Project Metrics week 5 Critical Thinking

Project Metrics, Monitoring, and Control

Module 5: Learning curves

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1. Theory of Learning Curves

Project management philosophy may state that experience curves are based on the old adage that “practice makes perfect.”

A service or product can always be made better and in less time in each succeeding attempt. In the 1960’s, true implications of experience curves became evident. Companies such as Boston Consulting Group showed that each time cumulative production doubled, the total manufacturing time and cost fell by a constant and predictable amount (Kerzner, 2009). Projects with repeatable processes have the same effect, meaning product deliverables are met earlier and at less cost.

Today’s management often measures the profitability of a corporation as a function of market share. As the market share increases, profitability will increase because of lower production costs that increase margins. This is the experience curve effect (Kerzner, 2009).

The following website contains an example of a risk management plan template that addresses the theory of learning curve:

(Source: http://youtu.be/E3GBCW3uvZE)

CMA Part 1 - Learning Curves (Video Lectures - Lynchpin Financial Training Centre)

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Project Metrics, Monitoring, and Control

Module 5: Learning curves

2. Learning Curve Concept

Kerzner states that learning curves stipulate that manufacturing human resources hours will decline each time an organization doubles its output. Generally, learning curves produce a cost and time savings of 10 to 30 percent each time a company’s experience at producing a product doubles (Kerzner, 2009).

Most companies that use learning curves would agree that it is more common to use human resource hours because exact costs are either not always known or not publicly disclosed by the firm. The use of costs implies the added complexity of considering escalation factor on salary, cost of living adjustment and time value of money. For projects that take fewer than 2 years, costs are often used instead of human resource hours (Kerzner, 2009).

These types of cost are also known as value-added costs and can also appear in the form of lower freight and procurement costs through bulk quantities. The customer and contractor both benefit from the value-added cost savings.

The more repetitive tasks become, the less the time is required to perform a task. Also, the amount of improvement decreases as more units are produced. Another point to note that supports learning curve concept is that the rate of improvement has sufficient consistency to allow its use as a prediction tool. “The consistency in improvement has been found to exist in the form of a constant percent reduction in time required over successive doubled quantities of units produced” (Kerzner, 2009, p. 819).

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Project Metrics, Monitoring, and Control

Module 5: Learning curves

3. Graphic Representation of Learning Curves

Graphic representation of learning curves can be displayed in various ways. For example, a horizontal axis can represent the total number of units produced, and the vertical axis can represent the total labor hours (or cost) for each unit. Another graphic might represent a hyperbola when drawn on ordinary graph paper showing the difference or amount of labor-hour reduction is not consistent.

The main purpose for learning curve graphic representation is to predict trends and forecast a product or service to capitalize on opportunities and gain competitive advantage in the market space. Learning curves are powerful analytical tools. Two fundamental models of the learning curve are generally used: the unit curve and the cumulative average curve. The unit curve focuses on the hours or cost involved in specific units of production. The cumulative average curve becomes important in determining the cost for a manufacturing project (Kerzner, 2009).

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Project Metrics, Monitoring, and Control

Module 5: Learning curves

4. Selecting Learning Curves

The selection of learning curves is a process and depends on the data a project manager has available. For example, existing experience curves reflect past experience or historical data. Trend lines are developed from accumulated data.

Kerzner says when selecting the proper curve for a new production item when only one point of data is available and the slope is unknown, there is an order to follow that should be considered.

• Similarity between the new item and an item or items previously produced • Physical comparison • Duration of time since a similar item was produced • Other comparable factors between similar items

If at least two points of data are accessible, the slope of the curve may be determined. The availability of additional points of data will enhance the reliability of the curve. Regardless of the of the number of points and the assumed reliability of the slope, comparisons with similar items are considered the most desirable approach and should be made whenever possible (Kerzner, 2009).

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References:

Kerzner, H. (2009). Project management: A systems approach to planning, scheduling and controlling (10th ed.). New York, NY:

John Wiley & Sons.

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