AmberLeaf specializes in quickly breaking down the barriers that stand between your data and action.
Software Consolidation and Its
Impact on Data Management
Presented by: Larry Goldman
DAMA–MN April 16, 2008
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Agenda
• Introduction to AmberLeaf
• Business Intelligence Vision
• Consolidation History
• Customer Benefits and Impacts
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Breaking Down the Barriers
Urgency, Speed, Focus, Expertise, Results
Information
•Data
Warehouse/Data
Mart strategy,
design and
development
•Data Integration
(ETL on Demand)
•Data Quality
•Customer
Information
Hygiene
DATA
Strategy
Insight
•Reporting
Architectures
•Management
Reporting
•Business
Performance
Management
•Analytical
Applications
•Measurement and
metrics
INFORMATION
•Loyalty Programs
•Advanced Analytics
•Customer Valuation
•Segmentation
•Marketing
Optimization
•Customer
Experience Strategy
• Sales
• Service
• Marketing
INSIGHT
STRATEGY
Action
•Customer
Experience
Optimization
•Marketing
Automation
•Personalization
•Process Design
•Change Agents
•Service
Optimization
•Sales Effectiveness
ACTION
Agenda
• Introduction to AmberLeaf
• Business Intelligence Vision
• Consolidation History
• Customer Benefits and Impacts
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
ETL Architecture
Metadata
External
Parties
ETL Architecture
Data
Files
CMDM_PHYQA_ERR_PARM
PHYQA_ERR_KEY
INFA_SESS_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
Source/Legacy
Systems
Support
Personnel
CMDM_INFA_SESS_EXP_PARM
INFA_SESS_EXP_KEY
INFA_SESS_KEY (FK)
EXP_NAME
EXP_DESC
LKP_TABLE_NAME
SOURCE_NAME
TARGET_NAME
CMDM_PROCESS_PARM
PROC_KEY
PROC_NAME
PROC_DESC
CMDM_INFA_SESS_PARM
INFA_SESS_KEY
PROC_KEY (FK)
INFA_FOLDER_NAME
INFA_WORKFLOW_N AME
INFA_SESS_NAME
CMDM_LOGQA_ERR_PARM
LOGQA_ERR_KEY
INFA_SESS_EXP_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
CMDM_ERR_LOG
ERR_LOG_KEY
INFA_SESS_KEY (FK)
INFA_SESS_EXP_KEY (FK)
AUDIT_KEY (FK)
ERR_TYPE_CODE
ERR_DESC
LOGQA_INPUT_VALUE
OPER_RESOLUTION
OPER_COMMENTS
ERR_STATUS_CODE
ERR_CALLING_MODULE
CMDM_AUDIT
AUDIT_KEY
PROC_KEY (FK)
PROC_STATUS_CODE
PHYQA_STATUS_CODE
LOGQA_STATUS_CODE
PROC_START_DTS
PROC_END_DTS
CMDM_INFA_SESS_STAT
INFA_SESS_STAT_KEY
PHYQA_ERR_KEY (FK)
INFA_SESS_KEY (FK)
AUDIT_KEY (FK)
AUDIT_STAT_DTS
NUM_RECS_SUCCESS
NUM_RECS_FAILED
NUM_RECS_TOTAL
PCTG_FAILED_RECS
SESS_STATUS_CODE
SESS_START_DTS
SESS_END_DTS
Audit Tables
CMDM_PHYQA_ERR_PARM
PHYQA_ERR_KEY
INFA_SESS_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
Unix Directories
Stage (TMP & PS)
Conform
EDW
Data Marts
CMDM_PROCESS_PARM
PROC_KEY
PROC_NAME
PROC_DESC
CMDM_INFA_SESS_PARM
INFA_SESS_KEY
PROC_KEY (FK)
INFA_FOLDER_NAME
INFA_WORKFLOW_N AME
INFA_SESS_NAME
CMDM_INFA_SESS_EXP_PARM
INFA_SESS_EXP_KEY
INFA_SESS_KEY (FK)
EXP_NAME
EXP_DESC
LKP_TABLE_NAME
SOURCE_NAME
TARGET_NAME
CMDM_LOGQA_ERR_PARM
LOGQA_ERR_KEY
INFA_SESS_EXP_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
Data Reconciliation Processing / Data Watching
Information
Consumers
Initiate Data Load Validate Data
Communicate Issues
CMDM_ERR_LOG
ERR_LOG_KEY
