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Project Planning with Sticky Notes

Techniques of Demand Forecasting

Broadly speaking, there are two approaches to demand forecasting- one is to obtain information about the likely purchase behavior of the buyer through collecting expert’s opinion or by conducting interviews with consumers, the other is to use past experience as a guide through a set of statistical techniques. Both these methods rely on varying degrees of judgment. The first method is usually found suitable for short-term forecasting, the latter for long-term forecasting. There are specific techniques which fall under each of these broad methods.

Simple Survey Method:

For forecasting the demand for existing product, such survey methods are often employed. In this set of methods, we may undertake the following exercise.

1) Experts Opinion Poll: In this method, the experts on the particular product whose demand is under study are requested to give their ‘opinion’ or ‘feel’ about the product. These experts, dealing in the same or similar product, are able to predict the likely sales of a given product in future periods under different conditions based on their experience. If the number of such experts is large and their experience-based reactions are different, then an average-simple or weighted –is found to lead to unique forecasts. Sometimes this method is also called the ‘hunch method’ but it replaces analysis by opinions and it can thus turn out to be highly subjective in nature.

2) Reasoned Opinion-Delphi Technique: This is a variant of the opinion poll method. Here is an attempt to arrive at a consensus in an uncertain area by questioning a group of experts repeatedly until the responses appear to converge along a single line. The participants are supplied with responses to previous questions (including seasonings from others in the group by a coordinator or a leader or operator of some sort). Such feedback may result in an expert revising his earlier opinion. This may lead to a narrowing down of the divergent views (of the experts) expressed earlier. The Delphi Techniques, followed by the Greeks earlier, thus generates “reasoned opinion” in place of “unstructured opinion”; but this is still a poor proxy for market behavior of economic variables.

3) Consumers Survey- Complete Enumeration Method: Under this, the forecaster undertakes a complete survey of all consumers whose demand he intends to forecast, Once this information is collected, the sales forecasts are obtained by simply adding the probable demands of all consumers. The principle merit of this method is that the forecaster does not introduce any bias or value judgment of his own. He simply records the data and aggregates. But it is a very tedious and cumbersome process; it is not feasible where a large number of consumers are involved. Moreover if the data are wrongly recorded, this method will be totally useless.

4) Consumer Survey-Sample Survey Method: Under this method, the forecaster selects a few consuming units out of the relevant population and then collects data on their probable demands for the product during the forecast period. The total demand of sample units is finally blown up to generate the total demand forecast. Compared to the former survey, this method is less tedious and less costly, and subject to less data error; but the choice of sample is very critical. If the sample is properly chosen, then it will yield dependable results; otherwise there may be sampling error. The sampling error can decrease with every increase in sample size

5) End-user Method of Consumers Survey: Under this method, the sales of a product are projected through a survey of its end-users. A product is used for final consumption or as an intermediate product in the production of other goods in the domestic market, or it may be exported as well as imported. The demands for final consumption and exports net of imports are estimated through some other forecasting method, and its demand for intermediate use is estimated through a survey of its user industries.

Complex Statistical Methods:

We shall now move from simple to complex set of methods of demand forecasting. Such methods are taken usually from statistics. As such, you may be quite familiar with some the statistical tools and techniques, as a part of quantitative methods for business decisions.

(1) Time series analysis or trend method: Under this method, the time series data on the under forecast are used to fit a trend line or curve either graphically or through statistical method of Least Squares. The trend line is worked out by fitting a trend equation to time series data with the aid of an estimation method. The trend equation could take either a linear or any kind of non-linear form. The trend method outlined above often yields a dependable forecast. The advantage in this method is that it does not require the formal knowledge of economic theory and the market, it only needs the time series data. The only limitation in this method is that it assumes that the past is repeated in future. Also, it is an appropriate method for long-run forecasts, but inappropriate for short-run forecasts. Sometimes the time series analysis may not reveal a significant trend of any kind. In that case, the moving average method or exponentially weighted moving average method is used to smoothen the series.

(2) Barometric Techniques or Lead-Lag indicators method: This consists in discovering a set of series of some variables which exhibit a close association in their movement over a period or time.

For example, it shows the movement of agricultural income (AY series) and the sale of tractors (ST series). The movement of AY is similar to that of ST, but the movement in ST takes place after a year’s time lag compared to the movement in AY. Thus if one knows the direction of the movement in agriculture income (AY), one can predict the direction of movement of tractors’ sale (ST) for the next year. Thus agricultural income (AY) may be used as a barometer (a leading indicator) to help the short-term forecast for the sale of tractors.

