Tuesday, April 21, 2015

Operations Improvement Role of Industrial and Systems Engineer - Conception of Gavriel Salvendy

This article is an adaptation of the view expressed by Salvendy in the 2001 Handbook
HANDBOOK OF INDUSTRIAL ENGINEERING

Salvendy states that improving technology to increase efficiency and quality at the work cell level was the initial focus of ISEs. He recommends that now ISEs need to focus at enterprise level and supply chain level.

Salvendy also highlights the role of work measurement as a device to quantify improvement. Then he advocates that many more things are to be measured now and ISE has to come forward and measurement. It is very interesting presentation and every IE needs to read it.


Operations Improvement Role


The traditional role of ISE is that of problem solving and operations improvement. Improvements in efficiency, quality, and technology (e.g., methods, hardware, software, procedures, processes) belong to this category. ISE's use of classical methods improvement techniques, operations research,
human factors, modern manufacturing methods or management systems methodology results in changes in how things are done and these changes have to be such that total system performance is improved. Traditionally, ISEs have operated at the work center level. Over the past 30 years (reference to 2001) the scope of the system of interest has broadened.


Unfortunately, industrial engineering tended to lag behind other disciplines in the evolutionary process. Our profession has missed opportunities to continue to add value over the past 30 years.  We believe that the decades to come will provide opportunities for ISE to reintegrate and reposition itself as a leader and doer in the field of performance improvement. This requires rethinking the role and relationship among positioning and strategy, conditions for success, and operations improvement.


The author say that their contention is that the bulk of the Handbook focuses on the traditional ISE role in achieving operations effectiveness. However, in the first chapter, they covered  a couple of areas of operations improvement that they felt might not have been  represented or covered adequately. These ares are: systems and process improvement (more specifically, business process reengineering) and measurement systems.

Business Process Improvement


The term unit of analysis applies to the scope of the system of interest. When IE first began, the unit
of analysis—the scope of the system of interest—was confined to the worker, the work cell, and
individual work methods. Over time, the scope of the system of interest to the ISE has increased to enterprise and now further to supply chain optimization .  Attending to larger units of analysis is a ‘‘transcend and include’’ strategy.

This migration to a larger system of interest also happened to process improvement. The focus on improving embedded processes has shifted to an enterprise-level focus on improving business processes. Once again we see the transcend-and-include principle being required. A business process begins and ends with the customer. Organizations can no longer afford to optimize a subsystem (embedded process) at the expense of the performance of the larger system (business process). So the techniques and methods that were employed to improve smaller processes are being adapted and enhanced with some expertise borrowed from organizational leadership and management of change, creating a whole new line of business for a large group of professionals.


First, systems thinking is required to do BPR. ISEs are trained to think systems. Second, many of the substeps in the process  require specific knowledge and skills that ISEs are grounded in. We understand that ISEs are involved in many BPR efforts in organizations today. We also know that many BPR efforts are information technology-driven and many exclude ISE involvement. We believe this is an error that leads to underperformance.



Building Effective Measurement Systems



Work measurement and methods engineering are terms that have traditionally described actions taken
to quantify the performance of a worker or a work unit and to improve the performance of the
individual and the unit. The relevant body of knowledge has been developed and preserved through
the entire history of ISE. Throughout that history, one principle has served as its unifying force: an
appreciation for and the applied knowledge of systems. In fact, Frederick Taylor (1856–1915), who
is generally recognized as the father of industrial engineering, wrote in 1911, ‘‘The system must be
first.’’ Methods engineering was pioneered by Frank Gilbreth and his wife Lillian, whose lives were
memorialized in the Hollywood film Cheaper by the Dozen. Soon after methods engineering began
to be practiced, the need for measurement technology became clear. This was inevitable. Once analysts proposed improvements to the way a job was done, natural curiosity led to the question ‘‘How much better is it?’’ The ISEs translation of and response to that question led to the development of tools and techniques for measuring work.

More recently, the importance of methods engineering and work measurement was underscored
by the late W. Edwards Deming in his legendary seminars.  He argued that insufficient thought and
planning went into the design of work systems. The lack of sufficient high-quality output, he taught, stemmed not from poor worker attitude, but from poor management and poor design of the methods, tools, and systems we provide to the otherwise willing worker.

Dr. Deming also promoted the ISEs contribution through work measurement with his insistence that decisions regarding process improvements be data driven. In practice, this means that effective  systems improvement activities require evidence as to whether the changes make any difference. The requirement is that we use our measurement expertise to quantify the results of our efforts to design and implement better systems. 

The ability to measure individual and group performance allowed organizations to anticipate work
cycle times, which led to more control over costs and ultimately more profitability and better positioning in the marketplace. Understanding how long it actually takes to do a task led to inquiry about how long it should take to do work through the application of scientific methods. Standard times became prescriptive rather than descriptive. The next step in the evolution was the integration of production standards into incentive pay systems that encouraged workers to exceed prescribed levels of output. Application of extrinsic rewards became an additional instrument in the ISE toolbox,
vestiges of which linger on.

