1. DASHBOARDS:
How to Identify, Track and
Display Key Performance
Indicators
Michael Cook, Ph.D., CFM
Director of Regional Building Operations
and Property Management,
Kaiser Permanente – Southern California
2. MANAGING CEUs AND CFM® MAINTENANCE
POINTS
You are eligible to receive Continuing Education Units (CEUs) and Certified
Facility Manager® (CFM) maintenance points for attending sessions at Facility
Fusion.
To receive CEU points you must pay the $12 processing fee, log onto
ceu.experient-inc.com/FFN121 and pass a five-question assessment developed
by the speaker. CEUs can only be earned upon successful completion of the
assessment.
To receive 20 CFM maintenance points you must place your registration
confirmation notice into your maintenance records. No assessment is needed if
you only want to earn CFM maintenance points.
An official IFMA transcript will be emailed for successful completion of courses
at Facility Fusion. Individuals seeking continuing education credit from other
organizations must contact those organizations for instructions on self-
reporting their credit hours.
3. CEU codes are no longer needed
to receive CEU points.
Simply pay the $12 CEU processing fee at
registration, visit the registration kiosks or
log on to
ceu.experient-inc.com/FFN121
and take the five-question test
assessments.
4. Facility Fusion Evaluations are online!
Evaluate sessions at the registration kiosks
or online at
ceu.experient-inc.com/FFN121
Your feedback is vital to our conference
planning.
5. Meet Our Presenter:
Michael Cook, Ph.D., CFM
Director of Facilities Services, Kaiser Permanente - Southern California Region
Michael is currently responsible for facilities and property management for an 11M
SF portfolio of leased and owned properties consisting of medical office buildings,
administrative buildings, pharmacies, labs and warehouses. He has more than 16
years of experience in facilities management in various industries, including:
Healthcare, Hospitality and Fitness, Entertainment and Government. Michael holds
a Doctorate in Public Administration and an MBA. He has achieved the CFM
certification, and is a Certified Six Sigma Black Belt. In addition to his work in
facilities management, Michael also serves as an adjunct professor teaching
Operations Management, and Quantitative Methods at the MBA level. He has been
an active member in IFMA for more than 10 years and has given presentations on
operations management and quality assessment.
6. Kaiser Permanente is an Integrated Health System
Kaiser
Foundation
Health Plan
Permanente
Medical
Groups
Kaiser
Foundation
Hospitals
Page 6
7. Pag
Kaiser Permanente’s Reach
Recognized as one of America’s leading health care
providers and not-for-profit health plans
8.9M
members
37 hospitals
611 medical
offices
9 states
and the
District of
Columbia
15,853 physicians
167,178 employees
$47.9B
operating
revenue
18. KPIs:
Measures, Metrics, and Targets
“Winston Churchill observed ‘First we shape
our buildings; thereafter they shape us,’ and
the same is even more true of performance
metrics” (Meyer & Kirby, Harvard Business Review, Jan.-Feb.
2012, page 70.)
19. KPIs:
Measures, Metrics, and Targets
Message:
* Behavior will be shaped by the metrics you select
You should:
* Select the “Critical Few” manageable metrics
And,
* Change your metrics if they are not useful
20. KPIs:
Measures, Metrics, and Targets
What are Measures, Metrics, and Targets?
“Measures” = a key variable (temperature)
“Metrics” = a quantitative value in a unit of the
measure (700F).
“Target” = a specific goal for the metric
(maintain 70-74 temps 80 percent of the time)
21. KPIs:
Measures, Metrics, and Targets
The Two Main Reasons for Measures and Metrics
are:
Drive Change in Behavior
Drive Change in Processes
22. Critical To
Quality KPIs:
Identifying the
“Critical Few”
Identify and Interview Decision
Makers
Research Trade Associations
Research Government Publications
Validate You have the Correct
Indicators
23. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and
Interview
Decision
Makers
Research Trade
Associations
Research Government
Publications
Validate You have the
Correct Indicators
24. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and
Interview Decision
Makers
Research Trade Associations
Research Government
Publications
Validate You have the Correct
Indicators
Who is Responsible for
Process Results?
