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Kirk Schmidt | Method Works Consulting
Data and Strategy:
Cultivating Their
Relationship
• 9 years in the charitable sector, 6 as a process and systems
consultant.
• IT background
• B.Math (Waterloo)
• Master Storyteller (when dice are involved)
Kirk Schmidt
• Data Acquisition Strategy
• Data-based Strategy in Fundraising
• Data Safety Strategy
• Questions/Comments/Tomato Dodgeball
Data and Strategy: Overview
“Trust, but verify.” -Reagan
Data Acquisition
Strategy
• What is the absolute minimum you are willing to put in your
database?
• Is there value in keeping a single piece of information as a
record?
• Can it be used to analyse and model?
Minimum Data
• Financial Cost
• Time spent entering the
data
• Time spent researching the
data
• Wasted time on data that
will never be of use
The Cost of Acquisition
• What data might you need
verification for?
• Determine if it is worth
investing (time or money)
in verification of data
• What could go wrong?
• What data requires
constant maintenance in
our database?
• Determine if it is worth
investing (time or money)
in maintenance of the data
• Maintaining researched
information
Maintenance and Verification
• Difficult cost to measure and plan for
• This cost is weighted against verification and maintenance
(or even against acquiring data in the first place)
• What risk does stale data pose? How can you deal with it?
The Cost of Getting It Wrong
• Minimum Data Strategy
• Cost of Acquisition
• Cost of Maintenance and Verification
• Cost of Getting It Wrong
You have to TRUST your data before you can use it to build
data-based strategies in fundraising.
Review: Data Acquisition Strategy
“However beautiful the strategy, you should
occasionally look at the results.” -Churchill
Data-based
Strategy in
Fundraising
• Definition: “commercial or professional procedures that are
accepted or prescribed as being correct or most effective.”
• Charities are at the infancy of data-based strategy
• Requisite Penelope Burk reference
• How do we do our own?
Best Practices
• Observations
• Questions
• Hypothesis
• Prediction
• Testing
• Analysis
The Scientific Method
OBSERVATION AND QUESTION TIME
Giving Time Vs. Third Gift
Most Common Giving Amounts
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
2010 2011 2012 2013 2014 2015 2016
Most Common Gift Amounts for Fiscal 2011 to 2015
Long Term Retention Rates
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Repeat 1 Repeat 2 Repeat 3 Repeat 4 Repeat 5
Long Term Retention Rate
Number of Gifts Processed by Time
• Once you have your questions, you can start hypothesising,
predicting, and testing.
• Change one variable at a time.
• Start small – observe your data and ask questions.
Review: Data-based Strategy
“The charitable sector is the easiest, and
most lucrative, target that has yet to really
see a major public breach.”
Data
Safety
Strategy
• The two cars
• You are a bigger target than your servers
Not Just IT
• Relatively accurate and comprehensive data
– Names, addresses, email, phone numbers, workplace
information, birth date and spousal information
– Donation history, sometimes including bank accounts and
partial credit card numbers
– Prospect research data (yachts!)
• Relatively small IT budgets and staff to deal with controls
and compliance
• No culture of awareness of the dangers
The Risk
• Exporting information out of the database into an excel file
and putting on external media.
• Printing out donor briefing documents and carrying them
around.
• Emailing information.
• Answering the telephone.
