By Steven A. Melnyk and R.T. "Chris" Christensen

In the first column of this series, we focused our attention on the notion of capacity and what goes into it. We tried to develop a better understanding of the complex nature of capacity and the need for managers to have a better understanding of it. At that time, we ended the article by noting that we would examine the issue of how to measure capacity in the next installment. Well, there was a slight foul-up in the process and the article never really got written. That is, not until a reader of this column, Jerry Schepp of MEC, brought this omission up to the authors. In response to his request, we now focus our attention on the problem of measuring capacity.


Embarking on capacity measurement
In the January issue, we showed how there were two views of capacity — one focusing on volume and one focusing on capabilities. The two were, as we pointed out, tightly linked. However, this discussion never really got to the issue of how to measure capacity. Measuring capacity should be, at first glance, a straightforward task. What we are doing is measuring in quantitative terms the size of the volume that we can produce. However, this is not quite the case. The reason being that we must not only measure capacity in terms of supply (e.g., the number of hours of capacity available) but also in terms of output (e.g., the number of units produced).

To begin this process, we must identify the limiting or bottleneck resource. This could be labor, a piece of equipment or tooling. For the purposes of this discussion, we will focus our attention on labor. Having identified the limiting capacity, we must identify and calculate two different measures of capacity. The first is the attendance hours. This is the total number of hours that the resource is available. For example, if we were dealing with a one-shift operation, then the attendance hours might be 9.5 hours. That is, the employees are on site from 7 a.m. until 4:30 p.m. While the employees are on site for 9.5 hours, they are not working for that entire time. The amount of time over which they are available for use is referred to by some as the Net Available Operating Time (NAOT).

The difference between the attendance hours and the NAOT is typically accounted for by breaks, lunch and planned maintenance time. For example, returning to our previous example, we know that we have 9.5 hours of time available. However, we also know that the employees are allowed two 10-minute breaks. They are also given a 60-minute lunch break and 20 minutes for end of shift maintenance. This means that the Net Available Operating Time is 9.5 hours or 570 minutes - 20 minutes (breaks) - 60 minutes (lunch) - 20 minutes (maintenance), or 470 minutes. However, it is important that we stop here and examine another time element that is often considered when calculating NAOT — safety capacity.


Safety capacity
Safety capacity is a buffer of capacity that management often introduces when planning capacity usage. It is a percentage of capacity or a time period during which, on average, we plan to leave capacity idle. For example, in our previous example, we could have planned to assign 45 minutes of every day to safety capacity. At first glance, this seems like an absurd policy. Why should we plan to leave perfectly good capacity idle. The answer is that safety capacity exists so that it can be used to accommodate unplanned orders or unplanned situations.

That is, we, as management, recognize that we are working in an environment which is highly dynamic. These uncertainties are encountered either on the demand side (i.e., the arrival of new unplanned orders from customers which require immediate processing, or unplanned or uncontrolled changes to the status of existing orders either in terms of due dates or order quantities) or on the supply side (e.g., problems with processing times or the need for extra units). One way of accommodating these uncertainties is to set aside capacity "just-in-case" it is needed. It is this "just-in-case" nature of safety capacity that lies at the heart of the controversy surrounding this concept.

While some managers believe in the use of safety capacity, others see no real value in it. Some managers do not consider safety capacity when measuring capacity and planning its use. The reason is simple. For many managers, safety capacity implicitly recognizes that management is unable to control either the flow of orders into the firm or the amount of capacity that is actually needed on the shop floor. As a result, management must turn to safety capacity as a means of protecting itself and the execution system from these problems. Rather than addressing the real root problems, we have elected to protect ourselves. Instead of better educating our customers about the real need for discipline when placing or changing orders, we have decided to accommodate the customer's bad habits. We have said, in effect, that it is acceptable for the customer to put in orders at the last minute and expect them to be delivered on time. In addition, others recognize that, on average, safety capacity results in dead capacity. That is, with safety capacity, we are paying for all the costs associated with capacity. These costs are real. Yet, there is no real revenue planned from this capacity. It only generates revenue when the level of capacity required exceeds the amount for which we have planned. When this occurs, it is random and difficult to predict.

Whether or not safety capacity is considered when planning production must be left up to the discretion of management. However, if it is considered, then the implications (and costs) of its use should be factored into the resulting analysis.


Making the transition from volume to output
Now that we have finished with the issue of volume, we must now convert this volume into planned output. In so doing, we must recognize that this is a more complex process. The reason being that the amount that is produced (i.e., output) is influenced by numerous factors, including (but not limited to): product mix (the more of the same products that you make, the higher the output due to the need for fewer setups and the opportunities for improvements through learning); length of runs; accuracy of standards; experience of the factors; past experience with the products (capacity needed might be more difficult to determine if the product being built is relatively new or a prototype); stability of priorities (when priorities are changing, we may abuse capacity as we react rather than plan for the best use of capacity); the scheduling system in place; and the level of work load (how much work is waiting to be processed). It is also important that the output be influenced by the demands coming from the customers (i.e., ideally we want to produce products at the rate that the customers want them) and the bottlenecks within our system.

Given these and other variables, we will explore the question of how to make this transition in the next article.


Lessons of capacity measurement

• In measuring capacity, we must understand and work with the differences between the volume and output dimensions of capacity.
• Attendance time identifies the total time that the capacity is present, but not the time that it is available.
• o identify the time over which capacity is available for use requires the notion of Net Available Operating Time. This is the attendance time minus breaks and lunch time.
• A major area of controversy is that of whether or not safety capacity should be considered or included in the NAOT calculation. Safety capacity is a buffer that we put in to protect ourselves from uncertainties in demand and uncertainties in processing.
• When dealing with safety capacity, it is important that we recognize that, on average, safety capacity is dead capacity. That is, it is capacity we pay for, but generates little if any revenue. It also deals with symptoms rather than addressing the underlying problems.
• When making the transition from volume to output, we must recognize that this transition is influenced by numerous factors such as product mix, operator experience, condition of equipment, work loads and scheduling practices.

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