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The Business Analytics Modernization Assessment (BAMA):
Listen, then Diagnose and Prescribe for Analytics Value
Roger Shears, Advisory Business Solutions Manager
BEST
PRACTICEBusiness Analytics Modernization Assessment
Overview:
Two and a half day on-site discovery session focused on understanding the client’s business and IT objectives, key initiatives, existing information management and analytics architecture, top challenges, and priorities.
Process:
• Review current business requirements, timeframes, critical success factors, and key business metrics (e.g. customer retention, customer acquisition).
• Review operational data sources to support business priorities.
• Review analytical priorities, strategy, process, and gaps.
Deliverables:
• Roadmap to optimize the client’s current and future IT-enabled analytical process.
• Projected business benefit resulting from proposed analytical architecture and process improvements.
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Strategic Analytics Capability Roadmap
People Process
Business
Driver
Customer
Objective
Results
Framework for the Business Analytics Modernization Dialogue
BUSINESS ANALYTICS MODERNIZATION ASSESSMENT (BAMA)
MODERNIZATION
Accuracy Governance Scalability
Economics
Challenges
Data TechnologyCulture
Actions &
EngagementsInfrastructure
Evaluation
Mechanism
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BAMA scope
Review and provide recommendations on:
• Business Analytics
− Advanced analytics
− Content delivery
− IT infrastructure
− Data management
− People and Processes
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BAMA milestones and timelines
• Fine tune agenda timings and duration
• Identification of Workshop participants
• Meeting facilities and dates
Week 0 - Sponsor alignment pre-call
• Distribute agenda
• Collect material including Workbooks
• Book workshop rooms, equipment, and people
Week 1 & 2 –Coordinate workshop
• Sponsor meetings
• Business workshops
• Technical workshops
• Present high-level findings and recommendations
Week 3 - On-site workshops
• SAS compiles report with findings, recommendations& best practices
• Coordinate early draft reviews with key contact
• Schedule final review meeting with sponsors
Week 4 & 5 - Finalize assessment report • Present final key
findings
• Present final recommendations
• Present target roadmap
Week 6 - Final presentation
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BAMA suggested attendees
Executive Sponsor
IT
• DBA
• Security administrators
• Database developer
• Enterprise metadata personnel
• ETL personnel
• Enterprise architects
Business
• SAS administrators
• Business users
• Lead SAS developer(s)
• Business process modelers
• Business/systems analysts
• Content Delivery personnel
• Lead modelers/analytic experts
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Before the BAMA workshop The Pre-assessment Workbook
• Layout (64 questions mapped to 8 dimensions and two measures)
• Definitions
− Metric Groupings
– Productivity
– Governance
– Timeliness
– ROI
– Effectiveness
– Accuracy
– Empowerment
– Maturity
− Measures
– Value
– Urgency
• How the book “works”
• How to read the graph
Copyr i g ht © 2012, SAS Ins t i tu t e Inc . A l l r ights reser ve d .
Copyr i g ht © 2012, SAS Ins t i tu t e Inc . A l l r ights reser ve d .
QUESTIONS ROI
1 The cost of inaccuracy is high and has a significant impact on profitability, market share and the ability to meet competitive pressures.2 There is little correlation between the cost of our technology and the value we receive from it.14 Costs within my organization are transparent and well understood.15 Key stakeholders generally agree on the benefits of new initiatives.20 Cost/benefit analysis for new initiatives is well documented.29 Our product offerings and services have remained relatively unchanged for a long period of time.30 We have the right amount of analytical talent in our organization to address critical business challenges.37 We could really benefit as a company if we could react faster to market changes or opportunities.42 Repeatable operational functions are typically not defined, documented, standardized or communicated.43 We need to get more value out of the current technology we have.46 I typically have all the information I need to make effective business decisions.51 We have difficulty analyzing data in a timely manner.56 A lot of costly business decision mistakes have been made in the past.59 Upper management strongly advocates or promotes analytics.63 End users are adequately trained in the software to analyze data.64 Most of our marketing efforts focus on either large customer segments or definitions of group membership rather than customized
approaches or micro-targeting.