Potential Failures
• Carry as little sensitive information as possible, or protect it
(if you have the know-how to do so)
• Process for checking out and checking in documents
• Email as little as possible, or transfer information through
more secure means
• On the phone, put onus on the caller
• Think like a hacker
Protecting Yourself
• Basic overview today
• Know that you are the biggest risk to your data, not the IT
infrastructure
• Understand why charities are potentially a relatively easy
and lucrative target
• Protect yourself and have process where possible
Data Safety Strategy
Wrapping it up
• Data Acquisition Strategy
– Acquiring, Maintenance, Verification, Getting it Wrong,
Minimum Data
• Data-based Strategy in Fundraising
– Using analytics to observe, question, test, and change process
• Data Safety Strategy
– Everyone’s responsibility
Data and Strategy
Kirk Schmidt
Method Works Consulting
kirks@methodworksconsulting.com
403-971-9905
Questions, Comments,
Tomato Dodgeball

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Data and Strategy: Cultivating Their Relationship

  • 1. Kirk Schmidt | Method Works Consulting Data and Strategy: Cultivating Their Relationship
  • 2. • 9 years in the charitable sector, 6 as a process and systems consultant. • IT background • B.Math (Waterloo) • Master Storyteller (when dice are involved) Kirk Schmidt
  • 3. • Data Acquisition Strategy • Data-based Strategy in Fundraising • Data Safety Strategy • Questions/Comments/Tomato Dodgeball Data and Strategy: Overview
  • 4. “Trust, but verify.” -Reagan Data Acquisition Strategy
  • 5. • What is the absolute minimum you are willing to put in your database? • Is there value in keeping a single piece of information as a record? • Can it be used to analyse and model? Minimum Data
  • 6. • Financial Cost • Time spent entering the data • Time spent researching the data • Wasted time on data that will never be of use The Cost of Acquisition
  • 7. • What data might you need verification for? • Determine if it is worth investing (time or money) in verification of data • What could go wrong? • What data requires constant maintenance in our database? • Determine if it is worth investing (time or money) in maintenance of the data • Maintaining researched information Maintenance and Verification
  • 8. • Difficult cost to measure and plan for • This cost is weighted against verification and maintenance (or even against acquiring data in the first place) • What risk does stale data pose? How can you deal with it? The Cost of Getting It Wrong
  • 9. • Minimum Data Strategy • Cost of Acquisition • Cost of Maintenance and Verification • Cost of Getting It Wrong You have to TRUST your data before you can use it to build data-based strategies in fundraising. Review: Data Acquisition Strategy
  • 10. “However beautiful the strategy, you should occasionally look at the results.” -Churchill Data-based Strategy in Fundraising
  • 11. • Definition: “commercial or professional procedures that are accepted or prescribed as being correct or most effective.” • Charities are at the infancy of data-based strategy • Requisite Penelope Burk reference • How do we do our own? Best Practices
  • 12. • Observations • Questions • Hypothesis • Prediction • Testing • Analysis The Scientific Method
  • 14. Giving Time Vs. Third Gift
  • 15. Most Common Giving Amounts 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 2010 2011 2012 2013 2014 2015 2016 Most Common Gift Amounts for Fiscal 2011 to 2015
  • 16. Long Term Retention Rates 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% Repeat 1 Repeat 2 Repeat 3 Repeat 4 Repeat 5 Long Term Retention Rate
  • 17. Number of Gifts Processed by Time
  • 18. • Once you have your questions, you can start hypothesising, predicting, and testing. • Change one variable at a time. • Start small – observe your data and ask questions. Review: Data-based Strategy
  • 19. “The charitable sector is the easiest, and most lucrative, target that has yet to really see a major public breach.” Data Safety Strategy
  • 20. • The two cars • You are a bigger target than your servers Not Just IT
  • 21. • Relatively accurate and comprehensive data – Names, addresses, email, phone numbers, workplace information, birth date and spousal information – Donation history, sometimes including bank accounts and partial credit card numbers – Prospect research data (yachts!) • Relatively small IT budgets and staff to deal with controls and compliance • No culture of awareness of the dangers The Risk
  • 22. • Exporting information out of the database into an excel file and putting on external media. • Printing out donor briefing documents and carrying them around. • Emailing information. • Answering the telephone. Potential Failures
  • 23. • Carry as little sensitive information as possible, or protect it (if you have the know-how to do so) • Process for checking out and checking in documents • Email as little as possible, or transfer information through more secure means • On the phone, put onus on the caller • Think like a hacker Protecting Yourself
  • 24. • Basic overview today • Know that you are the biggest risk to your data, not the IT infrastructure • Understand why charities are potentially a relatively easy and lucrative target • Protect yourself and have process where possible Data Safety Strategy
  • 26. • Data Acquisition Strategy – Acquiring, Maintenance, Verification, Getting it Wrong, Minimum Data • Data-based Strategy in Fundraising – Using analytics to observe, question, test, and change process • Data Safety Strategy – Everyone’s responsibility Data and Strategy
  • 27. Kirk Schmidt Method Works Consulting kirks@methodworksconsulting.com 403-971-9905 Questions, Comments, Tomato Dodgeball

Editor's Notes

  1. START THE STOPWATCH
  2. Meet me at an event. Socially awkward, strange, not very talkative. Meet me but prepped. You start talking geeky stuff. We’re good. Meet me with 3 days prep – marginally better conversation, but LAW OF DIMINISHING RETURNS 3 day prep but some information is wrong. END 6 MINUTES
  3. What data to acquire so that you can TRUST IT How to use data to support and enhance your fundraising strategy Keeping the data safe END 8 MINUTES
  4. -Trust -*Any* and *Every* Piece of information
  5. WHAT DATA IS THE MINIMUM YOU FEEL YOU SHOULD HAVE RE Minimum is Last Name. This isn’t particularly useful. However, are there cases where a single piece of information is useful? Email? (Email interest -> donor -> major gift donor – may want to model that) Your strategy needs to include what is a minimum amount that you will accept in your database END 11 MINUTES
  6. Data Entry Cost of renting lists Time spent researching data Strategy – how are you going to use this data? YACHTS Like any other wealth research What is the cost of this research? How are you going to use this data? Researcher at $36K, 1 month of research. If we increase an ask by $5k because of this research and get it, we have a 67% ROI What happens next year?
