Measurement Design Is an Opportunity to Learn
Publication: Leadership and Management in Engineering
Volume 6, Issue 3
Abstract
Measurement is a critical aspect of leadership. If you don’t have an accurate picture of where you’ve been and how things are working, it’s difficult to know how to improve. A primary benefit of measurement systems is their generation of data that support analysis and learning. However, measurement is often practiced “the same old way,” instead of being seen as an important system of leadership that requires continuous improvement to remain vital. I will summarize three articles leading up to this one to position the importance of measurement, following with a discussion of measurement in the context of leadership and provide examples of some recognized models. Finally, I present the notion that measurement design is an ongoing process, rather than a one-time event. By continuously improving measurements, an organization creates the opportunity to learn more and more about what works and what needs to be improved upon to respond to changing conditions. Hence it follows that measurement presents an important opportunity to learn how better to meet customer needs in providing engineering services.
Douglas Gilbert and I began this LME series with “Structuring Change in Providing Telecommunications Services” (DeVilbiss and Gilbert 2005b) in the April 2005 issue of the Journal. After recounting conditions that created an urgent need to reengineer services, we laid out a change initiative strategy. Several aspects of the strategy were described, yet all were predicated on the foundation of leadership and partnering throughout the process. The strategy included three major aspects: structure (redesign the organizational structure to match changed operational conditions), competence (carefully identify required competencies and match people’s capabilities to requirements), and systems (modeling all processes to provide roadmaps for continuous improvement). Examples of the need for measurement were presented to emphasize that progress must be planned and then tracked to ensure movement in the right direction.
In our second article, “Using Causal Relationships to Prioritize Action” (DeVilbiss and Gilbert 2005c), we examined eight objectives of an organizational vision and identified the cause/effect relationships among them. These relationships allowed us to structure the eight objectives to model the activity flow through the organization as it functioned to serve customer needs. The three primary causal objectives provide insight into areas for developing measurement parameters that capture predictive data. Effectual objectives, on the other hand, yield parameters for historical data. By using a systems theory approach, we posited that organizations could compare predictive and historical data to refine and improve their business model. Eventually this delivers an optimized system and creates the opportunity to recognize variation trends in the predictive measures before declining outcomes are measured in the historical data.
The third article, “Resolve Conflict to Improve Productivity” (DeVilbiss and Gilbert 2005a), appeared in the October 2005 issue. While it was not focused on measurement, it was a logical progression from the first two articles in that it addressed a priority issue of leadership to improve productivity. Specifically, leadership calls for a strategy to identify organizational conflict and go at it to ensure it is resolved. Unresolved conflict is a serious drain on productivity and contributes to unhealthy stress in the workplace. Furthermore, it is difficult to encourage people to be engaged in learning when they are distracted by personal feelings around conflicts brewing with coworkers or partners. The ability to resolve conflict is one of four key dimensions of productive partnering, and we presented a model process for accomplishing this important leadership activity. It follows that measurement around the amount of unresolved conflict would be an inverse predictive indicator of productivity.
In summary, we opened our series with a strategy and case study of a proactive approach to achieving success in significant organizational change initiatives. This presentation introduced the importance of measurement as an integral part of change initiatives. The next article addressed the question of how to determine where to measure performance—in predictive or historical parameters. It further posited the notion that a well-designed measurement system provides inputs to apply systems theory to monitor and control business function. Conflict resolution was chosen for our third article because of the significance of this topic and our desire to share an approach we have found very helpful in our own applications. The fewer unresolved conflicts, the more productive an organization will be.
Which brings us to the present and our intention to argue the significance of measurement as not only an important leadership tool, but also as a key mechanism to promote learning. Specifically, adaptive learning is simply assimilating existing knowledge, while generative learning is actually creating new knowledge. A well-understood measurement-design process can become an organizational norm that allows for dynamic change, which in a rapidly changing business environment is important for survival because it creates the opportunity for generative learning. As Peter Senge (1990) has said, “In the long run, the only sustainable source of competitive advantage is your organization’s ability to learn faster than the competition.”
Measurement and leadership
Lawrence Appley, in Formula for Success, a Core Concept of Management (1974) presents eight processes of leadership:
1.
