Kepner-Tregoe Methodology Skorkovský Department of business economy 1 Developed by Charles H. Kepner and Benjamin B. Tregoe in the 1960s. 2 The formulation of a problem is far more essential than its solution which may be merely a matter of mathematical or experimental skill” - Albert Einstein Apollo 13 – Houston, Houston, do you read me ? We have a big problem….! The Apollo 13 team is famous for bringing back the astronauts stranded in space by solving difficult and complex problems. The teams solving the problems has used the Kepner-Tregoe (KT) methodology ! 3 Decision Analysis –serious one 4 Sticky- lepkavý Lick – olíznout What is it K-T methodology ? Kepner Tregoe is used for decision making . It is a structured methodology for gathering information and prioritizing and evaluating it. It is very detailed and complex method applicable in many areas, which is much broader than just idea selection. It is called also a root cause analysis and decision-making method. It is a step-by-step approach for systematically solving problems, making decisions, and analyzing potential risks. 5 Access situation (situation appraisal) •Identify concerns (problems) by listing them •Separate the level of concern (importance, magnitude, level of influence) •Set the priority level to measure seriousness of impacts (influence), urgency and growth potential •Decide what action to take next (step by step approach) •Plan for who is involved, what they will be doing, where they will be involved, when it happened and the extent of involvement (magnitude) • 6 WHO WHAT WHEN WHERE EXTENT 7 Make decision (A choice between two or more alternatives) •Identify what is being decided (o čem se bude rozhodovat) •Establish and classify objectives (main ones, minor ones,..)- cíle •Separate the objectives into must (must to have) and want (nice to have) categories (we have to assign importance factors from 1-10, where 10 is the most important want objective) and assign criterion rating (weights) •Generate the alternatives (we can do it that way or we can take another way as well) •Evaluate the alternatives by scoring the wants against the main objective – see next slides •Review adverse (harmful) consequences of your corrective steps (risk evaluation, risk assessment) •Make the best possible choice what to do • 8 Criteria rating See similar example on the next slide 9 Importance can be understood as a Satisfaction score, meaning desirable but not essential. Criteria rating is related to want criteria and every car property Which car to buy ? 10 Criterion rating go to slide 37 and back Importance score, meaning desirable but not essential. See the Upcoming (approaching, next to come) and Potential Opportunity=solution=řešení) • •List the potential opportunities O{op1, op2 ,..,opN} •Consider the possible(suitable)solution (e.g. the second one) •Take the action to address the likely cause/solution •Prepare actions to enhance(vylepšit) likely (possible) effects • • 11 Uncover and handle problems (problem analysis) •State the problem (definition and description of the problem) •Specify the problem by asking what is and what is not •Develop possible causes of the problem (similar to CRT) •Test and verify possible causes •Determine the most probable cause (root cause) •Verify any assumptions (předpoklady, domněnky,..) •Try the best possible solution and monitor what will be a situation after applied correctives step 12 Description Problem 1 Problem N Description Causes Priority (urgency) Description Causes Priority (urgency) Solution (corrective action) 1 Solution (corrective action) X Solution (corrective action) 1 Solution (corrective action) Y Problem 1´ Problem N´ Situation Situation Oválný popisek: What WhereWhenExtent What WhereWhenExtent Oválný popisek: What WhereWhenExtent What WhereWhenExtent 13 Oválný popisek: WHERE and WHERE NOT WHERE and WHERE NOT Oválný popisek: WHERE and WHERE NOT WHERE and WHERE NOT Decomposition, priorities and causes Problem 1 Sub-problem 1 Sub-problem N Priority1 Priority N Problem 1 Problem 2 Sub-problem 1 Sub-problem N Cause 1 Cause N Problem 2 14 Example of problem manifestation (decrease of performance) performance time Planned performance Real performance Unfavourable deviation What do we see, hear, feel, taste, or smell that tells us there is a deviation? Final effect of the = PROBLEM (e.g. server crashed) Then we have to ask : What, Where, When, and to what Extent –Size (how much, how many)? 