Who Controls/Monitors
the Process?
What Business Decisions
are Most Critical?
What Behavior or Action
do You Want to Impact?
25. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and
Interview Decision
Makers
Research Trade Associations
Research Government
Publications
Validate You have the Correct
Indicators
What Data is Used to
Make Each Decision?
What Triggers the
Decision?
Who Has the Data?
How do You Know the
Decision was Correct?
26. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and Interview
Decision Makers
Research
Trade
Associations
Research Government
Publications
Validate You have the
Correct Indicators
27. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and Interview Decision
Makers
Research Trade
Associations
Research Government Publications
Validate You have the Correct
Indicators
International Facility
Management Association
(IFMA)
Building Owners and
Managers Association
(BOMA)
American Society for
Healthcare Engineering
(ASHE)
American Institute of
Architects (AIA)
28. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and Interview
Decision Makers
Research Trade
Associations
Research
Government
Publications
Validate You have the
Correct Indicators
29. (Released June 2009)
These survey data are from the 2008 Occupational Employment Statistics (OES) survey. The wages have all been updated to the first quarter of 2009 by applying the
US Department of Labor's Employment Cost Index to the 2008 wages. Occupations are classified using the Standard Occupational Classification (SOC) codes. For details of the methodology,
see the Overview of the OES Survey at http://www.labormarketinfo.edd.ca.gov.
Geography: Los Angeles-Long Beach-Glendale Metropolitan Division
Counties: Los Angeles
2009 - 1st Quarter Wages
MSA
Code Geographic Area Name
SOC
Code Occupational Title
May 2008
Employment
Estimates
Mean
Hourly
Wage
Mean
Annual
Wage
Mean
Relative
Standard
Error (1)
25th
Percentile
Hourly
Wage
50th
Percentile
(Median)
Hourly
Wage
75th
Percentile
Hourly
Wage
Occupational Employment (May 2008) & Wage (2009 - 1st Quarter) Data
Occupational Employment Statistics (OES) Survey Results
(Sorted by MSA code)
031084 Los Angeles-Long Beach-Glendale MD, CA 17-0000
Architecture and Engineering
Occupations 76,530 $40.85 $84,963 1.77 $29.33 $39.25 $51.04
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1011 Architects, Except Landscape and Naval 3,010 $46.70 $97,134 4.86 $32.16 $40.67 $54.25
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1012 Landscape Architects (3) $26.40 $54,904 5.43 $22.00 $23.99 $28.09
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1021 Cartographers and Photogrammetrists 100 $30.05 $62,492 3.2 $24.63 $29.69 $34.35
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1022 Surveyors 1,050 $38.29 $79,643 4.4 $33.16 $37.80 $42.99
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2011 Aerospace Engineers 6,190 $53.34 $110,959 2.54 $43.60 $52.28 $63.31
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2031 Biomedical Engineers 120 $46.42 $96,571 4.29 $37.09 $45.79 $53.99
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2041 Chemical Engineers 240 $47.59 $98,983 8.73 $35.95 $44.15 $51.94
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2051 Civil Engineers 7,900 $41.69 $86,716 1.58 $33.46 $41.04 $49.90
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2061 Computer Hardware Engineers 1,350 $51.64 $107,410 3.9 $37.09 $49.62 $67.74
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2071 Electrical Engineers 4,460 $43.45 $90,379 2.45 $33.04 $43.52 $53.06
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2072 Electronics Engineers, Except Computer 6,010 $47.45 $98,705 1.79 $36.44 $46.43 $58.80
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2081 Environmental Engineers 930 $40.81 $84,870 3.8 $32.20 $40.72 $48.58
031084 Los Angeles-Long Beach-Glendale MD, CA 37-0000
Building and Grounds Cleaning and
Maintenance Occupations 104,250 $12.81 $26,653 1.47 $9.43 $11.38 $14.85
031084 Los Angeles-Long Beach-Glendale MD, CA 37-1011
First-Line Supervisors/Managers of
Housekeeping and Janitorial Workers 3,840 $18.87 $39,267 1.54 $13.93 $17.48 $22.39
031084 Los Angeles-Long Beach-Glendale MD, CA 37-1012