  7. Yacht example – how much time is needed year over year to maintain? Is it worth it? 16:30 to 18 MINUTES Classic example of maintenance: National Change of Address. 15% move rate per year. 10,000 people on a list, that’s an expected loss of 1,500 accurate addresses. At $1/mailing, you’ve lost $1,500 in simply returned mail. A $500 investment in NCOA. Let’s say it fixes 50% of addresses (normally over 80%). Now you only lose $750 in lost mail, so you’re only really out $1,250 instead of $1,500. Those 750 that were fixed might even donate. 2% response rate at $50 a pop would yield another $750 you otherwise would not have received. So there is a strategy to maintenance. There are also costs to verification, and may be worth investing Deceased story What Happens If 21 TO 23 MINUTES
  8. What are the risks? Cost of getting it wrong can be hard to measure. Quick Tshirt example Can you plan for the tshirt example? No. Can you build a culture that finds maintenance and verification of data to be important? Sure. The real strategy here is – what is the cost of maintenance or verification vs getting it wrong? Our mailing example – cost of getting it wrong was $1,500 loss on mail. Is it worth the $500 NCOA? You bet. 27 to 28 MINUTES
  9. -Target Story -Burk: When donors were called by a board member within 48 hours of receiving the gift, those called gave an average of 39% more than those not called. 33 TO 35 MINUTE END
  10. Best Practice do not come from people saying, “I think…” or, “I feel…” They come from testing and data-centric models This does not mean you shouldn’t do some things. But you should constantly question it. 36 TO 38 MINUTE END
  11. We are going to look at some charts. Now these are analytics that we have performed for clients. This is all from live data, some of it random sampled, some of it the full dataset. We are going to look at what the data is telling us right now, and then what questions we can pose.
  12. This is a chart of something that should feel self-evident. Effectively, it is showing us that the percent of people who give a third gift is correlated with the number of months between their first and second gift. How can we get more people to give earlier (what if we did a matching for second gift within 3 months) ex 41 MINUTE END
  13. Next we have a bubble chart! This is actually showing us the top 5 giving amounts, and how many gifts they represent over the year. What if we changed ask ladders Why is it like this? 43 TO 45 MINUTE END
  14. This shows the percent of people who are repeat donors year over year from initial gift What type of question could you ask here? What happens if we can increase the first year? Can we use this to determine whether an acquisition strategy will make money? 46 to 48 MINUTE END
  15. Here’s a fun one. This is a time series chart of the amount of gifts processed per day over the last fiscal year, spread over a 10 business day moving average. Now this is far less about fundraising, but it is still about internal strategy. 49 to 52 MINUTE END
  16. 50 to 53 MINUTE END
  17. 52 TO 54 MINUTE END
  18. 54 TO 56 MINUTE
  19. Credit card replacement example
  20. DEFCON example for answering the telephone. 55 TO 60 MINUTE
  21. If time permits, KODAK example on think like a hacker. 63 TO 65
  22. 66 TO 68 END