1、 Max Zornada (2005),Slide 1,The DMAIC Process Detail The Measure Phase, Max Zornada (2005),Slide 2,DMAIC Process Storyboard,TEAM FORMATION,DEFINE,MEASURE,ANALYSE,IMPROVE - I : Generate Potential Solutions,CONTROL - Standardise,FUTURE PLANS,Define, Measure, Analyse, Improve, Control,Objective: Identi
2、fy and implement the measures required to establish baseline performance and quantify the opportunity.,Output: Team Project Charter, Work Plan, Measurable Customer Requirements, Process Map/Process Analysis,Objective: Identify and verify the root cause(s) of the problem.,Output: Root cause(s) identi
3、fied.,Objective: Determine possible solutions that will address the identified root cause(s) of the problem.,Action Plan,Step 1,Step 2,Step 3,Step 4,Step 5,Step 6,Output: Preferred solution or countermeasures,Key Steps:-,Generate potential solutions Assess potential solutions Select preferred soluti
4、on Test/Pilot preferred solution Develop implementation plan,Objective: Implement the preferred solution. Confirm that the problem and its root cause(s) have been reduced or eliminated.,Output: Confirmation that the best solution to eliminate the problem & its root cause(s) has been implemented.,Key
5、 steps:-,Implement preferred solution Verify effectiveness Apply comparative methods if necessary.,Objective: Prevent the problem and its root cause from recurring.,Output: Solution embedded and “routinised” in relevant process, procedures and standards.,Key steps:-,Standardise the solution (standar
6、ds & procedures) Document project Implement scorecard Implement controls,Objectives: Review team effectiveness, plan to address remaining issues and institutionalise the learning.,Output: Recommendations for future projects and improvements to team processes. Project documentation and learnings “pac
7、k”,Potential Solutions,IMPROVE - II: Implement and Check,Objective: Define the Problem/Opportunity, Customers, Customer Requirements, and Process.,Output: A quantified picture of the current process performance, problem impact. The process sigma rating.,Objective: Select problem/ opportunity theme,
8、select team members,Output: Problem/Opportunity selected, Team members selected.,Develop business case Develop project team charter Understand Customer Requirements Understand the Process.,Determine what to measure Understand the measures Understand Variation Assess measurement system Assess process
9、 performance,Key Steps:-,Key Steps:-,Team charter,Cause and Effect Diagram,Run chart or control chart,Analyse data Analyse process Determine potential root causes Hypothesis Testing Verify root causes,Key Steps:-,Key Steps:-,Review remaining project opportunities Review other applications Review lea
10、rnings, Max Zornada (2005),Slide 3,Overview of the Measure Phase,Determining what to Measure; Understanding and Describing Data; Understanding and Managing Variation; Statistical Process Control; Process Capability and Sigma Level; Overview of Sampling, Max Zornada (2005),Slide 4,Determining what to
11、 Measure, Max Zornada (2005),Slide 5,Y = f(x),The fundamental equation that drives Six Sigma; Output (Y) is a function of the Inputs and the Process,Examples of Y,Output Outcomes Effect Symptom A Dependent Variable A Key Performance Indicator,Examples of xs - x1, x2, x3 . xn,Inputs to the process Le
12、ading indicators/Drivers Problems and their causes “Noise” factors Complexity Independent Variables Control and “levers”, Max Zornada (2005),Slide 6,Approaches to identifying measures (and what data to collect),The process scorecard “generic” template; Cause and effect (fishbone diagram) around the
13、CTQ outcome of interest; The Critical-to-Quality (CTQ) Tree approach; Correlation analysis between measures and outcomes; The Measurement Assessment., Max Zornada (2005),Slide 7,Consider a Generic Process,Customer,Real Work Stream,Complexity Stream,Complexity Stream, Max Zornada (2005),Slide 8,Measu
14、ring Process Performance,Customer,Customer Interface Measures?,Process Performance Measures ?,Supplier Interface Measures?, Max Zornada (2005),Slide 9,Consider HTLC: Typical Measures Things like .,Customer Interface Measures Customer Satisfaction Complaints Orders not delivered on time/Late Overdue
15、orders Number of orders filled.,Process Measures Time to process an order Cost Number of orders in the system (work in progress) Order backlog,Supplier Interface Measures Incoming stock delivery performance Credit check turnaround time Backlog of items on order No. of Orders Received,Inputs,Process,
16、Outputs, Max Zornada (2005),Slide 10,A Generic Template for Developing Process Based Performance Measures,External Customer,Overall Organisation/Business Unit,End-to-End Core Process,External Suppliers,Customer Outcomes Measures Delivery Quality Value,Internal Process Outcomes Measures Time Cost Qua
