measuring output rates h - pearson...

LEARNING GOALS

After reading this supplement,you should be able to:

1. Provide examples of the uses ofwork standards by managers.

2. Describe procedures formeasuring output rates, usingseveral common approaches.

3. Discuss the managerialconsiderations of workmeasurement.

This supplement focuses on measuring the volume of work

produced per unit of time, called an output rate. The rate of

output is influenced by operations strategy, process choice,

technology, and job design. The first step in measuring an

output rate is determining a normal level of performance. A

work standard is the time required for a trained worker to

perform a task following a prescribed method with normal

effort and skill. Robots of the same type perform the same

repetitive tasks with little variation in output rate, but human

output is more difficult to evaluate because skill, effort, and

stamina vary from one employee to another.

SUPPLEMENT

Measuring Output Rates

H

H.1

H.2 SUPPLEMENT H > MEASURING OUTPUT RATES <

> WORK STANDARDS <Managers use work standards in the following ways.

1. Establishing Prices and Costs. Managers can use labor and machine time standards todevelop costs for current and new products, create budgets, determine prices, andarrive at make-or-buy decisions.

2. Motivating Workers. Standards can be used to define a day’s work or to motivate workersto improve their performance. For example, under an incentive compensation plan,workers can earn a bonus for output that exceeds the standard.

3. Comparing Alternative Process Designs. Time standards can be used to compare differ-ent routings for an item and to evaluate new work methods and new equipment.

4. Scheduling. Managers need time standards to assign tasks to workers and machines inways that effectively utilize resources.

5. Capacity Planning. Managers can use time standards to determine current and pro-jected capacity requirements for given demand requirements. Workforce staffing deci-sions also may require time estimates.

6. Performance Appraisal. A worker’s output can be compared to the standard output overa period of time to evaluate worker performance and productivity. A manager’s perfor-mance can be measured by comparing actual costs to standard costs of a process.

Work standards often are a source of conflict between management and labor. When anorganization uses output standards as the basis for pay, unions or workers may object if theybelieve that standards are set “too high” and management may object if they believe thatstandards are set “too low.” Both groups benefit from setting achievable standards becausesetting output standards at either extreme makes planning for appropriate capacity levelsdifficult, increases costs, and reduces profits.

Managers themselves disagree over the use of engineered work standards to increaseproductivity. Some managers believe that employees need to be involved in determiningwork standards, that time studies dehumanize workers, and that the costs of large industrialengineering staffs and the hidden costs of labor–management conflicts outweigh the benefitsof elaborate standards. Others believe that using engineered standards for piecework incen-tives actually defeats their purpose of increasing worker productivity because employees willhave little incentive to improve their work methods. Workers also may lose sight of quality asthey race to meet standards. However, when firms involve employees in defining their ownwork standards, the methods presented in this supplement can still increase productivity.

> METHODS OF WORK MEASUREMENT <The key to creating a work standard is defining normal performance. Suppose, for example,that the manager of a fast-growing company that manufactures frozen pizza wants to createa standard for pizza assembly. To assemble the pizza, a worker spreads sauce over the pizzashell, adds pepperoni and cheese, places the pizza in a box, and puts the assembled producton a cart for fast freezing. The entire process takes 20 seconds. At this pace, a worker couldassemble 1,440 pizzas in an eight-hour day.

Before settling on 20 seconds as the standard, however, the manager must considerwhether all the employees have the skills of the observed worker. He may be exceptionallyenergetic, experienced, and efficient. Moreover, the estimate of 20 seconds per pizza did notaccount for fluctuations in pace or scheduled rest periods. Generally, the time per unitobserved over a short period for one employee should not be used as a standard for anextended period of time for all employees.

Work measurement is the process of creating labor standards based on the judgment ofskilled observers. Managers often use informal methods to arrive at labor standards. Theycan develop simple estimates of the time required for activities or the number of employeesneeded for a job on the basis of experience and judgment. Formal methods of work mea-surement available to the manager include

1. the time study method

2. the elemental standard data approach

work standard

The time required for a trained worker toperform a task following a prescribedmethod with normal effort and skill.

work measurement

The process of creating labor standardsbased on the judgment of skilledobservers.

> METHODS OF WORK MEASUREMENT < H.3

3. the predetermined data approach

4. the work sampling method

The method chosen often depends on the purpose of the data. For example, when ananalyst needs a high degree of precision in comparing actual work method results to stan-dards, a stopwatch study or predetermined times might be required. Alternatively, an analystwho wants to estimate the percentage of time that an employee is idle while waiting for cus-tomers or materials requires a work sampling method.

Moreover, an analyst may use more than one approach to obtain needed work measure-ment information. In the remainder of this supplement, we assume that the worker has fullylearned the work method under study.

TIME STUDY METHOD

The method used most often for setting time standards for a job is called a time study, whichconsists of four steps.

Step 1: Selecting Work Elements Each work element should have definite starting andstopping points to facilitate taking stopwatch readings. Work elements that take less thanthree seconds to complete should be avoided because they are difficult to time. The workelements selected should correspond to a standard work method that has been runningsmoothly for a period of time in a standard work environment. Incidental operations notnormally involved in the task should be identified and separated from the repetitive work.

Step 2: Timing the Elements After the work elements have been identified, the analysttimes a worker trained in the work method to get an initial set of observations. The analystmay use either the continuous method, recording the stopwatch reading for each work ele-ment upon its completion, or the snap-back method, resetting the stopwatch to zero uponcompletion of each work element. For the latter method, the analyst uses two watches, onefor recording the previous work element and the other for timing the present work element.

If the sample data include a single, isolated time that differs greatly from other timesrecorded for the same element, the analyst should investigate the cause of the variation. An“irregular occurrence,” such as a dropped tool or a machine failure, should not be includedin calculating the average time for the work element. The average observed time based onlyon representative times is called the select time ( ). Irregular occurrences can be covered inthe allowances that we discuss later.

Step 3: Determining Sample Size Typically, those who use the time study method to setstandards want an average time estimate that is very close to the true long-range averagemost of the time. A formula, based on the normal distribution, allows the analyst to deter-mine the sample size, n, required:

where

n = required sample size

p = precision of the estimate as a proportion of the true value

= select time for a work element

s = standard deviation of representative observed times for a work element

z = number of normal standard deviations needed for the desired confidence

Typical values of z for this formula are

t

nzp t

=⎛⎝⎜

⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

⎡

⎣⎢⎢

⎤

⎦⎥⎥

σ2

t

time study

The method most often used for settingtime standards for a job; it consists offour steps: selecting work elements,timing the elements, determining samplesize, and setting the standard.

select time ( )

The average observed time based onlyon representative times.

t

Desired Confidence (%) z

90 1.65

95 1.96

96 2.05

97 2.17

98 2.33

99 2.58


For example, a z value of 1.96 represents ±1.96 standard deviations from the mean, leav-ing a total of 5 percent in the tails of the standardized normal curve. The precision of theestimate, p, is expressed as a proportion of the true (but unknown) average time for thework element.

