10 Decisions You Will Face With Any Donor Data Migration Project
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Transcript of 10 Decisions You Will Face With Any Donor Data Migration Project
10 Decisions you will face with any donor data migration
present
?
&
Our Agenda
1. Overview 2. Some ground rules 3. Data migration - the process, the plan 4. 10 unavoidable decisions
– And what to do about them
5. Takeaways and Q&A
Please participate in our online poll while we get organized for today’s event.
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Nonprofit Data Services Founded in 2013 by professionals with 20+ years of technology and data experience with
Fortune 500 companies, the federal government, and nonprofits Offices in Washington, DC and Seattle, WA metro areas
www.thirdsectorlabs.com
LEVEL 1: ASSESSMENTS, CLEANING
LEVEL 2: DATA MANAGEMENT,
ENRICHMENT, MIGRATION
LEVEL 3: WAREHOUSING, MINING,
INTEGRATION !
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Gary Carr President, Co-founder
[email protected]/in/gpfcarr
Let’s get started
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10 Decisions you will face in any donor data migration
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No decision is still a decision
Highly degradable … just like people’s
lives
As in “unavoidable”
There is always risk when you
move something
Data confounds us … why?
“It is a capital mistake to theorize before one has data.” • Sherlock Holmes !“Data is the new oil.” • Attributed to many people !!
“Data is not the new oil, but instead a new kind of resource entirely.” • Jer Thorp, in a Harvard Business Review article
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Confound, kon-FOUND, (verb), to perplex or amaze - to through into confusion
Here’s the heart of the problem …
“Personally, the NSA collecting data on me freaks me out. And I’m from the generation that wants to put a GPS in their kids so I always know where they are.” • Joss Whedon, screenwriter, director !!
We are feeling overwhelmed … !Big data = big confusion … !What data do we need … and what can we ignore?
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Answering this question …
!“What donor data do we need …
and what can we ignore?” !! ... sums up the purpose of today’s webinar.
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You are here today because …
1. You are in the midst of a CRM migration and you are looking for insights
!1. You have a CRM migration coming up !1. You have completed a CRM data migration recently and
you are still wrestling with some problems !1. Data inspires you!
– Then you must want a job with Third Sector Labs ☺
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Let’s set some ground rules
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“Never tear down a bridge before you know why it was built. It may be your only means of retreat.”
- Winning general - Smart technologist
Our data migration ground rules
1. Your donor relationships depend on data – all of them. Therefore you need your donor data to be as “complete” as possible. !
2. “Complete” = what you will actually use. !
3. Your shiny new CRM represents your fundraising future, NOT your past. !
4. Not making a decision is still making a decision. !
5. All data migrations start with an understanding of the process, and they require a plan.
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The process and the plan
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It’s data moving time
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?
The technical process
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We shove all of that …
01010100110111000101011000
11001010101010101010000101
10110001111100101001010010
… into there
The technical process … really
1. ANALY
SIS
2. MAPPING
3. DATA
EXTRACTION
4. CONFIGURE NEW
DATABASE
5. CREATE IMPORT FILES
6. IMPORT
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The technical process … really … REALLY
1. ANALYSI
S
2. MAPPI
NG
3. DATA
EXTRACTION
4. CONFIGURE NEW
DATABASE
5. CREATE IMPORT FILES
6. IMPORT
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Clean now or later?
Parse now or later?
Run test file
Re-configure database
Test import results
Re-import
Test again
Clean, parse?
Archive
Creating a plan
Actually, your data experts will build the plan !You want to plan ahead and be prepared … and ask better questions.
!Start with a checklist
!Here’s one from the Third Sector website. http://3rdsectorlabs.com/resources/data-migration-checklist/
Checklists
10 unavoidable decisions
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#1 Do we need data governance policies? (by the way, what is “data governance?”)
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Data governance
What’s that?
Correct answer
“Yes!” !
Why? !Without policies and standards, you won’t be able to make the necessary decisions to complete your data migration. !There will be too many unanswered questions.
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Examples
1. Purpose – For what purposes do we store donor / constituent data? – What defines a “complete” donor record?
2. Processes – What are our processes for data gathering / input? – How frequently (and on what schedule) will we clean / update / enrich our
donor data? 3. Storage
– How long do we store old records? – When does a prospect stop being a prospect and just become ‘bad data’? – How many instances of an address or phone # or email do we store?
4. Security – What are our data security standards?
5. Other … compliance? Systems integration?
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#2 How many years of donor data do we migrate?
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Wrong answer
The data hoarder in us all says:
! “Bring it all!”
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Correct answer
(Answering a question with a question) !When was the last time you logged into your CRM and studied donors or gifts older than 3 years?
