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SSG120MEASUREWeek4-5.xlsx
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Overview

MEASURE (submit both assignments in week 5)
1. Define your Data Collection Plan. Include the types of data you will be collecting (Discrete or Continuous), Why? (In many instances you will have a mix of both types of data depending on the Data source. (HINT: This plan should flow from the CTQ Tree you completed in the Define Phase)
2. Based on Customer requirements the project team collected initial data. Use Pareto Analysis of # occurrences data to determine the 5 factors which are causing over 95% of the problem with wait time. You need to determine the 'biggest contributors to the problem. One tool to accomplish this is the Pareto Chart. You need to know if it is reasonable to assume that these five 'parameters' are normally distributed. (SEE APPENDIX B)
a. Based on Pareto Analysis what are the focus areas?
b. What are the Key Performance Indicators (KPIs)?
c. Set up appropriate methods for tracking focus areas. You will need to track # of occurrences of each category and actual for measuring the ability to meet the requirements.
3. Based on the data collected Construct FIVE (5) histograms for the below data sets. (SEE APPENDIX C) for data sets
a. Interpret each of the histograms to determine whether the assumption of normality is reasonable.
b. If the data are not approximately normally distributed, why not?
4. The team also believed there was a Motorola shift during the process. Please describe the Motorola Shift and potential causes that they could have experienced the shift.
a. Calculate the DPMO for the entire process considering the 5 main opportunities for defects
b. Determine the baseline sigma with the Motorola shift.
5. Calculate the Process Performance, Pp and Ppk, based on the time the Doctor spends with the patient. Student will be able to compare current Process performance to Capability Study performed for process improvements. Tint: drawing a picture of the data based on a Normal Curve may help student visualize if data is skewed when evaluating population distribution. Use UCL = 60 minutes and LCL = 0 Minutes. In Healthcare LCL will frequently be “O”
Pp = (Upper Spec - Target Value)/(6*Standard Deviation)
Ppk = (Upper Spec - Mean)/(3*Standard Deviation)

Data Collection

DATA COLLECTION PLAN TEMPLATE (Performance Measures should come from the CTQ Tree)
PROJECT NAME DATE PREPARED BY
ID PERFORMANCE MEASURE OPERATIONAL DEFINITION DATA SOURCE & LOCATION SAMPLE SIZE WHO WILL COLLECT DATA? WHEN WILL DATA BE COLLECTED? HOW WILL DATA BE COLLECTED? HOW WILL DATA BE USED? ADDITIONAL DATA TO BE COLLECTED AT SAME TIME
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Pareto Chart Template

PARETO CHART TEMPLATE
The Pareto principle states that, for many events, roughly 80% of the effects come from 20% of the causes.
SORT DATA DESCENDING / HIGH-TO-LOW
C A U S E E F F E C T CUMULATIVE
CATEGORY / DESCRIPTION COUNT PERCENTAGE
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
ERROR:#DIV/0!
APPENDIX B: Based on VOC data to be used to construct CTQ’s. Project Team will identify key focus areas in Doctor’s Office using Pareto Diagram. These focus areas will then be monitored as defined in Data Collection Plan.
Time the Doctor was spending with Patients – 79
Number of times Dr arrives late - 4
Proper Medical Devices not Available - 30
Number of times patient is left in the hallway - 17
Rooms Available at Doctor’s Office -22
Number of times staff arrive late - 3
Staffing of Doctor’s Office -41
Number of times scheduling changes were made for patient testing - 15
Number of times patient had to be rescheduled for Dr visit - 10
Arrival Time of Patients - 52
COUNT CUMULATIVE PERCENTAGE 0 0 0 0 0 0 0 0 0 0