Estimating the Sample Size in a Time StudyEXAMPLE H.1

A coffee cup packaging operation has four work elements. A preliminary study provided the following results:

Standard SelectDeviation,S Time, Sample

Work Element (min) (min) Size

1. Get two cartons 0.0305 0.50 5

2. Put liner in carton 0.0171 0.11 10

3. Place cups in carton 0.0226 0.71 10

4. Seal carton and set aside 0.0241 1.10 10

t

Work element 1 was observed only five times because it occurs once every two work cycles. The study coveredthe packaging of 10 cartons. Determine the appropriate sample size if the estimate for the select time for anywork element is to be within 4 percent of the true mean 95 percent of the time.

SOLUTIONFor this problem,

p = 0.04 and z = 1.96

The sample size for each work element must be calculated, and the largest must be used for the final study sothat all estimates will meet or exceed the desired precision.

Decision Point All fractional calculations were rounded to the next largest integer. To be sure that all selecttimes are within 4 percent of the true mean 95 percent of the time, we must have a total of 58 observationsbecause of work element 2. Consequently, we have to observe the packaging of 48 (or 58 � 10) more cartons.

Work element 1: n =⎛⎝⎜

⎞⎠⎟

⎛1 960 04

0 03050 500

.

...⎝⎝⎜

⎞⎠⎟

⎡

⎣⎢

⎤

⎦⎥ =

=⎛⎝⎜

2

9

1 960 04

Work element 2: n..

⎞⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

⎡

⎣⎢

⎤

⎦⎥ =0 0171

0 1158

2..


⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

⎡

⎣⎢

⎤

⎦⎥ =1 96

0 040 0226

0 71

2..

..

33

1 960 04

0 02411 10


⎞⎠⎟

.

...

⎛⎛⎝⎜

⎞⎠⎟

⎡

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⎦⎥ =

2

2

Step 4: Setting the Standard The final step is to set the standard. To do so, the analystfirst determines the normal time for each work element by judging the pace of the observedworker. The analyst must assess not only whether the worker’s pace is above or below aver-age but also a performance rating factor (RF) that describes how much above or below aver-age the worker’s performance on each work element is. Setting the performance ratingrequires the greatest amount of judgment. Usually, only a few workers are observed during astudy. If the workers are fast, basing the standard on their average time would not be fair,particularly if a wage incentive plan is involved. Conversely, if the workers are slow, basing

TUTOR H.1

Tutor H.1 on the Student CD-ROMprovides a new example to practice theapproach to determine the appropriatesample size.

performance rating factor (RF)

An assessment that describes how muchabove or below average the worker’sperformance on each work element is.


the standard on their normal time would be unfair to the company. Furthermore, workersmay slow their pace when they are being observed in a time study. Thus, the analyst has tomake an adjustment in the average observed time to estimate the time required for a trainedoperator to do the task at a normal pace. Analysts go through training programs to ensureconsistency of ratings over many analyses.

The analyst must also factor in the frequency of occurrence, F, of a particular work ele-ment in a work cycle. Some work elements may not be performed every cycle. The analystfinds the normal time (NT) for any work element by multiplying the select time ( ), the fre-quency (F) of the work element per cycle, and the rating factor (RF):

Use F = 1 if the work element is performed every cycle, F = 0.5 if it is performed every othercycle, and so on. To find the normal time for the cycle (NTC), the analyst sums the normaltime for each element:

NTC = ΣNT

NT RF= t F( )( )

t

normal time (NT)

A measurement found by multiplying theselect time ( ), the frequency (F ) of thework element per cycle, and the ratingfactor (RF).

t

normal time forthe cycle (NTC)

A measurement found by summing thenormal time for each element.

allowance time

The time added to the normal time toadjust for certain factors.

standard time (ST)

A measurement found by incorporatingthe normal time added for allowances;ST = NTC(1 + A), where A equals theproportion of the normal time added forallowances.

Determining the Normal Time EXAMPLE H.2

Suppose that 48 additional observations of the coffee cup packaging operation were taken and the following datawere recorded:

Work Element F RF

1 0.53 0.50 1.05

2 0.10 1.00 0.95

3 0.75 1.00 1.10

4 1.08 1.00 0.90

t

Because element 1 occurs only every other cycle, its average time per cycle must be half its averageobserved time. That is why F1 = 0.50 for that element. All others occur every cycle. What are the normal times foreach work element and for the complete cycle?

SOLUTIONThe normal times are calculated as follows:

Work element 1: NT1 = 0.53 (0.50) (1.05) = 0.28 minute




Total = 2.18 minutes

The normal time for the complete cycle is 2.18 minutes.

Decision Point The normal time only tells us what the specific worker used for the study can do. It mustbe modified to get a useful measure of output for a group of workers.

We cannot use the normal time of 2.18 minutes for the cycle as a standard because itdoes not allow for fatigue, rest periods, or unavoidable delays that occur during an averageworkday. Hence, we must add some allowance time to the normal time to adjust for thesefactors. The standard time (ST) then becomes

ST = NTC(1 + A)

TUTOR H.2

Tutor H.2 on the Student CD-ROMprovides a new example to practice thedetermination of the normal time.


where

A = proportion of the normal time added for allowances

Most allowances range from 10 to 20 percent of normal time and cover factors that may bedifficult to measure. However, work sampling can be used to estimate some of those factors.

elemental standard data

A type of data used by analysts to derivestandards for various jobs when a highdegree of similarity exists in the workelements of certain jobs.

Determining the Standard TimeEXAMPLE H.3

Management needs a standard time for the coffee cup packaging operation. Suppose that A = 0.15 of the nor-mal time. What is the standard time for the coffee cup packaging operation, and how many cartons can beexpected per eight-hour day?

SOLUTIONFor A = 0.15 of the normal time,

ST = 2.18(1 + 0.15) = 2.51 minutes /carton

Decision Point For an eight-hour day, this translates into a production standard of

Management can now use that estimate to make production plans and cost estimates.

480191

minutes/day2.51 minutes/carton

cart= oons/day

Overall Assessment of Time Study Time study methods have some limitations. Theyshould not be used to set standards for jobs in which the nature of the task is different eachtime, such as a student solving a problem, a professor preparing a lecture, or an automobilemechanic diagnosing the cause of a nonroutine problem. In addition, an inexperienced per-son should not conduct time studies because errors in recording information or in selectingthe work elements to include can result in unreasonable standards. Finally, some workersmay object to time study because of the subjectivity involved. Nonetheless, time studiesconducted by an experienced observer usually provide a satisfactory, although imperfect,tool for setting equitable time standards.