17、lity/Waste, Max Zornada (2005),Slide 11,A Scalable Concept,External Customer,External Suppliers,But the specific measures developed will be different in each case.,Internal Customer,Internal Supplier,Workgroup A Subprocess,Workgroup B Sub-process,Internal Process Outcomes Measures Time Cost Quality/
18、Waste,Internal Process Outcomes Measures Time Cost Quality/Waste,Customer Outcomes Measures Delivery Quality Value,Customer Outcomes Measures Delivery Quality Value, Max Zornada (2005),Slide 12,Inputs, Process and Outcomes Measures A draft “generic” template for process measurement,Customer Outcomes
19、 Measures Delivery Quality Value,Internal Process Outcomes Measures Time Cost Quality/Waste,Customer Outcomes Measures (Inputs) Delivery Quality Value,Process,Customer outcomes the supplier(s) to the process work to, in order to meet the input requirements for the process,Input Measures,External Cus
20、tomer, Max Zornada (2005),Slide 13,What can you do about .,A late delivery to ensure its delivered on time - after its already been delivered late? A cost over run - after it has already been incurred? Avoiding dissatisfying a customer - after they have already been dissatisfied?We need some predict
21、ive measures as well; These are referred to as leading indicators or drivers., Max Zornada (2005),Slide 14,Consider our process,Customer,Real Work Stream,The Real Work Stream gives us the optimum: Processing time/order ( Nothing goes wrong. This will be the best this process can do., Max Zornada (20
22、05),Slide 15,Causes of Outcomes Drivers or Leading Indicators,What would cause an order to take longer to be processes? What would cause an order to cost more to be processed? What would cause an order to be delivered late? What would cause the process to operate other than perfectly (only real work
23、).,Complexity!, Max Zornada (2005),Slide 16,Understanding complexity provides insight into what the leading indicators should be,Customer,Real Work Stream,Eg. technician availability measure % order rescheduled due to “technician not available”,Eg. item in stock measure Backlog of items on Order,Exa
24、mple: HTLC, Max Zornada (2005),Slide 17,Shortcut method for identifying leading indicators (xs),What are all of the things that could stop the process ( internally)? What external factors could stop the process from meeting its customer and process outcomes? Can you measure these?, Max Zornada (2005
25、),Slide 18,The Process Scorecard A “generic” template for process measurement: Inputs, Process, Leading Indicator and Outcomes Measures,Customer Outcomes Measures Delivery Quality Value,Internal Process Outcomes Measures Time Cost Quality/Waste,Customer Outcomes Measures (Inputs) Delivery Quality Va
26、lue,Process,Input Measures,Customer,Customer Outcomes Measures,Internal Process Outcomes Measures,Leading Indicators (causes of the outcomes),Leading Indicators Process specific issues Key Complexity Issues External to process issues, Max Zornada (2005),Slide 19,Process Measurement: Y = f(x),Custome
27、r Outcomes Measures Delivery Quality Value,Internal Process Outcomes Measures Time Cost Quality/Waste,Customer Outcomes Measures (Inputs) Delivery Quality Value,Process,Input Measures,Customer,Usually the Ys,Potential xs found here,Leading Indicators Process specific issues Key Complexity Issues Ext
28、ernal to process issues, Max Zornada (2005),Slide 20,Fishbone Diagram HTLC Example,Inputs,Customer Outcomes,External Impacts,Process Outcomes,Delivery Performance,Complexity Issues,Other,Traffic conditions,Time of day deliveries scheduled,Item not in stock,Item out of stock,Not a stocked item,Techni
29、cian not available,No transport,Order incorrectly specified,Promised date too soon,Process Lead Time too long,Customer complaints,Late delivery,Processing time too long,Supplier didnt supply,Refund/Penalty claims,Return trips to same customer,Can we get measures for these things ?, Max Zornada (2005
30、),Slide 21,Identifying Measures,We can potentially generate lots of measures; Do we measure everything? Only a small number of measures may actually matter; Problem is identifying which ones? We can focus our measurement and data collection by considering the relationships between various potential
31、measures and the CTQ outcome which is the focus of the improvement effort; Build a measures correlation matrix., Max Zornada (2005),Slide 22,Measures Correlation Matrix,On-time delivery,Right Equip Delivered,No. of Order with item Out of Stock No. of Orders for Non-Stocked Item No. of Order on Backl
32、og No. of Orders with no tech allocated No. of Orders with no transport allocated Time of day order delivered Quoted Lead Time per Order No. of Orders incorrectly specified Processing time,Equipment Works,Total,Importance,Potential Input/Process/LI Measure (xs),9 3 0 12 1 3 3 15 9 0 1 10 9 0 0 9 9 0
