By contracting with a consultant who has had experience in implementing quality, an organization is able to purchase a sufficient pool of experience-based knowledge that is necessary to begin implementation. As it utilizes this pool of knowledge, it gains its own experience, and becomes more independent of the consultant. In essence, experience is the translation into reality of the true state of vision of the organization. In other words, experience is the "footprint" of the system in place. When experience is effectively utilized in connection with the other dimensions of quality, the experience of each interaction with the customer becomes a positive "moment of truth.
It is our understanding of the system that gives us the ability to measure the footprint and properly interpret the measurement. But it is our understanding of the footprint that gives us the ability to verify whether the desired system is actually in place. It is through following Dr. Deming's Plan-Do-Study-Act cycle that we make assumptions about our system, implement those assumptions, study the validity of those assumptions by measuring the footprint which is left by acting on those assumptions, and confirm or modify those assumptions based on the results of our measurement.
The Second Dimension of Quality: Measurement. Measurement gives quality the first of its multidimensional characteristics. Measurement provides the ability to not only assess that something was done experience but also to determine how well or how poorly it was done. Measurement has always been a characteristic of a quality system. Even primitive quality systems, founded on detection and inspection techniques, utilized measurement one-dimensional measurement to determine whether a part was accepted or rejected. As quality thinking evolved focus turned to standards, such as "zero defects" propounded by Philip Crosby.
With this, the focus went beyond acceptance or rejection of the individual part to a focus on a standard of performance two-dimensional measurement. However, it was Dr. Deming who provided enlightenment about the real power of measurement through use of statistical measures to understand operational processes. If a process is in control, says Dr. Deming, it will produce parts similar to the parts it has always produced under similar circumstances.
In that case, any improvement in quality must come from changes to the system itself the responsibility of management rather than from operator changes. Thus, three-dimensional, process measurement can be extremely valuable in understanding and improving a system or process. The measurement dimension utilizing statistical tools such as the check sheet, the Pareto chart, the histogram, the run chart, and the control chart provides us with knowledge of the system and permits us to then structure interaction with the system for the greatest efficiency. A new insurance agent, using a tracking technique provided by the insurance industry, tracked his client and referral contacts.
Through use of these methods he was able to generate sales in the first quarter of his second year that almost equaled his total first year volume. Systems thinking transforms a quality system beyond a shallow, two-dimensional system to one that is dynamic, integrated, and leveraged. The ability to see one set of data plotted against another set of data reveals relationships and common threads. From these, inferences can be drawn that begin to define the quality system and set its parameters. Then, as relationships begin to take shape--in both static and dynamic form--the full power of the system is realized.
Operationally, systems thinking is the fourth step of Dr. Deming's Plan-Do-Study-Act cycle. It is through standardization of processes which are effective that the system is established for consistent efficient processing of information or resources. The two basic forms of system thinking are static and dynamic. Static systems thinking captures a process or system as of a single point in time to show the flow of a process as each point in the process anticipates the flow of goods or services through it. Static methods include flow-charting, "fishbone" cause-effect diagrams, and other diagrams which show the relationship of one part of a system to the other parts or which show factors which lead to or are responsible for other factors.
The flow chart identifies physical components of a system. Each point in the system can be used to establish measurement points which provide insight as to how the system is working at that point in the process. The cause-effect diagram identifies the logical points in a system, and it can assist in determining the root cause of a problem in a system. It identifies the various parts of the system that might account for the result achieved and shows those in relationship to the other parts of the system.
No system is frozen in time or motion, but rather is dynamic as it receives the inputs of the system or process, applies resources to further processing in a unique physical and socioeconomic environment, and provides a product to the next process or system or stage. Dynamic systems thinking captures the interrelationship among all the parts of the system as they dynamically interact with one another in their environment. The language of dynamic systems thinking is best described by Peter M.
These are then constructed in "sentences," or system archetypes, which show basic patterns of interaction common in systems. Since dynamic systems thinking describes underlying forces, it provides us with knowledge about the underlying paradigms or rules or frames of reference in which the system is operating. The third dimension also addresses the impact of interpersonal relationships on trading relationships.
New research in relational economics has revealed that where there is a relationship, a buyer will pay more and a seller will accept less. But more important than that, the trade begins to take on a new dimension. As the relationship improves, the trade flows from the relationship rather than the relationship from the trade, and price becomes less of a consideration.
The implications of this are profound. A legal administrator of a law firm indicated that for the better established attorneys it is a common occurrence for clients to call with new business repeatedly, without regard to price. At some point, little or no consideration is given to other suppliers of a product or service because the trade is based on the relationship. Were it not for the relationship, price would be a major factor, and convenience trading would take place in order to find the best product to satisfy the need at the lowest price.
The first three dimensions give us the ability to establish a system, as we measure the results of relationships among various parts of the system and make modifications necessary to produce the desired results. However, a system existing only in three dimensions is a closed system. In traditional systems thinking, it is the "black box. The drawback of three dimensional thinking is that no system exists in isolation.
