1. 1/7/2017 Footer 1
Processing External Sources of Data
into Blackbaud CRM
PRESENTED BY WENDY JACCARD AND JULIE VARGO
2. 1/7/2017 Footer 2
• Presenter Intro/Backgrounds
• Overview of The Ohio State University
• Biographic Data
- SIS
- HR
• Gift Data
- Imaged Gifts
• Biographic and Gift Data
- Pel, WOSU, BMV
• Questions?
AGENDA
4. 1/7/2017 Footer 4
• Wendy Jaccard, Principal Consultant, Blackbaud
• Julie Vargo, Director of Application Development, The Ohio State
University
WHO ARE WE?
5. 1/7/2017 Footer 5
• $364,822,055 Raised in Fiscal year 2012
• 498,038 of living alumni
• 1,394,264 Individuals, 192,377 Organizations, and 266,261 Groups in
BBEC
• 444,004 of Gift processed Fiscal Year 2012
- On average we process 900 Gifts per day
• 900 system users
THE OHIO STATE UNIVERSITY
6. 1/7/2017 Footer 6
• We went live with BBEC 2.9 – Aug/Sept 2011
• Replaced 5 custom built applications
• We went live with BBIS – March 2012
• We are currently in middle of Phase 2 Project
- Upgrade to 2.94
- Migrate OSU Alumni Association and Wexner Center for the Arts to BBEC
• Our current customization count is around 90 at various levels of
complexity
- A number of those are dealing with interfaces
THE OHIO STATE UNIVERSITY
7. 1/7/2017 Footer 7
THE OHIO STATE UNIVERSITY
BBEC
Gifts
Smart
Call
SIS
HR
WOSU
PEL
BMV
Payroll
Imaged
Gifts
Alumni
Assoc.
9. 1/7/2017 Footer 9
• Receive 2 files weekly from university HR system
- One file contains biographic data on employees
- One file contains employees appointment data
• Any one who is considered an active employee and any one who has left
within the last 3 months of the processing date.
• High Level Process
- Bio File
• System Runs a compare against the previous weeks file
• File is produced with the changes between the file and imported into the
system.
• Business process is run to create an update and add constituent batch
- Employee Appointment File
• System process to replace all appointment information, no user
intervention.
HR – OSU EMPLOYEE DATA
10. 1/7/2017 Footer 10
• How does it know if it is Add or Update Batch
- Matches on OSU ID/ Employee ID from HR (Alternate ID in BBEC)
- Processer is responsible for finding a match if an individual already exist by
other means
HR – OSU EMPLOYEE DATA
11. 1/7/2017 Footer 11
HR – OSU EMPLOYEE DATA
Fields Updated or Added
Constituent Business Temporary
Last/Org/Group/Household
name
Business relationship
type
Pay Frequency
First name
Business reciprocal
type
Faculty Staff
Middle name Addresses Gender
Title Phones Start Date
HR Title 2 Email addresses Work Status
Suffix HR Error Code
Constituent type Job Title
Alternate lookup IDs Emeritus
14. 1/7/2017 Footer 14
• Pulled 3 times a semester
- Current Students
- Students Applying for Graduation
- Graduates
• High Level Process
- System Runs a Query to pull from SIS System Reporting Database
- Current Student runs Compare from previous run generates a change file
- Other two just used the file pulled from SIS
- Custom Business Process run to compare to data in BBEC
• If does not find record with matching OSU ID
– Creates Add Constituent Batch
• If finds record with OSU ID
– Compares to data in BBEC creates batches for changes
SIS – STUDENT DATA
15. 1/7/2017 Footer 15
• High Level Process (cont.)
- Instead of one update batch it creates several
SIS – STUDENT DATA
A Separate Batch For:
Email Changes
Gender Changes
Home Address Changes
Phone Changes
Name Changes
Education Information Changes
Other Changes (FERPA , Nationality, Alternate Lookup ID)
16. 1/7/2017 Footer 16
• High Level Process (cont.)