ELEMENTAL STANDARD DATA APPROACH

If a plant requires thousands of work standards, the time and cost required for the timestudy method may be prohibitive. When a high degree of similarity exists in the work ele-ments of certain jobs, analysts often use elemental standard data to derive standards forvarious jobs. In this approach, analysts use a work measurement approach, such as timestudy, or management opinions, to compile standards for the common elements. The stan-dards are stored in a database. If the time required for a work element depends on certainvariable characteristics of the jobs, an equation that relates these characteristics to the timerequired can also be stored in a database. Once established, the database can provide thedata needed to estimate the normal times for jobs requiring these work elements with vary-ing characteristics. However, allowances still must be added to arrive at standard times forthe jobs.

In addition to reducing the number of time studies or informed opinions needed, theelemental standard data approach can help managers develop standards for new workbefore production begins. This feature is helpful in product costing, pricing, and produc-tion planning.

Although the use of the elemental standard data approach reduces the need for timestudies or opinions, they cannot be eliminated. The analyst should periodically use workmeasurement methods to check the standards developed by the elemental standard dataapproach. Specifying all the job variables that affect times for each work element may be dif-ficult; consequently, this method may not produce good estimates for the normal time.

TUTOR H.3

Tutor H.3 on the Student CD-ROMprovides a new example of determiningthe standard time.


methods timemeasurement (MTM)

A commonly used predetermined datasystem.

PREDETERMINED DATA APPROACH

The predetermined data approach eliminates the need for time studies altogether. The ana-lyst divides each work element into a series of micromotions common to a variety of tasks.The analyst then consults a published database that contains the normal times for thesemicromotions, along with modifications for job variables. The normal time for any task canbe developed by accessing the database.

One of the most commonly used predetermined data systems is methods time mea-surement (MTM). Actually, there are several MTM databases, but we focus on the most accu-rate, MTM-1. In MTM-1 the basic micromotions are reach, move, disengage, apply pressure,grasp, position, release, and turn. The normal times for these micromotions, modified for jobvariables, were developed by trained observers, who applied performance ratings to obser-vations of motion picture studies of workers in various industrial settings.

Each micromotion is measured in time measurement units (TMUs). One TMU equals0.0006 minute. Setting standards from predetermined data involves several steps.

1. Break each work element into its basic micromotions.

2. Find the proper tabular value for each micromotion. Tabular values account for mitigat-ing factors such as weight, distance, size of object, and degree of difficulty.

3. Add the normal time for each motion from the tables to get the normal time for the total job.

4. Adjust the normal time for allowances to give the standard time.

For example, suppose that a worker must move an 18-pound object with both hands toan exact location 20 inches away. The hands are not in motion prior to the move. To find theTMU value for this action, we first go to Table H.1, which describes the move motion. The tableallows for differences in weight, distance moved, and circumstances of the move. Note thatcase C describes the circumstances of this move. Under column C, the entry for 20 inches is22.1 TMUs. Now make adjustments for the weight of the object. The worker is using two hands,so the weight per hand is 9 pounds, which is greater than 7.5 pounds and less than 12.5 poundsin the weight allowance columns. The dynamic factor is 1.11, and the static factor is 3.9 TMUs.To find the final TMU value for this activity, we multiply the tabular TMU value for the dis-tance moved by the dynamic factor and add the static factor: 22.1(1.11) + 3.9 = 28 TMUs.Similar tables are available for other motions.

Advantages and Disadvantages of the Predetermined Data Approach The pre-determined data approach offers some advantages over the other approaches that we havediscussed. First, standards can be set for new jobs before production begins, which cannotbe done with the time study method. Second, new work methods can be compared withoutconducting a time study. Third, a greater degree of consistency in the setting of time stan-dards is provided because the sources of error in time studies, such as data recording errors,are reduced. Finally, this approach lessens the problem of biased judgment because perfor-mance ratings are no longer needed in the derivation of a standard.

The predetermined data approach also has its drawbacks. Work must be broken intomicromotions, making this method impractical for products or services with low repeata-bility. Moreover, the sample of workers used to develop the predetermined data may not berepresentative of the workers in a particular facility.

Furthermore, performance time variations can result from a complex array of factors.For example, the time needed to move an object may depend on the shape of the object, butthe MTM-1 charts do not recognize this factor. Also, the method assumes that the timesassociated with the micromotions simply can be summed to get the total time for a task. Thisassumption disregards the possibility that the actual time may depend on the specificsequence of motions. Finally, there is a danger that the approach will be misused. Althoughthe approach appears to be easy to use, considerable training and experience are required toidentify all the micromotions and accurately judge the mitigating factors of the motion.

WORK SAMPLING METHOD

Work sampling involves estimating the proportions of time spent by people and machineson activities, based on a large number of observations. These activities might include pro-ducing a service or product, doing paperwork, waiting for instructions, waiting for mainte-nance, or being idle. The underlying assumption is that the proportion of time during whichthe activity is observed in the sample will be the proportion of time spent on the activity in

work sampling

The process of estimating theproportions of the time spent by peopleand machines on activities, based on alarge number of observations.


general. Data from work sampling also can be used to estimate how effective machines orworkers are, estimate the allowances needed to set standards for use with other work mea-surement methods, determine job content, and help assess the cost of jobs or activities.

Work Sampling Procedure Conducting a work sampling study involves the followingsteps:

1. Define the activities.

2. Design the observation form.

3. Determine the length of the study.

4. Determine the initial sample size.

5. Select random observation times using a random number table.

6. Determine the observer schedule.

7. Observe the activities and record the data.

8. Decide whether additional sampling is required.

A work sampling study should be conducted over a period of time that is representativeof normal work conditions, in which each activity occurs a representative number of times.For example, if an activity occurs only once a week, the study should probably span several

TABLE H.1 MTM Predetermined Data for the Move Micromotion

Time TMU Wt. Allowance

Distance Hand in StaticMoved Motion Wt. (lb) Dynamic Constant Case and

(in.) A B C B Up to Factor (TMU) Description

3/4 or less 2.0 2.0 2.0 1.7

1 2.5 2.9 3.4 2.3 2.5 1.00 0

2 3.6 4.6 5.2 2.9

3 4.9 5.7 6.7 3.6 7.5 1.06 2.2 A Move object to other hand

4 6.1 6.9 8.0 4.3 or against stop.