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Workshop Agenda
SET THE STAGE, LISTEN, DIAGNOSE AND PRESCRIBE
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BAMA understanding the analytical lifecycle
Leading organizations who leverage and grow their business with analytics do so in the context of the analytics lifecycle
This lifecycle is important as it:
• Gives insight to the customer on how much of it they follow today
• Enables dialog on what areas they can improve and grow
• Helps define needed resources and skills
IDENTIFY /
FORMULATE
PROBLEM
DATA
PREPARATION
DATA
EXPLORATION
TRANSFORM
& SELECT
BUILD
MODEL
VALIDATE
MODEL
DEPLOY
MODEL
EVALUATE /
MONITOR
RESULTS
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BAMA topics covered during the workshop
Why The come to work each day…
Business Needs
Timeframes
What Constitutes Success?
The Lay of the Land
Current Systems Review
(Analytics Focus)
Current Infrastructure
Current Process Flow
Current Software
Performance Perception
• Decisions
• Information Presented
Insight
• Data Transformed to InformationAnalytics
• Data Fit For Problem
• Data Credibility
• Operational DataData
Business View of an Application
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BAMA topics covered during the workshop
What Keeps Them from Sleeping?
Data Acquisition Issues
Analytic Insight Issues
Content Delivery Issues
Is It the End of the Tunnel or a Train?
Future Business Issues
Future IT Issues
Future Process Issues
• Decisions
• Information PresentedInsight
• Data Transformed to InformationAnalytics
• Data Fit For Problem
• Data Credibility
• Operational Data
Data
IT View of an Application
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Workshop Agenda
SET THE STAGE, LISTEN, DIAGNOSE AND PRESCRIBE
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Outcomes of the BAMA
Summary of Key Findings
Key Business Requirements and Priorities
Strengths and Challenges (now/future/real/perceived)
Key Processes – data/information/process gaps
Recommendations
Short, Medium and Longer-term
Deliverables
PowerPoint PRIOR to Exit
Full Document within 10-15 Business Days
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‘TO BE’
People
Process
Technology Culture
Vision
Medium-term Longer-termShort-term “We promise to be a bold,
innovative leader that empowers
our customers to compete and
prosper.”
‘AS IS’
Data
BAMA summary recommendations roadmap
Visual Analytics
training for Loyalty
and AE Reporting
personnel
Consider
usage of SAS
services for
Advanced
Analytics
needs
Deploy Self Service
Analytical Exploration
and Reporting
Leverage investment in SAS Visual
Analytics in Loyalty and HR reporting
(timesheets)
Explore usage of
SAS Fraud Analytics
to augment fraud
Use data mining to determine
cardmember and employee attrition
predictors and actions Implement SAS In-DB
Data Quality
Use analytics as operational
driver for Call Center interactions
Consolidation
and expansion
of analytics
expertise in
ACE
Pilot the usage of
Visual Analytics for
AE and Loyalty
Reporting with
automation of data
management (ready
for EDW)
Investigate value of
In-Database (TD) data
quality for EDW
hygiene
Form Executive Analytics
Steering Committee
Centralize analytics
governance with
Model Manager
Collaborate on Analytics
Center of Excellence (ACE)
best practices
Investigate SAS
ABM for P&L and
cost reduction Explore benefits of
data federation and
MDM for analytics
pre and post EDW
Internal
Analytics
Certification
Differentiate
based on
value of
Advanced
Analytics
Tailored SAS Executive
Briefing based on
Assessment results
Investigate SAS Data
Management and Quality
for source file ETL
Marketing
Optimization
Deploy analytics to
Call Center as
managed business
rules for real time
customer
interactions
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After workshop FINAL RECOMMENDATIONS REPORT
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Best practices HIGH LEVEL RECOMMENDATIONS
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ANALYTICAL ROLES, RESPONSIBILITIES AND PROCESSBest practices
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Best practices HIGH LEVEL RECOMMENDATIONS
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Best practices HIGH LEVEL RECOMMENDATIONS
Company Confidential - For Internal Use Only
Copyright © 2013, SAS Insti tute Inc. Al l r ights reserved.