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As we begin to think through the entire process, we begin to see that each part is integrally inter-connected with other parts and other systems which cannot be ignored. If three dimensional thinking is used as an end in itself rather than as a means of understanding a component of a universal system, then significant external impacts can be ignored, to the detriment of the system.
Deming notes the example of two suppliers who produced the same part for a customer. One part worked, and one did not. Both were produced according to the specifications of the customer. The supplier whose part worked understood how the part was to be used by the customer; the other supplier did not. The other viewed its role as a separate system merely providing inputs to another separate system. The fourth dimension gives us the ability to look beyond three dimensional thinking to the inter-connectivity of all systems and processes.
This gives us the power to understand the paradigm, or set of rules or guiding principles, upon which a system is based. With this thinking, we understand not only how the system works, but why it works as it does.
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It is dynamic systems thinking that gives us the power to assess the underlying undercurrents which explain the behavior of the system. Once the appropriate paradigm is learned, everything in the system will be explained by that paradigm. Thus, the fourth dimension provides the underlying logic of the system.
The footprint of experience which the system leaves can be, and universally is, interpreted under various paradigms. If the paradigm being used to explain the system mismatches the paradigm under which the system actually operates, then there will be "inconsistencies" in the system which are not explainable. Joel Barker notes that when a system reaches the point at which the inconsistencies appear insurmountable, we begin to look for a new paradigm which will explain our current understanding of the system, account for inconsistencies, and resolve the unresolvable problems of the system.
When a product of the system is inconsistent with the paradigm under which the system is operated, then the result is illogical. This is one reason change is resisted in an organization. Change is generally inconsistent with the operational paradigm even though it may be completely consistent with and thus logical under the true underlying paradigm. As a result, traditionally the impetus for change has come only at a time of crisis, when it has become clear that the existing paradigm is inadequate. This occurred in Japan shortly after World War II as a part of the reconstruction effort, and in the United States in the 's in response to the "quality crisis.
Consequently, a national focus on "Quality or Else" and Dr. The power of inter-connectivity is that it provides a foundation for quantum leaps in quality improvement. Once we begin to understand paradigms, we begin to realize that we can pre-select, or plan, the paradigm rather than just describe it. This then provides the power for comprehensive cultural change in an organization. Under traditional management methods, focus on behavioral psychology led us to attempt cultural change through change in behavior.
Major resistance was encountered, however, because the proposed change in behavior was inconsistent with the existing paradigm. Consequently, even if behavioral change took place, it tended to drift back to former patterns of behavior which belonged to the operational paradigm because the paradigm never changed. The value of planning the paradigm is that once the paradigm is defined and understood, the behavior will naturally follow the paradigm. This creates a flow mechanism for change rather than the push or pull mechanism of behavioral psychology. Thus, change can be accomplished much more effectively in an organization by shifting the paradigm and letting behavioral changes naturally flow with the new paradigm rather than attempting to change behavior directly.
Peter Scholtes of Joiner Associates 16 described a situation in which a firm's bereavement policy was three pages long and required the employee to follow a complicated procedure in order to obtain three days bereavement leave. The firm leadership reviewed the underlying paradigm of the policy and determined that it was written for the five percent of their employees whom they could not trust to not abuse the policy.
The policy became one paragraph which essentially said that an employee could take bereavement leave upon approval of his or her supervisor. This shift from a non-trusting paradigm to a trusting paradigm had a significant impact on the firm.
The incidence of use of bereavement leave increased dramatically. In this example, the shift in paradigms or, more correctly stated, the redesign of the system to reflect the existing underlying paradigm resulted in an actual change of behavior consistent with the new paradigm which could never have been obtained by asking people to reduce their use of bereavement leave under the old non-trusting paradigm. In fact, the behavioral approach of requesting employees to reduce their use of bereavement leave would have reinforced the undesirable non-trust paradigm.
Shifting of paradigms generally does not involve imposing an entirely new paradigm on an organization. Usually inefficiencies in a system are the product of an operational paradigm which is inconsistent with an underlying paradigm. By uncovering the underlying paradigm and permitting the system to reflect it in operation, the organization is able to eliminate inconsistencies which create inefficiencies.
As the new paradigm is discovered or un covered and applied, it provides the new logic to support the change. Thus, by planning the paradigm, change becomes a logical extension of the new paradigm rather than an illogical, inconsistent application of the old operational paradigm. The entire movement to employee empowerment and Dr. Deming's focus on employee involvement and on removing barriers that rob people of pride in workmanship is reflective of this concept. The older management styles created an operational paradigm which was inconsistent with the underlying employee paradigm of self-worth.
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Deming teaches, the employees must be permitted to see their part in the process. Permitting this paradigm to surface and become a part of the operating system empowers the employees to better, more efficiently utilize their knowledge and skills to improve the system, with which they, as front line workers, are far more familiar than managers who are functionally separated from the actual operations.
Separation of the decision power from the knowledge power created inefficiencies that the new empowerment paradigm resolves. The competition paradigm is a second dimension paradigm which breeds bureaucracy and destroys the system. Focus is directed toward "what others can do for me" and "what resources can I have," when often resources could be better directed to other departments or functions.