5 7.3 8.0 9.2 5.0 12.5 1.11 3.9

6 8.1 8.9 10.3 5.7

7 8.9 9.7 11.1 6.5 17.5 1.17 5.6

8 9.7 10.6 11.8 7.2

9 10.5 11.5 12.7 7.9 22.5 1.22 7.4

10 11.3 12.2 13.5 8.6 B Move object to approximate

12 12.9 13.4 15.2 10.0 27.5 1.28 9.1 or indefinite location.

14 14.4 14.6 16.9 11.4

16 16.0 15.8 18.7 12.8 32.5 1.33 10.8

18 17.6 17.0 20.4 14.2

20 19.2 18.2 22.1 15.6 37.5 1.39 12.5

22 20.8 19.4 23.8 17.0

24 22.4 20.6 25.5 18.4 42.5 1.44 14.3 C Move object to exact

26 24.0 21.8 27.3 19.8 location.

28 25.5 23.1 29.0 21.2 47.5 1.50 16.0

30 27.1 24.3 30.7 22.7

Additional 0.8 0.6 0.85 TMU per inch over 30 inches

Source: Copyright © by the MTM Association for Standards and Research. No reprint permission without written consent from the MTM Association, 16–01 Broadway,Fair Lawn, NJ 07410.


months. However, if the activity occurs continuously throughout the week and from week toweek throughout the year, the study might cover only several weeks.

Sample Size The goal of work sampling is to obtain an estimate of the proportion of timespent on a particular activity that does not differ from the true proportion by more than aspecified error. That is, the analyst wants to take a sample, calculate the sample proportion,

, and be able to say that the following interval contains the true proportion with a specifieddegree of precision:

where

= sample proportion (number of occurrences divided by the sample size)

e = maximum error in the estimate

The sample size affects the degree of precision that can be expected from work samplingfor any desired level of statistical confidence. Work sampling involves estimating propor-tions, so the sampling distribution is the binomial distribution. However, large sample sizesare required for this approach, and the normal approximation to the binomial distributioncan be used to determine the appropriate sample size. Figure H.1 shows the confidenceinterval for a work sampling study. The maximum error can be computed as

where

n = sample size

z = number of standard deviations needed to achieve the desired confidence

Because n is in the divisor of the equation, as n increases, the maximum error decreases. To de-termine the proper sample size for a given error, the analyst uses the formula for e to solve for n:

Initially, the analyst may have to make a reasonable guess for the proportion of time anactivity takes, use the formula to determine n, and then compute an estimate of the propor-tion based on the sample. The new estimate for the proportion can be used in the formulafor n to determine whether additional sampling is required.

Sampling Schedule The times of day the analyst gathers the sample data should beselected at random over the length of the study. This approach reduces the amount of bias inthe data. For example, if employees know that they will be observed each day at 2:30 P.M.,

nze

p p=⎛⎝⎜

⎞⎠⎟

−2

1ˆ( ˆ)

e zp p

n=

−ˆ( ˆ)1

p̂

ˆ ˆ ˆp e p p e− ≤ ≤ +

p̂

p – e p p + e

v v v

Confidence interval

Probability that true proportion will fall

within confidence interval

FIGURE H.1

Confidence Interval for

a Work Sampling Study


some of them may alter their behavior at that time. If that happens, the data will not repre-sent actual performance. After determining the observation times to be used, the analyst candevelop a schedule for the observer.

Activity

RN

LVN

Accessing records

124

28

Attending to patients

258

251

Other support activities

223

46

Idle or break

83

19

Total observations

688

344

FIGURE H.2

Results of the Initial Study

Using Work Sampling Data for Decision MakingEXAMPLE H.4

The hospital administrator at a private hospital is considering a proposal for installing an automated medicalrecords storage and retrieval system. To determine the advisability of purchasing such a system, the administra-tor needs to know the proportion of time that registered nurses (RNs) and licensed vocational nurses (LVNs) spendaccessing records. Currently, these nurses must either retrieve the records manually or have them copied andsent to their wards. A typical ward, staffed by eight RNs and four LVNs, is selected for the study.

a. The hospital administrator estimates that accessing records takes about 20 percent of the RNs’ time andabout 5 percent of the LVNs’ time. The administrator wants 95 percent confidence that the estimate foreach category of nurses falls within ±0.03 of the true proportion. What should the sample size be?

b. The hospital administrator estimates that the annual amortization cost and expenses for maintaining thenew automated medical records storage and retrieval system will be $150,000. The supplier of the newsystem estimates that the system will reduce the amount of time the nurses spend accessing records by25 percent. The total annual salary expense for RNs in the hospital is $3,628,000, and for LVNs it is$2,375,000. The hospital administrator assumes that nurses could productively use any time saved by thenew system. The pilot work sampling study resulted in the data shown in Figure H.2. Should the adminis-trator purchase the new system?

SOLUTIONa. Using estimates for the proportion of time spent accessing records of 0.20 for RNs and 0.05 for LVNs, an

error of ±0.03 for each, and a 95 percent confidence interval (z = 1.96), we recommend the following sam-ple sizes:

Eight RNs and four LVNs can be observed on each trip. Therefore, 683/8 = 86 (rounded up) trips are neededfor the observations of RNs, and only 203/4 = 51 (rounded up) trips are needed for the LVNs. Thus, 86 tripsthrough the ward will be sufficient for observing both nurse groups. This number of trips will generate 688observations of RNs and 344 observations of LVNs. It will provide many more observations than are neededfor the LVNs, but the added observations may as well be recorded as the observer will be going through theward anyway.

b. Before using the estimates from the work sampling study, we must be sure that additional sampling is notrequired. Figure H.2 shows that RNs accessed records 124 times and LVNs only 28 times. The computeroutput shows that the proportion of working time spent on accessing records is 0.1802 for the RNs and0.0814 for the LVNs. Thus, the original estimates were off the mark. The computer uses the new estimatesfor the proportions in the same formulas we used in part (a) to revise the sample sizes. However, the new

RN:

LVN:

n

n

=⎛⎝⎜

⎞⎠⎟

=

=

1 960 03

0 20 0 80 683

1

2..

( . )( . )

..

.( . )( . )

960 03

0 05 0 95 2032⎛

⎝⎜⎞⎠⎟

=

> MANAGERIAL CONSIDERATIONS IN WORK MEASUREMENT < H.11

Overall Assessment of Work Sampling The work sampling method is used frequentlyto estimate the proportion of time that people or machines spend on particular activitiesbecause it offers certain advantages over other approaches. No special training is requiredfor the observers, no stopwatches are needed, and several studies can be conducted simulta-neously. In addition, workers themselves often prefer this method of work measurementbecause it typically is directed at the activities of groups rather than individuals.

The major disadvantage to work sampling is the large number of brief observationsrequired to provide a reasonable degree of precision for the estimate. Unlike the otherapproaches discussed, this method usually is not used for setting standards for repetitive,well-defined jobs.

