presents a visual analysis webinar on: leverage your advancement data now with in memory warehouses...
DESCRIPTION
Are you wondering what all the talk is about "in-memory" data warehouses? How do they compare with the more traditional data warehouses? What are the advantages? Disadvantages? What are others doing to meet their data discovery and analysis needs? This webinar from www.AdvizorSolutions.com highlights the use of in-memory data management in higher ed fundraising, it is applicable to any team or organization that is looking to maximize insight from their data.TRANSCRIPT
©2010 ADVIZOR Solutions® 1www.AdvancementAdvizor.com
Leverage your Advancement Data NOW with In-Memory Data Management
©2010 ADVIZOR Solutions® 2www.AdvancementAdvizor.com
Participants
Doug Cogswell, President & CEO
ADVIZOR Solutions
Judy Doherty, Director, Info Management Systems
Dartmouth College
Ben Tompkins, Executive Director, Info Services
Emory University
Terry Handler, CEO
T. Handler Consulting
©2010 ADVIZOR Solutions® 3www.AdvancementAdvizor.com
Agenda
Confusion in the Marketplace (5 mins)
How Business Intelligence Fits Together (10 mins) Source Systems Data Warehouse In-memory Data Management Reporting & Scorecards Discovery & Analysis
Discussion (25 mins) Timing and Making It Work Case Study Discussions
Q&A (20 mins.)
Use webinar “question” panel and “raise hand” // we’ll unmute you
©2010 ADVIZOR Solutions® 4www.AdvancementAdvizor.com
Raiser’s EdgeDatatel
Banner Advance
Data Warehouse
Reporting
&
Scorecards
Discovery&
Analysis
Pieces of the Puzzle
©2010 ADVIZOR Solutions® 5www.AdvancementAdvizor.com
What we hear Data Warehouses
We could benefit from a data warehouse, but don't have the time, money or resources to implement one
We are having trouble implementing a data warehouse
We are experiencing higher than expected costs and delays in getting up and running
We are frustrated because solutions for our department are 2 years away because others are implementing first
We need a more flexible discovery and analysis environment
ResourcesResources
TimeTime
FlexibilityFlexibility
©2010 ADVIZOR Solutions® 6www.AdvancementAdvizor.com
Discovery&
Analysis
DatatelBanner
Data Warehouse
Reporting
&
Scorecards
Needs Vary
OperationsAdvancement
Raiser’s EdgeAdvance
©2010 ADVIZOR Solutions® 7www.AdvancementAdvizor.com
Datatel Banner
Operations Warehouse(student side in Higher Ed)
Reporting &
Scorecards
Operations drives Reporting
Discovery&
Analysis
Gra
de
Rep
orts
Stu
den
t B
ills
Cou
rse
Eva
luat
ion
s
. . .
©2010 ADVIZOR Solutions® 8www.AdvancementAdvizor.com
Datatel Banner
Reporting &
Scorecards
Gra
de
Rep
orts
Stu
den
t B
ills
Cou
rse
Eva
luat
ion
s
. . .
Often leaving Advancement in Limbo
Raiser’s EdgeAdvance
Discovery&
Analysis
Discovery&
Analysis
Operations Warehouse(student side in Higher Ed)
©2010 ADVIZOR Solutions® 9www.AdvancementAdvizor.com
Advancement Data Warehouse
Reporting &
Scorecards
Discovery&
Analysis
Cam
pai
gn R
epor
ts
Exe
cuti
ve M
etri
cs
Sta
ff M
etri
cs
. . .
Pro
spec
t Id
enti
fica
tion
Sta
ff P
erfo
rmce
Mgm
t
Ap
pea
ls T
arge
tin
g
Cal
l Cen
ter
Op
t.
. . .
Advancement has its own Needs
Operations Advancement
Banner
Reporting &
Scorecards
Discovery&
Analysis
Operations Warehouse(student side in Higher Ed)
Call CenterCore Systems* Other Data
©2010 ADVIZOR Solutions® 10www.AdvancementAdvizor.com
Reporting &
Scorecards
Discovery&
Analysis
Cam
pai
gn R
epor
ts
Exe
cuti
ve M
etri
cs
Sta
ff M
etri
cs
. . .
Pro
spec
t Id
enti
fica
tion
Sta
ff P
erfo
rmce
Mgm
t
Ap
pea
ls T
arge
tin
g
Cal
l Cen
ter
Op
t.
. . .
. . . and doesn’t need to wait for a Data Warehouse
Operations
Banner
Reporting &
Scorecards
Discovery&
Analysis
Advancement
Operations Warehouse(student side in Higher Ed)
Call CenterCore Systems* Other Data
©2010 ADVIZOR Solutions® 11www.AdvancementAdvizor.com
Reporting &
Scorecards
Discovery &Analysis
Cam
pai
gn R
epor
ts
Exe
cuti
ve M
etri
cs
Sta
ff M
etri
cs
. . .
