April 2015 Data is Your Friend Extracting and Analyzing Statistics

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1 April 2015 Data is Your Friend Extracting and Analyzing Statistics April Harris & Aimee Gilbreath

2 TODAY S AGENDA Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 2

3 Why is Data Collection & Analysis Important? 3

Of those: 30% Neonatal Kittens 30% Medical Needs 40% Highly Adoptable Pit Bull Type dogs make up 20% of total dog

4 Anecdotes vs. Data Rescue groups cherry pick all of the highly adoptable animals. The shelters are full of nothing but pit bulls. In 2014, rescue partners pulled 1,500 animals. Of those: 30% Neonatal Kittens 30% Medical Needs 40% Highly Adoptable Pit Bull Type dogs make up 20% of total dog intake. On average, pit bull type dogs are held for 35 days prior to an outcome versus 14 days for other dogs. Which is more useful for designing and managing programs? 4

5 Ways to Use Data Analysis to Drive Impact Identify new program opportunities Geo target S/N or TNR programs Monitor compliance with policy Negotiate rates with contract cities Communicate with community Design adoption incentives Identify best/worst kennels Monitor program effectiveness Incentivize and reward staff Motivate volunteers and donors Identify opportunities for better process Save Time Save Money Save Lives 5

6 A Love Story.... Salt Lake County + Data 6

7 Steps in Data Analysis Process Collect & Validate Analyze Interpret & Act 7

8 TODAY S AGENDA Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 8

9 Your Brain Incredibly Powerful, Slightly Dangerous 9

10 Heuristics A heuristic is a mental shortcut that allows people to solve problems and make judgments quickly and efficiently. Heuristics are helpful in many situations, but they can also lead to biases. 10

11 Cognitive Bias Cognitive bias describes the inherent thinking errors that humans make in processing information. These thinking errors can prevent us from accurately understanding reality, even when we have all the needed data and evidence to form an accurate view. Said another way, cognitive bias is the common tendency to acquire and process information by filtering it through one's own likes, dislikes, and experiences. 11

12 Availability Heuristic An availability heuristic is a mental shortcut that relies on immediate examples that come to mind. As a result, you might judge that those events are more frequent and possible than others. You give greater credence to this information and tend to overestimate the probability and likelihood of similar things happening in the future. For example, after seeing several television programs on shark attacks, you start to think that such incidences are relatively common. When you go on vacation, you refuse to swim in the ocean because you believe the probability of a shark attack is high. What is an animal welfare example of the availability heuristic? 12

13 Frequency Illusion Frequency Illusion is the phenomenon in which people who just learn or notice something start seeing it everywhere. For example, when you are considering buying a particular type of car, you notice many more of that type of car on the road than ever before. The cognitive error is that you often conclude that this is because that car is becoming much more common or fashionable, rather than recognizing the reality that the only thing that's changed is that you're taking notice of those cars now. What is an animal welfare example of frequency illusion? 13

14 Negativity Bias Negativity Bias is a tendency to notice, pay more attention, or give more weight to negative experiences or information over positive. At parent-teacher conferences, your child s teacher has made several glowing comments about your son, but also mentions that he talks too much and can be disruptive at times. And though she said that they ve been working on it and that he s getting better, the only thing you heard was that your son is being disruptive in the classroom. There was only one negative comment about your son yet there were several wonderful comments, including, he s a pleasure to have in my class. What is an animal welfare example of negativity bias? 14

15 TODAY S AGENDA Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 15

16 Accurate Data Collection is Key: Beware GIGO! Garbage IN Garbage OUT If input data are not complete, accurate, and timely, then the resulting output is unreliable and of no useful value 16

17 GIGO Example: Cat Intake Zip codes with shelter locations 17

18 A Few Words on Shelter Software Different features and functions mean no one size fits all approach Data you input, you should be able to extract and analyze Standard and custom reports usually available Well worth having staff member(s) with expertise on your system 18

19 Demographic Data can be a Helpful Overlay Demographics The characteristics of human populations and population segments, especially when used to identify consumer markets. Age, Race/Ethnicity, Income, Education, Employment, Language Spoken, Housing Type, Access to Vehicle, etc. Data Sources Zip code summary Detailed zip data City/County data 19

Demographic Data Example 90064 Population 25,403 HH Income $84,579 43% Urban Chic 90031 Population 39,316 HH Income $34,655 59% Las Casas Well-educated, married couple families and singles; live in

20 Demographic Data Example Population 25,403 HH Income $84,579 43% Urban Chic Population 39,316 HH Income $34,655 59% Las Casas Well-educated, married couple families and singles; live in the suburbs of major metros on both coasts. Professional/managerial jobs fund exclusive, upscale, and sophisticated lifestyles. Portfolios are healthy, filled with stocks, bonds, and real estate investments. 2/3 own homes. Tech savvy, tops for owning Apple products, use devices to shop, bank, and research information. Leisure time is spent visiting museums, traveling, drinking imported wine, going to the movies, skiing, and practicing yoga. Mostly young married Hispanic couples with kids; live in large multi-generational households. Found in older neighborhoods on the edge of large West Coast metros. Rent houses or apartments. Bank in person, minimal savings, very little debt. Family-oriented; spending reflects interest in children and also desire to look good. Buy baby products as well as the latest trendy fashions. Big soccer fans; watch Spanish language TV channels; visit Spanish web sites. 20