When departmental lines are broken down, a fourth-dimensional partnership paradigm begins to emerge as each participant realizes there is greater value in working together than in working against each other. At the Michigan State Bar Foundation, data entry involves entry of the interest and service charges on about 4, bank accounts each month. This involved entry of the account number and then interest and service charges. Some account numbers were as long as 15 digits, creating significant room for error.
A shift in thinking permitted the staff to realize that the computer already "knew" which accounts were associated with each bank, so "blank" transactions could be created by the computer for each account, and they could be called up in the order in which they appeared on the remittance form. This eliminated the need to enter each account number, significantly reducing data entry time. But more importantly, with the new shift in thinking, the data entry person began to voluntarily take on new functions to utilize the time saved by the data entry procedure. This involved balancing and posting the transactions, freeing the time of the finance staff for other functions.
There is a universal paradigm that provides a foundation for a complete quality system. Woodall WH: The Use of control charts in health-care and public-health surveillance. J Qual Technol. Qual Saf Health Care. Collins G, Jibawi A, McCulloch P: Control chart methods for monitoring surgical performance: a case study from gastro-oesophageal surgery. Crit Care Med. Kirkham JJ, Bouamra O: The use of statistical process control for monitoring institutional performance in trauma care.
J Trauma. J Thorac Cardiovasc Surg. Montgomery DC: Other univariate statistical process monitoring and control techniques. Alwan LC: Effects of autocorrelation on control chart performance.
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Winkel P, Zhang NF: Serial correlation of quality control data - on the use of proper control charts. Scand J Clin Lab Invest. Statistical development of Quality in Medicine. J Eval Clin Pract. Moran J, Solomon P: Mortality and Intensive Care volume in ventilated patients, , in the Australian and New Zealand bi-national adult patient intensive care database.
J Crit Care. Risk prediction of hospital mortality for critically ill hospitalized adults. Cook DA, Coory M, Webster RA: Exponentially weighted moving average charts to compare observed and expected values for monitoring risk-adjusted hospital indicators. BMJ Qual Saf.
Shiskin J: Decomposition of economic time series. Montgomery DC: Cumulative sum and exponentially weighted moving averaged control charts. Reynolds MR, Stoumbos ZG: Comparisons of some exponentially weighted moving average control charts for monitoring the process mean and variance. Zhang NF: Statistical control for autocorrelated data. Fang Y, Zhang J: Performance of control charts for autoregressive conditional heteroscedastic processes. J Appl Stat. Nonlinear Anal-Theor. J Time Ser Econom. J Monet Econ. Pierce DA: Trend and autocorrelation. Commun Stat. Tsay RS: Asset volatility and Volatility models.
Edited by: Tsay RS. J Econ Perspect. J Bus Econ Stat.
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J Oper Res Soc. Sociol Method Res. StataCorp: tssmooth exponential -Single-exponential smoothing. Time Series Manual: Release Bisgaard S, Kulahci M: Quality quandaries: the effect of autocorrelation on statistical process procedures. Qual Eng. Box G, Narasimhan S: Rethinking statistics for quality control. Apley DW, Lee HC: Robustness comparison of exponentially weighted moving-average charts on autocorrelated data and on residuals.
Ann Thorac Surg. Int J Qual Health Care. Lwin T: Parameter estimation in first-order autoregressive model for statistical process monitoring in the presence of data autocorrelation. J Stat Plan Infer. Commun Stat-Theory. Runger GC: Assignable causes and auto correlation: control charts for observations or residuals?.
Apley DW: Time series control charts in the presence of model uncertainty. Lee HC, Apley DW: Improved design of robust exponentially weighted moving average control charts for autocorrelated processes. Qual Reliab Engng Int. Zhang NF: A statistical control chart for stationary process data. Med Care. Crit Care Resusc. J Stat Softw. Bottle A, Aylin P: Predicting the false alarm rate in multi-institution mortality monitoring.
Marshall T, Mohammed MA, Rouse A: A randomized controlled trial of league tables and control charts as aids to health service decision-making. J Appl Econ. Pan X, Jarrett JE: Why and how to use vector autoregressive models for quality control: the guideline and procedures. Qual Quant. Stat Model. Comput Stat Data An. Download references. Correspondence to John L Moran. Both authors read and approved the final manuscript. This article is published under license to BioMed Central Ltd.
Reprints and Permissions. Search all BMC articles Search. Abstract Background Statistical process control SPC , an industrial sphere initiative, has recently been applied in health care and public health surveillance. Methods Monthly mean raw mortality at hospital discharge time series, —, at the individual Intensive Care unit ICU level, were generated from the Australia and New Zealand Intensive Care Society adult patient database.
Results The overall data set, , consisted of records from ICU sites; average raw mortality was Conclusions The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. Open Peer Review reports. Statistical analysis i Monthly raw risk-unadjusted and risk-adjusted RA mortality time series at the individual ICU were generated. Formal exegesis proceeded using a single exemplar complete ICU series end Results The overall data set, , consisted of records from ICU sites; mean hospital mortality was