From Data to WisdomProfessor Christopher Weare

Government Transformation Conference Feb. 2015

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Fi$CalNewly Digitized Data

What will Happen to Public Managers?

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The Road to WisdomData

InformationKnowledge

Wisdom

Raw Data is of Little UseRespondent Quarter Year Office Mode

# of Cust. Served Staff Transaction Time spent

Overall Rating

HelpfulnessRating

AccomplishedGoal?

FormsUnderstandable

1001 Q1 2012 Mail 1577 3 4 1 4 5 51002 Q2 2014 1 Office 1622 9 4 20 4 3 4 51003 Q3 2014 4 Office 1312 9 8 24 2 5 4 51004 Q4 2013 4 Office 1308 12 8 9 5 2 2 51005 Q1 2013 1 Office 1780 12 1 12 2 3 3 51006 Q2 2013 Mail 1127 3 29 4 5 3 21007 Q3 2014 2 Office 1557 10 7 28 3 1 5 51008 Q4 2013 Internet 858 7 6 5 4 3 31009 Q1 2014 Internet 976 2 16 5 1 1 51010 Q2 2011 Mail 976 7 6 4 2 5 51011 Q3 2012 2 Office 872 17 4 19 1 5 5 51012 Q4 2014 Internet 1523 2 3 4 5 4 51013 Q1 2013 Mail 1711 8 27 4 4 2 21014 Q2 2012 Internet 994 3 27 5 4 1 31015 Q3 2012 Mail 1879 5 6 3 4 2 51016 Q4 2014 Internet 1980 2 5 3 1 3 21017 Q1 2013 1 Office 1467 12 4 29 3 5 3 41018 Q2 2014 3 Office 1006 11 1 22 1 3 5 21019 Q3 2012 Mail 1227 6 27 1 5 1 11020 Q4 2012 Mail 860 8 15 5 1 3 51021 Q1 2011 Internet 892 5 23 3 5 2 51022 Q2 2011 Internet 1086 3 27 4 2 1 11023 Q3 2011 Mail 938 6 19 5 4 2 11024 Q4 2012 Mail 1308 7 22 1 1 4 31025 Q1 2012 3 Office 1189 15 2 27 1 3 3 31026 Q2 2014 4 Office 1105 9 7 5 1 3 1 51027 Q3 2012 Mail 1065 5 11 4 4 5 41028 Q4 2011 1 Office 979 14 3 23 5 2 2 41029 Q1 2013 4 Office 1737 12 1 21 1 3 1 51030 Q2 2014 3 Office 1854 11 2 13 2 2 4 51031 Q3 2013 Internet 1756 5 29 5 1 3 31032 Q4 2014 Internet 981 2 26 2 3 2 21033 Q1 2012 3 Office 1017 15 8 23 3 1 4 11034 Q2 2013 Internet 1497 8 22 1 5 3 41035 Q3 2013 1 Office 1239 12 2 9 3 3 4 11036 Q4 2012 Internet 1522 3 22 1 2 3 41037 Q1 2013 Mail 1149 8 30 1 4 3 5

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The Road to WisdomData HUH?!?InformationKnowledge

Wisdom

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The Road to WisdomData

Information What is going on?Knowledge

Wisdom

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The Road to WisdomData

Information Knowledge How do results arise?

Wisdom

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The Road to WisdomData

InformationKnowledge

Wisdom Why and how does data further organizational mission

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How to Navigate the Road to Wisdom?

Data

KnowledgeInformation

WisdomInquire

Explain

Lead

• Do not fear curiosity!• All data has a story to

tell• Look for– Trends– Outliers– Anomalies– Performance Gaps– Performance Examplars

Graph It!

Excel’s Most Powerful Functions

Agency Performance Dashboard • 4th Q 2014 Performance

10%

10%

20%

30%

40%

50%

60%

70%

80%

Applicant Satisfaction 2014 4Q

% Rating Service Good or Excellent

Target: 70%

Target Achieved

Applicant Satisfaction measures on a 5-point scale how satisfied our customers were completing and submitting a service request

All That Data Going to WasteRespondent Quarter Year Office Mode

# of Cust. Served Staff Transaction Time spent

Overall Rating

HelpfulnessRating

AccomplishedGoal?