21 Data Collection & Validation Tips Things to do BEFORE you start an analysis 1. Identify what data you want to analyze and why 2. Verify how that data is currently being captured in your system (i.e. who, when, how) 3. Consider whether the data is processed or modified after it is entered (i.e. intact status) 4. Validate that data values are within realm of reality (i.e. negative LOS) 5. Look for anomalies or outliers that need to be explored 21

NFHS Has Defined Minimum Shelter Data to Collect All Data by Species (Cat/Dog) and age (</> 5 mo) Annual beginning and ending shelter count Intake Stray/At Large, Relinquished by Owner, Owner

22 NFHS Has Defined Minimum Shelter Data to Collect All Data by Species (Cat/Dog) and age (</> 5 mo) Annual beginning and ending shelter count Intake Stray/At Large, Relinquished by Owner, Owner Intended Euthanasia, Transferred in from Agency, Other Outcomes Adoption, Returned to Owner, Transferred to another Agency, Returned to Field, Other Live Outcome Died in Care, Lost in Care, Shelter Euthanasia, Owner Intended Euthanasia Data Matrix & Definitions What s Your Rate? Calculation Guidance 22

Additional data will allow you to do deeper analysis that will benefit your

23 Additional Data is Very Helpful Shelter Animals Count minimum data will allow you to calculate release rates and do basic intake and outcome analysis. Additional data will allow you to do deeper analysis that will benefit your organization so we strongly suggest adding: Breed Length of Stay Intake Zip Code 23

24 TODAY S AGENDA Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 24

25 Data Analysis - OR Lies, Damn Lies, and Statistics Which shelter has the best euthanasia statistics? Shelter A Shelter B Shelter C Population Served 600, , ,000 Intake 10,000 25,000 5,000 Euthanasia 5,000 6,000 1,500 Euthanasia as % of Intake 50% 24% 30% Euthanasia per 1,000 Pop Reliance on any single metric will not give a full picture of performance 25

26 A Tale of Two Shelters Part 1 12,000 10,000 8,000 6,000 4,000 2,000 0 North Central , % 3,871 38% 4,942 48% 12,000 10,000 8,000 6,000 4,000 2,000 0 West LA , Population Served: 669,561 Intake per 1,000: 6.7 Euthanasia per 1,000: % 38% 3,139 70% % Intake RTO Population Served: 1,065,897 Intake per 1,000: 9.7 Euthanasia per 1,000: 4.6 Adoption Euthanasia Intake RTO Adoption Euthanasia 26

27 A Tale of Two Shelters Part North Central West LA Population 1,065, ,561 Intake 10,292 4,495 Intake per 1, Euthanasia 4, Euthanasia per 1, HH Income <$25,000 38% 19% HH Income <$50,000 66% 39% Renter occupied 72% 60% Speak Spanish at Home 59% 14% HH w/o Vehicle 28% 9% High School or Less 65% 24% 27

28 Making Great Graphs To compare, keep same axis scale 38% Use Data Labels to show #s Start data axis at zero Waterfall style graphs give great data visualization 28

29 Pivot Tables are Your Friend!! A pivot table is a tool in Excel that allows you to explore large sets of data interactively. Once you create a pivot table, you can quickly transform huge amounts of data into a meaningful summary. 29

Pivot Table Example Cat Intake & Outcomes 2,500 2014 Cat Intake & Outcomes by Month 2,000 1,500 1,000 500 Nearly 0 50,000 rows of outcome data becomes.

30 Pivot Table Example Cat Intake & Outcomes 2, Cat Intake & Outcomes by Month 2,000 1,500 1, Nearly 0 50,000 rows of outcome data becomes.... Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Kitten Intake Kitten Euthanasia Cat Intake Cat Euthanasia Pivot Table Tutorial 30

31 Geographic Information Systems Also Powerful Mapping Kitten Intake in Tompkins County J. Scarlett 31

Tools Available via ASPCA X Maps Spot Project http://aspcapro.

32 Tools Available via ASPCA X Maps Spot Project 32

33 Data Analysis Tips & Tricks 1. Look at numbers (#) and percentages (%) 2. Use graphs to visualize data; Waterfall style graphs are especially useful 3. Use good graph hygiene; always start graph axis at zero to avoid distortion 4. For comparison between graphs, keep same axis maximum and scale 5. For comparison between geography, normalize per 1,000 human population 6. Two words: PIVOT TABLES!! 33

34 Beware Data Analysis Pitfalls Garbage IN = Garbage OUT Boiling the Ocean Analysis Paralysis 34

35 Keep the Big Picture in Mind Goal: Maximize Live Release Decrease Intake Spay Neuter Increase Live Release Adoption Know your INTAKE What pets are coming into shelter? Why? Know your OUTCOMES What happens to pets in shelter? Why? 35

Intake by impound type (Field, OTC, etc.