Histogram plots

APPENDIX C: Data set to be used to construct 5 Histograms 
1. Percent of Rooms fully equipped with Proper Medical Devices
• This varies between 10.5 and 11. This is the number of devices or number of times devices were not available in the rooms.
2. Rooms available -
• Varies from 7.45 -7.66. This is the percentage of rooms available
3. Staffing at Dr. Office
• Varies from 0.54-0.56. Effort per day (which is a value used depicting that people that had multiple duties so you could have a fraction of a person available).
4. Arrival Time of Patients
• Minutes late
5. Time Dr. Spends with Patients
• Minutes
Date % of Rooms fully equipped with Proper Medical Devices % Rooms Available at Dr. Office Staffing at Dr. Office Percent time spent Minutes late Time Dr. Spends with Patients (min) 
4-Jul 10.82 7.45 0.55020 172 48
5-Jul 10.82 7.55 0.55220 169 34
6-Jul 10.86 7.67 0.54600 177 23
7-Jul 10.87 7.65 0.54620 170 32
8-Jul 10.84 7.62 0.54910 174 19
9-Jul 10.85 7.59 0.54860 175 37
10-Jul 10.86 7.60 0.54280 167 20
11-Jul 10.87 7.52 0.53320 171 47
12-Jul 10.89 7.49 0.54720 168 27
13-Jul 10.80 7.54 0.55220 172 31
14-Jul 10.81 7.52 0.54940 168 44
15-Jul 10.89 7.61 0.55190 163 27
16-Jul 10.81 7.52 0.55090 174 61
17-Jul 10.90 7.61 0.54120 169 17
18-Jul 10.87 7.53 0.55180 171 26
19-Jul 10.86 7.57 0.55230 172 50
20-Jul 10.85 7.59 0.54150 172 11
21-Jul 10.85 7.55 0.54770 168 53
22-Jul 10.86 7.61 0.55300 169 18
23-Jul 10.86 7.54 0.55000 166 75
24-Jul 10.83 7.57 0.54370 172 27
25-Jul 10.89 7.51 0.54630 168 36 Graph Histograms Here
26-Jul 10.76 7.63 0.55660 174 40
27-Jul 10.78 7.50 0.54100 175 30
28-Jul 10.86 7.58 0.55420 164 23
29-Jul 10.90 7.55 0.55690 173 15
30-Jul 10.83 7.51 0.54320 168 15
31-Jul 10.82 7.50 0.54870 170 35
1-Aug 10.87 7.59 0.55370 173 45
2-Aug 10.88 7.58 0.54100 170 25
3-Aug 10.67 7.64 0.55540 173 42
4-Aug 10.72 7.48 0.55210 167 64
5-Aug 10.65 7.57 0.55320 169 23
6-Aug 10.70 7.46 0.55630 172 53
7-Aug 10.67 7.53 0.55080 165 50
8-Aug 10.65 7.60 0.55270 170 16
9-Aug 10.60 7.49 0.55460 169 41
10-Aug 10.66 7.65 0.54780 170 7
11-Aug 10.61 7.55 0.54680 165 31
12-Aug 10.69 7.55 0.55660 172 18
13-Aug 10.71 7.51 0.55310 168 53
14-Aug 10.66 7.49 0.54820 173 34
15-Aug 10.64 7.49 0.54730 172 37
16-Aug 10.62 7.49 0.54420 170 80
17-Aug 10.63 7.56 0.54910 176 19
18-Aug 10.67 7.59 0.55960 175 26
19-Aug 10.62 7.47 0.54910 170 13
20-Aug 10.62 7.58 0.55070 169 18
21-Aug 10.63 7.55 0.55600 177 36
22-Aug 10.65 7.47 0.54280 178 7
23-Aug 10.68 7.63 0.54880 172 34
24-Aug 10.68 7.47 0.55310 171 28
25-Aug 10.63 7.68 0.54830 171 44
26-Aug 10.68 7.55 0.54310 171 18
27-Aug 10.58 7.47 0.54500 177 23
28-Aug 10.59 7.59 0.53920 172 17
29-Aug 10.64 7.57 0.55120 170 25
30-Aug 10.64 7.53 0.54650 169 15
31-Aug 10.68 7.58 0.54790 164 23
1-Sep 10.60 7.60 0.54520 174 21
Upper Spec  11  7.66  0.56  180  60 
Lower Spec  10.5  7.45  0.54  165  0 
Target  10.75  7.55  0.55  170  20 

