What is the scientific method
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The document discusses the scientific method and its application to process improvement. It begins by discussing key thinkers who helped establish the scientific method, such as Einstein, Pearson, Broad, Popper, Dewey, Simon, and Ackoff. It then covers concepts like the scientific method, theory development and testing, bounded rationality in decision making, and systems thinking. The document concludes by discussing statistical process control pioneers like Shewhart, Juran, and their contributions to using statistics and understanding process dominance to analyze and improve processes, setting up the DMAIC method as a strategic approach.
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What is the scientific method
- 1. STRATEGICAL APPROACH USING THE HISTORICAL DMAIC APPROACH Michael R. Büchler on Lean & Six Sigma 1
- 2. The scientific method permits advances for mankind: “A theory can be proved by an experiment; but no path leads from an experiment to the birth of a theory.” “A theory is the more impressive the greater the simplicity of its premises is, the more different kinds of things it relates, and the more extended is its area of applicability.” “As far as the laws of mathematics refer to reality, they are not certain; and as far as they are certain, they do not refer to reality.” “Epistemology without contact with science becomes an empty scheme. Science without epistemology is, insofar as it is thinkable at all, primitive and muddled.” “As for the search for truth, I know from my own painful searching, with its many blind alleys, how hard it is to take a reliable step, be it ever so small, towards the understanding of that which is truly significant.“ ‐Albert Einstein‐ Michael R. Büchler on Lean & Six Sigma 2
- 4. What is the sientific method? • There are three key steps in the scientific method: ‐ The origin of a theory or working hypothesis ‐ Experimentation and testing of the theory or working hypothesis ‐ Confirmation and the development of confidence in predictions based on the theory or working hypothesis through the nontrivial replication of results. • The power of this method rests on integration of content knowledge and experience with prediction, experimentation, and confirmation. • In any realm where these elements form the basis for rational decision making, and the non‐trivial replication of results forms the basis for confirmation, the principles of the scientific method are at work. Michael R. Büchler on Lean & Six Sigma 4
- 5. Scientific theory explains reality – actual entities: Theory must be related to phenomena for quality to be scientific: • Good theory fits historical observations flawlessly and must be predictive of new experiences. • Hypothetical theories must be tested to determine validity, not based on assertion or anecdotal commentary. • Scientific theory results from testing and proving hypotheses. “Scientific theory comprises a collection of concepts, including abstractions of observable phenomena expressed as quantifiable properties, together with rules (called scientific laws) that express relationships between observations of such concepts. A scientific theory is constructed to conform to available empirical data about such observations, and is put forth as a principle or body of principles for explaining a class of phenomena.” ~ Merriam Webster Dictionary Michael R. Büchler on Lean & Six Sigma 5
- 6. Presenting science as free from metaphysics of belief: Karl Pearson (1857‐1938) British Mathematical Statistician The Grammar of Science (1892) Addressed the issue of how the concepts of dynamic science could be learned free from the impositions of metaphysical assumptions. • “All science is description and not explanation.” • “The science of the future will replace knowledge by belief in the perceptual sphere, and will reserve the term ‘knowledge’ for the conceptual sphere – the region of their own concepts and ideas.” • “The duty of science does not end with showing an argument to be fallacious; it has to investigate the origin of the fallacy and show the nature of the process by which it has arisen.” Michael R. Büchler on Lean & Six Sigma 6