36 A&A Recommended Analysis List Must Haves Intake by species Intake by type (stray, owner surrender, etc.) Outcome by type by species Live release rate (LRR) by species REALLY Nice to Haves Intake by species, age, breed Intake by impound type (Field, OTC, etc.) LOS by species, age, breed LRR by species, age, breed LOS pre-adoption and preeuthanasia Euthanasia type by species and age Animal care days by species Foster numbers Length of stay (LOS) by species 36

37 TODAY S AGENDA Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 37

38 Correlation is NOT Causation Studies have shown that people who eat yogurt regularly have a healthier body weight than those who do not eat yogurt regularly Can we therefore say that if you eat yogurt you will have a healthier body weight? YOGURT CAUSES HEALTHY WEIGHT Or, might it be that people who make healthier diet choices overall tend to eat more yogurt? HEALTHY PEOPLE EAT YOGURT We can say that eating yogurt is CORRELATED with healthy weight, we cannot say that eating yogurt CAUSES healthy weight Most results have multiple contributing causes Resist the urge to oversimplify cause and effect 38

39 Does a Poor Economy Cause Intake to Rise? Likely accurate to say worsening economy was a contributing factor to increased intake But, economy was not the only factor influencing intake 39

40 Does Seasonal Kitten Intake Cause Higher Euthanasia? 2014 Feline Intake 2014 Feline Euthanasia Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Cat Intake Kitten Intake Kitten Euthanasia Cat Euthanasia 40

Data Interpretation Tips & Tricks 1. Don t get too attached to your initial hypothesis, look for other explanations 2. Remember that correlation does not imply causation 3.

41 Data Interpretation Tips & Tricks 1. Don t get too attached to your initial hypothesis, look for other explanations 2. Remember that correlation does not imply causation 3. Recall that most outcomes are the result of multiple different variables resist the urge to over simplify! 4. Always ask yourself questions What else could be going on here? What else has changed? 41

42 Don t Despair Help is Available! Where to look for help: Your local government Area universities Professors Class projects Interns Your volunteers! 42

43 TODAY S AGENDA Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 43

44 2010 Los Angeles Intake & Outcomes - Numbers Thousands Intake Thousands % Save Rate Intake Dogs Puppies Cats Kittens 7 Euthanasia Dogs Puppies Cats Kittens 2010 Euthanasia 44

45 2010 LA Outcomes by Animal Type - Percentages 45

NKLA Program Started 2011 Used 2010 data analysis and community input to design several programs with aim to make Los Angeles No Kill by 2017 Initial programs

46 NKLA Program Started 2011 Used 2010 data analysis and community input to design several programs with aim to make Los Angeles No Kill by 2017 Initial programs included: Grants for zip code targeted spay neuter (low income) Adoption subsidies for rescue groups Kitten nursery/foster programs New adoption facilities 46

47 2010 vs 2014 Los Angeles Intake - Numbers Thousands Intake Thousands Intake Intake Dogs Puppies Cats Kittens Intake Dogs Puppies Cats Kittens 47

48 2010 vs 2014 Los Angeles Euthanasia - Numbers Thousands Euthanasia Thousands Euthanasia 77% Save Rate Euthanasia Dogs Puppies Cats 7 Kittens 5 0 Euthanasia Dogs Puppies 4 Cats 4 Kittens 48

49 2014 Outcomes by Animal Type - Percentages 49

50 Next Steps for NKLA CATS, CATS, CATS!!! Shifting S/N grant focus to cats More kitten nursery/ foster capacity Cat adoption promotions Targeting TNR to areas with high kitten intake 50

51 Does Cage Type Impact LOS for Cats at Adopt & Shop? 51

52 Cage Type Data Collection & Analysis Process What data to analyze, and why? Adult cats, In a single kennel for entire stay, after Nov Pull data from system and process Date of outcome DOB = Age Check data for errors and anomalies Eliminate records with negative LOS Calculate metrics and graph Average LOS by kennel type, range Interpret and act....all grate front kennels? 52

53 Cage Type Data Collection & Analysis Process What can we conclude? Cats in Sample

54 Where to Find This Presentation 55

Could Your Organization Use More $$$ to Save Lives? www.crowdrise.

55 Could Your Organization Use More $$$ to Save Lives? Any Questions? 54

Questions? Aimee Gilbreath a.gilbreath@foundanimals.

56 Questions? Aimee Gilbreath April Harris Follow Found Animals! 56

Today s Agenda. Why does this matter? A Dangerous Mind. Data Collection. Data Analysis. Data Interpretation. Case Studies

Today s Agenda. Why does this matter? A Dangerous Mind. Data Collection. Data Analysis. Data Interpretation. Case Studies Today s Agenda Why does this matter? A Dangerous Mind Data Collection Data Analysis Data Interpretation Case Studies 2 Why is Data Collection & Analysis Important? 3 Anecdotes vs. Data Rescue groups cherry