INFA_SESS_KEY (FK)
INFA_SESS_EXP_KEY (FK)
AUDIT_KEY (FK)
ERR_TYPE_CODE
ERR_DESC
LOGQA_INPUT_VALUE
OPER_RESOLUTION
OPER_COMMENTS
ERR_STATUS_CODE
ERR_CALLING_MODULE
CMDM_AUDIT
AUDIT_KEY
PROC_KEY (FK)
PROC_STATUS_CODE
PHYQA_STATUS_CODE
LOGQA_STATUS_CODE
PROC_START_DTS
PROC_END_DTS
CMDM_INFA_SESS_STAT
INFA_SESS_STAT_KEY
PHYQA_ERR_KEY (FK)
INFA_SESS_KEY (FK)
AUDIT_KEY (FK)
AUDIT_STAT_DTS
NUM_RECS_SUCCESS
NUM_RECS_FAILED
NUM_RECS_TOTAL
PCTG_FAILED_RECS
SESS_STATUS_CODE
SESS_START_DTS
SESS_END_DTS
Meta Data
Repository
Information
Metadata
•
•
•
DATA
Access Types
It has been estimated that ETL and data integration make up
anywhere from 50% to 80% of all data warehouse efforts
ETL technology from leading vendors like DataStage (IBM)
and Informatica continue to make their applications easier to
use, more scalable, more interoperable, and able to capture
better meta-data
However, for the most part, many users find that these tools
have not had any revolutionary new functionality in the last
couple releases
INFORMATION
INSIGHT
STRATEGY
ACTION
Dynamic Data Warehousing/MDM
Order
Entry
SFA
•
•
•
None of the hard parts of
ETL go away
But some of these
technologies buffer
the end result (data mart)
from changes in sources,
business rules, or business
models
Some generate BI meta
data models
Customer
Data
DATA
INFORMATION
Customer
Service
Web
Inventory
ETL Engine
Staging
Active Meta Data
Product
Data
INSIGHT
Sales
Analysis
Marketing
Performance
STRATEGY
ACTION
Business Intelligence Architecture
Metadata
External
Parties
Source/Legacy
Systems
Process
Metadata
ETL Architecture
Data
Files
CMDM_PHYQA_ERR_PARM
PHYQA_ERR_KEY
INFA_SESS_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
CMDM_PROCESS_PARM
PROC_KEY
PROC_NAME
PROC_DESC
CMDM_INFA_SESS_EXP_PARM
INFA_SESS_EXP_KEY
INFA_SESS_KEY (FK)
EXP_NAME
EXP_DESC
LKP_TABLE_NAME
SOURCE_NAME
TARGET_NAME
CMDM_INFA_SESS_PARM
INFA_SESS_KEY
PROC_KEY (FK)
INFA_FOLDER_NAME
INFA_WORKFLOW_N AME
INFA_SESS_NAME
CMDM_LOGQA_ERR_PARM
LOGQA_ERR_KEY
INFA_SESS_EXP_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
CMDM_ERR_LOG
ERR_LOG_KEY
INFA_SESS_KEY (FK)
INFA_SESS_EXP_KEY (FK)
AUDIT_KEY (FK)
ERR_TYPE_CODE
ERR_DESC
LOGQA_INPUT_VALUE
OPER_RESOLUTION
OPER_COMMENTS
ERR_STATUS_CODE
ERR_CALLING_MODULE
CMDM_AUDIT
AUDIT_KEY
PROC_KEY (FK)
PROC_STATUS_CODE
PHYQA_STATUS_CODE
LOGQA_STATUS_CODE
PROC_START_DTS
PROC_END_DTS
CMDM_INFA_SESS_STAT
INFA_SESS_STAT_KEY
PHYQA_ERR_KEY (FK)
INFA_SESS_KEY (FK)
AUDIT_KEY (FK)
AUDIT_STAT_DTS
NUM_RECS_SUCCESS
NUM_RECS_FAILED
NUM_RECS_TOTAL
PCTG_FAILED_RECS
SESS_STATUS_CODE
SESS_START_DTS
SESS_END_DTS
Audit Tables
Support
Personnel
CMDM_PHYQA_ERR_PARM
PHYQA_ERR_KEY
INFA_SESS_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
Unix Directories
Conform
Stage (TMP & PS)
EDW
Data Marts
CMDM_PROCESS_PARM
PROC_KEY
PROC_NAME
PROC_DESC
CMDM_INFA_SESS_PARM
INFA_SESS_KEY
PROC_KEY (FK)
INFA_FOLDER_NAME
INFA_WORKFLOW_N AME
INFA_SESS_NAME
CMDM_INFA_SESS_EXP_PARM
INFA_SESS_EXP_KEY
INFA_SESS_KEY (FK)
EXP_NAME
EXP_DESC
LKP_TABLE_NAME
SOURCE_NAME
TARGET_NAME
CMDM_LOGQA_ERR_PARM
LOGQA_ERR_KEY
INFA_SESS_EXP_KEY (FK)
TOLERANCE_TYPE_CODE