Baseline Sigma

Calculating "The Perfect Visit"
In order to calculate the DPMO, three distinct pieces of information are required:
a) the number of units produced (Patient Seen)
b) the number of defect opportunities per unit (5)
c) the number of defects (count of defects in column A)
The actual formula is:
DPMO = (Number of Defects X 1,000,000)
((Number of Defect Opportunities/Unit) x Number of Units)
Baseline DPMO and Sigma (With the Motorola 1.5 Shift)
Upper Spec  11  7.66  0.56  180  60 
Lower Spec  10.5  7.45  0.54  165  0  DPMO Sigma
Target  10.75  7.55  0.55  170  20 
Defects Date % of Rooms fully equipped with Proper Medical Devices % Rooms Available at Dr. Office Staffing at Dr. Office Percent time spent Minutes late Time Dr. Spends with Patients (min)  Without 1.5 sigma shift With 1.5 sigma shift
4-Jul 10.82 7.45 0.55020 172 48 Sigma Level DPMO Yield Defect Rate DPMO Yield Defect Rate
5-Jul 10.82 7.55 0.55220 169 34 1 317310 68.2690000% 31.7310000% 697612 30.23880% 69.76120%
6-Jul 10.86 7.67 0.54600 177 23 1.1 271332 72.8668000% 27.1332000% 660082 33.99180% 66.00820%
7-Jul 10.87 7.65 0.54620 170 32 1.2 230139 76.9861000% 23.0139000% 621378 37.86220% 62.13780%
8-Jul 10.84 7.62 0.54910 174 19 1.3 193601 80.6399000% 19.3601000% 581814 41.81860% 58.18140%
9-Jul 10.85 7.59 0.54860 175 37 1.4 161513 83.8487000% 16.1513000% 541693 45.83070% 54.16930%
10-Jul 10.86 7.60 0.54280 167 20 1.5 133614 86.6386000% 13.3614000% 501349 49.86510% 50.13490%
11-Jul 10.87 7.52 0.53320 171 47 1.6 109598 89.0402000% 10.9598000% 461139 53.88610% 46.11390%
12-Jul 10.89 7.49 0.54720 168 27 1.7 89130 91.0870000% 8.9130000% 421427 57.85730% 42.14270%
13-Jul 10.80 7.54 0.55220 172 31 1.8 71860 92.8140000% 7.1860000% 382572 61.74280% 38.25720%
14-Jul 10.81 7.52 0.54940 168 44 1.9 57432 94.2568000% 5.7432000% 344915 65.50850% 34.49150%
15-Jul 10.89 7.61 0.55190 163 27 2 45500 95.4500000% 4.5500000% 308770 69.12300% 30.87700%
16-Jul 10.81 7.52 0.55090 174 61 2.1 35728 96.4272000% 3.5728000% 274412 72.55880% 27.44120%
17-Jul 10.90 7.61 0.54120 169 17 2.2 27806 97.2194000% 2.7806000% 242071 75.79290% 24.20710%
18-Jul 10.87 7.53 0.55180 171 26 2.3 21448 97.8552000% 2.1448000% 211927 78.80730% 21.19270%
19-Jul 10.86 7.57 0.55230 172 50 2.4 16395 98.3605000% 1.6395000% 184108 81.58920% 18.41080%
20-Jul 10.85 7.59 0.54150 172 11 2.5 12419 98.7581000% 1.2419000% 158686 84.13140% 15.86860%
21-Jul 10.85 7.55 0.54770 168 53 2.6 9322 99.0678000% 0.9322000% 135686 86.43140% 13.56860%
22-Jul 10.86 7.61 0.55300 169 18 2.7 6934 99.3066000% 0.6934000% 115083 88.49170% 11.50830%
23-Jul 10.86 7.54 0.55000 166 75 2.8 5110 99.4890000% 0.5110000% 96809 90.31910% 9.68090%
24-Jul 10.83 7.57 0.54370 172 27 2.9 3731 99.6269000% 0.3731000% 80762 91.92380% 8.07620%
25-Jul 10.89 7.51 0.54630 168 36 3 2699 99.7301000% 0.2699000% 66810 93.31900% 6.68100%