> MANAGERIAL CONSIDERATIONS

IN WORK MEASUREMENT <In light of new technologies and management philosophies, managers should carefully evalu-ate work measurement techniques to ensure that they are used in ways that are consistentwith the firm’s competitive priorities. Balancing the need to control operations and the needfor employee involvement is a difficult task. Traditional work measurement techniques oftenare viewed as repressive and not conducive to good management–employee relations.Nonetheless, management needs the data in order to measure outputs and the results ofprocess improvements.

Technological change is another reason to reexamine work measurement techniques.For example, when a firm increases its level of automation, its methods of work measurement

sample sizes are smaller than those already used, so no additional sampling is required. If the sample sizeswere too small for the proportions found, additional sampling would have to be performed. In addition, theconfidence interval shows the range possible in the “true” proportions, based on the results of the pilotstudy. For example, the actual proportion of time spent by the RNs on accessing records could be as low as0.15 and as high as 0.21.

Confidence IntervalTotal Activity Proportion Required

Workgroup Obs. Obs. of Total Lower Upper Sample Size

RN 688 124 0.1802 0.15151 0.2090 631

LVN 344 28 0.0814 0.05250 0.1103 320

Because the nurses will not be using the system all the time, we accept the supplier’s estimate of 25 per-cent to determine the value of the time spent accessing records. Estimated annual net savings from the pur-chase of the automatic medical records storage and retrieval system are

Net savings = 0.25[($3,628,000)(0.18) + ($2,375,000)(0.08)] � $150,000

= $60,760

Decision Point The confidence intervals indicate that the true proportions could be as low as 0.15 for RNsand 0.05 for LVNs. If that “worst-case” situation occurred, the net savings would be

Net savings = 0.25[($3,628,000)(0.15) + ($2,375,000)(0.05)] � $150,000

= $15,737

Based on the results of the work sampling study, the new system appears to be a good investment, providedthe nurses can spend the time saved productively on other duties.


must also change. The need to use traditional work measurement techniques to developwork standards is less for automated operations because many computer-controlled machinescan gather data on their operations. Hence, standards for machines can be set without hav-ing to sample unit processing times. Application of the techniques discussed in this supple-ment can then focus on less prevalent activities that are largely controlled by the pace ofworkers.

1

0.500.500.200.700.751.451.302.75

2

0.553.300.153.450.604.051.205.25

3

0.455.700.255.950.556.501.10

7.60

4

0.608.200.358.550.709.251.10

10.35

0.0570

0.0742

0.0791

0.1000

5

0.5010.850.2511.100.6511.751.30

13.05

t

0.52

0.24

0.65

1.20

RF

1.1

1.2

1.2

0.9

Work Element

Observations

tr

trtrtr

1. Check form completion and signatures

2. Enter claim amounts,check math

3. Determine proportion of claim to be disallowed

4. Generate form letter, enter data for check

Operation: Insurance claim processing Date: 10/07 Observer: Jennifer Johnson

�

FIGURE H.3

> KEY EQUATIONS <

1. Required sample size in a time study:

2. Normal time for a work element: 3. Normal time for the cycle: NTC = ΣNT

NT RF= t F( )( )

nzp t

=⎛⎝⎜

⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

⎡

⎣⎢⎢

⎤

⎦⎥⎥

σ2 4. Standard time: ST = NTC(1 + A)

5. Required sample size in a work sampling study:

nze

p p=⎛⎝⎜

⎞⎠⎟

−2

1ˆ( ˆ)

> SOLVED PROBLEM 1 <For a time study of a health insurance claims-adjusting process, the analyst uses the continuousmethod of recording times. The job is divided into four work elements. Shown in Figure H.3are the performance rating factors, RF, and the continuous method recorded times, r, for eachwork element.

a. Calculate the normal time for this job.

b. Calculate the standard time for this job, assuming that the allowance is 20 percent ofthe normal time.

c. What is the appropriate sample size for estimating the time for element 2 within ±10 per-cent of the true mean with 95 percent confidence?

SOLUTION

a. To get the normal time for this job, we must first determine the observed time, t, foreach work element for each cycle. We calculate the time for each observation by findingthe difference between successive recorded times, r. For example, the time for the fifthobservation of the first work element is the difference between the recorded time whenthat element was completed (at 10.85 minutes) and the time when the fourth observa-tion of the fourth work element was completed (at 10.35 minutes): 10.85 minutes �10.35 minutes = 0.50 minute. Similarly, the time for the fifth observation of the second

> SOLVED PROBLEM 2 < H.13

work element is 11.10 minutes � 10.85 minutes = 0.25 minute. With no extreme varia-tion in the observed times for the work elements, they are representative of the process.All the data can be used for calculating the average observed time, called the selecttime, , and the standard deviation of the observed times, σ. The results of those calcu-lations are given in Figure H.3. Every work element occurs during every cycle, so thefrequency, F, equals 1. The normal times are calculated as

b. Standard time = (Normal time per cycle)(1.0 + Allowances), or

ST = NTC(1.0 + A) = 2.72(1.0 + 0.2)

= 3.264 minutes

c. The appropriate sample size for 95 percent confidence that the select time for work ele-ment 2 is within ±10 percent of the true mean is

nzp t

=⎛⎝⎜

⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

⎡

⎣⎢⎢

⎤

⎦⎥⎥

=⎛⎝⎜

⎞⎠⎟

σ2

1 960 10

0..

...

. ,

07420 24

36 72

2⎛⎝⎜

⎞⎠⎟

⎡

⎣⎢

⎤

⎦⎥

= oor 37 observations

Total minutes= 2 720.

Work element 1: NT min1 = =( . )( )( . ) .0 52 1 1 1 0 572 uuteWork element 2: NT2 = =( . )( )( . ) .0 24 1 1 2 0 288 minuteWork element 3: NT3 = =( . )( )( . )0 65 1 1 2 0..

( . )( )( .780

1 20 1 0minute

Work element 4: NT4 = 99 1 080) .= minutes

NT RF= t F( )( )

t

> SOLVED PROBLEM 2 <A library administrator wants to determine the proportion of time the circulation clerk isidle. The following information was gathered randomly by using work sampling:

Number of Times Number of Times Total Number of Day Clerk Busy Clerk Idle Observations

Monday 8 2 10

Tuesday 7 1 8

Wednesday 9 3 12

Thursday 7 3 10

Friday 8 2 10

Saturday 6 4 10

If the administrator wants a 95 percent confidence level and a degree of precision of ±4 per-cent, how many more observations are needed?

