10 Decisions you will face with any donor data migration

present

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&

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

gcarr@thirdsectorlabs.comlinkedin.com/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

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“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 gcarr@thirdsectorlabs.com

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!