SIS – STUDENT DATA
Fields Updated or Added
Constituent Addresses
Program (UGRAD, GRAD,
ect.)
Last/Org/Group/Household
name
Phones
Degree (when
graduated)
First name Email addresses
College/School (put
college here)
Middle name
Gender
Division (put school here)
Title Birth Date
Department (Major
description)
Suffix Educational Institution
Degree type (MAJ, MIN,
ect.)
Suffix Date From/To Campus (Attribute)
Constituent type
Class Of/ Preferred
Class
Graduation Date (when
graduated)
Alternate lookup IDs Education Status Involvements
18. 1/7/2017 Footer 18
• Images for gifts are created in 3 ways
- Manually Scanned Batches
- Electronic Lockbox
- Credit Card Image
IMAGED GIFTS
19. 1/7/2017 Footer 19
• Manually Scanned Batches
- <<enter a pic of scanned batch>>
- Daily checks and any accompanying documentation is scanned into Onbase
- A custom system process runs every <<30>> minutes to create revenue
batches of 35 in BBEC
• Depending on the documents with the check/cash various fields are filled
in due to bar coding.
- After the gifts are successfully committed a system process ties the gift back
to the image in Onbase
IMAGED GIFTS
20. 1/7/2017 Footer 20
• Electronic Lockbox
- With the move to BBEC we also took advantage of an electronic lockbox
- Monday thru Friday we receive a two files from Chase Bank,
• One is a file containing the image of our checks and accompanying
documents
• One is file listing checking information and the amount.
- The image is input into Onbase and then a system process is run to create
batches of 35 into BBEC
- After the gifts are successfully committed a system process ties the gift back
to the image in Onbase
IMAGED GIFTS
22. 1/7/2017 Footer 22
IMAGED GIFTS
• Credit Cards
- Custom-built online giving pages
- Custom-built interface between our several Cybersource files and BBEC
- An image is created for each gift with key processing information collected
from the Cybersource file and online giving page
- A daily revenue batch is created for each Cybersource file. Some of the
batch fields are pre-populated based off of data entered on the online giving
page
24. 1/7/2017 Footer 24
PEL/WOSU/BMV
• We receive files of gift transactions that were initially capture in an
outside system
- PEL – Pelotonia Bike Race – raise money for cancer research
- WOSU – Our public broadcast station
- BMV – Bureau of Motor Vehicles – OSU licenses plates
• Challenges with each of these
- Little to no control over the file format
- Some lack a common ID
- Data completeness is lacking
• If we were to use the “out of the box” processes challenges would lead
to tons of duplicates.
25. 1/7/2017 Footer 25
PEL/WOSU/BMV
• High level of custom process
1. Custom application outside of BBEC was built for Business to load each file
to check for correct file format
2. Business process is run to import the files into BBEC and then divides
them up into different batches / buckets
• Match Bucket – A constituent was found within the system so a revenue
batch is created with all of these
• No Match – A constituent was not found it systematically creates one and
then a revenue batch is created with the new created constituent attached
• In the Middle “Squishy” – A “firm” match was not found but there is a
possibility that there is a match. A constituent batch is created.
26. 1/7/2017 Footer 26
PEL/WOSU/BMV
• High level of custom process
3. Processor manually processes the “middle” batch constituent batch, once
committed the revenue batch is systematically created
4. Process then commits the individual revenue batches or commits them as
a group
- Keys to the process
• Customization was built so the business could set up different match/no
match/ middle per file
• Built a custom processing screen to the business could see the file data
within BBEC and what “bucket” they system process put them into.
27. 1/7/2017 Footer 27
PEL/WOSU/BMV
• Overview of the customization match/no match/middle criteria
- SQL server process that allows the matching of one set of data to another
and assigns a match percentage
- Customization allows the business to build combinations of fields to come up
with an overall match percentage
- The business then can define what overall percentage qualifies for the
match / non match / middle buckets