SOLUTION

The total number of observations made was 60. The clerk was observed to be idle 15 times.The initial estimate of the sample proportion is . The required sample size fora precision of ±4 percent is

As 60 observations have already been made, an additional 391 are needed.

nz p p

e= − =

2

2

2

2

1 1 96 0 25 0 75

0 04

ˆ( ˆ) ( . ) ( . )( . )

( . )

or 451 observations= 450 19. ,

ˆ / .p = =15 60 0 25


TABLE H.2 Time Study Results of Hamburger Preparation

Observation

Work Element 1 2 3 4 5 F RF NT

1. Prepare patty 0.45 0.41 0.50 0.48 0.36 1 0.9

2. Cook first side 0.85 0.81 0.77 0.89 0.83 1 1.2

3. Flip, press, and cook other side 0.60 0.55 0.59 0.58 0.63 1 1.2

4. Assemble 0.31 0.24 0.27 0.26 0.32 1 1.0

Normal time per cycle (NTC) =

t

TABLE H.3 Work Element 3 Time Study

Observation

Work Element 1 2 3 4 5 6 7 8 9 10

Revised work element 3 0.45 0.31 0.50 0.48 0.39 0.31 0.44 0.29 0.33 0.40

> PROBLEMS <1. During a time study in a machine shop, five observations

of a milling operation performed by an operator whoserating factor is 95 percent yielded the following times (inminutes): 40, 48, 48, 46, and 42. The allowance for thistype of operation is 15 percent.

a. Determine the normal time for this operation.

b. Determine the standard time for this operation.

2. The manager of Stetson and Stetson Company is trying todevelop a time standard for the powder filling and pack-ing operation. This operation has five work elements,each of which is performed once every cycle. Theallowance for each work element is 18 percent. The oper-ation was studied for 20 cycles, and the following sum-mary data were obtained:

b. Determine the sample size necessary if the estimateof the select time for the work elements is to be within3 percent of the true mean 95 percent of the time.

c. Is the sample size chosen to determine the standardtime adequate? If not, how many additional cyclesshould be observed?

3. A time study involving the preparation of hamburgers atBill’s fast-food restaurant used the snap-back method toobtain the data (in minutes) shown in Table H.2. Allow-ances typically constitute 15 percent of normal time. Theschedule calls for 300 hamburgers to be prepared duringthe lunch rush. If each part-time employee works 190minutes per day, how many employees will be needed?

4. A cook at Bill’s restaurant (see Problem 3) has devised anew method of quickly flipping and pressing hamburgersthat he believes will save time in cooking the second side ofhamburgers (work element 3 in Table H.2). The cook askeda peer to conduct a time study for this work element, withthe results shown in Table H.3. This cook is renowned forsuperior strength and speed in hamburger flipping andpressing. The rating factor for this study is 1.2. Allowancestypically constitute 15 percent of the normal time.

a. What is the average of select times for revised workelement 3? For the revised normal time?

b. What is the revised normal time per cycle? The revisedstandard time?

c. The managers seem very interested in this revisedmethod for work element 3. They say that if they could

Work Select Time Standard Deviation Element (minutes) (minutes)

1 0.40 0.021

2 0.20 0.011

3 0.31 0.018

4 0.15 0.005

5 1.25 0.085

a. Determine the standard time for the filling and pack-ing operation. Assume the rating factor = 1.0.

> PROBLEMS < H.15

be sure the average of the select times for this studywas within ±13 percent of the true average time forthis new method, they could afford to buy healthinsurance for the part-time cooks. How many obser-vations would be required to be 98 percent confidentthat the average of select times for this study waswithin ±13 percent of the true mean?

d. The cook is not only quick with a spatula but alsoquick with a calculator and a bit suspicious of man-agement’s motives. If the average of the select timesfound in part (a) were inflated by 13 percent, howmany cooks would Bill’s restaurant need?

5. The information (in minutes) shown in Table H.4 pertainsto a package filling operation at the Black Sheep WoolCompany. When three bags are full, the third work ele-ment involves transporting the three bags down the lane.What is the normal cycle time for this operation?

6. A time analyst for the Super-Fast speedway pit crewobserved the mechanic in charge of changing both fronttires during a pit-stop practice session. Her job is dividedinto six work elements and a preparation time betweendrills. The element times (in seconds) for the first sixcycles are shown in Table H.5.

a. Calculate the normal time for changing tires.

b. What sample size is appropriate for estimating theaverage time for work element 3 within ±1 percent ofthe true mean with 99 percent confidence?

c. What is the standard time for changing tires if theallowance is 20 percent?

TABLE H.4 Time Study Results of the Package Filling Operation

Observation

Work Element 1 2 3 4 5 6 7 8 9 10 11 12 F RF

1. Fill bag 0.20 0.22 0.24 0.18 0.20 0.21 0.22 0.19 0.24 0.18 0.19 0.25 1.00 1.2

2. Sew closed 0.40 0.38 0.37 0.41 0.41 0.40 0.36 0.37 0.41 0.42 0.39 0.36 1.00 0.8

3. Transport 0.82 0.84 0.73 0.85 0.33 1.1

TABLE H.5 Pit Crew Time Study Data

Observation

Work Element 1 2 3 4 5 6 F RF

1. Wait for car lift 2.9 3.2 2.6 0.5 1.0

2. Remove lugs 3.3 3.8 3.6 3.8 4.0 4.3 1.0 0.9

3. Switch tires 6.4 7.1 6.8 7.3 6.2 6.4 1.0 1.2

4. Tighten lugs 4.1 3.8 3.5 4.9 3.5 4.2 1.0 0.8

5. Move to right side 3.8 — 4.3 — 3.2 — 0.5 1.2

6. Clear away for drop — 2.1 — 2.7 — 2.0 0.5 0.9

7. A time study has been conducted on a cellular telephoneassembly operation. The data shown in Table H.6 (inminutes) were obtained. A standard time within ±3 per-cent of the true mean with 95 percent confidence isdesired.

a. Calculate the standard time for the assemblyoperations.

b. How many more observations will be required?

8. Consider the recorded observations of 10 cyclesof the cup packaging operation, shown in Fig-ure H.4.

a. Determine the select times for each work ele-ment, the normal time for the cycle, and thestandard time per package.

b. Suppose that we want a sample size that gives anaverage time within ±5 percent of the trueaverage 95 percent of the time. Did we makeenough observations? If not, how many moreshould we make?

c. Suppose that all we wanted was a precision of±10 percent. How many additional observationswould we need?