NUM_RECS_TOLERANCE
PCTG_TOLERANCE
Data Reconciliation Processing / Data Watching
Information
Consumers
Initiate Data Load
Validate Data
Communicate Issues
CMDM_ERR_LOG
ERR_LOG_KEY
INFA_SESS_KEY (FK)
INFA_SESS_EXP_KEY (FK)
AUDIT_KEY (FK)
ERR_TYPE_CODE
ERR_DESC
LOGQA_INPUT_VALUE
OPER_RESOLUTION
OPER_COMMENTS
ERR_STATUS_CODE
ERR_CALLING_MODULE
CMDM_AUDIT
AUDIT_KEY
PROC_KEY (FK)
PROC_STATUS_CODE
PHYQA_STATUS_CODE
LOGQA_STATUS_CODE
PROC_START_DTS
PROC_END_DTS
CMDM_INFA_SESS_STAT
INFA_SESS_STAT_KEY
PHYQA_ERR_KEY (FK)
INFA_SESS_KEY (FK)
AUDIT_KEY (FK)
AUDIT_STAT_DTS
NUM_RECS_SUCCESS
NUM_RECS_FAILED
NUM_RECS_TOTAL
PCTG_FAILED_RECS
SESS_STATUS_CODE
SESS_START_DTS
SESS_END_DTS
Meta Data
Repository
Information
Metadata
Decision Support Framework
Access Types
Data Dictionary
Data Extracts
Ad-Hoc
Reporting
Statistics
Standard
Reporting
Dashboards
Delivery Methods
RATE PLAN HISTORY
SUBSCRIPTION RATE PLAN HISTORY
RATE PLAN
PLAN DESC
CODE
BILL ACCOUNT HISTORY
RATE
SUB ID
SITE CODE
BILL
ACCT ID
BILL
ACCT ID
MKT NUM
RATE PLAN CODE
BILL FNAME
SALES AREA CURRENT
PRODUCT CODE
SUBSCRIPTION
RATE PLAN PRD CODE
BILL MNAME
- Bill Account
PRODUCT CODE DESC
RATE PLAN PRD GRP CODE
BILL LNAME
- Subscription
PRODUCT
CODE TYPE
SUB ID
RATE PLAN PRD SUB GRP CODESVC
BILL IN CARE OF NAME
TYPE CODE
BILL DAY
ACCT ID
VALUESHARE
FLAG
ACCT FNAME
SITE CODE
PYMT TYPE CODE
BILL
SVC
TYPE CODE
ACCT MNAME
SITE NAME
VARIANCE 1
SUB FNAME
PYMT TYPE CODE
ACCT IN
LNAME
SUB SITE CODE CODE
VARIANCE 2
SUB MNAME
EFF DTS
ACCT
CONSOLIDATED
VARIANCE 3
CO
NAMECARE OF NAME
SUB LNAME
END DTS
SAC NAME
VARIANCE
4
ESTABLISH DATE
SUB IN CARE OF NAME
TIER NUM
ACCESS
CHARGE
COST CENTER
SUB ADDR
ADDR LINE2
LINE1 SUBSCRIPTION STATUS HISTORY
HRIS MKT NUM
ACCT LEVEL IND
BIRTH
DATE
SUB
JDE COMPANY NAME
COMMISSION FLAG
SOCIAL SECURITY NUM
SUB ADDR LINE3
JDE WLN
WLS
PACKAGE MINS
CREDIT BUREAU SCORE
JDE
RISKCO
CO NUM
NUM SUB CITY
SUB ID
BILL SYSTEM CODE
DEPOSIT REQUIRED JDE
FLAGLD CO NUM
SUB ZIP
BILL ACCT ID
SRC DTS
SYSTEM CODE
DEPOSIT REQUIRED JDE
AMTPREPAY CO NUM
SUB STATE
EFF DTS
DISTRIBUTION CHANNEL
EFF
DEPOSIT TAKEN AMTJDE INT CO NUM SUB COUNTRY
END DTS
END DTS
PICTURE ID
ID STATE VPGM
JDE PAGE
CO NUM ESTABLISH
GENDER
DIST CHAN CODE
OFFPEAK
MIN
PICTURE
FNAME
DATE SUB STATUS ID DIST
CHAN SUB
CODE
NAME
PEAK
MIN
GEO CODE
VPGM MNAME
MIN
DIST CHAN
GRP
CODE
ANYTIME
MIN
LAST HOTLINED DATE
VPGM LNAME
MDN
DIST CHAN SUBM2M
GRPMIN
NAME
LAST NPD DATE
VPGM EMPL POSTNESN
NUM
DIST
CHAN
GRP
CODE
CALL
DELIVERY
RATE
CPNI
MAP FNAME
WORK PHONE
DIST CHAN GRPPOST
NAME
PKG PEAK RATE
CREDIT REFERENCE
MAP
NUMLNAME
MNAME
HOME PHONE DATE
CANCELLATION
POST PKG OFFPEAK RATE
DECISION
CODE
MAP
VOL DISC FLAG
POST PKG M2M RATE
NEXT BILL DATE
MAP EMPL POSTN NUM
IN CONTRACT FLAG
CALENDAR
REV ACCT CODE
MAJOR ACCT FLAG RP FNAME
CDPD NEI
ROAMING MINS
MAJOR ACCT CODE RP MNAME
SALES REP HISTORY
BILL STATUS
CALENDAR
DATE
MAJOR ACCT ID
RP LNAME
MAKE
MODELCODE
ID - Sub Handset
DAY
OF WEEK
NAME
ACCT
RP
EMPL
POSTN NUM
RATE PLAN CODE - Subscription
DAY OF WEEK SHORT
NAME
ACCT STATUS
TYPE ID ID
COO
FNAME
RATE PLAN PRD CODE
DAY IN WEEK MAKE MODEL
CREDIT CLASS ID
