1 Continuous Improvement. 2 1.Overview of the PDCA Problem Solving Cycle. 2.Foundations of the PDCA Cycle 3.Plan Step 4.Do Step 5.Check Step 6.Act Step

1

Continuous Improvement

2

Continuous Improvement

1. Overview of the PDCA Problem Solving Cycle.2. Foundations of the PDCA Cycle3. Plan Step4. Do Step5. Check Step6. Act Step7. Using the Problem Solving Tools and PDCA

3

Overview of the PDCA Problem Solving Cycle: The PDCA Wheel

PLAN

DO

CHECK

ACT

Design or revise business process components to improve results.

Implement the plan and measure its performance.

Assess the measurements and report the results to decision makers.

Decide on changes needed to improve the process.

The concept of the PDCA Cycle was originally developed by Walter Shewhart at Bell Laboratories in the 1930s. It was then popularized by W. Edwards Deming in the 1950s onward and is frequently referred to as “the Deming Wheel.”

4

Foundations of the PDCA Cycle

The foundations of the PDCA cycle and Deming’s teachings consist of the following three principles:

1.Customer Satisfaction: Satisfying customers’ needs should be paramount for all workers in the organization.

2.Management by Fact. Decision making must be made on data collected from operations and analyzed using statistical tools. Decision makers must practice and encourage a scientific approach to problem solving.

3.Respect for People. A sustainable problem solving and continuous improvement approach should be based on the belief that employees are self-motivated and are capable of coming up with effective and creative ideas.

5

Steps of PDCA: The Plan

step

Recognize the problem and establish priorities.Problem may be outlined in very general terms based on information from several sources.

Form the problem solving team.Interdisciplinary teams of individuals close to the problem are best.

Define the problem and its scope clearly.Who,What,Where and When.Pareto Analysis can be useful in defining the problem.

Analyze the problem/process. Process flowcharts can be useful a useful tool.

Determine possible causes.Cause-and-effect diagrams are helpful in identifying root causes of a problem. Data from the diagrams can be organized using check sheets, scatter diagrams, histograms, and run charts.

Identify possible solutions.Brainstorm to find solutions. Avoid the temptation to propose quick, immediate fixes. Goals should be specific, measurable, achievable, and realistic.

Evaluate potential solutions. Focus on solutions that address root causes and prevention of problem occurrence. Solutions should be cost-effective; achieving group consensus is important.

6

Steps of PDCA (continued)

The Do step

Implement the solution or process change Monitor results and collect data

The Check step Review and evaluate the result of the change Measure progress against milestones Check for any unforeseen consequences

The Act step If successful,

Standardize process changes Communicate to all involved Provide training in new methods

7

Problem Solving Tools

1. Check Sheet. A simple tool for collecting data about problems or complaints.

Example 1.

Appliance Department ComplaintsLate Wrong Faulty Total Units %

Month delivery appliance installation installed Complaints

January 2 3 3 8 800 1.00%February 4 3 4 11 900 1.22%March 1 4 3 8 750 1.07%April 4 5 2 11 1050 1.05%May 3 5 5 13 1400 0.93%June 2 6 3 11 980 1.12%July 3 4 4 11 1030 1.07%August 5 6 6 17 1500 1.13%September 3 5 5 13 1330 0.98%October 4 6 6 16 1500 1.07%November 3 7 5 15 1320 1.14%December 3 8 6 17 1550 1.10%

8

Problem Solving Tools (continued)

2. Histogram. A graph which presents the collected data as a frequency distribution in bar-chart form. Example 1

Complaint Type

0

1

2

3

4

5

6

7

8

9

Month

Fre

qu

en

cy

Late

Wrong

Faulty

9


3. Pareto Chart. Orders problems by their relative frequency in decreasing order. Focus and priority should be given to problems that offer the largest potential improvement.

Example 1

Pareto Chart for complaints

0

10

20

30

40

50

60

70

Wrong appliance Faulty installation Late delivery

Complaint category

Nu

mb

er o

f co

mp

lain

ts

10


4. Scatter Diagram. A graphical tool to check if two relationships exist between two variables. Example 1

Scatter Diagram for faulty installations

0

20

40

60

80

100

120

140

160

180

0 1 2 3 4 5 6 7

Number of faulty installations

Num

ber

of in

stal

latio

ns p

er c

rew

11


5. Flowchart. A visual representation of a process which can help in identifying points where failures may occur and intervention is useful. Example 2

Rounded box - represents an event which occurs automatically, such as receive telephone call.Rectangle or box - represents an event which is controlled within the process. A step or action which is taken. Diamond - represents a decision point in the process. Typically will require a `yes' or `no' response. Circle - represents a point at which the flowchart connects with another process. The name of the other process appears within the symbol.