First-Line Supervisors/Managers of
Landscaping, Lawn Service, and
Groundskeeping Workers 1,940 $23.13 $48,106 3.8 $16.15 $21.74 $28.95
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2011
Janitors and Cleaners, Except Maids and
Housekeeping Cleaners 54,000 $12.11 $25,194 1.72 $9.19 $10.77 $13.80
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2012 Maids and Housekeeping Cleaners 21,400 $11.09 $23,068 1.3 $9.08 $10.32 $12.73
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2019 Building Cleaning Workers, All Other (3) $13.22 $27,500 7.56 $10.78 $13.79 $15.44
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2021 Pest Control Workers 2,300 $15.63 $32,506 5.87 $12.01 $15.31 $18.31
031084 Los Angeles-Long Beach-Glendale MD, CA 37-3011
Landscaping and Groundskeeping
Workers 18,890 $13.79 $28,680 2.12 $10.25 $12.13 $16.42
30. 031084 Los Angeles-Long Beach-Glendale MD, CA 17-0000
Architecture and Engineering
Occupations 76,530 $40.85 $84,963 1.77 $29.33 $39.25 $51.04
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1011 Architects, Except Landscape and Naval 3,010 $46.70 $97,134 4.86 $32.16 $40.67 $54.25
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1012 Landscape Architects (3) $26.40 $54,904 5.43 $22.00 $23.99 $28.09
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1021 Cartographers and Photogrammetrists 100 $30.05 $62,492 3.2 $24.63 $29.69 $34.35
031084 Los Angeles-Long Beach-Glendale MD, CA 17-1022 Surveyors 1,050 $38.29 $79,643 4.4 $33.16 $37.80 $42.99
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2011 Aerospace Engineers 6,190 $53.34 $110,959 2.54 $43.60 $52.28 $63.31
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2031 Biomedical Engineers 120 $46.42 $96,571 4.29 $37.09 $45.79 $53.99
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2041 Chemical Engineers 240 $47.59 $98,983 8.73 $35.95 $44.15 $51.94
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2051 Civil Engineers 7,900 $41.69 $86,716 1.58 $33.46 $41.04 $49.90
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2061 Computer Hardware Engineers 1,350 $51.64 $107,410 3.9 $37.09 $49.62 $67.74
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2071 Electrical Engineers 4,460 $43.45 $90,379 2.45 $33.04 $43.52 $53.06
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2072 Electronics Engineers, Except Computer 6,010 $47.45 $98,705 1.79 $36.44 $46.43 $58.80
031084 Los Angeles-Long Beach-Glendale MD, CA 17-2081 Environmental Engineers 930 $40.81 $84,870 3.8 $32.20 $40.72 $48.58
031084 Los Angeles-Long Beach-Glendale MD, CA 37-0000
Building and Grounds Cleaning and
Maintenance Occupations 104,250 $12.81 $26,653 1.47 $9.43 $11.38 $14.85
031084 Los Angeles-Long Beach-Glendale MD, CA 37-1011
First-Line Supervisors/Managers of
Housekeeping and Janitorial Workers 3,840 $18.87 $39,267 1.54 $13.93 $17.48 $22.39
031084 Los Angeles-Long Beach-Glendale MD, CA 37-1012
First-Line Supervisors/Managers of
Landscaping, Lawn Service, and
Groundskeeping Workers 1,940 $23.13 $48,106 3.8 $16.15 $21.74 $28.95
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2011
Janitors and Cleaners, Except Maids and
Housekeeping Cleaners 54,000 $12.11 $25,194 1.72 $9.19 $10.77 $13.80
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2012 Maids and Housekeeping Cleaners 21,400 $11.09 $23,068 1.3 $9.08 $10.32 $12.73
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2019 Building Cleaning Workers, All Other (3) $13.22 $27,500 7.56 $10.78 $13.79 $15.44
031084 Los Angeles-Long Beach-Glendale MD, CA 37-2021 Pest Control Workers 2,300 $15.63 $32,506 5.87 $12.01 $15.31 $18.31
031084 Los Angeles-Long Beach-Glendale MD, CA 37-3011
Landscaping and Groundskeeping
Workers 18,890 $13.79 $28,680 2.12 $10.25 $12.13 $16.42
(Released June 2009)
These survey data are from the 2008 Occupational Employment Statistics (OES) survey. The wages have all been updated to the first quarter of 2009 by applying the
US Department of Labor's Employment Cost Index to the 2008 wages. Occupations are classified using the Standard Occupational Classification (SOC) codes. For details of the methodology,
see the Overview of the OES Survey at http://www.labormarketinfo.edd.ca.gov.