FormsUnderstandable

1001 Q1 2012 Mail 1577 3 4 1 4 5 51002 Q2 2014 1 Office 1622 9 4 20 4 3 4 51003 Q3 2014 4 Office 1312 9 8 24 2 5 4 51004 Q4 2013 4 Office 1308 12 8 9 5 2 2 51005 Q1 2013 1 Office 1780 12 1 12 2 3 3 51006 Q2 2013 Mail 1127 3 29 4 5 3 21007 Q3 2014 2 Office 1557 10 7 28 3 1 5 51008 Q4 2013 Internet 858 7 6 5 4 3 31009 Q1 2014 Internet 976 2 16 5 1 1 51010 Q2 2011 Mail 976 7 6 4 2 5 51011 Q3 2012 2 Office 872 17 4 19 1 5 5 51012 Q4 2014 Internet 1523 2 3 4 5 4 51013 Q1 2013 Mail 1711 8 27 4 4 2 21014 Q2 2012 Internet 994 3 27 5 4 1 31015 Q3 2012 Mail 1879 5 6 3 4 2 51016 Q4 2014 Internet 1980 2 5 3 1 3 21017 Q1 2013 1 Office 1467 12 4 29 3 5 3 41018 Q2 2014 3 Office 1006 11 1 22 1 3 5 21019 Q3 2012 Mail 1227 6 27 1 5 1 11020 Q4 2012 Mail 860 8 15 5 1 3 51021 Q1 2011 Internet 892 5 23 3 5 2 51022 Q2 2011 Internet 1086 3 27 4 2 1 11023 Q3 2011 Mail 938 6 19 5 4 2 11024 Q4 2012 Mail 1308 7 22 1 1 4 31025 Q1 2012 3 Office 1189 15 2 27 1 3 3 31026 Q2 2014 4 Office 1105 9 7 5 1 3 1 51027 Q3 2012 Mail 1065 5 11 4 4 5 41028 Q4 2011 1 Office 979 14 3 23 5 2 2 41029 Q1 2013 4 Office 1737 12 1 21 1 3 1 51030 Q2 2014 3 Office 1854 11 2 13 2 2 4 51031 Q3 2013 Internet 1756 5 29 5 1 3 31032 Q4 2014 Internet 981 2 26 2 3 2 21033 Q1 2012 3 Office 1017 15 8 23 3 1 4 11034 Q2 2013 Internet 1497 8 22 1 5 3 41035 Q3 2013 1 Office 1239 12 2 9 3 3 4 11036 Q4 2012 Internet 1522 3 22 1 2 3 41037 Q1 2013 Mail 1149 8 30 1 4 3 5

Compare, Compare, Compare• Time• Geographic subunits• Delivery method• Service populations• Administrative units• To similar governments (other states)• To benchmarks

Graph It!

Ask for a line chart

Organize by Year and Quarter

Are we Improving with Time?

Now we have some useful information concerning WHAT is going in our organization

Building Knowledge from Information

• What is behind this decline in customer satisfaction?

• Tell a story . . .

The rise of the internet and changing expectations

• Draw some expectations

Graph It!

Ask for a line chart

Organize by quarter & delivery mode

Hmm, Office Visits are not popular

Dig Deeper

Ask for a line chart

Compare Performance of Offices

Dig Deeper

Be Skeptical• Don’t believe everything that you think• Don’t believe everything the data says– Is Manager D’s poor ratings due to poor performance? – Or, is it simple bad luck?

• That is a hypothesis test (yes, a little statistics comes in handy)

• Avoid chasing shadows

If Managers Are Not the Root Cause, Then What?

• Tell another story . . .

Budget cuts have hit office staffing very hard compromising their ability to provide top-notch

service• You have data on staffing and customer load• Division is essential analytic tool:

Staffing Appears Increasingly Strained

2011 4Q 2012 1Q 2012 2Q 2012 3Q 2012 4Q 2013 1Q 2013 2Q 2013 3Q 2013 4Q 2014 1Q 2014 2Q 2014 3Q 2014 4Q0

20

40

60

80

100

120

140

160

Average Customers / Staffer 2011-14

Dig Deeper

Compare transaction/staff to

satisfaction

Ask for a Scatter Plot

Customer Load Decreases Satisfaction

80 90 100 110 120 130 140 1500.4

0.5

0.6

0.7

0.8

0.9

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Relationship Between Staffing and Customer Sat-isfaction 2011-2014

Customers Served per Staffer

% Rating Service Good or Excellent

Now we have knowledge of HOW declines in satisfaction are coming about.Understanding cause-effect relationships is the foundation for management.

Wisdom: The most illusive goal

WISDOM

Knowledge is Ambiguous

Avoid Rigidity

Leadership

• Judicious application of knowledge• Create a culture of curiosity• Build organizational purpose around

data-based knowledge• If you can't measure it, you can't manage it.”

Former NYC Mayor Michael Bloomberg

• Think capacity building not accountability

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RecapData

Raw and unintelligible KnowledgeInformation that has

been explained

InformationOrdered data that can

be interpreted

WisdomKnowledge promotingorganizational purposeInquire

Graph DataUse all the Data

Compare, CompareSearch for trends &

anomalies

ExplainTell Stories

Check ImplicationsBe SkepticalDig Deeper

LeadManage Judiciously

Promote Analytic CultureLink Org. Purpose to Data

Capacity over Accountability

Want to Know More? weare-performance-management.blogspot.com

USC in Sacramento

•6th ranked MPA in the country•Complete the degree in Sacramento•Finish in 2 years while working fulltime