MKT CODE
SLSCODE
REP ID
RATE PLAN PRD GRP
DAY IN MONTH MAKE MODEL ID
CREDIT CODE ID
COO MNAME
EMPL
DISPLAY
NAME
RATE PLAN PRD SUB
GRP
CODE
DAY IN QUARTER
CREDIT CODE DESC MKT NUM
MAKE
HRIS
MKT
NUM DAY
CREDIT CODE
CLASS ID
ID BILL
YEAR
BILL DAY
COO LNAME
MODEL
SYSTEM CODE
CREDIT
WEEKININ
MONTH
BILL SYSTEM
CYCLE IDCODE COO
MKT NAME
MANUFACTURER
REP DCID
CREDIT CODE DESC
WEEK IN QUARTER
BILL
EMPL POSTN NUM
LIFE CYCLE CODE
EFF DTS
TYPIST ID
WEEK IN YEAR TECHNOLOGY
BILL HOLD
CEO FNAME
TYPE CODE
END
DTS
REP ID
MONTH
BILL CT
RDM MKT CODE SLS
COMPARABLE MAKE
DIST CHAN CODE
MONTH NAME COMPARABLE
BILL IN ARREARS FLAG
MKT AREA CODE SUB
MODEL
ID
MONTH IN QUARTER
TREAT BAL
CONTROL
CEO MNAME
PHONE WEIGHT
CURR
DUE
MKT STATUS
NUM
QUARTER
SOFTWARE
VER
MKT AREA
AMT30
MKT AREA CODE
YEAR
WUW SOFTWARE VER
CEO
LNAMENAME REGION
AMT60
CODE SUBSCRIPTION HANDSET
HOLIDAYHISTORY
FLAG DIG STANDBY TIME
REGION CODE
AMT90
SITE CODE
WEEKEND FLAGDIG TALK TIME
CEO EMPL POSTN NUM
AMT120
SUB SITE CODE SUB ID
LAST DAY IN MONTH
BATTERY
FLAGTYPE CODE
REGION NAME
AMT150
SVC
TYPE
CODE
BILL
ACCT
ID
SALES
DAY
OF
WEEK
VIB
ALERT
FLAG
SRC SYSTEM
SYSTEM CODE
CODEPYMT TYPE CODEMAKE
AMT180
BILL
SALES WEEK
RING TONE FLAG
MODEL
EFF DTS
SUB TYPE ID
MID MTH COMMISSION
RING TONE
MTHDOWNLOAD FLAG
HS ID
END DTS
BILL SYSTEM CODE
MID MTH COMMISSION
DATA FAX
QTR
FLAG
HS SLS DATE
BLUETOOTH FLAG
ESN MODEL ID
VOICE DIAL FLAG
MAKE
SPEAKER
PHONE FLAG
BILL ACCOUNT ADDRESS
HS CHG REASON CODE
WUW
FLAG
ITEM NUM
TTY FLAG
BILL ACCT ID
ITEM QTY
GPS FLAG
BILL ADDR
ADDR LINE2
LINE1
UNIT COST
AXCESS SHOP FLAG
BILL
RETAIL AMT
ONE TOUCH DIAL FLAG
BILL ADDR LINE3
SUBSIDY
AMT
MEMORYIDLOC
CT
BILL CITY
ORDER ID
CALLER
FLAG
BILL ZIP
COAM HISTORY
CPE FLAG
NAME DISPLAY FLAG
BILL STATE
SUBSCRIPTION CONTRACT
SHIP FEE
AMT
PRL FLAG
BILL
SHIP COST AMT
ACCTCOUNTRY
ADDR LINE1
SUB ID
FULLFILLMT
ACCT ADDR
ADDR LINE3
LINE2
CONTRACT START DATE
SLS
REP ID COST
ACCT
HANDSET
BILL ACCT ID
RETURN FLAG TYPIST
CREDIT CLASS ACCT CITY
CONTRACT END DATESRC
SYSTEM CODE
- Sub Handset
ACCT STATE
ZIP
HS IDDESC
CONTRACT LENGTH BILL
SYSTEM CODE
- Subscription
BILL SYSTEM CODE
ACCT
ITEM
CONTRACT
EFF DTS
CREDIT CLASS ID ACCT COUNTRYEARLY
RETAIL PRICE
DISC TYPE
PENALTY END
DTS
TYPISTDISPLAY
ID
CREDIT CLASS DESC
HOME PHONE EFF DTS
MAKE
EMPL
NAME
W ORK PHONE END DTS
MODEL
BILL SYSTEM CODE
Data Model
Web
DATA
INFORMATION
Email
INSIGHT
FTP
Client App
STRATEGY
ACTION
Brett Hively – BRM Agent Desktop
Home Page
My Lounge
My Rankings
Search
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Help
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Brett Hively’s Home Page
AE Home Page
RM Scorecard Detail
Scorecard Summary
Key Metrics
Funded
Volume
Funded
Units
527
Broker
Penetration
Weighted
Deviation
Funding
Ratio
Share of
Wallet
Cost per
1st Lien
Units
Loans per
AE
FastQual
%
Brokers
Funded in
90 Days
14.5%
.53
66.8%
34%
$2,680
17.4
33.3%
178
Yesterday
$119,830,703
Same Day Last Month
$120,543,987
400
15%
.60
60.4%
30%
$2,589
16.5
27%
165
Quarter to Date
$119,830,703
527
14.5%
.53
66.8%
34%
$2,680
17.4
33.3%
178
RM Home Page
Internal Performance
Loan Performance
