productivity in the engineering disciplines

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  • Productivity in the Engineering Disciplines

    A technique for balancing staff and workload, engineering performance analysis can help

    organizations give their engineers more time to do engineering.

    Keith A. Bolte

    R i s i n g costs, strengthening foreign competition, and increasing demands for profit improvement are forcing American businesses to examine a wide vari- ety of new management techniques to enable them to produce more products and services at a higher level of quality for less cost. Implicit in this shift toward scientific management is the understanding that the real productivity gains of the future will be in the white-collar environment as opposed to the traditional blue-collar efforts. Further, the definition of white collar has been expanded from the rather narrow focus on the administrative/clerical realm to include such functions as data processing, engineering, sales, mar- keting, and materials. Essentially, white-collar em- ployees are those employees who do not directly man- ufacture a product. Under this definition, over 65 percent of the employees in American business today are working in white-collar areas.

    Productivity measurement in engineering

    Within both the manufacturing and service in- dustries, a significant percentage of the total staff are engaged in such engineering disciplines as mechani- cal, quality, test, design, process, electrical, soft- wadhardware, and line maintenance. Historically, the most common form of productivity measurement for an engineering organization has been performance against schedule (PAS). But while PAS is important, it should not be considered as the primary measure- ment of the effectiveness and efficiency of an engi- neering organization, for these reasons:

    1. PAS does not measure productivity. It sim- ply tracks the completion of the milestones within a

    134 National Productivity Review

  • A high-payback area might be an engineering group spending 65 percent of its time on

    administratiue functions.

    project against a schedule, and the schedule is only as good as the time estimates used for developing the tasks and milestones within the project.

    from traditional work measurement programs, which tend to deteriorate with time as measured jobs change. The six phases are:

    2. PAS does not measure quality. Because a project is completed on time does not ensure that the end product of that project has any value.

    3. PAS cannot reflect the efficiency or ineffi- ciency of the engineering staff involved in the project. What is needed is a method of developing perfor- mance indicators that will allow management to as- sess accurately the efficiency and the effectiveness of engineering and other technically oriented operations.

    Engineering performance analysis

    During this authors four years as manager of productivity for Intel Corporation, he and his staff de- veloped a technique for assessing the overall effi- ciency and effectiveness of an engineering organiza- tion and for establishing ongoing measures of performance. Since that time, this technique has been used successfully in other industries. The approach is called engineering performance analysis (EPA).

    Essentially, EPA is a management-control system that ensures that jobs are performed by the ap- propriate skill levels in the most efficient manner pos- sible, given the constraints of the working environ- ment, and that staffing levels are balanced against the amount of work to be done. Once implemented, this control system can:

    0 Highlight problem areas in manpower utili-

    0 Evaluate alternate methods and systems; 0 Balance staff and work load; 0 Measure group performance; 0 Forecast personnel requirements; and 0 Load and schedule work.

    zation;

    The six phases of EPA analysis

    The six phases of the EPA ensure its continu- ing value. In combination, these phases set EPA apart

    1. Position content analysis; 2. Review of functions and methods; 3. Elimination/devolution of tasks; 4. Development of reasonable expectancy

    goals; 5. Establishment of task function relation-

    ships; and 6. Implementation of continuous performance

    reporting.

    Position content analysis (PCA)

    Position content analysis is accomplished through a series of interviews with the management and supervision of each group within the organiza- tion. The overall mission(s) of each group is broken down into the basic work functions as each relates to specific outputs of the group, and the percentage of time expended on each function is estimated. Each function is then broken down into its respective tasks. This stratification allows the separation of tasks asso- ciated with one type of output from similarly named tasks associated with other outputs. Stratification also provides a rational basis for combining tasks within or across output lines when time values have been deter- mined.

    Review of functions and methods

    Once the functions for each group have been identified and the percentage of total time expended on each function has been established, it is possible to identify high-payback areas for productivity im- provements. An example of a high-payback area might be a group that is spending 65 percent of its total time on administrative functions and only 35 percent on engineering-related activities. In such a group, every 1 percent of time that can be eliminated from administrative functions or the transfer of those administrative activities to technical or clerical people

    Spring 1986 135

  • can buy more engineering resources at no additional cost.

    To put this concept in perspective, imagine an engineering group of thirty-five full-time engineers spending 55 percent of its time on administrative functions and 45 percent on engineering-related func- tions. If, through productivity improvements, the ad- ministrative load could be reduced by 10 percent, in effect, the labor hours equivalent to 3.5 engineers would be released for work on engineering-related ac- tivities.

    Once several high-payback areas have been identified, small blue-ribbon task forces are imple- mented. They are charged with the responsibility for correcting the major problems identified. The task forces are given immediate training on whatever tech- nique might be the most effective in solving the prob- lems- for example, work simplification, value anal- ysis, or cause-and-effect analysis.

    Each blue-ribbon task force is then given a charter and a time frame in which to solve a problem. The solutions are divided into two categories-short term and long term. The short-term category includes corrective actions that can be accomplished within ninety days. The long-term category generally in- cludes those solutions that will require assistance from other departments, such as data processing.

    Eliminatioddevolution of tasks

    While the various task forces are engaged in solving the major operational problems identified, in our capacity as consultant we work with the managers and supervisors to evaluate the tasks being performed. The two questions continually asked during this pro- cess are: (1) Should this task be done at all? and (2) If it must be done, is it being done by the right skill level? The overall objectives of this phase are to elim- inate unnecessary work and to devolve nontechnical work from engineers to technicians or clerical staff.

    Thus, there are two major objectives for phases 1, 2, and 3 of the EPA. First, identify and do a preliminary quantification of the actual work per- formed by a group; and, second, strip out the bu- reaucracy and get the organization back to doing what it was chartered to do.

    Phases 4, 5 , and 6, discussed next, are de- signed to prevent the problems of unnecessary or in- appropriate work from recurring in the future and to establish reliable measures of performance.

    Development of reasonable expectancy goals

    Traditional work-measurement programs will not be effective in most analytical disciplines, such as engineering. Staff in these operations do not do the same thing hundreds of times each hour. Their work involves asking questions, solving problems, doing research, and making decisions. Therefore, attempt- ing to set work standards in this type of group is like trying to teach a pig how to sing. It wastes time and annoys the pig. However, it is reasonable to set ex- pectancy goals for how long, on the average, it should take to perform a task or function. Without this type of measurement it is virtually impossible to determine whether or not available human resources are being utilized in the most efficient manner.

    Expectancy goals for each task are determined by the manager or supervisor, with input from his or her staff. When establishing these time goals, the manager or supervisor should review each task in light of three criteria. What is the least amount of time it could take to do this task? What is the maximum amount of time it could take to do this task? What is the realistic average time it takes to do this task? In- dustrial engineers find this methodology most dis- tasteful because of its lack of precision. However, one must bear in mind that finite measurements are not the objective. The objective is the development of reliable performance measures that apply reasonable stan- dards, rather than standards carried out to four deci- mal places.

    Having the managers and supervisors deter- mine the time values overcomes the biggest obstacle to any measurement program-ownership- since they are working with their own numbers.

    Establishment of tasWfunction relationships

    Once time-expectancy goals have been estab. lished for each task, it is possible to group the tasks

    136 National Productivity Review

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