Inventory—determine where we are now.
2.
Planning—determine what we want people to do.
3.
Organize Human Resources—determine the people needed to do it.
4.
Organize Physical Resources—determine what the people need to do it.
5.
Standards of Performance—determine how well people should do it.
6.
Progress Review—determine how well they do it.
7.
Development and Controls—determine what help people need to do better.
8.
Rewards and Incentives—determine what we will pay.
Of these eight processes, three are related to measurement: inventory, standards of performance, and progress review. Further, if rewards and incentives are tied to business performance, one could argue that half the processes are related. This clearly suggests that measurement is a critical aspect of leadership. Three common axioms that make this point are: “What gets measured gets managed,” “The only alternative to management by data is management by assumption,” and “What gets rewarded gets repeated.” So, from these observations, it is difficult to imagine anyone expecting to practice leadership without having to become comfortable with measurement processes.
If we accept that effective leadership and measurement are closely linked, we must then ask the question, “What is the purpose of measurement?” One obvious answer: “To see how we have done.” However, knowing what an organization has produced is only half the puzzle. What change-friendly organizations also seek is information that tells them how to improve, or what kind of change is needed. So keeping track of performance is one purpose of measurement. Yet the more important and often overlooked purpose is to identify opportunities to get better.
Which brings us back to the importance of cause/effect in measurement systems. By only capturing effectual, or outcome information, we are then left with the challenge of determining the causes of changed performance. While a measurement system that includes causal, or predictive information, yields indications of how changes affect process as well as outcomes. Of course, process influence is the information that best supports continuous improvement initiatives. Consequently we see that it would be a significant factor in proactive and dynamic leadership.
So, what is the challenge in continuous process improvement? It seems evident that an effective program of positive change implies the ability to always be learning. More specifically, it suggests that generative learning is necessary. This is true because generative learning results in new knowledge, or expanding awareness. In other words, continuous improvement requires us to constantly seek new ways of looking at old issues, and to practice diligent investigation to quickly identify new issues. Hence, a measurement system that only produces effectual or historical data cannot support learning as effectively as needed. Therefore the very nature of leadership and continuous improvement dictate that an effective measurement system must provide predictive data as input to timely generative learning.
By recognizing this reality, we can argue that a business’s measurement system is a foundational component of creating a learning organization. So, from this point forward, we need to explore the characteristics of measurement systems that support learning. Specifically, we will address the question, “Is it possible to have a measurement design process that creates opportunities for learning?”
Measurement systems are linked to management strategy
There are two examples of systems we will now explore: the Quality Performance Management System (QPMS) developed by the Construction Industry Institute (CII 1990); and the balanced scorecard developed by Howard Kaplan and David Norton (1996). Both of these systems are designed to provide structure, process, and data for managing business function. QPMS was developed primarily for construction projects and balanced scorecard was developed initially for better managing government function. We will examine these systems; however, there is a simple conclusion available from studying their descriptions and implementation guides.
Upon investigation, it is clear that both systems recognize that measurement must support the management system. Which leads to the unavoidable conclusion that measurement processes must be aligned with the way an organization does business. Further, if an organization chooses to implement one of these example systems, leadership must recognize that organizational and cultural change is necessary. In other words, measurement systems are inextricably linked to management strategy. To try to change one without changing the other is less than fully effective.
QPMS was developed by CII to “present a blueprint for implementing a system to categorize and measure quality-related costs involved in the design and construction of engineered projects. Management can use the information generated to make intelligent benefit/cost decisions regarding quality-related efforts in the execution of projects.” This system is not appropriate for overall project management, but only for capturing the costs associated with producing quality. At the same time it is an excellent example of the systemic nature of measurement and its relationship to management strategy.
QPMS was developed to meet specific criteria (CII 1990), including to:
1.
Be capable of tracking quality-related costs involved in the design and construction of engineered projects and answer the following four questions:
a.
What quality management activities and deviation categories were involved?
b.
When were the quality management activities and deviation costs incurred?
c.
Why did the deviations occur (i.e., their root causes)?
d.
How did the re-work relate to the quality management?
2.