“Start with 3 years” !Justify anything else with specific use cases … not fear of losing data !Archive the rest
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#3 What about lapsed donors – do import them too?
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Hint
• This is a communications / fundraising problem. • NOT a data problem
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????
Correct answer: “It depends”
Option A: “Segment your lapsed donors upon import.” • For newer, retention-based
CRMS like Bloomerang
Why? You need a separate outreach strategy for lapsed donors: - 2 or 3 communications - New messaging,
targeted - Anyone responding goes
into the new CRM - Purge non-respondents
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Correct answer: “It depends”
Option B: “Do not import lapsed donors.” • If you can use your old system • To manage the targeted
outreach campaign mentioned on the previous slide
Why? The majority of your lapsed donors are probably lost - Don’t muck up your new
CRM engine with a bunch of gunk
- Only bring over the lapsed donors that you re-engage
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#4 What about data that we can’t / don’t import?
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Wrong answer
• “Keep trying … there’s got to be a way to get it all in there.” !
• “But it all fits in the old system!”
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Correct answer
Why? • Legacy data may be poorly
formatted • Corrupt • Doesn’t fit new CRM data
structure • Doesn’t fit with new data
governance policies • You want to be able to get
to it later … if you need it
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• No, not in an actual file cabinet …
• Microsoft Excel, Access … something simple
“Archive it.” !
#5We have a couple of ad hoc text fields with lots of notes – what do we do about them?
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Wrong answer
“We need text fields in our new CRM database.” !“You never know when we may need the flexibility.”
L Name F Name Gift Notes
Abrams Sally $500 Born 3/4/74 Married, Dave One child, Cindy Michigan State
David Randel $250 Has vacation home in Florida Wife, Cheryl Subscriber to
Forresta Jacque 4/17 – spoke about giving; made pledge 5/14 – followed up
Nevers Alicia $50 Only send emails; do not direct mail
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Correct answer
“Save it, and parse it …
later”
Why? • Don’t let a parsing project
interfere with a data migration … it will slow you down.
• The text data needs analysis.
• The parsing potential needs to be assessed against your CRM database.
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What is parsing?
1. Analyze fields 2. Look for opportunities to
break data into multiple fields
3. Export to suitable tool … (Excel often works)
4. Separate the data in a new file
5. Map the new fields to the database
6. Re-import data in the new file format
L Name F Name Gift Notes
Abrams Sally $500 Born 3/4/74 Married, Dave One child, Cindy Michigan State
David Randel $250 Has vacation home in Florida Wife, Cheryl Subscriber to
Forresta Jacque 4/17 – spoke about giving; made pledge 5/14 – followed up
Nevers Alicia $50 Only send emails; do not direct mail
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The result
L Name F Name Gift D.O.B. Spouse Children Alma Mater
Subscriber
Comm Choice
Soft Credit
Notes
Abrams Sally $500 3/4/74
Dave Cindy Michigan State
All Dave Smith
David Randel $250 Cheryl Yes All Has vacation home in Florida
Forresta Jacque All 4/17 – spoke about giving; made pledge 5/14 –
Nevers Alicia $50 Email
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Ground rule reminder: !
“Complete” = what you will use
#6When should our data be cleaned, before or after the data migration?
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Data hygiene polling dataWhen was the last time you cleaned your donor
data?
0.53
0.04
0.13
0.29
3 months6 months12 monthsNot sure
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*Data from TSL 2014 webinar attendees
Correct answer: “It depends”
Rule of thumb: “Before migration.”
Why? Only bring over clean data: - Apply data governance - Normalize - De-dupe - Purge !Post import: - Append - Parse
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Correct answer: “It depends”
Exception to the rule: “After migration.”
Why? • If the plan calls for it !• If too many records are
co-mingled in a larger database … uncertainty about record ownership
!• If there is migration
urgency
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#7We are three months into our data migration project and we just figured out that some data fields won’t translate to the new CRM. What do we do now?
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We feel this way, but …
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This is not uncommon
1. This usually occurs after analysis, data mapping, CRM configuration and initial testing is underway.
2. Then … Ah-ha!! 3. Some fields in the new CRM are not interpreting data
the way you expected . 4. How do you know?
– Reports look wrong – Data seems missing – Donor profiles appear incomplete
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What to do
1. Stop the imports 2. Identify data gaps and mistakes 3. Re-map
– This can be tedious
4. Re-configure the new CRM database – Do you need new or custom fields?
5. Create new test files – Does the problem lie with the test file itself?
6. Then re-run your test imports
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But be open minded
!• If you can’t figure out a way for the new CRM to
accommodate the old data, you probably don’t need it … and you were trying to hold onto it for the wrong reasons.