9. Management in a large hospital is planning to installa computer to reduce the time spent by nurses doingpaperwork. First, management needed to know howmuch time nurses spend doing paperwork in order toestimate the potential savings from the computerinstallation. A work sampling study comprising


TABLE H.6 Cellular Telephone Time Study Data

Observation

Work Element 1 2 3 4 5 6 7 8 F RF

1. Assemble unit 0.78 0.70 0.75 0.80 0.79 0.82 0.81 0.80 1.0 1.2

2. Insert batteries 0.20 0.21 0.16 0.19 0.23 0.25 0.24 0.26 1.0 1.0

3. Test 0.61 0.60 0.55 0.57 0.63 0.61 0.62 0.60 1.0 0.9

4. Package 0.41 0.36 0.45 0.37 0.39 0.40 0.43 0.44 1.0 1.1

Work Element

Observations

Date: 1/23 Observer: B. LarsonOperation: Coffee cup packaging

1 2 3 4 5 6 7 8 9 10 t F RF

1. Get two cartons

t

r

2. Put liner in carton

t

r

3. Place cups in carton

t

r

4. Seal carton, set aside

Normal time for cycle:

Allowances (% of total time): 15 % Standard time: minutes per piece

t

r

0.48

0.59

1.33

2.43

2.56

3.24

4.39

4.85

4.94

5.65

6.72

6.82

7.51

8.60

9.14

9.25

9.98

11.10

11.23

11.93

13.04

13.53

13.61

14.29

15.38

15.50

16.24

17.32

17.83

17.93

18.64

19.74

19.83

20.55

21.68

0.5

1.0

1.0

1.0

1.05

0.95

1.10

0.90

FIGURE H.4

500 observations taken at random over a week yieldedthe following data:

10. The manager of a loading dock is concerned about the timespent by his crew in nonproductive activities (e.g., waiting forpaperwork, idle time, etc.). Although he is not sure what thetrue proportion of nonproductive time is, he believes that itis close to 20 percent. If he wants to use work sampling toestimate this proportion with 95 percent confidence, a maxi-mum error of 3.5 percent, how many samples should he take?

11. Mayor Jonathan (Johnny) Johnson of Graft City is runningfor reelection. At a big rally in the city park, volunteers willassemble signs, “A vote for Johnny is a vote for Graft,” tobe placed on front lawns and city property. To ensure thatthe rally will go smoothly, the mayor directs the publicworks department to conduct a preliminary time study toestimate the rate of work and number of city workers thatwill be needed to make signs during the rally. The results(in seconds) are shown in Figure H.5.

a. Because of the chaos and uncontrolled environmentat the city park rally, allowances will be 25 percent ofthe normal time. Determine the normal time for thecycle and the standard time.

b. The mayor doesn’t like to leave things to chance.Suppose that he wants 99 percent confidence thateach work element’s average time from the study is

a. Estimate the proportion of time that the nurses spenddoing paperwork.

b. Construct a 95 percent confidence interval for yourestimate.

c. If an hour of a nurse’s time costs the hospital $40, es-timate the annual savings in cost if the installation ofthe computer cuts time spent on paperwork by 80 per-cent. Assume 24 hours per day, 365 days per year ofoperation.

Activity Number of Observations

Attending to patients 180

Moving between stations 40

Consulting with doctors 60

Taking a break or idling 50

Doing paperwork 170

> PROBLEMS < H.17

passports? What proportion of time do the clerksspend on each activity?

b. If a machine to sell special stamps could be purchasedoutright for $3,500, would you recommend buying it?Discuss.

14. As manager of an encoding department in a bank, you areconcerned about the amount of time your encoder clerkshave to spend cleaning their machines because of mal-functions. You obtained a proposal to modify the designof the machines to reduce the number of malfunctions.The modification will reduce the amount of time spentcleaning the machines by 75 percent. You employ 20encoder clerks at an average salary of $36,000 for working2,000 hours per year. To help you decide whether the pro-posal is worth considering, you had a pilot work samplingstudy made, which provided the following results:

Work Element

Observations

Date: 9/27 Observer: Jerimiah (Jerry) JohnsonOperation: Yard sign assembly

1 2 3 4 5 6 7 8 9 10 t F RF

1. Get stake and sign

t

r

2. Put glue on stake

t

r

3. Place sign, four staples

t

r

4. Check assem., set aside

Normal time for cycle:

Allowances (% of total time): 25% Standard time: seconds per piece

t

r

8

1 4

25

30

39

46

60

64

70

75

90

97

1 07

1 1 2

1 26

1 32

1 42

1 51

1 68

1 76

1 81

1 85

1 96

1 99

207

21 4

236

245

254

259

270

276

282

285

298

303

31 2

31 6

338

343

1 .0

1 .0

1 .0

1 .0

1 .05

0.8

0.9

1 .2

FIGURE H.5

a. Estimate the value of the annual labor savings frommodifying the encoding machine design.

b. Construct a 95 percent confidence interval foryour estimate. Would you suggest a larger samplesize? Why? (Hint: Base your confidence intervalon the normal approximation to the binomialdistribution where the standard error is

.)σp p p n= −ˆ( ˆ)/1

If the department wants a 99 percent confidence leveland a degree of precision of ±0.01, how many more obser-vations are needed?

13. The manager of the Valley Forge post office is interestedin the amount of time that window clerks spend on ancil-lary services such as selling special issue stamp sets orcommemorative T-shirts and helping customers withpassport applications. Three clerks, each earning $36,000per year, staff the windows. When they are not needed atthe window, they sort mail for the carriers. The results of apreliminary work sampling study are shown in Table H.7,where entries reflect number of occurrences.

a. For a degree of precision of ±0.05, is the sample sizeadequate for special stamp sets? For T-shirts? For

within ±5 percent of the true average. Did the publicworks department make enough observations? If not,how many more should be made?

12. The information systems department of Universal LifeInsurance Company wants to determine the proportion oftime that the data entry operator is idle. The followinginformation was gathered randomly using work sampling:

Number Number Totalof Times of Times Number of

Date Clerk Busy Clerk Idle Observations

8/22 11 2 13

8/23 12 3 15

8/24 11 3 14

8/25 12 4 16

8/26 13 1 14

8/27 13 3 16

8/28 6 6 12

Activity Observations

Processing checks 52

Cleaning machine 15

Other duties 25

Breaks 8

Total 100


Time

Monday

Tuesday

Wednesday

Thursday

Friday

S

I

S

R

R

R

R

S

S

R

B

I

R

R

S

R

R

R

I

B

R

R

R

S

B

R

S

I

R

S

S

S

R

S

R

R

R

R

B

I

8 9 10 11 12 1 2 3 4 5

S = Setup R = Running I = Idle B = Breakdown

FIGURE H.6

ADVANCED PROBLEM

Problem 15 requires prior reading of the Simulation supplement.