ENTERPRISE ANALYTICS ARCHITECTURE: HADOOP
MEDIUM CONFIGURATION2B
SAS®
ARCHITECTURE
MODERNIZATION
HPA Suite SAS® LASRTM Suite
SAS
Mid-
Tier
SAS
Metadata
Hadoop
Cluster
SAS
Embedded
Process
SAS Grid
SAS Rack
ENTERPRISE ANALYTICS ARCHITECTURE: HADOOP
MEDIUM CONFIGURATION
SAN
Company Confidential - For Internal Use Only
Copyright © 2013, SAS Insti tute Inc. Al l r ights reserved.
SAS ARCHITECTURE
MODERNIZATION
SAS Compute Hadoop Cluster
SAS Metadata SAS Mid-Tier SAS Grid HPA Suite SAS LASR Suite Cloudera or
Hortonworks
RHEL 6.5 RHEL 6.5 RHEL 6.5 RHEL 6.5 RHEL 6.5 RHEL 6.5
1 OS instance
(minimum)
1 OS instance
(minimum)
2 OS instances 4 OS instances 4 OS instances Min 4 servers
2 sockets / server
(min)
2 sockets / server
(min)
4 sockets / server 4 sockets / server 4 sockets / server Intel Xeon E7-
4890 v2 or Intel
Xeon E5-2690 v2
Starting at 128 GB
per OS instance
Starting at 128 GB
per OS instance
Starting at 256 GB
per OS instance
256 - 512GB+ per
OS instance
(min. 1600MHz)
256 - 512GB+ per
OS instance
(min. 1600MHz)
Min
256GB/server
8+ active cores
per OS instance
8+ active cores
per OS instance
Up to 60 active
cores per OS
instance
Up to 60 active
cores per OS
instance
Up to 60 active
cores per OS
instance
Hadoop Cluster
Starts at 800GB
SSD per OS
instance
Starts at 800GB
SSD per OS
instance
Starts at 4 PCIe
1.6TB SSD per OS
instance -
reference SAS
I/O and file
system
Starts at 6 data
SSDs for Local
(800GB each)
Starts at 6 data
SSDs for Local
(800GB each)
Intel® SSDs
Cloudera HadoopHortonworks
HadoopThird Party
Impala, Core
Components,
Cloudera
Manager
Ambari, HDFS,
MapReduce,
Nagios, Ganglia,
Hive
Ganglia, MS
Office 2013,
PuTTy,
MobaXterm
SAS Configuration
HPA Suite, SAS LASR Suite (SAS In-Memory Statistics
for Hadoop, SAS Visual Analytics, SAS Visual
Statistics), SAS Grid Manager, SAS Data Management,
SAS Enterprise Model Management, SAS In-Database
Code Accelerator, SAS Data Quality Accelerator, SAS
Scoring Accelerator, SAS/ACCESS® Interface to
Hadoop, SAS/ACCESS Interface to Impala, SAS Office
AnalyticsThe sample architecture referenced in the table above is for informational purposes only, is not a
performance benchmark, and does not constitute a performance guarantee. SAS and Intel recommend that
customers engage in a formal sizing exercise before acquiring hardware.
Enterprise Analytics Architecture - Medium Hadoop
All servers are Intel® Xeon® processor E7-4890 v2 (2.8GHz, 15C) and are 4 socket except where 2 socket is
indicated. Multiple OS instances may share a single physical machine to best leverage resources. Intel
recommends 2 Boot Intel SSD DC S3700 Series - 200GB per OS instance running SAS.
Total Intel SSD DC P3700 Series with NVMe - 1.6TB: 4+, Total Intel SSD DC S3700 Series - 800GB: 14+, Network
recommendation: 10Gb Ethernet minimum.
SAS In-MemorySAS Administrative Foundation
Enterprise Analytics Architecture - Storage and Network
Enterprise Analytics Architecture - Software
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Next steps ENGAGING WITH SAS BAMA TEAM
Contact your Account Executive
Americas: Roger Shears – [email protected]
EMEA/AP: Adrian Jones - [email protected]
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