Geography: Los Angeles-Long Beach-Glendale Metropolitan Division
Counties: Los Angeles
2009 - 1st Quarter Wages
MSA
Code Geographic Area Name
SOC
Code Occupational Title
May 2008
Employment
Estimates
Mean
Hourly
Wage
Mean
Annual
Wage
Mean
Relative
Standard
Error (1)
25th
Percentile
Hourly
Wage
50th
Percentile
(Median)
Hourly
Wage
75th
Percentile
Hourly
Wage
Occupational Employment (May 2008) & Wage (2009 - 1st Quarter) Data
Occupational Employment Statistics (OES) Survey Results
(Sorted by MSA code)
31. Critical To Quality KPIs:
Identifying the “Critical Few”
Identify and Interview
Decision Makers
Research Trade
Associations
Research Government
Publications
Validate You
have the
Correct
Indicators
32. Descriptive Statistics is a valuable
way to begin analyzing the data.
Identify and Interview
Decision Makers
Research Trade
Associations
Research Government
Publications
Validate You
have the
Correct
Indicators
Statistic Sq Ft $hour/lbr traffic hrs sick flr care
Mean 68540.93 10.19 661.74 46.33 11.49
StD Error 6256.97 0.24 6.34 7.36 2.29
Median 44264.00 9.66 664.48 21.00 0.00
Mode #N/A #N/A #N/A 0.00 0.00
StD Dev 61624.01 2.31 62.46 72.47 22.52
Sample Var 3797518244.34 5.36 3900.93 5252.56 506.93
Kurtosis 2.21 -1.15 0.40 7.19 14.45
Skewness 1.70 0.10 -0.35 2.49 3.47
Range 267992.00 7.85 300.15 412.02 140.85
Minimum 8877.00 6.48 484.88 0.00 0.00
Maximum 276869.00 14.33 785.03 412.02 140.85
Sum 6648470.00 988.39 64188.61 4494.05 1114.40
Count 97.00 97.00 97.00 97.00 97.00
Largest(1) 276869.00 14.33 785.03 412.02 140.85
Smallest(1) 8877.00 6.48 484.88 0.00 0.00
CI (95%) 12419.99 0.47 12.59 14.61 4.54
33. Multilple Regression analysis is
useful way to scientifically validate
indicator relationships
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.710
R Square 0.504
Adj R Sq 0.482
Std Error 44346.893
Obs 97
ANOVA
df SS MS F Sig F
Regression 4 183630238388.053 45907559597.013 23.343 0.000
Residual 92 180931513068.442 1966646881.179
Total 96 364561751456.495
Coefficients Standard Error t Stat P-value
Intercept 146822.154 52180.686 2.814 0.006
$hour/lbr -18370.431 2164.424 -8.487 0.000
traffic 159.405 76.002 2.097 0.039
hrs sick 59.595 69.335 0.860 0.392
flr care 57.410 219.459 0.262 0.794
-100000
0
100000
200000
0 5 10 15 20
Residuals
$hour/lbr
$hour/lbr ResidualPlot
Identify and Interview
Decision Makers
Research Trade
Associations
Research Government
Publications
Validate You
have the
Correct
Indicators
34. Data Visualization
How to Display Data Graphically
“The ability to visualize and communicate
data is critical, because even with good data,
the results will not convince if poorly
visualized” (Mena Doshi, “Statistics, thy name is Flexibility,”
AMSTATNEWS, Jan. 2012, issue 415).