Internal
Performance
Loan
Count
Average Days
To Next Stage
Underwriting
40
2
Potential FPD’s
8
Account Manager
250
8
30 Day
1
Doc’s Out
157
4
60 Day
1
Doc’s Out
140
5
90 Day
0
REO’s
1
Investor Rejects
2
Total Days Sub to Close
13.5
RM Alert Summary
RM Lead Summary
Total Alerts
Status
185
New
110
Attention
25% Submission Drop
100
60
40 % Below Funding Ratio
50
30
New Loan Officers
25
15
Docs in Past 3 Days
10
5
DATA
Internal
Performance
INFORMATION
Total Leads
185
110
Status
Assigned Unassigned
Approved
100
60
Pending
50
30
Qualified
25
15
Validated
10
5
Terminated
5
-
INSIGHT
Loan
Count
RM Territory Summary
Broker Swap Candidates
Period
Funded
60 Days
100
90 Days
50
120 Days
25
180 Days
10
STRATEGY
Never Funded
60
30
15
5
ACTION
Lapse Likelihood by Sales Deciles
Lapse Likelihood Index by Sales Decile (100 = Average Likelihood)
BEST CUSTOMERS ARE LESS LIKELY TO BE LAPSED CUSTOMERS. HOWEVER,
SIGNIFICANT PROPORTIONS OF BEST CUSTOMERS ARE STILL LAPSED.
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Seamless Transition From…
•
•
•
•
•
•
•
DATA
Strategy
Tactical Plans
Dashboards
Management Reporting
Ad-hoc Reporting
Multi-dimensional Analysis
Statistical Analysis
INFORMATION
INSIGHT
STRATEGY
ACTION
Real-Time Coordination
SFA
•
•
•
Order
Entry
Web
Some architectures have chosen a
distributed methodology
Others have chosen ODS
Others have chosen hybrids
Customer
Service
Inventory
Distribution
Architecture
Operational
Data Store
ETL
Decision
Support
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Operational Business Intelligence
Continuous visibility
– For critical, intra-day measurements
– Aggregated across multiple systems
Flexible user interface
– Self-service model
– User-defined thresholds and alerts
– Graphical watch points
Role-based delivery
– Role based data level security
– Customization by end users
Collaboration
– Built-in workflow/collaboration
– Complete loop from discovery to action
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Brett Hively – BRM Agent Desktop
Home Page
My Lounge
My Rankings
Search
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Help
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Assign Broker
Brett Hively’s Broker List
All
Funded
Never Funded
Swap Candidate
60 Days
Broker List
Select DispAll
ute.
Broker Name
Broker
Stage Code
Assigned AE
# of Loan
Officers
# of Funded
Units
Broker
Temp
Last Assign
Date
• Dispute
Broker ABC
At Risk
Frank Morley
10
24
Un Happy
1/2/06
• Assign
Broker DEF
At Risk
Jim Smith
5
3
Un Happy
2/8/06
Broker GHI
At Risk
Brian Slucki
25
39
Un Happy
1/12/06
• AE
Assignment
History
Assign Broker
Broker NameBroker JKL
City
Broker MNO
Broker ABC
Irvine
Broker PQR
Broker
STU
Assignment
History
At Risk
# of Loan
AssignedPete
AE Berchich
Officers
Mike Masters
Frank Morley
10
Todd Walsh
At Risk
Joe Widlowski Broker
StateAt Risk
At Risk
CA
Broker VWXAssigned Jr. AE
At Risk Last Assign
Dustin Lagar
Assigned AE
Date
Broker YZ
At Risk
Bob Purchase
Frank Morley
1/2/06
Broker ABC
At Risk
Frank Morley
Jim Smith
2/8/06
Broker DEF
At Risk
Jim Smith
Brian Slucki
1/12/06
Dennis Ugolini
Jr.