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Ground rule reminder: !
The new CRM represents your future, not your past!
• Is the real issue that the old database is suffering from bad data management practices that the new CRM won’t tolerate?
#8We can’t agree on what data to keep and what to purge. Can’t we just bring it all over to the new CRM and decide later?
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Correct answer
“No!” !
Why? • You are stuck on one or
more data governance policies that you don’t want to follow. !
• Work through the problem. !
• Remember: archiving data is your piece of mind.
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Ground rule reminder: !
No decision IS a decision
#9Once the migration is completed – and our data is rock solid – who should be responsible for maintaining data quality?
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Potential answers
1. Tech team or dba (database administrator)
2. Marketing / communications 3. Fundraising 4. Consultant
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(Just don’t expect this level of enthusiasm)
Correct answer
!
“Any of them”
Why? • All are good choices • Depends on your org
structure !
What is necessary: 1. Accountability 2. Budget 3. Manage data quality on
its own schedule
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What do we know about data quality?
“If your data isn’t getter better, it’s getting worse” -- TSL data scientist
!!“What? Harumph! Why?”
-- audience
Data DEGRADES!Cause #1: your organization
– Lack of data entry standards – Unskilled data entry workers – Common mistakes – Record fragmentation
Cause #2: the technology – Multiple, disparate systems – System upgrades – Integration, processing errors – Sheer volume of data
Cause #3: those darned donors … life! – Change in address … every 5 to 7 years – Change in jobs … 9 to 11 jobs in a lifetime – Family / life event … divorce rate, birth of children, death … what else?
This guy is not the problem
Data quality “BIG THREE”
Three necessary ingredients: !1. Accountability
!2. Budget
!3. Schedule
– (separate from fundraising and communication deadlines)
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#10 Do we need a data consultant to complete our CRM migration, or can we just rely on our new vendor?
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At the risk of sounding self-serving …
“Probably” !
(unless you have in-house staffing with time on their hands)
Why? !
• You need one or more resources who can: – Extract legacy data – Clean, normalize and purge – Create import files for the
new CRM – Create post-migration
archives
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Remember the technical process?
1. ANALYSI
S
2. MAPPI
NG
3. DATA
EXTRACTION
4. CONFIGURE NEW
DATABASE
5. CREATE IMPORT FILES
6. IMPORT
58
Clean now or later?
Parse now or later?
Run test file
Re-configure database
Test import results
Re-import
Test again
Clean, parse?
Archive
Who is doing this work?
CRM vendor tech resources
• Want to receive a clean data set • Configure the CRM database • Import the clean data • Get done as quickly as possible !
Advice: Be sure to review a plan - including roles and responsibilities - with your new vendor.
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Ground rule reminder: !
Data migrations require a plan
Desired outcome of making these unavoidable decisions
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There are many
1. Future focused, ready to go 2. Clean data 3. No wasted money on per-record SaaS costs 4. No wasted time due to bad data clogging up systems,
exports, etc. 5. Better donor relationships 6. Improved fundraising results
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Remember … even with a new CRM
garbage in, garbage out
In conclusion
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Take-aways
1. Understand the CRM data migration process 2. Identify the key decisions that will be made along the
way 3. Understand your options, but make your decisions 4. Have a sense of preparedness and control over your
next data migration project
How we can help
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Data basics • Assessments, hygiene, management !
Data intermediates • Migrations, integrations, security !
Data advanced • Warehousing, mining, analytics,
integrations
Gary Carr President, Co-founder
ThirdSectorLabs.com [email protected]
linkedin.com/in/gpfcarr
For your time and attendance …and …
a special thanks to our host
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Thank you!
We’d like to hear from you!Please submit your questions…
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Q & A
Extra slides for now
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Suggested poll questions
1. Is it easier or more difficult to execute a fundraising campaign today than 5 or 10 years ago? – Easier – More difficult – About the same
2. How many technology systems are you using to execute the campaign?
– 1 – 2 – 3 – 5 – 6+
3. Who is responsible for maintaining data quality in your organization?
– Database / tech staff – Marketing or fundraising staff – Well call a consultant – Not sure
The technical process … really
1. ANALYSIS 2. MAPPING 3. DATA EXTRACTION
4. Clean now or later?
5. Parse now or later?
6. NEW DATABASE
CONFIGURATION
7. Test file8. Re-
configure database
9. CREATE DATA IMPORT
FILES10. IMPORT 11. Test 12. Re-import
13. Test14. Remaining
cleaning, parsing
15. Create archives
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Steps most people focus on
Data quality vs. data degradation
“Data degrades” !
• What does that mean?
Who is making sure you break down silos …
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To achieve one complete view?
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Aha! Here she is!