Generally, this barometric method has been used in some of the developed countries for predicting business cycles situation. For this purpose, some countries construct what are known as ‘diffusion indices’ by combining the movement of a number of leading series in the economy so that turning points in business activity could be discovered well in advance. Some of the limitations of this method may be noted however. The leading indicator method does not tell you anything about the magnitude of the change that can be expected in the lagging series, but only the direction of change. Also, the lead period itself may change overtime. Through our estimation we may find out the best-fitted lag period on the past data, but the same may not be true for the future. Finally, it may not be always possible to find out the leading, lagging or coincident indicators of the variable for which a demand forecast is being attempted.

3) Correlation and Regression: These involve the use of econometric methods to determine the nature and degree of association between/among a set of variables. Econometrics, you may recall, is the use of economic theory, statistical analysis and mathematical functions to determine the relationship between a dependent variable (say, sales) and one or more independent variables (like price, income, advertisement etc.). The relationship may be expressed in the form of a demand function, as we have seen earlier. Such relationships, based on past data can be used for forecasting. The analysis can be carried with varying degrees of complexity. Here we shall not get into the methods of finding out ‘correlation coefficient’ or ‘regression equation’; you must have covered those statistical techniques as a part of quantitative methods. Similarly, we shall not go into the question of economic theory. We shall concentrate simply on the use of these econometric techniques in forecasting.

We are on the realm of multiple regression and multiple correlation. The form of the equation may be:

D_X = a + b₁ A + b₂P_X + b₃P_y

You know that the regression coefficients b₁, b₂, b₃ and b₄ are the components of relevant elasticity of demand. For example, b₁ is a component of price elasticity of demand. The reflect the direction as well as proportion of change in demand for x as a result of a change in any of its explanatory variables. For example, b₂< 0 suggest that D_X and P_X are inversely related; b₄ > 0 suggest that x and y are substitutes; b₃ > 0 suggest that x is a normal commodity with commodity with positive income-effect.

Given the estimated value of and b_i, you may forecast the expected sales (D_X), if you know the future values of explanatory variables like own price (P_X), related price (P_y), income (B) and advertisement (A). Lastly, you may also recall that the statistics R2 (Co-efficient of determination) gives the measure of goodness of fit. The closer it is to unity, the better is the fit, and that way you get a more reliable forecast.

The principle advantage of this method is that it is prescriptive as well descriptive. That is, besides generating demand forecast, it explains why the demand is what it is. In other words, this technique has got both explanatory and predictive value. The regression method is neither mechanistic like the trend method nor subjective like the opinion poll method. In this method of forecasting, you may use not only time-series data but also cross section data. The only precaution you need to take is that data analysis should be based on the logic of economic theory.

(4) Simultaneous Equations Method: Here is a very sophisticated method of forecasting. It is also known as the ‘complete system approach’ or ‘econometric model building’. In your earlier units, we have made reference to such econometric models. Presently we do not intend to get into the details of this method because it is a subject by itself. Moreover, this method is normally used in macro-level forecasting for the economy as a whole; in this course, our focus is limited to micro elements only. Of course, you, as corporate managers, should know the basic elements in such an approach.

The method is indeed very complicated. However, in the days of computer, when package programmes are available, this method can be used easily to derive meaningful forecasts. The principle advantage in this method is that the forecaster needs to estimate the future values of only the exogenous variables unlike the regression method where he has to predict the future values of all, endogenous and exogenous variables affecting the variable under forecast. The values of exogenous variables are easier to predict than those of the endogenous variables. However, such econometric models have limitations, similar to that of regression method.

Three Scope Change Management Techniques

There are a lot of interesting scope change management techniques that can be easily applied to your project. Here are three that will keep you out of trouble.

Make Sure Only the Sponsor Approves Changes

A typical problem on a project is that the team does not understand the roles of the sponsor, client and end users in the area of change management. In general, the project sponsor is the person who is funding the project. If the client were embodied in one person, it would be the project sponsor. The people that the project team tends to work with most often are users. These are the people that use the solution that the project is building. The end users are the ones that will generally make requests for changes to deliverables. However, no matter how important a change is to a user, they cannot approve scope changes. The sponsor (or their designee) must give the approval. If the change is important enough the sponsor will approve it, along with the appropriate budget and duration changes. If the change is not important enough, it will not be approved. 

Saying 'Yes' to Change Requests May not Show Good Client Focus

The project manager and project team sometimes think that they are being client-focused by accepting scope change while still trying to deliver the project within the original commitments. However, if the project is delivered late or over budget, it is usually not good enough to point out all the additional work that was included because of this 'client focus'. 

The sponsor is the primary client representative. Allowing the sponsor (or their designee) to make scope change decisions shows good client focus. If the project team or project manager approves scope changes, he is not showing good client focus from the sponsor's perspective.

An Engaged Sponsor Will Often Say 'No' to Scope Change Requests

One of the neat things about enforcing the discipline of having the sponsor approve scope change requests is that, unless the change is very important, the sponsor will often say 'no'. The sponsor is usually someone high in the organization. He normally doesn't want to hear about requests for small changes. He wants the original project fulfilled within the original commitments for cost, effort and duration. Even though it may be hard for the project manager to say 'no', the project sponsor usually doesn't have any problem saying 'no' to the people in sponsor's own organization.