35. Data
Visualization:
How to Display
Data Graphically
Common Graphical Presentation
Methods:
Data Table:
Bar Chart:
Scatter Graph:
Time Series:
Box Plot:
Bullet Graph:
36. Data Visualization
How to Display Data Graphically
Common Graphical Presentation
Methods:
Data Table
Bar Chart:
Scatter Graph:
Time Series:
Box Plot:
Bullet Graph:
Categories 28
Property: ANA Date: 2/15/2012 Unsat (X) 4
Location Code: XXXFF Property Manager:
Building Type: MOB Contractor/Supplier: IN-HOUSE JANITORIAL
Service Area: O.C. SCORE: 86%
ID S U ID S U
STAIRWAYS
4 0 3 0
4 0 2 X
5 0 4 0
3 0 5 0
4 0 5 0
3 0 4 0
4 0 4 0
3 0 5 0
4 0 3 0
4 0
RESTROOMS SAFETY/CODE COMPLIANCE
4 0 5 0
2 X 5 0
5 0 4 0
4 0 3 0
3 0 4 0
2 X 5 0
5 0
4 0 2 X
5 0 4 0
4 0 3 0
3 0 4 0
planters
BUILDING INSPECTION
Dust
Cleanliness
FLOORS
Surface Surface
Litter
Steps
Doors
Fixtures/lights/mirrors
Walls
Wash Basin
Floor
Seating
WAITING ROOMS
Light Fixtures
LOBBY
Seating
Walls
fire extinguiser
Biohazard(logs, clean, etc)
Landings
electrical rooms
Floors
Cobwebs
Floor
Commode/Urinals
shrubs/color
Curbing/striping/signage
Doors
Spots
exit signs
sprinkler systems
Gloss
Trip Hazards
Counter
LAND/HARDSCAPE
Windows/Treatments
bldg entrance
Partitions/trashcans/doors
EXAM ROOMS
Floor
Walls
Doors
Counter Tops
Walls
safety lighting
38. Data Visualization
How to Display Data Graphically
Box Plot:
Visualize Data Distributions by
Meaningful Groups
1 3 5
Lobby
Exam Room
Waiting
Rooms
Restrooms
Floors
Landscape
Safety/Code
Rating (1 to 5)Categories 28
Property: ANA Date: 2/15/2012 Unsat (X) 4
Location Code: XXXFF Property Manager:
Building Type: MOB Contractor/Supplier: IN-HOUSE JANITORIAL
Service Area: O.C. SCORE: 86%
ID S U ID S U
STAIRWAYS
4 0 3 0
4 0 2 X
5 0 4 0
3 0 5 0
4 0 5 0
3 0 4 0
4 0 4 0
3 0 5 0
4 0 3 0
4 0
RESTROOMS SAFETY/CODE COMPLIANCE
4 0 5 0
2 X 5 0
5 0 4 0
4 0 3 0
3 0 4 0
2 X 5 0
5 0
4 0 2 X
5 0 4 0
4 0 3 0
3 0 4 0
planters
BUILDING INSPECTION
Dust
Cleanliness
FLOORS
Surface Surface
Litter
Steps
Doors
Fixtures/lights/mirrors
Walls
Wash Basin
Floor
Seating
WAITING ROOMS
Light Fixtures
LOBBY
Seating
Walls
fire extinguiser
Biohazard(logs, clean, etc)
Landings
electrical rooms
Floors
Cobwebs
Floor
Commode/Urinals
shrubs/color
Curbing/striping/signage
Doors
Spots
exit signs
sprinkler systems
Gloss
Trip Hazards
Counter
LAND/HARDSCAPE
Windows/Treatments
bldg entrance
Partitions/trashcans/doors
EXAM ROOMS
Floor
Walls
Doors
Counter Tops
Walls
safety lighting
39. Data Visualization
How to Display Data Graphically
Common Graphical
Presentation Methods:
Data Table:
Bar Chart:
Scatter Graph:
Time Series:
Box Plot:
Bullet Graph: 0
500
1000
1500
2000
2500
apr may jun jul aug sep
Series1
41. Data Visualization
How to Display Data Graphically
Common Graphical
Presentation Methods:
Data Table:
Bar Chart:
Scatter Graph:
Time Series:
Box Plot:
Bullet Graph: 65
70
75
80
85
90
95
8/18 8/25 9/1 9/8 9/15
42. Time Series -
Example
Temperature
Scenario:
Complaint:
It’s TOO HOT!
