November 11, 2012

MU0010 [Manpower Planning and Resourcing] Set1 Q2

Q.2 Explain demand forecasting techniques. 
What are the benefits of manpower demand forecasting?

ANS:


Demand Forecasting

Demand forecasting is a process of evaluating the quality and quantity (number) of employees a firm or organization requires to meet its future needs. A forecast could be a long-term or a short-term plan depending on the activity levels for each function and departments. There are several internal and external factors to be considered in demand forecasting.

Internal factors include budget constraints, production levels, new products and services.
External factors include competition from other firms; it could be from the domestic or international firms, economic value, changes in technology etc.

A few good reasons to conduct demand forecasting are:
Determine the jobs necessary for offering services.
Determine the staff required for future needs.
Determine the correct staffing levels in different parts of the firm or organization.
Determine the shortage of employees when and where they are needed the most.

A demand forecast is the prediction of what will happen to your company's existing product sales. It would be best to determine the demand forecast using a multi-functional approach. The inputs from sales and marketing, finance, and production should be considered. The final demand forecast is the consensus of all participating managers. You may also want to put up a Sales and Operations Planning group composed of representatives from the different departments that will be tasked to prepare the demand forecast.


Demand Forecasting Techniques

Forecasting is an expensive way to help a company plan and prepare for the future years. Forecasting is not fortune telling; it is but an educated guess of how much manpower will be required and utilized by a firm or organization. It is a tool used to help in budgeting and allocating finances or hiring employees as perfectly as possible. One of the important features of forecasting is the quality of manpower resources (knowledge, skill, values and competency, capacity etc) as well as the quantity of manpower resources. 

There is no right way of forecasting, but there are many different types of forecasting methods. Each one is specifically planned and designed to help different retail organization and it is up to each of them to choose the model which is best and most appropriate for them.Manpower planning is done based on the manpower forecasts. 

The common manpower forecasting techniques are:

(1) Expert Forecasts
This is a group forecasting method in which experts present their independently developed forecasts to the group. However, the experts do not meet each other. The group keeps refining their forecasts until a group consensus is reached. This is called as the Delphi technique. In this method managers estimate future manpower requirements based on their experience and judgment.

(2) Trend Analysis 
This technique requires studying the past data of an organization. Based on the past forecast, utilization and requirement actually experienced in the business, the future forecast is made. For example, if an organization had 12 secretaries in the firm and this number were increasing by 1 secretary every year for the last 4 years. Then the trend analysis would forecast a requirement of 13 secretaries for the following year. That is one additional secretary for the year.

Past data is used to make future predictions. Known or Independent variables are used for predicting unknown or dependent variables, using the trend equation called “Predictive analysis”. Based on trend equation, we find ‘Line of Best Fit’ and then it is projected in a scatter diagram, dividing points equally on both sides.

The time series analysis has three goals: 
(i) Forecasting (also called predicting), (ii) Modeling (iii) Characterization. 

The logical order in which to tackle these three goals depends on the key objective. The idea of deciding the order is to ensure that one task leads to another and /or justifies the other tasks. Sometimes the objective is getting better forecasts. Then the order is forecasting, modeling and characterization. Sometimes the objective is to understand and explain what is going on. Then modeling is the key, though out-of-sample forecasting may be used to test any model. Often modeling and forecasting proceed in an iterative way and there is no ‘logical order’ in the broader sense. You may model to get forecasts, which enable better control, but iteration is again likely to be present. 

The trend equation is:
Y^ = a + b X + E
Y^ = Estimated value of Y
a = Constant or Intercept
b = slope of trend line
X = independent variable
E = Error term

Explained variation – means the extent to which the independent variable explains the relative change in the dependent variable. Higher the explained variation, lower the error value leading to accurate forecast.
R2 = Explained Variation
1- R2 = Unexplained Variation

Trend Analysis – Line of Best Fit

This process may be followed at the organization level as a whole or for parts of the organization based on department, location etc. Doing this at a granular with assumptions being documented and shared with the approving authority increases the forecast accuracy. The drawback is that you follow practices that you followed in the past. If the organization is experiencing the same rate of growth then this may work. But for extraordinary circumstances either good or bad for the organization, the trend analysis forecasting method often fails. Also this may build in turn the organization teeth to tail ratio unfavorable for making profits or enhancing profits. Teeth are the no. of employees who are directly into revenue earning jobs. E.g.: production employees, operations employees and sales staff. Tail is the no. of employees who are enabling the employees involved in directly revenue earning jobs. E.g.: secretaries, finance, administration & human resources.