12


6. Cause-and-effect diagram (fishbone diagram). Offers a structured approach for identifying all possible causes of a problem. The classic diagram is as shown:

In retail, a better representation is the 5S (Pal & Byron 2003):

13


7. Control Chart. Is a statistical tool used to monitor the performance of a process over time. It is a time-ordered graph of sample data which can be used to identify when assignable causes of variation may be present.Example 1

If observations fall between the lower control limit and the upper control limit, then the process is in control. Otherwise, corrective action is needed.

Control Chart for Complaints

0.70%

1.00%

1.30%

0 2 4 6 8 10 12 14

Month

% c

ompl

aint

s

Upper Control Limit

Lower Control Limit

14


Process variations can be one of two types:a) Random variations which are created by many

minor factors. b) Assignable variations whose main source can be

identified and corrected.

There are four types of control charts:1. Control Charts for Variables. Variables are

measured such as length of time a certain item is out of stock. Control charts can be:

1.a. Mean Control Charts1.b. Range Control Charts

2. Control Charts for Attributes. Attributes are counted such as number of service calls and number of returns on an item. Control charts can be:

2.a. p-charts2.b. c-Charts

15


Mean Control Charts: Used to measure the mean (central tendency) of a process. Example 3: A store manager is concerned about the length of time items are out of stock. The store manager has a policy that the average time items can be out of stock is 2.2 days (30.8 hours based on 14-hour days) with a standard deviation of 5 hours. A sample of 10 out of stock items was taken and the length of time they were out of stock was measured. The data is shown below:

LCL=Mean-2(Standard Deviation) = 30.8 – 2 (5)= 20.8 hrsUCL=Mean+2(Standard Deviation) = 30.8 + 2 (5)= 40.8 hrsSince 41.2 is larger than 40.8, the duration of out of stock has a mean larger than 30.8 hours.

Duration Item out of stock

1 182 333 294 455 506 457 608 319 40

10 61Average 41.2

16


Range Control Charts: Used to measure the variability (dispersion) of a process. Example 3: Suppose that the average range for the mean stock out duration over the last 5 samples has been R1=32 hours

Range = R = 61 – 18 = 43 hours

LCLR = D3 R =0.22 × 32= 7.04 hours

UCLR = D4 R = 1.78 × 32= 56.96 hours

Since 43 is between 7.04 and 56.96, the dispersion of the stock out times has not changed.

17


p-charts: Used to monitor the percentage of failures generated by a process. Example 1: Suppose that managers are concerned about increased number of complaints in Oct-Dec. Has the installation process deteriorated over the last three months?Using Jan-Sep dataProportion of complaints =103/9740=0.01057For sample size of 100 installations for Oct, Nov, and Dec, Standard deviation of p = ((0.015057)(1-0.01057)/400)1/2=0.005113LCL=0.01057-2(0.005113)=0.000348UCL=0.01057+2(0.005113)=0.02080

Since all sample proportions are between 0.00348 and 0.02080, the process is in control.

Late Wrong Faulty Total Sample %delivery appliance installation Size Complaints

October 1 3 4 8 400 2.00%November 1 3 3 7 400 1.75%December 2 2 3 7 400 1.75%

18


c-Charts: Used to monitor the number of defects per unit. Example 4: Number of defectives per 25 yd2 of installed bathroom tile in 10 samples of 25 yd2 are:

LCL=Average–2 (average)1/2 =1.90–2 (1.90)1/2 = -0.857 LCL=0

UCL=Average+2(average)1/2 =1.90+2 (1.90)1/2 = 4.65

A new sample of 25 yd2 was examined and the number of defects was 5. Since 5>4.65, the process needs to be examined.

Number Sample of defects

1 22 33 04 25 16 37 28 19 2

10 3Average 1.90

19


8. Run Chart. A graphical tool to monitor important process variables over time. A helpful tool in identifying trends and cycles. Example 1

9. Brainstorming. An idea generating technique for a group of people to solve problems.

Encourage unrestrained collective thinking All ideas are welcomed No single member dominates the session

Run chart for good installations

98.60%

98.70%

98.80%

98.90%

99.00%

99.10%

1 2 3 4 5 6 7 8 9 10 11 12

Period

% g

oo

d i

nsta

llati

on

s

20


10. Interviewing. A technique for identifying problems and collecting information. It can be used with employees for internal problems and customers for external problems.

11. Benchmarking. A process of measuring performance against best in the industry or the best in other industries. Steps:

Identify the process that needs improvement Find the store that excels in the process Obtain data on the way they perform the

process Analyze the data Implement process improvements in your

own process

12. Fail Safe Methods. The implementation of methods and warnings to decrease probability of mistakes.

Documents

1 Continuous Improvement. 2 1.Overview of the PDCA Problem Solving Cycle. 2.Foundations of the PDCA Cycle 3.Plan Step 4.Do Step 5.Check Step 6.Act Step