- 7. Sensing is not the same as seeing … Charlie D. Broad (1887‐1971) British Philosopher, Cambridge University Perception, Physics and Reality (1914) Scientific Thought (1923) The Mind and its Place in Nature (1925) • “. . . I have an extreme dislike for vague, confused, and oracular writing; and I have very little patience with authors who express themselves in this style. I believe that what can be said at all can be said simply and clearly in any civilized language or in a suitable system of symbols, and that verbal obscurity is almost always a sign of mental confusion.” • “In psychology we deal with minds and their processes, and leave out of account as far as possible the objects that we get to know by means of them. In all the sciences except psychology, we deal with objects and their changes, and leave out of account as far as possible the mind which observes them.” Michael R. Büchler on Lean & Six Sigma 7
- 8. Evolutionary process of scientific inquiry: Karl R. Popper (1902‐1994) The Logic of Scientific Discovery (1934) Conjectures and Refutations (1963) Objective Knowledge: An Evolutionary Approach (1972) The Self and its Brain (1977) Knowledge and the Mind‐Body Problem (1994) • The outcome of scientific inquiry is never settled; there is an evolutionary path in the development of knowledge. The essence of science is prediction – gaining a probabilistic understanding of the behaviour of phenomena. • Described his rationalist approach to science as an evolutionary development of knowledge where verification and falsifiability are a focus of the scientific process of discovery. • Popper postulated that it is between interaction of tentative theory (conjectures) and error elimination by falsification (refutations) that true scientific knowledge evolves: “the fact remains that the investigator can test his theory only by trying to refute it.” Michael R. Büchler on Lean & Six Sigma 8
- 9. Pragmatic philosophy links practice with theory: John Dewey (1859‐1952) Professor, Columbia University American Educator, Philosopher, and Psychologist • How We Think (1910) • The Quest for Certainty (1929) • Logic: The Theory of Inquiry (1938) • Knowing and the Known (1949) “There is no question of theory versus practice but rather of intelligent practice versus uninformed practice.” “Every great advance in science issues from audacity of imagination.” “Failure is instructive. The person who really thinks learns quite as much from his failures as from his successes.” Experience is the ultimate test of truth and by explaining connections and gaining meaning that we develop an understanding of the reality that we observe, so experiential verification is the criteria that is both necessary and sufficient for validating theory. Michael R. Büchler on Lean & Six Sigma 9
- 10. Decisions are constrained by “bounded rationality:” Herbert A. Simon (1916‐2001), Nobel Laureate Administrative Behaviour (1947) Organizations (with James G. March, 1958) Models of Bounded Rationality (1982, 1997) Reason in Human Affairs (1983) The Sciences of the Artificial (1996) An Empirically‐based Microeconomics (1997) “Boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) information.” “The human being striving for rationality and restricted within the limits of his knowledge has developed some working procedures that partially overcome these difficulties. These procedures consist in assuming that he can isolate from the rest of the world a closed system containing a limited number of variables and a limited range of consequences.” Complete “truth” is not possible, but decisions must be made under constraints of (1) quality of available information; (2) competence of decision‐makers; and (3) urgency of timeframe for decision‐making. Michael R. Büchler on Lean & Six Sigma 10
- 11. Systems have a purpose which focuses collaboration: Russell L. Ackoff (1919‐2009) Introduction to Operations Research (1957) On Purposeful Systems (1972) The Art of Problem‐Solving (1978) “The systems approach to problems focuses on systems taken as a whole, not on their parts taken separately. Such an approach is concerned with total system performance even when a change in only one or a few of its parts is contemplated because there are some properties of systems that can only be treated adequately from a holistic point of view. These properties derive from the relationship between parts of systems: how the parts interact and fit together.” “Managers are not confronted with problems that are independent of each other, but with dynamic situations that consist of complex systems of changing problems that interact with each other. I call such situations messes. Problems are extracted from messes by analysis. Managers do not solve problems, they manage messes.” Michael R. Büchler on Lean & Six Sigma 11