26-Jul 10.76 7.63 0.55660 174 40 3.1 1935 99.8065000% 0.1935000% 54801 94.51990% 5.48010%
27-Jul 10.78 7.50 0.54100 175 30 3.2 1374 99.8626000% 0.1374000% 44566 95.54340% 4.45660%
28-Jul 10.86 7.58 0.55420 164 23 3.3 966 99.9034000% 0.0966000% 35931 96.40690% 3.59310%
29-Jul 10.90 7.55 0.55690 173 15 3.4 673 99.9327000% 0.0673000% 28716 97.12840% 2.87160%
30-Jul 10.83 7.51 0.54320 168 15 3.5 465 99.9535000% 0.0465000% 22750 97.72500% 2.27500%
31-Jul 10.82 7.50 0.54870 170 35 3.6 318 99.9682000% 0.0318000% 17864 98.21360% 1.78640%
1-Aug 10.87 7.59 0.55370 173 45 3.7 215 99.9785000% 0.0215000% 13903 98.60970% 1.39030%
2-Aug 10.88 7.58 0.54100 170 25 3.8 144 99.9856000% 0.0144000% 10724 98.92760% 1.07240%
3-Aug 10.67 7.64 0.55540 173 42 3.9 96 99.9904000% 0.0096000% 8197 99.18030% 0.81970%
4-Aug 10.72 7.48 0.55210 167 64 4 63 99.9937000% 0.0063000% 6209 99.37910% 0.62090%
5-Aug 10.65 7.57 0.55320 169 23 4.1 41 99.9959000% 0.0041000% 4661 99.53390% 0.46610%
6-Aug 10.70 7.46 0.55630 172 53 4.2 26 99.9974000% 0.0026000% 3467 99.65330% 0.34670%
7-Aug 10.67 7.53 0.55080 165 50 4.3 17 99.9983000% 0.0017000% 2555 99.74450% 0.25550%
8-Aug 10.65 7.60 0.55270 170 16 4.4 10 99.9990000% 0.0010000% 1865 99.81350% 0.18650%
9-Aug 10.60 7.49 0.55460 169 41 4.5 6 99.9994000% 0.0006000% 1349 99.86510% 0.13490%
10-Aug 10.66 7.65 0.54780 170 7 4.6 4 99.9996000% 0.0004000% 967 99.90330% 0.09670%
11-Aug 10.61 7.55 0.54680 165 31 4.7 2 99.9998000% 0.0002000% 687 99.93130% 0.06870%
12-Aug 10.69 7.55 0.55660 172 18 4.8 1 99.9999000% 0.0001000% 483 99.95170% 0.04830%
13-Aug 10.71 7.51 0.55310 168 53 4.9 0.96 99.9999040% 0.0000960% 336 99.96640% 0.03360%
14-Aug 10.66 7.49 0.54820 173 34 5 0.574 99.9999426% 0.0000574% 232 99.97680% 0.02320%
15-Aug 10.64 7.49 0.54730 172 37 5.1 0.34 99.9999660% 0.0000340% 159 99.98410% 0.01590%
16-Aug 10.62 7.49 0.54420 170 80 5.2 0.2 99.9999800% 0.0000200% 107 99.98930% 0.01070%
17-Aug 10.63 7.56 0.54910 176 19 5.3 0.116 99.9999884% 0.0000116% 72 99.99280% 0.00720%
18-Aug 10.67 7.59 0.55960 175 26 5.4 0.067 99.9999933% 0.0000067% 48 99.99520% 0.00480%
19-Aug 10.62 7.47 0.54910 170 13 5.5 0.038 99.9999962% 0.0000038% 31 99.99690% 0.00310%
20-Aug 10.62 7.58 0.55070 169 18 5.6 0.021 99.9999979% 0.0000021% 20 99.99800% 0.00200%
21-Aug 10.63 7.55 0.55600 177 36 5.7 0.012 99.9999988% 0.0000012% 13.35 99.99867% 0.00134%
22-Aug 10.65 7.47 0.54280 178 7 5.8 0.007 99.9999993% 0.0000007% 8.55 99.99915% 0.00086%
23-Aug 10.68 7.63 0.54880 172 34 5.9 0.004 99.9999996% 0.0000004% 5.42 99.99946% 0.00054%
24-Aug 10.68 7.47 0.55310 171 28 6 0.002 99.9999998% 0.0000002% 3.4 99.99966% 0.00034%
25-Aug 10.63 7.68 0.54830 171 44
26-Aug 10.68 7.55 0.54310 171 18
27-Aug 10.58 7.47 0.54500 177 23
28-Aug 10.59 7.59 0.53920 172 17
29-Aug 10.64 7.57 0.55120 170 25
30-Aug 10.64 7.53 0.54650 169 15
31-Aug 10.68 7.58 0.54790 164 23
1-Sep 10.60 7.60 0.54520 174 21