Everything You Wanted to Know About Action Items

An action item is work that requires follow-up execution. By their nature, action items normally cannot be planned for in advance. They arise on an ad-hoc basis during meetings or as a by-product of working on something else. An action item is assigned because there is not enough knowledge, expertise or time to resolve the item at the time it originally surfaced.

In many cases, action items are trivial in nature, but in other cases they can require substantial work to complete. Action items need to be assigned, worked on later and completed. (If they are not going to be completed, they should not be called action items. Instead, simply note that the item will not be followed up on and then forget about it.) Examples of action items include forwarding information to someone, arranging a meeting and providing a quick estimate on a piece of work. 

Sometimes an action item is established to investigate an area where there may be a potential problem. Because of this, action items are sometimes mixed in with issues. However, this is not right; an action item should not be confused with an issue. An issue is a problem which will have a detrimental impact on the project if left unresolved. An action item may lead to the discovery of an issue or a risk (a potential issue in the future), but the action item itself is not an issue.

There are two common approaches used to manage action items. The best approach is to document the items as activities in the project schedule. A resource and end-date are assigned as well, and the activity is then managed and tracked as any normal activity on the schedule. In general, this is the better approach to follow, because it keeps the work items in one place and allows the project manager to enforce the discipline of knowing ‘if it’s not on the schedule, it will not be worked on.’ This approach also allows the project manager to see the impact of the action items on the schedule. For instance, you may have a small action item that is 3 hours of work. If you assign this action item to a person on the critical path, you may see the resulting delay to your project. This may result in you assigning the action item to someone else instead.

The second approach is to create a section on your meeting minutes for action items. Action items can be placed here if they are trivial (less than two hours) and they are scheduled to be completed by the next meeting. If you use this technique you can start each meeting with a review of the prior action items to validate that they are completed and then cross them off the list.

Don't Mix Issues and Action Items on the Same Log

In many cases, project managers are not using the Issues Log to identify and track true issues. Many items that are classified as issues are really risks (potential problems) or just action items. If you find that your Issues Log has dozens of items on it, you are probably tracking action items instead. Because issues are large problems, there should not be many items open at any one time. If you find that your Issues Log is full of action items, chances are that your true issues are hidden and not worked on as they should.

Understand These Three Estimating Concepts

Understand These Three Estimating Concepts

Estimate in Phases

One of the most difficult aspects of planning projects is the estimating process. It can be hard to know exactly what work will be needed in the distant future. It can be difficult to define and estimate work that will be done three months from now. It's harder to estimate six months in the future. Nine months is even harder. There is more and more estimating uncertainty associated with work that is farther and farther out in the future.

A good approach for larger projects is to break the work into a series of smaller projects, each of which can be planned, estimated and managed separately with a much higher likelihood of success. From an estimating perspective, the closest project can be estimated more precisely, with the subsequent projects estimated with a higher level of uncertainty. When one project completes, the next project can be estimated with a higher degree of confidence, with estimates refined for the remaining projects. This technique also provides checkpoints at the end of each project so that the entire initiative can be revalidated based on current estimates to ensure that it is still viable and worth continuing.

Estimate Fixed Costs and Variable Costs

You may hear the terms fixed and variable cost when you are estimating the cost of a project. Variable costs are those that change relative to how many units are being used. An obvious variable cost on a project is contract labor. The more hours you use from a contactor, the more the cost to the project. The cost of contract labor is variable depending on the number of hours worked.

Fixed costs are those that are basically the same for the project regardless of the resources being used. For instance, if you were building a house, the cost of the lot would be fixed and would not change based on the size of the house you built. Similarly, if you outsource part of a project to a third party for a fixed price, it becomes a fixed cost to the project as well. Even if the work takes longer or shorter than estimated, your project cost should still be the agreed upon fixed cost.

Estimate Time-Constrained and Resource-Constrained Activities

Activities can be classified as time or resource-constrained based on whether the duration can change if more resources are applied. An activity is resource-constrained if the duration changes based on the number of resources applied. For instance, you might estimate that it will take 80 hours for one person to build a roof on top of a house. If the person worked forty hours per week, it would take two weeks to complete the job. If you applied two people to the job, the effort is still be 200 total effort hours, but the job would only take one week to complete.

On the other hand, if an activity is time-constrained, the duration remains the same regardless of the number of resources applied. For example, lets say one person attends a three-day class. If you send two people to the class, the class does not get shorter; it still takes three days. Likewise, the time it takes for concrete to dry, or to mail a letter, is not impacted by the number of people involved. They just take a certain amount of time. If you find that applying resources has no impact on the project duration (or very little impact), then the activity is time-constrained.