- 12. What can be knowable with confidence? Chester I. Barnard (1886‐1961) President, New Jersey Bell Telephone (1927‐1949) Functions of the Executive (1936) Mind in Everyday Affairs (1936) There are distinct categories of facts that bias proposed problem solutions. We can observe facts using one perspective (e.g., physical), but interpret it using a different perspective (e.g., political). Thus, “managing by facts” may become distorted due to subjective manipulation by those who lack perspective. Limits of Knowledge: What can we know with confidence? Type of Data Physical date Biological data Process data Economic data Political data Social data Moral data Explanation of Data Nature of Data Continuous variables (engineering quality data) Tangible Ergonomic data (time and motion) Less Tangible Timing and attribute data (pass/fail compared to criteria) Approximations (estimates based on probability forecast) Leadership and strength of relationship (fixed scale/rank) More Intangible Interactions or relationship (group norm relativity) Values or personal philosophy (individual relativity) Intangible Michael R. Büchler on Lean & Six Sigma 12
- 13. Rational sub‐groups help identify variance patterns: W. Tukey (1915‐2000) Exploratory Data Analysis (1977) “Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.” “There is no data that can be displayed in a pie chart, that cannot be displayed BETTER in some other type of chart.” • • • Exploratory data analysis is an attitude AND a flexibility AND some graphs. No catalogue of techniques can convey a willingness to look for what can be seen, whether or not anticipated. This is at the heart of exploratory data analysis. The graphs are used to recognize that the picture‐examining eye is the best finder we have of the wholly unanticipated. Once upon a time statisticians only explored. Then they learned to confirm exactly; to confirm a few things exactly, each under specific circumstances. As they emphasized exact confirmation, their techniques inevitably became less flexible. most used techniques gave poor insights to the past. Michael R. Büchler on Lean & Six Sigma 13
- 14. Control of processes can be analysed using statistics: Walter A. Shewhart (1891‐1967) The Economic Control of Quality of Manufactured Product (1931) Statistical Method from the Viewpoint of Quality Control (1939) Shewhart is called the “father of statistical quality control” who developed a “Theory of Control” and the statistical process control chart. “To indicate the relationship which the theory of control bears to exact science, it is interesting to consider six stages in the development of better ways and means of making use of past experience. They are: 1. 2. 3. 4. 5. 6. Belief that the future cannot be predicted in terms of the past. Belief that the future is pre‐ordained. Inefficient use of past experience in the sense that experiences are not systematized into laws. Control within limits. Statistical Process Control Maximum control. Knowledge of all laws of nature – exact science.” Michael R. Büchler on Lean & Six Sigma 14
- 15. Process dominance as a key to process management: Joseph M. Juran (1904‐2008) American Quality Consultant • Quality Handbook (1951, 1962, 1974, 1988, 1999) • Managerial Breakthrough (1964) • Management of Quality Control (1967) • Quality Planning and Analysis (1970) • Upper Management and Quality (1980) • • • Often there is a single variable that will dominate in its contribution to the performance of an overall process. In a physical process the usual forms of dominance are elements such as: setup‐ dominance, time‐dominance, component‐dominance, worker‐dominance, and information‐ dominance. Processes will vary in terms of the appropriate performance measures as well as the degree of ability to self‐regulate or control quality in their results. Patterns of activities that dominate a process will also provide the key for their effective control and each dominance pattern will employ different types of control mechanisms to produce effectively stable results. Michael R. Büchler on Lean & Six Sigma 15
- 21. Union of Japanese Scientists and Engineers (1959): A P C D Michael R. Büchler on Lean & Six Sigma 21
- 22. Hitoshi Kume (1985): QC Story for Problem‐Solving Problem: Undesirable result from work 1 Define the Problem Clearly – Process Diagram – Pareto Analysis 2 Recognize the Features of the Problem – Collect Data – Histogram – Scatter Diagram, Correlation and Regression – Control Charts 3 Analyse to find the main causes – Fishbone Diagram – Statistical Inference and Analysis of Variance – Hypothesis Test 4 5 6 7 Act to Eliminate the Causes Check to assure the problem does not recur Standardize for a permanent solution Review the procedure and plan future work Michael R. Büchler on Lean & Six Sigma 22