Pp Ppk

HINT: Always be sure to use Stdev() in Excel NOT Stdev.P()
If the process is in between the LSL and USL, calculate both and
select the lowest Ppk value
Ppk = xbar- Lower spec limit Ppk = Upper Spec Limit - xbar
3 x standard dev 3 x Standard Dev
APPENDIX C: Data set to be used to construct 5 Histograms 
Date % of Rooms fully equipped with Proper Medical Devices % Rooms Available at Dr. Office Staffing at Dr. Office Percent time spent Minutes late Time Dr. Spends with Patients (min) 
4-Jul 10.82 7.45 0.55020 172 48 Mean (xBar) LSL USL Target StDev Ppk (LSL) PpK (USL)
5-Jul 10.82 7.55 0.55220 169 34 % of Rooms fully equipped with Proper Medical Devices 10.749 10.50 11.00 10.75 0.107
6-Jul 10.86 7.67 0.54600 177 23 % Rooms Available at Dr. Office 7.554 7.45 7.66 7.55 0.056
7-Jul 10.87 7.65 0.54620 170 32 Staffing at Dr. Office Percent time spent 0.549 0.54 0.56 0.55 0.005
8-Jul 10.84 7.62 0.54910 174 19 Minutes late 170.750 165.00 180.00 170.00 3.368
9-Jul 10.85 7.59 0.54860 175 37 Time Dr. Spends with Patients (min)  31.783 0.00 60.00 20.00 15.922
10-Jul 10.86 7.60 0.54280 167 20
11-Jul 10.87 7.52 0.53320 171 47
12-Jul 10.89 7.49 0.54720 168 27 Calculate Ppk (LSL) and Ppk (USL) and select the lowest score
13-Jul 10.80 7.54 0.55220 172 31
14-Jul 10.81 7.52 0.54940 168 44
15-Jul 10.89 7.61 0.55190 163 27
16-Jul 10.81 7.52 0.55090 174 61
17-Jul 10.90 7.61 0.54120 169 17
18-Jul 10.87 7.53 0.55180 171 26
19-Jul 10.86 7.57 0.55230 172 50
20-Jul 10.85 7.59 0.54150 172 11
21-Jul 10.85 7.55 0.54770 168 53
22-Jul 10.86 7.61 0.55300 169 18
23-Jul 10.86 7.54 0.55000 166 75
24-Jul 10.83 7.57 0.54370 172 27
25-Jul 10.89 7.51 0.54630 168 36
26-Jul 10.76 7.63 0.55660 174 40
27-Jul 10.78 7.50 0.54100 175 30
28-Jul 10.86 7.58 0.55420 164 23
29-Jul 10.90 7.55 0.55690 173 15
30-Jul 10.83 7.51 0.54320 168 15
31-Jul 10.82 7.50 0.54870 170 35
1-Aug 10.87 7.59 0.55370 173 45
2-Aug 10.88 7.58 0.54100 170 25
3-Aug 10.67 7.64 0.55540 173 42
4-Aug 10.72 7.48 0.55210 167 64
5-Aug 10.65 7.57 0.55320 169 23
6-Aug 10.70 7.46 0.55630 172 53
7-Aug 10.67 7.53 0.55080 165 50
8-Aug 10.65 7.60 0.55270 170 16
9-Aug 10.60 7.49 0.55460 169 41
10-Aug 10.66 7.65 0.54780 170 7
11-Aug 10.61 7.55 0.54680 165 31
12-Aug 10.69 7.55 0.55660 172 18
13-Aug 10.71 7.51 0.55310 168 53
14-Aug 10.66 7.49 0.54820 173 34
15-Aug 10.64 7.49 0.54730 172 37
16-Aug 10.62 7.49 0.54420 170 80
17-Aug 10.63 7.56 0.54910 176 19
18-Aug 10.67 7.59 0.55960 175 26
19-Aug 10.62 7.47 0.54910 170 13
20-Aug 10.62 7.58 0.55070 169 18
21-Aug 10.63 7.55 0.55600 177 36
22-Aug 10.65 7.47 0.54280 178 7
23-Aug 10.68 7.63 0.54880 172 34
24-Aug 10.68 7.47 0.55310 171 28
25-Aug 10.63 7.68 0.54830 171 44
26-Aug 10.68 7.55 0.54310 171 18
27-Aug 10.58 7.47 0.54500 177 23
28-Aug 10.59 7.59 0.53920 172 17
29-Aug 10.64 7.57 0.55120 170 25
30-Aug 10.64 7.53 0.54650 169 15
31-Aug 10.68 7.58 0.54790 164 23
1-Sep 10.60 7.60 0.54520 174 21
Upper Spec  11  7.66  0.56  180  60 
Lower Spec  10.5  7.45  0.54  165  0 
Target  10.75  7.55  0.55  170  20 

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