15. You have been asked by your boss to make a presentation atthe next management committee meeting on the methodol-ogy of work sampling and its use in your machine shop. Aconsultant has recommended this approach to manage-ment for use in estimating the proportion of nonproductivetime for production equipment, such as a punch press. Thecommittee members want an insider to brief them on thismethod. Sampling in real time is not possible during themeeting, so you decide to develop a chart that is a “virtualrepresentation” of use of the punch press in the “realmachine” shop. The chart is to cover all time intervals duringthe five working days of the week. To develop this virtualrepresentation of the actual operation, you ask an assistantto observe it each day of the week and record running,setup, idle, and breakdown times along a time line from 8:00A.M. to 5:00 P.M. After making the observations, your assistantsummarized his findings in a chart, as shown in Figure H.6.You intend to use this chart to simulate work sampling,thereby executing a work sampling plan in minutes thatwould normally take a week. You can then compare the pro-portions of time devoted to different activities estimated

TABLE H.7 Valley Forge Work Sampling Data

Day Selling Postage Priority Mail Special Stamp Sales T-Shirt Sales Passports Other Total

1 6 1 1 2 10

2 6 1 1 1 1 10

3 9 1 10

4 6 1 1 1 1 10

5 8 1 1 10

6 7 2 1 10

7 7 1 1 1 10

8 6 1 1 2 10

9 8 1 1 10

10 6 3 1 10

from the sample with the actual proportions and explainhow to obtain estimates corresponding to any desired confi-dence level and within any specified maximum error.

a. Use a random number table to select 20 times duringthe week you will “observe” the punch press. Use arandom number first to select the day and then useanother random number to select the time of day.Omit the time period 12 P.M. to 1 P.M. each day becausethat is lunchtime, during which the machine will beshut down. Put these 20 times in an observationschedule.

b. Using your observation schedule, determine fromFigure H.6 what the machine is doing from Figure H.6at these times. Determine the sample proportion ofthe time spent in each category.

c. What are the actual proportions of time spent in eachcategory from Figure H.6 ? How do they compare withthe sample estimates?

d. Determine the sample size needed to ensure accuracywithin 4 percent with 95 percent confidence.

e. Based on your experiment, what can you tell manage-ment about sample sizes and the accuracy of theestimates?

> CASE < H.19

CASE The Facilities Maintenance Problem at Midwest University

Sean Allen is the manager in charge of facilities maintenanceat Midwest University. Located on a 500-acre tract of landoutside St. Louis, Missouri, Midwest University is home to15,000 students. Allen is responsible for maintaining all thephysical facilities on campus, which comprise 60 buildings.They include dormitories, academic buildings, administra-tion and office buildings, two athletic stadiums, and a basket-ball coliseum. To carry out this function Allen manages a large,diverse workforce that has traditionally been segmented byskilled craft into electricians, carpenters, plumbers, painters,heating and air conditioning specialists, masons, dry wallers,and so on. Allen also is responsible for the custodial andcleaning crews for each facility.

A recurring nightmare for Allen has been the inability offacilities maintenance to respond quickly to work-orderrequests. A review of the data indicated that a response timeof 5 to 10 days was not unusual. This was unacceptable.

Allen applied what he had learned in a series of continu-ous improvement workshops that focused on problem iden-tification, data collection and analysis, and problem resolu-tion. He soon discovered that 85 percent of the work-orderrequests took less than an hour to handle. Furthermore,almost 40 percent of the requests were for routine mainte-nance items such as clogged drains, burned-out light bulbs,and loose towel racks. His analysis led him to the conclusionthat an ineffective organizational structure was a primarycause of the long response times.

Facility maintenance personnel were grouped by craftand centrally located at the physical plant offices. As workorders were received, Allen would try to prioritize the requestsand allocate craft personnel to fix the problem. Schedulingwork to be done was complicated. Both the importance of thejob and the location had to be considered. Maintenance per-sonnel often spent a large portion of their time traveling backand forth across campus, going from one job to the next.Allen also discovered that jobs frequently could not be com-

pleted because more than one type of craft was required. Forinstance, repairing a set of wall-mounted bookshelves in adormitory room required both a carpenter and a painter.Personnel in each craft were scheduled independently.

As Allen thought about what to do, he kept coming backto what he had learned in the continuous improvement work-shops about “getting closer to the customer” and establishingcross-functional work teams that focus on processes, not out-puts. A new structure with enhanced job responsibilitiesmight just be the answer. The big questions were “What kindof organizational structure would make sense?” and “Howcould he minimize time spent traveling back and forth acrosscampus and more effectively utilize his skilled craftspeople?”

Finally, there was the issue of implementation. After hehad designed a new organizational structure and establishednew job responsibilities, how could he get the facilities main-tenance personnel to support the changes? One phrase keptgoing through Allen’s mind: “You get what you measure.” Inaddition, any reorganization would mean a realignment ofemployee performance evaluation and recognition procedures.

QUESTIONS

1. How would you restructure the facilities maintenanceorganization at Midwest University?

2. What can Sean Allen do to alleviate the problem of exces-sive travel time for work crews?

3. As Allen redesigns job responsibilities, how should heevaluate his personnel’s performance? What should hemeasure? How should he reward employees?

Source: This case was prepared by Dr. Brooke Saladin, Wake ForestUniversity, as a basis for classroom discussion.


> SELECTED REFERENCES <Ellis, Christian M., and Lea A. P. Tonkin. “Mature Teams Rewards

and the High-Performance Workplace: Change and Oppor-tunity.” Target, vol. 11, no. 6 (1995).

Gephart, Martha A. “The Road to High Performance.” Trainingand Development, vol. 49 (June 1995), pp. 29–44.

Hammer, Michael. “Reengineering Work: Don’t Automate,Obliterate.” Harvard Business Review (July–August 1990),pp. 104–112.

Herzberg, F. “One More Time: How Do You Motivate Employ-ees?” Harvard Business Review (September–October 1987),pp. 109–120.

Katzenbach, Jon R., and Douglas K. Smith. “The Discipline of Teams.” Harvard Business Review (March–April 1993), pp. 111–120.

Knights, David, Hugh Willmott, and David Collision, eds. JobRedesign. Hants, England: Gower, 1985.

“Motorola: Training for the Millennium.” Business Week (March 28,1994), pp. 158–162.

Niebel, Richard W. Motion and Time Study, 8th ed. Homewood,Ill.: Irwin Professional Publication, 1988.

Schonberger, Richard J. Building a Chain of Customers: LinkingBusiness Functions to Create the World Class Company. NewYork: Free Press, 1990.

Sherman, Stratford. “Levi’s: As Ye Sew, So Shall Ye Reap.” Fortune(May 12, 1997), pp. 104–116.

“What the Experts Forgot to Mention.” Inc. (September 1993),pp. 66–77.

“When the Going Gets Tough, Boeing Gets Touchy-Feely.” Busi-ness Week (January 17, 1994), pp. 65–67.

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