- 32. BEST Lean Six Sigma ™ (2006): DMAIC: The What’s important to the customer? What’s important to the business/strategy? What are the expectations? What historical data is available? Define Management Direction LSS Project Defined and Customer Requirements Matrix Problem Statement Drafted Critical-to-Satisfaction Y’s Customer Outcome Data Customer surveys Is/is not analysis Historical Process Data What is between/within variation? SIPOC map What data is available/practical? Exploratory data analysis Is data variable or attribute? Project Charter Analyze Critical Sources of Variation and Priority Opportunities for Improvement Identified What is the best internal practice? What is benchmark performance? What is the long & short term capability? What are the Xs and Ys? Measure Value Stream Map Failure Analysis Process Capability Study Histogram Scatter plot 5S Housekeeping Fishbone Analysis Measurement Evaluation Performance Measures Pareto Chart Exploratory Data Analysis Baseline Measurement Current Performance Characterized Probability plots Regression analysis Rational sub-grouping Cycle time analysis Hypothesis testing ANOVA Bottleneck analysis Work flow analysis How do you hold the gains? How will you know you’ve improved? Design schematics Residual analysis What’s next? Have the objectives been met? What is the response variable? Where else can we apply this? What are the savings? What’s in the revised process map? Improve Improved Performance Verified Process DoE Benchmarking Control Charts Hypothesis Testing Process Laboratory Decision Workout Kaizen Blitz Simulation Analysis Michael R. Büchler on Lean & Six Sigma Control Performance Validated Control charts Benefits Obtained Mistake proofing Lessons Leveraged Document/standardize Changes Audit and monitor performance measures 32
- 33. Whats Next 2013? First we need to understand our operational definitions and strategies of your business accumen! Recognize Define Measure Analyse Improve Control Scouting, Targeting Diagnosis: The client’s attention comes to focus on a limited although perhaps vaguely understood, problem area or source of difficulty and dissatisfaction. Recognize alleviates the typical situation for a company’s management team – selecting projects without a systematic approach based on performance measurement. Stress, Relief, Catharsis: The client reduces inhibiting effects of past frustrations, anxieties, and conflicts. Blame casting, fault finding, injustices are expressed, set aside, and client’s attention is to some degree freed for concentration on the change process. Define builds consensus among management about what needs to be urgently addressed. Self‐Awareness: Data gathering, modelling the present system, and studies of “How we do it now” increase the client’s self‐perception and self‐objectification. Measure determines baseline conditions, tolerance of customers to change, ability of data collection to measure and status of current process performance. Self‐Evaluation: The client comes to make his or her own evaluation of present behaviour. Analyse uses statistical tools to develop insight into profound knowledge about how work systems operate and allows managers to discover opportunities for improvement within the work processes. Self Designed Change Strategies: The client or client organizations plans or accepts plans for new behaviours, methods and systems. Trying out the new behaviour: Client experiments with the new methods and systems. Improve plans new methods and tests their effectiveness in a real‐world situation. Reinforcing the New Behaviour: To be replicated, to be made part of the individual’s or organization’s repertory of behaviours, it must be rewarded and reinforced. Control sustains the change through standardization and statistical methods for managing data. Inspiration of workers should occur through participation – not by direction! Reference: William T. Morris (1979) Implementation Strategies for Industrial Engineers [Courtesy : Mikko Porter] Michael R. Büchler on Lean & Six Sigma 33
- 35. Confront the problem directly! What has changed in your process its standard way of working? Problem: a gap between our desired or target state and our current state. SELECT ISSUE DEFINE PROBLEM ASSESS CAPABILITY 7 1 6 2 5 4 3 DETERMINE GAP IDENTIFY CUSTOMER • • • • • • DESCRIBE GOAL MEASURE RESULTS • What changed? When did it change? What else changed at that time? Why did it change? How much did it cost? How does it affect our productivity? How does it affect our customers? Michael R. Büchler on Lean & Six Sigma 35