15 Server crashed !!!! (home study !!!) •Server crashed (this is a very poor problem definition) •The e-mail system crashed after the 3rd shift support engineer applied hot-fix XYZ to Exchange Server 123 (better definition of the problem) • • History (and best practice) says that the root cause of the problem is probably due to some recent change. WHAT, WHERE, WHEN and EXTENT will be shown on next slides 16 Test the Most Probable Cause (home study !!!) Clarifying problem Analysis (example) We have to ask (where Qi =QUESTION i) : Question IS IS NOT What (identify) Q1 Q2 Where (locate) Q3 Q4 When (timing) Q5 Q6 Extent (magnitude) Q7 Q8 See next slides 17 Problem Analysis - What •What specific object(s) has the deviation? • •What is the specific deviation? • • •Is •Is Not nWhat similar object(s) could have the deviation, but does not? (It did not happen) nWhat other deviations could be reasonably observed, but are not? (It did not happen) • Example for Is : 1. What specific object IS related to the defect? Inventory Valuation Objects in database A 2. What specifically is the defect (deviation)? Inventory Adjustment does not work 1-> see setup of the database and see differences 2->see algorithm used for calculation and parameters used. You can see , that in production calculation it dose not work Example for Is Not : 1. What specific object IS NOT related to the defect? Inventory Valuation Objects in database B 2. What specifically is not the defect (deviation)? 1 -> Setup has another parameters On 2-> Algorithm is used also for production where not error occurs 1. 18 See two MS Dynamics Setup screens (related to the problem specified recently) 19 Problem Analysis - What •What specific object(s) has the deviation? • • •What is the specific deviation? - bites on the neck • • •Is •Is Not nWhat similar object(s) could have the deviation, but does not? (It did not happen) n n What is the specific deviation? but does not? (It did not happen) – bites, anemia • Example for Is : 1. Nice young girl´s neck and strange look of anemic person 1.Girl with garlic in her hands 2. No bites 3. Zaftig 20 Example of Is Not : Another example for What IS and What IS NOT Example Customer X and Customer Y both use product B but only to customer X was sent the wrong product so the object IS Customer X , but IS NOT Customer Y 21 Example for When and IS and IS NOT Customer X and Customer Y both use product B but only customer X was sent the wrong product if Salesman Tony was on holiday in this time and Salesman Mustafa was in charge, so the object IS Salesman Mustafa , but IS NOT Salesman Tony 22 Another example for Where IS and Where IS NOT Example IS girl visited Dracula lower castle without a bunch of garlic, but IS NOT not the one having bunch of garlic and visiting Špiberk castle in Brno 23 Problem Analysis - Where •Where is the object when the deviation is observed? (geographically) • •Where is the deviation on the object? • nWhere else could the object be when the deviation is observed, but is not? nWhere else could the deviation be located on the object, but is not? •Is •Is Not Example for Is : 1.Old castle in the mountains (Romania) Where IS : Romanian Carpathian mountains where it is very easy to meet a lot of vampires there Example for Is Not 1. Brno castle Špilberk Where IS NOT possible to meet vampires (only lovers and children and seniors) 24 Problem Analysis - When •Is •Is Not •When was the deviation observed first (clock and calendar time)? • •When since that time has the deviation been observed? • •When, in the object’s history or life cycle, was the deviation observed first? nWhen else could the deviation have been observed first, but was not? nWhen since that time could the deviation have been observed, but was not? nWhen else, in the object’s history or life cycle, could the deviation have been observed first, but was not? 25 Problem Analysis - Extent •How many objects have the deviation? • •What is the size of a single deviation? •How many deviations are on each object? • •What is the trend? –Occurrences? –Size? •How many objects could have the deviation, but don’t? •What other size could a deviation be, but isn’t? •How many deviations could there be on each object, but are not? •What could be the trend, but isn’t? •Occurrences? •Size? •Is •Is Not 26 Problem Analysis Confirm True Cause •What can be done to verify any assumptions made? •How can this cause be observed at work? •How can we demonstrate the cause-and-effect relationship (e.g. Current Reality Tree or Ishikawa Fishbone Diagram)? •When corrective action is taken, how will results be checked? 27 Let’s Look At Some Problems! 28 Systematic Problem Solving and Decision making Overview 29 Planning the Next Steps •Problem Analysis •Do we have a deviation? •Is the cause unknown? •Is it important to know the cause to take effective action? • •If the answer is YES to ALL three, than you have a big problem, Huston !!! 30 Problem analysis table template (Home study) 31 Problem description (example) •On a new model of airplane, flight attendants develop rash on arms, hands, face (only those places). It only occurs on flights using new aircrafts and flying over oceans • •Usually disappears after 24 hours. No problems on old planes over those routes. Old planes are not used for transatlantic flights • •Does not affect all attendants on these flights, but same •number of attendants get it on each flight. Those who get rash have no other ill effects. • •No measurable chemicals, etc., in cabin air. Rash arm -> 32 Problem analysis real table Distinction=Difference 33 Results ???? 