Today Discovery & Analysis largely missing
Operations
Banner
Reporting &
Scorecards
Discovery&
Analysis
Advancement
Operations Warehouse(student side in Higher Ed)
Call CenterCore Systems* Other Data
©2010 ADVIZOR Solutions® 12www.AdvancementAdvizor.com
Problem: the “Cycle of Pain”
Custom Report Requests: Custom query submitted to IT Backlog – 5 days to get answer Begs another question, back through the cycle Frustration on both sides
Excel: Download “extracts” Slice and dice in Excel Time consuming and challenging Don’t have all the data Hard to show to management “Shadow data systems”
Collaboration
Kill the “Cycle of Pain”!!
©2010 ADVIZOR Solutions® 13www.AdvancementAdvizor.com
In-Memory Data Management
DISCOVERY & ANALYSIS (ADVIZOR)Interactive Visualization & Predictive Analytics
So
luti
on
s:
Gen
eral
Man
agem
ent:
•
Sta
ff P
erfo
rman
ce M
gmt
• C
ampa
ign
Ana
lysi
s•
Ad
Hoc
Rep
ortin
g
Lea
der
ship
Giv
ing
:•
Pro
spec
t Ide
ntifi
catio
n•
Pro
spec
t Man
agem
ent
An
nu
al G
ivin
g:
• A
ppea
ls T
arge
ting
• V
olun
teer
Ass
ignm
ents
• C
all C
ente
r O
ptim
izat
ion
Mem
ber
/ A
lum
ni R
ltn
s:•
Eve
nts,
Trip
s, a
nd C
lubs
In-Memory “Pool” of Linked Tables
*Advance, Banner, Datatel, Millennium, Raiser’s Edge, etc.
Call CenterCore Systems* Other Data
Answer: In-Memory Data Management
©2010 ADVIZOR Solutions® 14www.AdvancementAdvizor.com
In-Memory Data Management
DISCOVERY & ANALYSIS (ADVIZOR)Interactive Visualization & Predictive Analytics
So
luti
on
s:
Gen
eral
Man
agem
ent:
•
Sta
ff P
erfo
rman
ce M
gmt
• C
ampa
ign
Ana
lysi
s•
Ad
Hoc
Rep
ortin
g
Lea
der
ship
Giv
ing
:•
Pro
spec
t Ide
ntifi
catio
n•
Pro
spec
t Man
agem
ent
An
nu
al G
ivin
g:
• A
ppea
ls T
arge
ting
• V
olun
teer
Ass
ignm
ents
• C
all C
ente
r O
ptim
izat
ion
Mem
ber
/ A
lum
ni R
ltn
s:•
Eve
nts,
Trip
s, a
nd C
lubs
In-Memory “Pool” of Linked Tables
*Advance, Banner, Datatel, Millennium, Raiser’s Edge, etc.
Call CenterCore Systems* Other Data
End UserEnd UserEmpowermentEmpowerment
Answer: In-Memory Data Management
©2010 ADVIZOR Solutions® 15www.AdvancementAdvizor.com
Demonstration . . .
©2010 ADVIZOR Solutions® 16www.AdvancementAdvizor.com
Demonstration
Staff Performance Management Identify best practices and manage operations
against set metrics that include: Activities such as in-person visits and # of proposals issued over past 12 months The value of proposals issued vs. the rated value of the prospects Speed of movement through proposal stages The balance of visits and proposals by type and level of prospect Close rates and gifts recorded
26 Tables from Oracle Database (Advance) Entity Assignments Contacts
100k entities, 10k staffed prospects 25+ Calculated Metrics:
In-person Contacts Last 12 Months Active Comprehensive Proposals Total Lifetime Giving Prospect Expected Value Etc.
Proposals Gifts Etc.
Trend Analysis
Proposal Portfolio
Prospect Moves
©2010 ADVIZOR Solutions® 17www.AdvancementAdvizor.com
Discussion . . .
©2010 ADVIZOR Solutions® 18www.AdvancementAdvizor.com
Discussion
1. What should Advancement do? How to balance the “big bang” vs. “getting
something going now”?
What benefits will a full data warehouse provide?
How is a “warehouse” different than a “mart” or
“reporting tables”
3. How far can you go with in-memory data discovery tools?
4. What have you done to kill the “cycle of pain”?
ResourcesResources
TimeTime
FlexibilityFlexibility
©2010 ADVIZOR Solutions® 19www.AdvancementAdvizor.com
Q&A:
use webinar “question” panel and “raise hand” // we’ll unmute you . . .
(or email [email protected])
Distribution by Class YearLocation of Top Prospects FYTD Closes