Edgewater presented a case study on developing and implementing a BI platform at the IDMA 2015 Annual Meeting and Seminar.

1. From Strategy to Implementation the
Right Steps to Creating a BI Platform
IDMA 2015 ANNUAL MEETING AND SEMINAR

2. Agenda
2
• Edgewater Overview
• The Business Problems
• The Strategy
– BI Strategy and Requirements
– Empower the Business to Make Decisions on
Directions and Needs
– Define the Phases
• The Implementation
• What’s Next
• Questions and Answers

3. Overview
3

4. Edgewater Corporate Overview
• Founded in 1992
• Focus on upper-middle and
global 2000 markets
• 500+ employees
• 1000+ clients
• 5,300+ projects completed to
date
• Large North American footprint
– UK presence
• Publicly traded (NASDAQ:
EDGW)
– Public in 1996 (STAF)
– Reverse IPO in 2000 (EDGW)
• Co-founders still with the
Company
4

5. Edgewater Insurance Competencies
5
PAS
Illustration
Conversion
BI/Data
Strategy
Doc Gen
Automated
Print
Ecommerce

6. The Client: Business Problems
6
• It takes too long to get reports
• The reports are inconsistent, so which one
is correct
• The report was right last month, but now it
is wrong
• As the business grows, the reporting can’t
keep up

7. Strategy Project - Approach
7
• Meet with representative IT, business, and executive
stakeholders to capture their high-level business
requirements for the enterprise data warehouse;
• Examine the identified source systems, to assess their
ability to provide the data needed to meet the defined
reporting and analytic needs, and to understand the
nature and mechanics of the data collection;
• Meet with representative business stakeholders and
other appropriate end-users to capture the detailed
requirements for data, reporting and analytics to be
supported by this data warehouse.

8. Enterprise Data Pipeline
8
• Gather Requirements
DataCapture
Admin
Cust. Care
Finance
Sales
DataTransformation
Claims
Operational
Financial
Policy
Other
Universal
Data Model
Extraction/
Mapping
Translation
DataConsumption
Subject Area
Data Marts
Data Cubes
Master
Reference Data
Analytics/
Self Service
Alerts and
Dashboards
Standard Reports

9. Findings
9
• Continually Evolving Policy Administration System
(PAS) - ALIP
• Inability to Produce or Obtain Information Needed
Today
• Excessive Turnaround Time for Critical Information
• Inconsistency of Enterprise Terminology
• Manual Reporting Processing and Tools
• Multiple Databases, FTEs, and Costs in Reporting
• Fear of Inability to Scale for the Future

10. Phase Planning
10
• Define, Prioritize, Schedule, Execute –
Phase-Specific Plans
1. Examine each Data Domain
1
2
34
5
6
2. Position Data Domain within
Enterprise Content Model
3. Assess Scoping &
Prioritization Criteria
4. Develop Phase-Specific
Data Integration Plan
5. Align with Data Architecture,
Overall Program,
Governance
6. Schedule &
Execute Phase-Specific Plan
Data Supply
Assess &
Prioritize
User Demand
• Analytic needs
of end-users
• Business
priorities
• Data Domains
• From multiple
source
systems

11. 3-Year Timeline
11
Year 1 Year 2 Year 3
Ongoing Phase Prioritization and Definition
Phase 1 – 7 months
Finance
Correspondence
Operations
Actuarial
Investments/HR

12. The Implementation
12
• Build an Enterprise Data Warehouse that will serve as:
– an integrated, multi-subject-area repository that will hold the critical information
needed by various stakeholders, decision makers, analysts and sales staff across the
organization;
– a focal point to enable coordination and integrate the definition, collection, processing,
management, analysis, presentation and dissemination of various sources and
formats of data pertaining to numerous functional and subject areas;
– the foundation of an end-to-end architecture that is cost-effective, flexible, scalable,
and meets requirements for security and audit-ability.
• Build a Sales & Marketing Data Mart that will:
– introduce key Sales & Marketing subject areas
– integrate and replace stand-alone Sales & Marketing specific spreadsheets
– introduce key reports and dashboards that can be used as templates for self-service
reporting and analysis

13. Architecture
13
SQL Server 2008 R2 (SP3)
ALIP
Source System
Extract
ETL System
SQL Server Integration Services 2014
Enterprise Data Warehouse
SQL Server 2014
Dimensional Data
Model
LoadTransform
OLAP Cubes
SQL Server Analysis Services 2014
(Multi-Dimensional Model)
Load
Reporting
SQL Server Reporting
Services 2014
MDX

14. What’s Next
14
• Departments
– Finance
– Government Affairs
– HR
– Investments
– Operations
• New Business
• Underwriting
• Policy Holder Services
• Beneficiary Services
• Actuarial Data Mart and Advanced Analytics
Project Initiation
Requirements
QA Test
(Test Cases)
User Test
Knowledge
Transfer and
Deployment
Steering Committee Appropriate SMEs IT Staff

15. 15
Questions?
Thank You!