(3) Work Study Technique
It is a technique that can be used when it is possible to apply work measurements to know how long operations should take and the amount of labor required. It is calculated in two ways.
• Work-Load Analysis
• Work-Force Analysis

i) Work-Load Analysis
One more method of forecasting is by evaluating the work load in a department or job role. This then enables deciding the no. of employees required for doing the job. This depends on the nature of the work load in a branch, department, or a division in a firm or organization.

Example: In BPOs, if an agent can handle 18 calls in a day of about 25 minute duration. If 2 lakh calls are received in a month, then the workload is evaluated on a per day basis. Calls receivable per hour are plotted. Then the no. of employees required to service those number of calls is calculated. Also the service level is considered. Some clients do not want to keep their customers on hold for more than 1 minute, in such cases the service level may be taken as 100%. This requires for staffing additionally such that the customers are not on hold for more than 1 minute. Staffing is decided to ensure per hour manpower adequacy to support the service level required by the client. The client understands the cost involved and is willing to pay for a higher service level. Based on all the above inputs the workload evaluation technique allows forecasting manpower demand.

ii) Work-Force Analysis
In workforce analysis a sufficient margin for absenteeism, labor turnover and idle time on the basis of past experience is made. This allows for completing the total job at hand undertaken by an organization despite the challenges of labor turnover or absenteeism. The organization needs to make reasonable prediction of labor turnover or absenteeism. However, if the actual labor turnover or absenteeism exceeds the predicted value, then it puts the business under loss. This could mean the profits of the company reducing or the company experiencing a loss. As we all know that a business organization with high overheads cannot sustain losses for more than a certain number of weeks or months depending on the business. This would mean many people go jobless if the company happens to shut down.

Therefore the workforce analysis has to be done with caution and by an experienced person with data validated for the past periods. Also the forecasting person, needs to be able to keep in mind any seasonal variations and special events that are likely to occur for the predicted period. Demand forecasting is a very responsible job. The entire organizations future depends on this. The organization leaders get involved to ensure that the demand forecasts are realistic and there is a reasonable buffer built in, so as to be able to sustain any deviations without a severe compromise in profitability or credibility with the client.

(4) Managerial Judgment Technique
This is a simple technique. In this the managers of different departments sit together, discuss and arrive at conclusions as to the number employees required for future operations based on their past experiences. This technique involves a “top-down” or “bottom-up approach.”

• In “Top-down” approach the managers prepare departmental forecasts. These are viewed by department heads and a decision is taken. 
• In “Bottom-up” approach the managers submit their departmental proposals to top managers who arrive at forecast.

Neither of these forecasts is accurate but both when combined could achieve effective results. This technique is used in smaller retail organizations or where there is not enough data available.

(5) Cost-Benefit Analysis
This is a term that refers both to:
(i) Helping to appraise, or assess, the case for a project or proposal, which itself is a process known as project appraisal; and 
(ii) An informal approach to making economic decisions of any kind. 

Under both definitions the process involves, whether explicitly or implicitly, weighing the total expected costs against the total expected benefits of one or more actions in order to choose the best or most profitable option. The formal process is often referred to as either CBA (Cost-Benefit Analysis) or BCA (Benefit-Cost Analysis).

Benefits and costs are often expressed in money terms, and are adjusted for the time value of money, so that all flows of benefits and flows of project costs over time (which tend to occur at different points in time) are expressed on a common basis in terms of their “present value.” Closely related, but slightly different, formal techniques include cost-effectiveness analysis, economic impact analysis, fiscal impact analysis and Social Return On Investment (SROI) analysis. The latter builds upon the logic of cost-benefit analysis, but differs in that it is explicitly designed to inform the practical decision-making of enterprise managers and investors focused on optimizing their social and environmental impacts.

Work that is done by hand can be done faster by machines. It is also uniformly done. Number of employees is also less, hence you save up every month on their salary but it has gone into the purchase of a machine which is a onetime investment. So it does prove to be beneficial to the firm or organization. E.g. tagging or stamping an item or product for sale.

(6) Markov Analysis
This is a mathematical technique. It forecasts the availability of internal job candidates. In this analysis, various job classifications can be predicted based on past movements (transfers, promotions, attrition, new joiners, resignations, and retirement).

(7) Statistical Judgment Technique 
This technique concentrates on using the past to predict the future by identifying trends, patterns and business drives within the data to develop a forecast. This forecast is referred to as a statistical forecast because it uses mathematical formulas to identify the patterns and trends while testing the results for mathematical reasonableness and confidence. These include ratio-trend analysis and econometric models. In ratio trend analysis the ratios are calculated for the past data and these are used to calculate future manpower requirements.

Example:

These models are built up by analyzing past statistical data 

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