Provide valuable cost-of-quality information to establish baselines and identify opportunities for improvement, without providing either too much or too little detail.
3.
Be adaptable to various types and aspects of design and construction projects.
4.
Be easily implemented by owners, designers and contractors.
5.
Be cost-effective.
6.
Be compatible with existing cost systems used by management.
What is important here is to recognize how carefully the design criteria were described. It is very important to understand what you are trying to accomplish with a management system and how measurements support achieving the system requirements.
CII (1990) also lists a seven-step implementation strategy, saying: “In most companies a ‘corporate cultural’ bias exists against this type of effort, which must be overcome if the QPMS is to be successful. The company will achieve the desired result only by assuring everyone that the results are going to be used to help an organization improve the quality of its operations and the products and services it provides to is customers, thereby improving the organization’s competitive position. Furthermore, the company must assure personnel that the system will not be used as a tool for punishment.” This clearly acknowledges the cultural change element of implementing a management/measurement system. It further tacitly recognizes the risk-averse nature of most company cultures. So, implementing a measurement system must be a carefully planned and communicated process to avoid adverse reactions among staff.
Balanced scorecard, on the other hand, looks at business function as a system and captures process data as a predictive component and outcome data as historical measurement. Paul Arveson (1998) quotes the founders (Kaplan and Norton) of the balanced scorecard, saying:
“The balanced scorecard retains traditional financial measures. But financial measures tell the story of past events, an adequate story for industrial age companies for which investments in long-term capabilities and customer relationships were not critical for success. These financial measures are inadequate, however for guiding and evaluating the journey that information age companies must make to create future value through investment in customers, suppliers, employees, processes, technology, and innovation.”
The balanced scorecard suggests that we view the organization from four perspectives, and to develop metrics, collect data, and analyze it relative to each of these perspectives:
•
The learning and growth perspective (“To achieve our vision, how will we sustain our ability to change and improve?”)
•
The business process perspective (“To satisfy our shareholders and customers, what business processes must we excel at?”)
•
The customer perspective (“To achieve our vision, how should we appear to our customers?”)
•
The financial perspective (“To succeed financially, how should we appear to our shareholders?”)
Upon examination, it is apparent that the first two of these perspectives are process oriented, and the last two are outcome oriented. Arveson (1998) points out that implementing balanced scorecard requires recognition of it as a management strategy, not just a measurement system. He further acknowledges that deciding to use balanced scorecard will require the cultural transformation of an organization. What is not stated is that while this system is comprehensive, it requires the organization to adapt to the system, rather than the system to adapt to the organization.
What I believe is more appropriate is a measurement design system that allows an organization to examine its existing strategies and processes and generate learning on ways to improve the business from the inside out. Such a system was described as “Kentrel” in “Measuring Systemic Unity in a Learning Organization” (French and DeVilbiss 2000).
Kentrel model as a guide to measurement design
Before addressing the specific principles that enable Kentrel to provide a comprehensive measurement design, it is important to address the two dimensions upon which it is based. These dimensions are unity and completeness. Unity relates to harmony and is the dimension of connectedness. Achieving unity amounts to cultivating optimum function. When all aspects of a business operation are unified, they are mutually supportive and none is over- or underworked. Completeness, on the other hand, has to do with capturing the full picture. This relates to having enough information of the right kind to paint the complete picture of what is going on. Incomplete data leaves holes, or blind spots, in the assessment of business function. These blind spots are where “gotchas” come from. The o-ring failure in the Shuttle disaster was the result of incomplete data.
High-quality measurement design must incorporate these dimensions. In other words, we want to capture a comprehensive picture of how harmoniously the business system is functioning. One effective way to do this is to approach measurement design as a repeatable process based in universal principles. If we can identify a set of principles to use as guides in any measurement application, it is possible to develop tailored measurements for any business function, as well as the whole system. It follows that such a process would then generate not only useful data, but a continuous improvement approach, which leads to ongoing learning. Kentrel is based in nine universal principles:
1.
Linkage: This is the principle of a system. We break off part of the system and examine the simpler, isolated part. This is the only way we can grasp it. However, when we get through, we need to ask the question, what else is linked and will be affected?
2.