Broker GHI
At Risk
Brian Slucki
Pete Berchich
2/11/06
Broker JKL
At Risk
Pete Berchich
Mike Masters
Broker MNO Eddie Olson At Risk
DATA
2/3/06
Broker
Last Assign2/11/06
30 # of Funded 22 Satisfaction
Un Happy
Units
Date
Reason
20
12
Un Happy
2/3/06
24
Un Happy
1/2/06
15
33
Un Happy
1/31/06
20
Assignment
4
Un Happy
2/8/06
Assignee
50
6
Un Happy
2/4/06
Frank Morley
10
14
• Assign
Un Happy
1/11/06
10
24
5
3
AE Assignment
25
22
Mike Masters
30
Tim Smith
20
12
39
Broker PQR
At Risk
Todd Walsh
15
33
Un Happy
1/31/06
Broker STU
At Risk
Joe Widlowski
20
4
Un Happy
2/8/06
Broker VWX
At Risk
Dustin Lagar
50
6
Un Happy
2/4/06
Broker YZ
At Risk
Bob Purchase
10
14
Un Happy
1/11/06
Broker STU
At Risk
Joe Widlowski
20
4
Un Happy
2/8/06
Broker VWX
At Risk
Dustin Lagar
50
6
Un Happy
2/4/06
Broker YZ
At Risk
Bob Purchase
10
14
Un Happy
1/11/06
Broker YZ
At Risk
Bob Purchase
10
14
Un Happy
1/11/06
INFORMATION
INSIGHT
• Broker
Scorecard
• AE Scorecard
• Broker
Relationships
• Broker
Un Happy
1/2/06
Scorecard
Un Happy
• AE Scorecard 2/8/06
Un Happy
1/12/06
• Broker
Relationships
Un Happy
2/11/06
• Cancel
Un Happy
2/3/06
Assigned Jr. AE
• Undispute
STRATEGY
ACTION
Brett Hively – BRM Agent Desktop
Home Page
My Lounge
My Rankings
Search
Windows
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AE Ranking
Frank Morley’s
Rankings
Frank Morley’s Ranking for Funded Units as of April 4th, 2008
Ranking
Same Day
Last Month
Same Day
Last Month
Metric Value
Current
Ranking
Current
Metric Value
Scott Soga
1
23
15
9
Brian Pavur
2
22
14
10
Tony Bafano
3
21
13
11
Rick Harris
4
20
12
12
Mark Liskewicz
5
19
11
13
Frank Morley
6
18
10
14
Frank Melella
7
17
9
15
Joanna Basil
8
16
8
16
Robin Budz
9
15
7
17
Kristi Volger
10
14
6
18
Steve Tangenhorse
11
13
5
19
Ron Chester
12
12
4
20
Heather Thompson
13
11
3
21
Anthony Astrowski
14
10
2
22
Terra Arthur
15
9
1
23
Conversion Ratio
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
What Do We Want?
•
•
•
•
•
•
•
•
•
DATA
Save us time?
Save us money?
Easier maintenance?
Faster development?
Better integration between ETL and Business Intelligence?
Easier impact analysis across the ecosystem?
Sharing business rules between real-time and ETL data integration?
Ability to seamlessly work between BI technologies?
Ability to embed BI in our CRM/ERP applications?
INFORMATION
INSIGHT
STRATEGY
ACTION
Agenda
• Introduction to AmberLeaf
• Business Intelligence Vision
• Consolidation History
• Customer Benefits and Impacts
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
SAP Acquisitions
Business Objects, OutlookSoft, Pilot Software,
Callixa, A2i
Business Objects
Crystal, Infommersion, Cartesis, Nsite,
SRC, OLAP@work, Acta, Medience, FirstLogic,
Inxight, Informatik
Indicates duplicate product sets due to acquisition
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Oracle Acquisitions
Siebel, Hyperion, IRI, Thinking Machines,
Sunopsis, One Meaning, TimesTen, Stellent,
InnoDB, PeopleSoft
Siebel
Hyperion
Nquire
Upstream, Brio, Razza,
Decisioneering
Indicates duplicate product sets due to acquisition
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Microsoft Acquisitions
ProClarity, Stratature
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
IBM Acquisitions
Cognos, Informix, Ascential, AlphaBlox,
DWL, FileNet, DataMirror, Venetica, Trigo,
Green Pasture, SRD
Cognos
Celequest, Applix, Adaytum,
DecisionStream, Frango
Indicates duplicate product sets due to acquisition
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Marketing Automation
Aprimo
DoubleClick
Unica
Marketing Central,
MarketSoft, Sane Solutions
Indicates duplicate product sets due to acquisition
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Marketing Automation (cont’d)
Lyris
Lyris, EmailLabs, ClickTrack, Hot Banana
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Agenda
• Introduction to AmberLeaf
• Business Intelligence Vision
• Consolidation History
• Customer Benefits and Impacts
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Did It Make Sense? - BI
ETL
Oracle
SAP
MDM
Analytical
Applications
Reporting
OLAP
Stats
Dashboard
X
X (major
duplication)
X (major
duplication)
X (major
duplication)
X (major
duplication)
X (not
well
known)
X (major
duplication)
X(du
plicat
ion)
X
X
X
(duplication
)
X
(duplication
)
X
(duplication
)
X
X
X
X
Microsoft
X
IBM
X
DATA
X
X
INFORMATION
X
X
INSIGHT
STRATEGY
Operation
-al BI
X
ACTION
Did It Make Sense? – Marketing
Campaign
Marketing
Resource
Management
Statistics
Bidirectional
Reporting
Real-Time
Offer/Event
Detection
Lead
Management
Web
Analytics
Unica
X
X
(duplication)
X
X
X
X
X
Aprimo
X
X
X
X
X
Lyris
X
DATA
INFORMATION
X
INSIGHT
STRATEGY
ACTION
Conclusions
•
Most of the acquisitions over the past few years have propelled the “aquirers” into
marketplaces where they were lacking or had no previous capabilities
•
Some of these companies have moved into fairly new areas
