michael_cook_DASHBOARDS-IFMA Presentation-3-5-2012 (2)

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

http://ifma.confex.com/ifma/ff2012/proposals/extra/index.cgi?username=2074&password=326830&EntryType=Session&returnurl=http://ifma.confex.com/ifma/ff2012/speakerscorner.cgi?EntryType=&username=470&password=664735&returntext=Back to Speaker's Corner

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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.

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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.

Kaiser Permanente is an Integrated Health System

Kaiser Foundation Health Plan

Permanente Medical Groups

Kaiser Foundation Hospitals

Page 6

Page 7

Kaiser Permanente’s Reach

Recognized as one of America’s leading health care providers and not-for-profit health plans

8.9M members

37 hospitals611 medicaloffices

9 states and the District of Columbia

15,853 physicians167,178 employees

$47.9B operating revenue

DASHBOARDS:

How to Identify, Track, and Display Key Performance Indicators

This May Not Be For You If:

Not For You If:

No Excel Experience

Fear of Raw Data

Charts Make You

Dizzy

You’re Bored If:

You’re Bored If:

You’re an Excel Power User

You Program in Visual Basic

You’ve Produced 100’s of Dashboards

Just Right If:

Just Right If:

Moderate Excel Experience

Need to Understand Your Data Better

Focused on Making Decisions

Success Defined As:

Success Defined As:

Increased Knowledge of Key

Performance Indicators

Can Apply Techniques Today

Willing to Continue to Learn

IDENTIFYING KEY PERFORMANCE INDICATORS

(KPIs)

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.)


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


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)


The Two Main Reasons for Measures and Metrics are:

Drive Change in Behavior

Drive Change in Processes

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

Critical To Quality KPIs:Identifying the “Critical Few”










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?






What Data is Used to Make Each Decision?

What Triggers the Decision?

Who Has the Data?

How do You Know the Decision was Correct?











International Facility Management Association (IFMA)

Building Owners and Managers Association (BOMA)

American Society for Healthcare Engineering (ASHE)

American Institute of Architects (AIA)






(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


Building and Grounds Cleaning and

Maintenance Occupations 104,250 $12.81 $26,653 1.47 $9.43 $11.38 $14.85


First-Line Supervisors/Managers of

Housekeeping and Janitorial Workers 3,840 $18.87 $39,267 1.54 $13.93 $17.48 $22.39



Landscaping, Lawn Service, and

Groundskeeping Workers 1,940 $23.13 $48,106 3.8 $16.15 $21.74 $28.95


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


Landscaping and Groundskeeping

Workers 18,890 $13.79 $28,680 2.12 $10.25 $12.13 $16.42


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


Building and Grounds Cleaning and

Maintenance Occupations 104,250 $12.81 $26,653 1.47 $9.43 $11.38 $14.85



Housekeeping and Janitorial Workers 3,840 $18.87 $39,267 1.54 $13.93 $17.48 $22.39



Landscaping, Lawn Service, and

Groundskeeping Workers 1,940 $23.13 $48,106 3.8 $16.15 $21.74 $28.95


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


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)






Descriptive Statistics is a valuable way to begin analyzing the data.





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

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

Re

sid

ual

s

$hour/lbr

$hour/lbr Residual Plot





Data VisualizationHow 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).

Data Visualization:

How to Display Data Graphically

Common Graphical Presentation Methods:

Data Table:

Bar Chart:

Scatter Graph:

Time Series:

Box Plot:

Bullet Graph:



Data TableBar 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

Categories 28





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


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


Walls

Wash Basin

Floor

Seating

WAITING ROOMS

Light Fixtures

LOBBY

Seating

Walls

fire extinguiser


Landings

electrical rooms

Floors

Cobwebs

Floor

Commode/Urinals

shrubs/color


Doors

Spots

exit signs

sprinkler systems

Gloss

Trip Hazards

Counter

LAND/HARDSCAPE

Windows/Treatments

bldg entrance


EXAM ROOMS

Floor

Walls

Doors

Counter Tops

Walls

safety lighting


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





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


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


Walls

Wash Basin

Floor

Seating

WAITING ROOMS

Light Fixtures

LOBBY

Seating

Walls

fire extinguiser


Landings

electrical rooms

Floors

Cobwebs

Floor

Commode/Urinals

shrubs/color


Doors

Spots

exit signs

sprinkler systems

Gloss

Trip Hazards

Counter

LAND/HARDSCAPE

Windows/Treatments

bldg entrance


EXAM ROOMS

Floor

Walls

Doors

Counter Tops

Walls

safety lighting



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

BAR GRAPH

BENEFITS:

Graph

Distribution

Great for Time Series

Easy to Interpret

0

500

1000

1500

2000

2500

apr may jun jul aug sep

Series1



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

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

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



Complaint:

It’s TOO HOT!

Action:

Plotted Data

Peak Temps Above 90 Degrees

65

70

75

80

85

90

95

8/18 8/25 9/1 9/8 9/15



Shaded Weekends

65

70

75

80

85

90

95

8/18 8/25 9/1 9/8 9/15



Shaded Weekends

Added High and Low Limits

65

70

75

80

85

90

95

8/18 8/25 9/1 9/8 9/15



Shaded Weekends

Added High and Low Limits

Added Legend

65

70

75

80

85

90

95

8/18 8/25 9/1 9/8 9/15

weekend

Int Temp (F)

low temp

high temp

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

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

COMBINATION

BENEFITS:

Show Several Series at Once

Provides Context

Easy to Interpret

65

70

75

80

8/17 8/24 8/31

weekend

Int Temp (F)

high temp

low temp



Data Table:Bar Chart:

Scatter Graph:

Time Series:

Box Plot:Bullet Graph:

1

3

5

Lobby Exam Room WaitingRooms

Restrooms Floors Landscape Safety/Code

Rati

ng

(1 t

o 5

)

Key Inspection Areas

Property Management Building Inspection –Cleaning

BOX PLOT DATA LAYOUT


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

BOX PLOT

BENEFITS:

Graph

Descriptive

Inter-Quartile Range

Median 1

3

5

Lobby Exam Room WaitingRooms

Restrooms Floors Landscape Safety/Code

Rati

ng

(1 t

o 5

)

Key Inspection Areas

Property Management Building Inspection – Cleaning



Data Table:

Bar Chart:

Scatter Graph:

Time Series:

Box Plot:

Bullet Graph:0

25

50

75

100

Bed-STAT Bed-NEXT HCAHPS AVATAR GLOWGERM - OR

GLOWGERM -

PAT CARE

Excellent

Good

Fair

Poor

Actual

Target

BULLET GRAPH DATA LAYOUT


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

BULLET GRAPH

BENEFITS:

Target vs. Actual

Qualitative Range

Adjustable by Category

0

25

50

75

100

Bed-STAT Bed-NEXT HCAHPS AVATAR GLOWGERM - OR

GLOWGERM - PAT

CARE

Excellent

Good

Fair

Poor

Actual

Target

Final Cover of Dashboard

BENEFITS:

Combine Several Elements

Provide Overall Perspective

For attending this educational offering at IFMA’s Facility Fusion.

Thank You!

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