So much for the evolution of the work measurement and methods aspects of traditional ISE
practice.

The following are some evolutionary enhancements that have become part of the ISE measurement
value proposition:

• Statistical thinking plays a more critical role in understanding work performance. Variation is
inherent in all processes and systems. Discovering the underlying nature of variation and managing
the key variables to reduce defect has become now an important activity under name of six sigma.


• The role of production quotas is being reexamined. Should we throw out all standards, quotas,
and targets, as Dr. Deming suggested? We think not. We contend that the effective approach is
to establish a system within which teams of employees hold themselves and each other accountable
for system performance and are encouraged to reduce variation and improve performance
on their own. Standards that control and limit employee creativity should be eliminated.
The key is understanding performance variation and what causes it and creating a partnership
with employees so that they are integral members of the team working to improve it.

• Work measurement and methods improvement became detached, to some extent, from the larger
system of improvement efforts. Today, efforts to improve what workers do and how they do it
is being tied to overall business strategy and actions. This means that measures of performance
at the work unit level will have to be tied to and integrated with measures of performance for
larger units of analysis. Linkages between individual worker and team performance and system level
measures of performance are becoming better understood and managed. Here again, the authors'
message is ‘‘transcend and include.’’ Efforts to understand how long something does or should
take at the employee or work center level will expand to include understanding of how the unit level
systems need to perform in order to fill the treasure chest of the organization.

• Time and quality are no longer the only indicators of organizational performance. The balance score card approach recommends a set of performance indicators, including efficiency, effectiveness, productivity, financial performance, quality of work life, customer satisfaction, and innovation (Kaplan and Norton 1996).

• Visibility of measurement systems and portrayal of performance data are being recognized as
critical elements in the deployment of enhanced measurement systems. Traditionally, a worker
knew the standard and that was it. In the future, employees at every level of the organization
will have continual access to their scorecard indicators. Furthermore, they will be aware of how
these measures are linked to the performance of more inclusive systems. For example, employees
at the checkout counter will understand that their behaviors and attitudes influence whether
the store is a compelling place to shop and will have data to tell them how this helps to fill the
treasure chest and how that affects them. As a result, daily, hourly, moment-to-moment
decisions will be made on the basis of visible data and facts.

The ISE's have to participate in the design, implementation, and maintenance of these comprehensive and very visible measurement systems.

Organizational Systems Performance Measurement


An organizational system is two or more people whose activities are coordinated to accomplish a
common purpose. Examples of organizational systems are a work unit, a section, branch, plant,
division, company, enterprise.


The management system consists of three elements: who manages, what is managed, and how managing is accomplished. In a traditional organization, ‘‘who’’ may be the manager; but in the contemporary organization, ‘‘Who’’ refers to a management team. For the long-range planning horizon, the management team establishes the goals and objectives—the vision—of what the organization is to become. In the short time horizon, levels of system performance must be specified. The ‘‘What’’ is the system that is being managed; the organization, system, or process of interest, the object of the management efforts. ‘‘How’’ refers to managerial processes and procedures and more specifically to the transformation of data about the performance of the organization (‘‘What’’) into information regarding the need for actions or interventions.


The management system model can also be characterized as a feedback or closed-loop control
system. In this version, the management team is the controller (who), the process is the system being
controlled (what), and the instrumentation (how) monitors the system states and feeds these back to
the controller so that deviations between the actual and the desired states can be nulled. The interfaces between each of the elements also represent the management process. Between the ‘‘what’’ and the ‘‘how’’ elements is the measurement-to-data interface. Between the ‘‘how’’ and ‘‘who’’ elements is the information portrayal/information perception interface. And between the ‘‘who’’ and the ‘‘what’’ elements is the decision-to-action interface. Viewed from the perspective of this model, the management of a function would entail:

1. Determining what performance is expected from the system
2. Monitoring the system to determine how well it is performing in light of what is expected
3. Deciding what corrective action is necessary
4. Putting the correction into place
Note that any embedded organizational system is operating in the context of a larger system and
the linkages are critical to total system optimization (Sink and Smith 1994).

This model provides the frame and the outline to be followed in building an effective measurement
system.

What constitutes success for an embedded system must be clearly understood and operationally defined. The model for success must also be operationalized and understood.

Without a clear, specific, focused understanding of what the key result areas and their related key performance indicators are, it is difficult for workers or managers to assess how they are doing and on what basis to make those assessments. The measurement system allows for effective Study (S) in the Shewhart/Deming PDSA improvement cycle. A modern measurement system will have to be comprehensive, well integrated, and strategic as well as operational. It needs to portray causal linkages from the system of interest to the next-larger system. This assists in ensuring that we do not fall into the trap of optimizing the subsystem at the expense of the larger system.

In our experience, ISEs understand measurement perhaps better than other disciplines.  The key to ISE being better integrated to enterprise improvement is that ISEs apply their strengths in a way that avoids suboptimization and clearly ties to the higher organizational good.



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