in losses that may result from poor forecasting as more efforts are there in forecasting. So, if the efforts are high then the losses will be less. Forecasting cost gets high with the rise of forecasting efforts because the effort is considered the function of forecasting. Cost implications of the forecast can be represented graphically as per the below diagram:
In the above diagram, it is compulsory to increase the forecasting effort in order to maintain the total cost of forecasting at a minimum level. The acceptable level of raising forecasting effort is the one where it is acceptable to have certain uncertainty and so, the organization can be ready to bear some possible losses.
Wherein, there is no point to increase the forecasting effort for improving the forecasting accuracy as forecasts are influenced by some unknown unpredictable parameters and market dynamics that may not be controllable.
Forecasting as a Decision-making Tool
Forecasting has a major role to play in the decision-making process as it helps in improving its efficiency. Different demand forecasting techniques such as qualitative and quantitative are used by organizations to estimate the demand for their products in the future and decisions are made accordingly.
There is always an uncertainty level exit in forecasting due to the dynamic environment and so, improving the accuracy of the forecast will increase the cost of forecast rather than accuracy. Due to this, decision-makers make decisions by following the below rule:
By keeping in the view of uncertainty and allowance, it is required to include two aspects in forecast output i.e. estimation of demand in the best way and error estimation to creep in the forecast. Though it is difficult to calculate the scope of error, still, it becomes easy to calculate if decision-makers are aware of the actual demand. So, we can say, that the error forecast is:
Classification of Forecasting Process
The methods of forecasting can be classified as per the below categories:
A) Based on Database Type
There are two categories in this i.e.
Quantitative or Statistical Forecasting
These methods include a more scientific approach and historical data. It uses mathematical tools or models for processing the information. Qualitative methods provide an estimation of future demand by using numerical tools and previous effects. These are objective in nature and dependability on mathematical calculations is quite high in this method.
Qualitative or Subjective Forecasting
These methods depend highly on observation, opinion, and listening skills. In other words, qualitative forecasting includes factors that are more subjective, opinion-oriented.
B) Based on Forecast Time Horizon
This includes a short time frame and is based on the nature and type of the industry. Short-term forecasting is usually done for a period of six months and up to one year. In most cases, this type of forecasting is utilized in tactical decisions and day-to-day planning processes related to production, workforce applicability, inventory, etc.
This forecast includes a time frame of one year to three years and is useful in cash budget planning, layout planning, capital budget planning, production planning, sales & marketing planning, etc.
This forecast is done for a longer duration and generally covers a time horizon of more than three years. It facilitates long-term strategic planning decisions related to expansion planning of plant, capacity planning while opening a new manufacturing unit, etc.
C) Based on the Economy
Forecasting at Macro-level
This includes general economic environment forecasting of a country’s economy and is focused on business conditions across a nation’s whole economy. This is measured by the national income or expenses, industrial production, general employment level, etc.
Forecasting at Industry-level
This is concerned with the overall demand for the products of a whole industry and includes analyzing statistical trends. Trade associations prepare an industry-level forecast. Forecasting cement and cloth demand of a country are a few examples of this forecast method.
Forecasting at Firm-level
This covers the demand forecasting of the products of a specific firm. Few examples include forecasting the demand for Asian paints, Amul milk, etc.
D) Based on the Methodology
Statistical methods can be used at the time of conducting a forecast for an existing product as past statistical data is available in existing products. These include:
This is useful when the historical data of a product or product line for past years are available and there is a clarity of trends and relationships of different variables.
Quantitative or Casual Methods
These methods of forecasting include the assumption that the variable of forecasting is connected with non-dependent/ independent variable(s) through a cause-effect relationship.
Predictive or Qualitative Methods
In case of non-availability of any statistical data, qualitative methods that are based on opinion may be considered.
Both Quantitative and Qualitative methods of forecasting are further divided into the below methods:
We’ve thoroughly explained forecasting methods with examples in a separate article here:
Forecasting and Product Life Cycle (PLC)
There is always a fluctuation in the product demand once it goes through various life cycle stages. Starting with zero value, the demand increases with the movement of the product at each stage of its life cycle. Once the product becomes outdated, then its demand gradually starts declining or diminishing. For example, Android technology and 4G technology in mobile phones are currently in the growth stage of the life cycle, so, the forecast can be based on growth. But, if we talk about 3G technologies, then its demand is declining due to 4G. So, forecasting in this case is required to be done in a careful manner by considering its declining usage.
Below diagram shows the relationship between sales demand volume and product life cycle:
Stages of product life cycle and forecasting
To forecast the demand for a product at its introduction stage is quite challenging due to the non-availability of historical data. Demand related to the product introduction stage starts at a slow speed and rises with an increase in promotion activities. Accurate forecasts can be achieved by examining the launching of other similar products. In case no comparable products are available then the market can be tested by selling the product in small quantities to target a focused group of people in the market. Survey of the product rating and the liking of the product among people of the focused group of the target market, support the organization with forecasting.
One product is introduced, the next stage is related to its overall growth which can be identified through the pattern of linear growth. For example, the sale of a product was 100 units in the first week. By the end of the third week, sales rise to 1000 units. After that, there is an increase of 20% every week and this pattern continues over the next four weeks. So, we can say that from the third week onwards, the product has entered the growth stage, and thus, demand can be forecasted by making a projection of a 20% increase on weekly basis for the duration of the growth stage.
During this stage of the product life cycle, the growth in sales starts declining as the product is at its peak point of market acceptance. In this case, forecast needs to be done for predicting comparatively mode gradual rise rather than projecting a steadily increase in demand. This stage is also considered a market saturation stage and once the product enters it, the organization starts forecasting steady demand.
This is the last stage of the product life cycle in which both sales and profits decline. Though organizations may use different tactics such as improvement in product features, new and attractive packaging, different promotional activities, etc. to extend the above maturity stage of the life cycle of a product; still, sales decline with time. The organization is able to know that product has entered this stage when the sale which has already started declining in the maturity stage, starts decreasing at a fast rate.
Accuracy of Forecasting
To check the accuracy of forecasts derived from different forecasting methods is also an important aspect. There are possibilities of deviations in the value derived from the forecast and actual value. There are chances of more error if the deviation is higher. To examine such issues of accuracy, there are different measures. The two most popular methods are:
Mean Absolute Deviation (MAD) Method
This method is mostly used in short-term forecasting and measures the closeness between actual values and forecast values. The formula for calculating MAD is as below:
MAD= Aggregate of absolute deviation for n periods/ total number of periods.
In the above formula, the deviation is the variance between the actual value and forecast value.
Standard Error (SE) of Estimate Method
In this method, the variability of the observed values is measured throughout the regression line.