Finiteness: Finiteness is a driving force for excellence and competition. There is only so much time, money, and human energy available. If there were an infinite amount, we would not need to improve our competitiveness.
3.
Variation: Variation is the thermodynamic and psychological principle found in all science, human projects, learning, and life. It means that we can never do the same thing twice; there will always be variation. Look at the leaves on a tree—no two are identical.
4.
Sameness: As human beings we are paradoxical. We are all the same, yet we are all unique. We all have fingerprints, yet each one is different. We all have intelligence, yet it manifests differently in each of us.
5.
Structure: Structure is the formal intellectual system of who does what and how. Who has authority in what area? Structure divides things, people, and power into functional units. We all are humanly equal but we have different organizational functions.
6.
Security: From the leader’s standpoint, the very existence of the company is part of the daily struggle. Is it strong in the market? Can it handle a new competitor? Security for the worker means assurance that his/her job will be there next week, next year, and that they can count on support from co-workers in times of need.
7.
Mind: Mind refers to our human ability to think, learn, and create. Creativity, education, communication, inventions, and solutions are here.
8.
Feelings: Feelings are just that—our emotions. There are love, hate, joy, sadness, generosity, envy, depression, and many more. Talk to workers in a company that is poorly run and you will find that feelings are a major part of their dissatisfaction, and divert much time and energy from productive work.
9.
Fulfillment: Fulfillment is the human longing that drives us all. We all have things we desire to do, learn, see, and be. This is a driving force for change at the personal level. At the organizational level fulfillment is about having a purpose, then setting goals and striving to meet them.
Three of these principles address the individual: mind, feeling, and fulfillment; three address the group: sameness, structure, and security; and three address the business: linkage, variation, and finiteness. Simply measuring profit does not take into account the health of the people collectively or individually. Similarly, measuring employee satisfaction likely produces little usable information about business function overall. However, by recognizing the completeness of these nine principles, we can use them to cycle through a process of examining comprehensive aspects of any business function.
Measurement design can now be seen as a process of engaging a group of people in systematically examining a business function. By assembling a team of people who have working knowledge of the function and its relevance in the business, we can stimulate robust dialogue by exploring how each of the nine principles operates in that business function.
For instance, take the linkage principle, and apply it to inventory management. One can readily see there must be consideration of both supplier and customer activity. However, upon thorough discussion, it might emerge that linking inventory to cash flow can contribute to data that optimizes inventory levels and minimizes capital frozen in material sitting in a warehouse.
Similarly, the business function of staff levels may be influenced by the fulfillment principle. Without a systematic approach to collecting meaningful measurements, it is easy to overlook the personal aspects of employees leaving and attribute it predominantly to market conditions or other external factors. Many studies have shown that people are influenced less by their financial compensation than by the opportunity to be part of something satisfying. Yet without an approach to guiding attention to this reality, it is easy to overlook.
Learning through measurement design
These simple examples are very limited. Yet they suggest that a systematic process of using the Kentrel model affords businesses the opportunity to broadly examine a business function. By assembling a knowledgeable group and cycling through the nine principles, it is possible to paint a complete picture of how that function is performing and the influence it has on other aspects of the business. This systematic approach generates business measurement data. However, it also creates the opportunity for the group developing the measures to explore unity and learn more about how the overall business system operates.
As an example, let us return to the issue of staff levels. Assume a team of people is assembled with representatives from diverse aspects of the business. Imagine these people discussing the following set of questions:
1.
Linkage: How do staffing levels impact our operational productivity?
2.
Variation: Do turnover rates vary from one department to another?
3.
Finiteness: What does it cost to turn over one high-skill operations position?
4.
Sameness: What values must a prospective employee have to be aligned with our culture?
5.
Structure: Is the job description for each position complete and accurate?
6.
Security: What growth potential would motivate a person to stay in this position?
7.
Mind: What opportunities for learning and development does the position provide?
8.
Feeling: How is the morale of people interacting with this position?
9.
Fulfillment: What contributes to this position providing a satisfying work opportunity?