– IBM in user facing tools
– SAP as an independent tool vendor
•
Though this helps the software company, it has rarely had, or is having, a positive
impact on the user base
•
The most immediate impact would be one-stop shopping and pricing
•
Except for consolidating the number of vendors you need to call, no real new
capability has come (or has even been announced) from these organizations
•
Examples of successful BI acquisitions:
–
–
–
–
DATA
Business Objects and Acta: Provides a full data warehouse suite for some BO clients
Oracle and IRI: Provides OLAP and relational database from one company
Unica and Marketsoft: Provides the bridge between sales and marketing
Siebel and Paragren and nQuire: Provides the most powerful CRM suite, analytical
and marketing capabilities
INFORMATION
INSIGHT
STRATEGY
ACTION
What May Be Next
• Hopefully, we will see some innovation down the road:
– True operational BI from Oracle by combining Oracle ERP, Siebel
CRM, and Siebel Analytics (and possibly Thinking Machines).
– True operational BI from Microsoft by combining Business Intelligence
Services and Microsoft Dynamics. The key for Microsoft will be to
make analytics as simple as Microsoft Word for the masses: Guided
Analytics, pre-canned solutions, and vertical integration.
– Pre-packaged, right-time BI engine from IBM by combining Websphere,
Ascential, and Cognos.
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Thank you.
Larry Goldman, President
773.456.3996
larry@amberleaf.net
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
AmberLeaf specializes in quickly breaking down the barriers that stand between your data and action.
Social Networking and Customer
Feedback – It’s all about the Data
Presented by: Larry Goldman
DAMA–MN April 16, 2008
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Agenda
• The New Data Hunger
• Players
• New Structures
• Example
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
360 Degree of the Customer - Example
Organizations
(UCM/MDR)
Web Activity
(Web Trends)
Geography
(Excel)
Responses
(CISPUB/PICK/
FRS/ARGI/SJO/
ATG, MPS, Unica,
SPIN)
Books
(UPM/SPIN)
Customer
Adoptions (ATG,
CISPUB/PICK/FRS)
Journals (UPM)
Alerts (ATG, SJO)
Course (MDR/
FRS/PICK/ATG)
DATA
INFORMATION
INSIGHT
Orders/Quotes/
Usage (CISPUB/
PICK/ARGI/
MS CRM,MPS)
STRATEGY
ACTION
Internal Web Tracking
•
DATA
Software like Omniture,
Unica NetInsight, and
WebTrends provide
metrics about your site:
– Site Usage and
Optimization
– Standard metrics: page
views, visits, and unique
visitors
– Marketing Conversion
– Referral sites
– Repeat visitor analysis
•
Traditional software does not
tell you:
– Are your metrics good
compared to your competitors?
– Where are your customers
when they are not on your
site?
– What are clients saying about
you when they are not filling
out your surveys?
– What are your customers
interested in beyond your
products and services?
– What are the major changes in
the behavior of your industry’s
on-line customers?
– What are the major changes in
the perspective of your
customer base regarding your
brand, new products, or
service?
INFORMATION
INSIGHT
STRATEGY
ACTION
DW’s Start Chasing The Dream Again
Non-vertical
Web Behavior
Look-a-like
Prospects
Business to
Business Contacts
Competitive
Web Behavior
Reviewed
Products
Customer
Product/Company
Ratings
Credible
Reviewers
Cross Brand
Analysis
Net Promoter
DATA
INFORMATION
INSIGHT
Brand Attributes
STRATEGY
ACTION
Agenda
• The New Data Hunger
• Players
• New Structures and Challenges
• Example
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Competitive Web Metrics
Element
Definition
Sources of Information
ISP’s, Corporate licenses, proprietary
toolbars/panels
Panel size
Vendors range between 500K to over 3million
users
Outliers
Does the vendor correct for non-standard
activity or coupon grabbing?
Algorithm to understand overall audience size
Typically, random dialing and surveys to
understand the general population of the
internet
Projection Algorithm
How does the vendor forecast actual web
metrics based on their sample data?
Search
How detailed does the vendor capture search
referrals and results?
Auxiliary information
Does the vendor supplement the click stream
with attitudinal or demographic data?
Regional organizations
Is the information national in perspective or
does it have enough representation locally?
Vertical expertise
Ability to compare functionality across different
sites in the same vertical?
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Vendors
•
Nielsen: This advertising rating company collects information on the
Web mostly focused on Media buyers to help organizations understand
reach of different sites and where to place their media. Query tools are
not great and custom reports are expensive. Nielsen contains B-to-B
data as well as home PC user data.