Action:
Installed Data
Loggers
Logged Over
650 Data
Points in 3
Weeks
Date Time Int Temp (F)
8/18/11 12:41 PM 80.25
8/18/11 1:41 PM 71.01
8/18/11 2:41 PM 69.43
8/18/11 3:41 PM 69.18
8/18/11 4:41 PM 68.57
8/18/11 5:41 PM 67.79
8/18/11 6:41 PM 67.42
8/18/11 7:41 PM 70.09
8/18/11 8:41 PM 73.04
8/18/11 9:41 PM 74.32
8/18/11 10:41 PM 74.8
8/18/11 11:41 PM 74.54
8/19/11 12:41 AM 73.7
8/19/11 1:41 AM 73.17
8/19/11 2:41 AM 72.82
8/19/11 3:41 AM 72.47
43. Time Series
BENEFITS:
Shows Trends
Over Time
Great For
Near-Term
Forecasting
Identify and
Explain Peaks
and Valleys
65
70
75
80
85
90
95
8/18 8/25 9/1 9/8 9/15
48. 3 Full Weeks of Data Only Working Hours
65
70
75
80
85
90
95
8/18 8/25 9/1 9/8 9/15
Time Series - Example
65
70
75
80
8/18 8/25 9/1 9/8 9/15
49. 3 Full Weeks of Data Only Working Hours
65
70
75
80
85
90
95
8/18 8/25 9/1 9/8 9/15
Time Series - Example
65
70
75
80
8/18 8/25 9/1 9/8 9/15
San Diego Power Outage
51. Data Visualization
How to Display Data Graphically
Common Graphical
Presentation Methods:
Data Table:
Bar Chart:
Scatter Graph:
Time Series:
Box Plot:
Bullet Graph:
1
3
5
Lobby Exam Room Waiting
Rooms
Restrooms Floors Landscape Safety/Code
Rating(1to5)
Key Inspection Areas
Property Management Building Inspection –
Cleaning
52. BOX PLOT DATA LAYOUT
Data Visualization
How to Display Data Graphically
Statistic Lobby Exam Room Waiting Rooms Restrooms Floors Landscape Safety/Code
1st Qrtile 3 2.75 4 2.25 3.75 4 4
min 3 2 3 2 3 3 3
median 4 3.5 4 3.5 4 4 4.5
max 4 4 5 5 5 5 5
3rd Qrtile 4 4 5 4 4.25 4.75 5
54. Data Visualization
How to Display Data Graphically
Common Graphical
Presentation Methods:
Data Table:
Bar Chart:
Scatter Graph:
Time Series:
Box Plot:
Bullet Graph:
0
25
50
75
100
Bed-STAT Bed-NEXT HCAHPS AVATAR GLOW
GERM - OR
GLOW
GERM -
PAT CARE
Excellent
Good
Fair
Poor
Actual
Target
55. BULLET GRAPH DATA LAYOUT
Data Visualization
How to Display Data Graphically
Bed-STAT Bed-NEXT HCAHPS AVATAR GLOW GERM - OR GLOW GERM - PAT CARE
Poor 40 40 25 25 40 40
Fair 30 30 25 25 30 30
Good 15 15 25 25 15 15
Excellent 15 15 25 25 15 15
Actual 59.04 90.00 65.00 82.00 95.00 91.00
Target 95 90 70 80 93 90