33、 0 9 1 0 0 1 3 0 0 3 3 9 3 15 1 0 0 0,10 9 7,Outcome Measure (Y), Max Zornada (2005),Slide 23,Measures Correlation Matrix,On-time delivery,Right Equip Delivered,No. of Order with item Out of Stock No. of Orders for Non-Stocked Item No. of Order on Backlog No. of Orders with no tech allocated No. of
34、Orders with no transport allocated Time of day order delivered Quoted Lead Time per Order No. of Orders incorrectly specified Processing time,Equipment Works,Total,Importance,Potential Input/Process/LI Measure (xs),9 3 0 12 1 3 3 15 9 0 1 10 9 0 0 9 9 0 0 9 1 0 0 1 3 0 0 3 3 9 3 15 1 0 0 0,10 9 7,Ou
35、tcome Measure (Y), Max Zornada (2005),Slide 24,The Tree Diagram Approach to Identifying Measured, Max Zornada (2005),Slide 25,Identifying Measures using a CTQ Tree HTLC Example,Ontime delivery performance,The Outcome Measure (Y), Max Zornada (2005),Slide 26,Identifying Measures using a CTQ Tree HTLC
36、 Example,Ontime delivery performance,Stock Availability,Technician Availability,Transport Availability,Credit check turnaround time,The Outcome Measure (Y),Brainstorm things that could affect the outcome. Refer previous analysis., Max Zornada (2005),Slide 27,Identifying Measures using a CTQ Tree HTL
37、C Example,Ontime delivery performance,Stock Availability,Technician Availability,Transport Availability,Credit check turnaround time,Orders receivedOrders filled from stockOrder placed on backlog,The Outcome Measure (Y),Brainstorm things that could affect the outcome. Refer previous analysis., Max Z
38、ornada (2005),Slide 28,Deciding what data to collect,Two basic uses of data: Monitoring: Aggregate data: data used to tell you at what level the process is operating and to indicate when something has changed; Improvement: Disaggregate or Stratify: need to be able to identify specific linkages betwe
39、en data elements and sources;, Max Zornada (2005),Slide 29,Using a Measurement Assessment Tree,No. of late deliveries,Output (Y),How many are late?,Are there trends of patterns?,How much is it costing?,Questions we want to answer about the process,Stratification Factors (x variables),Measures,By tim
40、e period,By type of customer,By location,By value,# late, by day of week,# late, by hour of day,# late, regular contract,# late, casual sales,# late, by region,# late, by suburb,# late, by distance from w/h,# late, small orders,# late, large orders,Does this metric potentially help predict the outpu
41、t Y?,Does data exist to obtain this metric,Y,Y,Y,Y,Y,Y,Y,N,N,Y,Y,Y,Y,Y,Y,N,N,N, Max Zornada (2005),Slide 30,Operational Definitions,A measurement must give consistent results no matter who does the measuring; An Operational Definition gives a description of what something is and how it is measured;
42、Therefore, before data is collected, we must agree on the operational definition of all terms and on the measurement criteria to be used., Max Zornada (2005),Slide 31,Normalisation,Correcting for different scales of measurement is called normalisation; Normalisation allows us to compare two groups o
43、f data, where the raw data may have been collected in different ways; e.g. different time frame, different units, different sample size. Data are usually normalised by time, volume or task., Max Zornada (2005),Slide 32,Understanding Data and Variation, Max Zornada (2005),Slide 33,Hi-Tech Leasing Cor
44、poration,Monitoring the performance of the Order Fulfillment Process, Max Zornada (2005),Slide 34,The Funnel Experiment,A,B,C,D,E,F,G,H,Target,Radius of circle = 4 cm Defines on time delivery zone,Flip chart paper,Result of an individual pencil drop,Distance from centre in cm = days to fill the orde
45、r,Late deliveries zone (outside the circle), Max Zornada (2005),Slide 35,The funnel experiment,The Funnel experiment is used to simulate the performance and an order fulfillment process; The company promise customers delivery within 4 days; Each pencil drop through the funnel represents an order goi
46、ng through the process; The distance the drop lands from the target is measured in centimeters. This represents how long that particular order took to fill in days. Orders landing inside the inner circle of radius 4 cm represent orders delivered within the service standard; Order landing outside the
47、 inner represent late deliveries; The zones labeled A, B, C, D, E, F, G, H represent the different reasons for which the delivery was late., Max Zornada (2005),Slide 36,The funnel experiment The Rules,Group 1: Aim for the target, lock in the settings and take 50 shots for the target without re-targe
48、ting. Group 2: Same as group 1, except if you miss, you can re-target to improve your chances next time. Group 2: Aim each shot where the last one landed.,Measure the 1st 25 shots and record the measurement on the worksheet. Note: Measurements must be made in the order in which they occur., Max Zornada (2005),