•
Comscore: Comscore offers almost the exact same services as Nielsen.
The focus is on media buying and reach rankings. Comscore contains
international and domestic panels.
•
Hitwise: Hitwise tries to commoditize this marketplace by offering a
large amount of canned reports across many different industries. Brittle
and not much customization outside of the canned reports.
•
Compete: Boasts the largest panel of all the vendors and provides deep
analytics in a subset of verticals across national ISP’s. Compete has indepth analysis on Search data as well as provides free general metrics
on their web site.
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Web 2.0 Metrics
Element
Definition
Sources of Information
How many blogs, how many sites, how far back?
Scraping Technology
How does the vendor scrape sites and can they
extract individual fields, ratings, and
recommendations? How does the technology react
to site changes?
Language Parser
What is the origin of the text parser? Does it come
from the off-line world? How was it trained?
Sentiment Analysis
Can the technology understand the difference
between a positive and negative statement?
Categorization
Can you categorize different key words together as
a specific concept? Can you customize the
categories?
Influencers
Can you identify who is influencing the crowd as
opposed to following the flock?
Access to Detail
Do you have access to the detail and ad-hoc
query?
Custom Roll Ups
How does the analysis group roll up products and
services?
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Vendors
•
Umbria: Does not provide direct access to the data, but provides
deep dive analysis on a per project basis.
•
Chatter Guard: Focuses on the travel industry by reading all blog
and feedback sites and manually scoring, rating, and categorizing the
different items.
•
Clarabridge: Less a service than an ETL tool for unstructured
information. Combines sentiment and language parser in order to
provide key performance indicators on social networking sites.
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Agenda
• The New Data Hunger
• Players
• New Structures and Challenges
• Example
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
New Data Sources/ETL
Internal
Systems
•
•
•
Third Party
Demographics
Outsourced
Systems
Competitive
Web
Scraping,
Language
Parsing
Standard ETL
New outside vendor for
competitive web analysis
Some vendors will send
extracts and others will only
allow access
New technology for interpreting
unstructured Internet data
DATA
INFORMATION
Blogs,
Community
EDW
Business
intelligence
INSIGHT
STRATEGY
ACTION
New Structures
•
•
DATA
New ETL challenges arise on how to match up the various
customer level information
– Internal data is at a very low level
– External data will be aggregated
– Screen names and e-mails may be available to consolidate in some
cases
Data Modeling Efforts
– Competitor. Need to normalize against your organization structure
– Web behavior. Need to normalize against your site sections or
taxonomy
– Competitive Products. Need to normalize against your product
hierarchy
– New Customer Transactions. Ratings, reviews, pageviews, visits
INFORMATION
INSIGHT
STRATEGY
ACTION
Data Quality Concerns
Program Management Office
Steering Committee
•
Program Management Group
· Project Manager
· Project Analyst
New subject areas
– Competitive organizations
– Competitive products
– Competitive sites
– Competitive behavior
– Social Networking transactions
Project
Sponsor
Project
Data Management Group
· Data Warehouse Architect
· Data Administrator
Data Steward
Responsible for a Data
Category
Tech
Liaison
Data
Liaison
Source System
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Agenda
• The New Data Hunger
• Players
• New Structures and Challenges
• Example
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Available Insight
•
•
•
DATA
Hotel
– City
– Name
– Chain (where applicable)
– Owner (where applicable)
Author
– Author
– Channel Score – how many postings and author makes
– Credibility – other on-line members’ ratings on how helpful the author’s
comments are
– Velocity – how often an author posts
– Influence – identifies if the author is leading or following the discussion
Reviews
– Author
– Hotel
– Date
– Overall Rating for the hotel
– Would the author recommend the hotel?
– Rating for how good of a value the hotel was
INFORMATION
INSIGHT
STRATEGY
ACTION
Available Insight (Cont’d)
•
Hotel Metrics
– Awareness – How much is being discussed
– Favorability – Score that is a proxy for loyalty and how often the
Hotel would be recommended by authors
– Satisfaction - Based on overall ratings from reviews
– Value – Based on value ratings from review
– Net Promoter – based on promoters and detractors from the last
year
– Metrics can be sliced for influencers only or the entire Author base
•
Key Words
– Score of how influential the key word is for that hotel
– Metrics can be sliced for influencers only or the entire Author base
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Creating Competitive Categories
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Pageviews by Competitor
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Looking At Browsing Demographics
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Customer Browsing Loyalty
DATA
DATA
INFORMATION
INFORMATION
INSIGHT
INSIGHT
STRATEGY
STRATEGY
ACTION
ACTION
Key Social Networking Metrics
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Master Data Meta Data
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Cross Master Data Meta Data
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Competitive Benchmarking
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Text Parsing and Mining
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION
Thank you.
Larry Goldman, President
773.456.3996
larry@amberleaf.net
DATA
INFORMATION
INSIGHT
STRATEGY
ACTION