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Why Data Matters Building and Sustaining a Business Case

Why Data Matters Building and Sustaining a Business Case. NEAUC Conference June 18, 2014. Presentation. Evaluation versus Performance Measurement Types of Performance Measures Inputs Outputs Outcomes Impacts Data Sources Process. 2. Evaluation versus performance measurement. 3.

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Why Data Matters Building and Sustaining a Business Case

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  1. Why Data MattersBuilding and Sustaining a Business Case NEAUC Conference June 18, 2014

  2. Presentation • Evaluation versus Performance Measurement • Types of Performance Measures • Inputs • Outputs • Outcomes • Impacts • Data Sources • Process 2

  3. Evaluation versus performance measurement 3

  4. Comparison 4

  5. Evaluation • What are the goals? • How is my program performing compared to goals or expectations? • How does it compare to other programs? • How can the program improve? 5

  6. Performance Measurement • How can I measure? • My organization’s efforts and inputs • Outcomes of those efforts • How we impacted clients • How we impacted utility • How has this changed over time? • How does my organization compare? • What are higher performers doing? • Are those actions related to results? • Can I implement those actions? 6

  7. Types of performance measures 7

  8. Types of Measures 8

  9. Inputs • Staff hours • Equipment • Travel costs • Supplies 9

  10. Input ExampleDelivery Costs 10

  11. Input ExampleItemized Costs 11

  12. Outputs • Number of customers applied • Number of customers enrolled • Service delivered • Participant characteristics • Services coordinated with other programs 12

  13. Output ExampleCustomers Served 13

  14. Output ExampleCustomer Characteristics 14

  15. Output ExampleCustomer Characteristics 15

  16. Output ExampleService Type 16

  17. Output ExamplePayment Type 17

  18. Output ExampleGrant Type 18

  19. Output ExampleMeasures Installed 19

  20. Outcomes • Reduction in bill • Reduction in energy burden 20

  21. Outcome ExampleBurden Reduction 21

  22. Outcome ExampleBurden Reduction 22

  23. Outcome ExampleHeat Restoration 23

  24. Impacts • Bill payment coverage rates increased • Service terminations declined • Energy usage declined 24

  25. Impact ExampleCustomer Survey 25

  26. Impact ExampleArrearage Impacts 26

  27. Impact ExampleService Terminations 27

  28. Impact ExampleUsage Impacts 28

  29. Impact ExampleMajor Measures 29

  30. Impact ExampleCost-Effectiveness 30

  31. Data sources 31

  32. Agency Records • Most accessible • Should be put in a database • May not be needed if good program database • Data • Customers served • Characteristics – income, poverty level, elderly, children • Services provided 32

  33. Public Use Data • Available for free download • Characterize eligible population in service territory • Programming skills needed • Data • Number eligible • Geography • Characteristics – income, poverty level, elderly, children, language • Energy costs 33

  34. Customer Survey • Real time feedback • Requires staff time • Document methodology • Data • Customer characteristics • Satisfaction • Self-reported impacts 34

  35. Program Database • Program manager – state or utility • Canned reports • Queries • Data • Customers served • Characteristics – income, poverty level, elderly, children • Services provided 35

  36. Utility Data • Difficult to obtain • Easier for utility managed program • Requires software and programming skills • Data • Customer type – heating, water heating, baseload • Energy usage • Energy bills • Customer payments • Energy assistance 36

  37. process 37

  38. Process • Start with available data • Identify performance measures • Determine additional data sources • Collect additional data • Develop additional performance measures 38

  39. summary 39

  40. Summary • Performance measurement overlaps with evaluation • Start with program goals • Work with available data • Identify ways to enhance data • Measure performance over time • Identify areas for improvement • Impact measures require more data and analysis 40

  41. Contact Jackie Berger, Ph.D. President and Co-Founder APPRISE 32 Nassau Street, Suite 200 Princeton, NJ 08542 609-252-8009 jackie-berger@appriseinc.org www.appriseinc.org 41

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