34 Tree of the casual relationships I –example •Decline of revenue due to : •Lower merchantability of the items •New competitors •Change of the customer preferences •Poor (not sufficient) quality of the item –Restriction of capacity production •Downtime due to machine failure, obsolete machinery, irregular maintenance – 35 Let’s Look At Some Problems again! 36 Decision making process •Problem definition •Requirements identification •Goal establishment •Evaluation criteria development •Select decision –making tool •Apply tool (K &T, Pros-Cons,…) •Check • • 37 38 Step 1 Problem: Pick a replacement vehicle for the motor pool fleet The definition of the problem dictates the requirements. As the vehicle is for a motor pool, the requirements will differ from those for a family car, for example. Step 2 Requirements: 1. Vehicle shall be made in U. S. A. 2. Vehicle shall seat at least four adults, but no more than six adults 3. Vehicle shall cost no more than $28,000 4. Vehicle shall be new and the current model year Step 1 and Step 2 39 Min Max Max 28000 USD New car (current model) 40 Step 3 and Step 4 Step 3 Goals: · Maximize passenger comfort · Maximize passenger safety · Maximize fuel-efficiency · Maximize reliability of the car · Minimize investment cost Step 4 Alternatives: There are many alternatives but the requirements eliminate the consideration of a number of them: Requirement 1 eliminates the products not manufactured in the USA Requirement 2 eliminates vans, buses, and sports cars (Ferrari no !!!!) Requirement 3 eliminates high-end luxury cars Requirement 4 eliminates used vehicles 41 Step 5 Criteria: “Maximize comfort” will be based on the combined rear seat leg and shoulder room. (Note: front seat passenger leg and shoulder room was found to be too nearly the same to discriminate among the alternatives.) 5 “Maximize safety” will be based on the total number of stars awarded by the National Highway Traffic Safety Administration for head-on and side impact. 10 “Maximize fuel efficiency” will be based on the EPA fuel consumption for city driving. 7 “Maximize reliability” will be based on the reliability rating given each vehicle by a consumer product testing company. 9 “Minimize Cost” will be based on the purchase price. 10 Step 5 Weighted criteria vector C(5,10,7,9,10) are values assigned by decision makers !!!! 42 Kepner-Tregoe table (for 4 cars : Arrow, Baton, Carefree and Dash) 43 Last Step Validate Solution: The totals of the weighted scores show that the Dash most nearly meets the wants/goals (or put another way, has the most “benefits”). Dash meets all the requirements and solves the problem !!! Last step – Validation (check) Go back to slide 10 44 CRT-Ishikawa 45 12 1 2 3 7 4 6 1 2 3 7 4 6 1 2 3 4 6 7 John 8 7 4 3 5 6 Caroline 9 5 7 8 5 6 Mean 8,5 6 5,5 5,5 5 6 1 •= Nature (see, forest, mountains, jungle, river,..) 2 •= Hotel type 3 •= Amenities (pool, golf course, wellness,.. ) 4 •= Period (spring, summer, fall, winter). 12 1 2 3 4 1 R1 R2 Prerequisite Requirement P1 P2 Conflict Alternative 1 Alternative 2 Alternative means how to solve problem and what kind of pay-off you will get Alternatives 46 1 R1 R2 Prerequisite Requirement P1 P2 Conflict Alternative 1 Alternative 2 1 R1 R2 Prerequisite Requirement P1 P2 Conflict Alternative 3 Alternative 4 Alternative /Market SOHO Medium size Big player A1 6000000 7000000 12000000 A2 2000000 4000000 9000000 A3 800000 1300000 4000000 A4 200000 800000 1000000 SW Package A1 King Kong A2 SW Kings A3 Accounting Devils A4 Hamsters One possible solution Decision making methods without probabilities (MaxiMax and MaxiMin) – 1st slide-explanantion 47 MaxiMax is the rule for the optimist. A slogan for MaxiMax might be "best of the best" - a decision maker considers the best possible outcome for each course of action, and chooses the course of action that corresponds to the best of the best possible outcomes MaxiMin Payoff •Select the alternative which results in the maximum of minimum payoffs; a pessimistic criterion Outcomes Alternatives O1 O2 O3 A $1,000 $1,000 $1,000 B $10,000 -$7,000 $500 C $5,000 $0 $800 D $8,000 -$2,000 $700 •Minimum Payoff •$1,000 •-$7,000 •Payoff Table •$0 •-$2,000 •A > C > D > B Make decision (A choice between two or more alternatives) •Identify what is being decided (e.g. how many rooms I have to order if I am owner of the travel agency)–see next slide (in this case K-T method is not considered) • • 49 Decision making without probability •Hotel industry simple example (placed ordered-> alternatives and how many •of them will really arrive) 51 52 Example of analysis- use of questions 53 Thanks for Your attention 54