The beauty of this model and in the application of a structured process is in its universality. It doesn’t matter what the business function is—financial, operational, personnel—these same nine principles afford the opportunity to ask probing questions and explore a complete picture of how that business function affects systemic unity. By creating the discussion, there is a simultaneous creation of the opportunity to learn. The process encourages people to step out of their paradigms and systematically explore business function. Which, of course, creates the opportunity for systemic learning, while generating new and meaningful data to monitor the health of the business.
As aspects of business function are explored, key business parameters can be identified. This is accomplished using cause/effect analyses (DeVilbiss and Gilbert 2005c) to determine critical success factors. For instance, it may be discovered in the above example that a primary causal aspect of staff level management (turnover) is alignment of the employee’s personal values with the core values of the business culture. An individual who values consistency and stability might not fit well into an engineering or construction business culture that values innovation and risk taking. In this case, regardless of the technical competence of the individual, or the need the business has to fill the position, it is likely a poor fit. This type mismatch can produce stress and lessened productivity in both the individual and the business.
In our simple example the business measurement parameter is alignment of employees’ values with the business culture’s core values. Through the structured process of applying the Kentrel model to explore staffing level management, it was recognized that a significant factor was values alignment. Then a simple cause/effect analysis identified this alignment parameter as causal and a critical success factor. Which leads to the conclusion that values alignment is likely a relatively simple, yet powerful predictor of how well prospective employees “fit” the business. The better a candidate fits the business, the more likely he or she will be productive and derive satisfaction from staying with the business for the long haul. So the Kentrel model provides a structure for any business to explore business function and identify primary measurable parameters that indicate the causal aspects of long-term success.
Give it a try!
Summary
This article begins with a summary of three preceding articles that address an approach to managing change, the notion of cause/effect and predictive/historical measures, and conflict resolution. Then measurement is addressed in the context of it being an important aspect of leadership. To lead, one must know where one is and how much progress is being made. Next we provide discussion of how measurement is linked to management strategy. A strategic focus implies recognition of critical aspects of business function, or application of Pareto’s law (the eighty/twenty rule).
The dimensions of unity and completeness are presented to introduce the value of the Kentrel model. Then Kentrel’s nine universal principles of work are briefly described before simple examples of their application are shared. Application of the Kentrel model in a structured process affords the opportunity to design complete measurements for any business function.
Finally the issue of learning is addressed. We suggest that by using the Kentrel model and a structured process for engaging in dialogue, any business creates the opportunity to learn more and more about its overall function and hence systematically improve its unity and effectiveness.
References
Appley, L. (1974). Formula for success: A core concept of management, AMACOM, New York.
Arveson, P. (1998). “What is the balanced scorecard?” Online, ⟨http://www.balancedscorecard.org/basics/bsc1.html⟩ [accessed March 2006].
Construction Industry Institute (CII). (1990). “Quality performance management system (QPMS).” Publication 10-3, CII, Univ. of Texas at Austin, Austin, Tex.
DeVilbiss, C., and Gilbert, D. (2005a). “Resolve conflict to improve productivity.” Leadership Manage. Eng., 5(4), 87–91.
DeVilbiss, C., and Gilbert, D. (2005b). “Structuring change in providing telecommunications services.” Leadership Manage. Eng., 5(2), 29–34.
DeVilbiss, C., and Gilbert, D. (2005c). “Using causal relationships to prioritize action.” Leadership Manage. Eng., 5(3), 62–67.
French, B., and DeVilbiss, C. (2000). “Measuring systemic unity in a learning organization.” J. Manage. Eng., 16(4), 39–46.
Kaplan, R., and Norton, D. (1996). The balanced scorecard: Translating strategy into action, Harvard Business School Press, Boston.
Senge, P. (1990). The fifth discipline: The art and practice of the learning organization, Doubleday/Currency, New York.
Biographies
Carl DeVilbiss is president of Aegis Building Concepts, Inc., in Nashville, Tennessee. He can be reached via e-mail at [email protected].
Information & Authors
Information
Published In
Leadership and Management in Engineering
Volume 6 • Issue 3 • July 2006
Pages: 123 - 128
Copyright
© 2006 ASCE.
History
Published online: Jul 1, 2006
Published in print: Jul 2006
ASCE Technical Topics:
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