SlideShare ist ein Scribd-Unternehmen logo
1 von 73
MNP Technology Consulting
Presents:

Business Analytics:
Top Line Growth and Bottom Line Results

May 8, 2012
Introductions - Facilitators
Brian Beveridge
Partner, Technology Consulting Leader
MNP LLP

Shelley Legin
Credit Union Consulting Lead
MNP LLP
Agenda
• 1:45 – 2:45 – Presentation
• 2:45 – 3:00 – Interactive Session
• 3:00 – 3:15 – Q & A
Objectives
Give Credit Union Executives and Board
Directors an Understanding of:
1. What Business Analytics is
2. How could it be applied to Your Credit
Union
3. How could you get started on a
Business Analytics Project
Does anyone have any other Objectives?
Topics
1. Introduction
2. A Business Analytics Primer
3. The link between Business Success and
Business Analytics
4. How can Business Analytics address the
Key Issues in Credit Unions?
5. Is there an App for That? (Mobile
Business Analytics)
Topics
6. How to get started with Business Analytics
projects
7. Interactive Session
8. Q & A
What is Business Analytics?

-7-
We live in a
Connected, Instrumented, Dat
a-Rich World
Nissan Leaf Dashboard
My Ski Goggles
What is Business Analytics?
“Business Intelligence” Term Coined by
Gartner in 1989
– Simply defined as “using information
effectively to make better decisions”.
What is Business Analytics?
Gartner‟s Emphasis Today: “Corporate
Performance Management “
CPM means getting a better finger on the
pulse of an organization to make a
better, more accurate, and more timely
assessment of how an organization is doing.
Enterprises need to move away from
asking, “How did we do last month or last
quarter” to “How are we doing right now” as
well as “How will we do next week”
MNP‟s Definition of Business
Analytics
Improving our client‟s business
results by providing business
insights to all employees leading
to better, faster, more
relevant decisions
The link between Business
Success and Business Analytics
Information is the Key to a New Wave of
Opportunity…

44x

as much Data and Content
Over Coming Decade

But Businesses are
Challenged to Leverage it….

1 in 3
2020
35 zettabytes

Sources:
• The Guardian, May 2010
• IBM Institute for Business Value, 2009
• IBM CIO Study 2010
• TDWI: Next Generation Data Warehouse Platforms Q4 2009

Business leaders frequently
make decisions based on
information they don’t trust, or
don’t have

1 in 2

Business leaders say they don’t
have access to the information
they need to do their jobs

83%

of CIOs cited “Business
intelligence and analytics” as
part of their visionary plans
to enhance competitiveness
Organizations embracing Business
Analytics have the answers …

3x
Organizations that lead in
analytics outperform those
who are just beginning to
adopt analytics

5.4x
Top Performers are more
likely to use an analytic
approach over intuition*
*within business processes

Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010.
Winners in the Financial Industry
Customer analytics

Operational efficiency

Using advanced
analytics to profile
and segment target
customers, First
Tennessee Bank
improved
marketing
effectiveness by:

Using financial
analytics to
streamline
statement creation,
First Command
accelerated monthend updates by
over:

600%

Risk management
Using business
intelligence to
create an online
credit tool, Argos
generated an
annual business
value for each
customer of:

500% $855K
A Business Analytics Primer
Problems with Traditional Reporting
and Analysis

• Predefined Reports built into specific applications
such as Financials, HR, Point of Sale, etc.
• Some capability to customize layouts and
parameters but typically limited
• Biggest limitation has been the „scope‟ – i.e. You
cannot easily combine and analyze data across
application boundaries – i.e. HR and Financial
information combined in the same report
• Limited ability to „model‟ and try different scenarios
• Changes often require IT to customize which costs
time and $$
Page  19
Traditional Reporting and Analysis
Does a Pretty
Good Job

Typically not
“real time”

Typically –
not
addressed

Page  20
Business Analytics Helps with Corporate
Performance Management
How are
we doing?

What should
we be doing?
Analytics

Why?
BA Helps with Corporate Performance
Management
■ Performance

■ Decision Making

■ Information

■ Data
What if you had all the answers to win?

Which
customers
are thinking
of leaving?

Which
transactions
are
suspicious?

How is
Margin
Compression
affecting my
credit union?

The ultimate differentiator today…
…is being able to make more informed choices with
confidence, to anticipate and shape business outcomes.

How can I
extract
insight from
all of my
information?
A Taste for Analytics

-24-
Guided Exploration of Your Data
• Enables guided exploration of information
that pertains to all dimensions of your
business
• Continuous exploration and investigation of
past performance to gain new insights and
aid in business planning
• Facilitates complex analysis and scenario
modeling easily and quickly without requiring
IT resources
• Gets to the “why” behind an event or action
to improve business performance.
• Provides navigation from summary to detail
levels of information effortlessly
The Four Styles of Analysis
Line
Managers

Business
Users

Financial
Analysts

Business
Analysts

Business
Managers

Executives

How are we doing?

Why?

What should we be doing?

Immediate, visual insight into
business performance

Self-service analysis of
trends and patterns

Insight to determine strategy,
allocate resources and set targets

Analytic
Reporting

Predictive
Analytics

Trending

Scenario
Modeling

• Top down view
• Drillable reports
• Sort top & bottom
• Review then query

• Personal exploration
• Compare & contrast
• Rotate and nest
• Work disconnected

• Model scenarios
• Compare
scenarios
• Save versions

• Uncover patterns
• Statistical calcs
• Mine data/text
• Predict will be”
”What outcomes

• Budget Variance
• Product ranking

• Sales trend analysis
• Market analysis

• Financial analysis
• Profitability
analysis

• Fraud prevention
• Churn analysis

”Drill-Down”

”Slice and Dice”

”What if”
The Four Styles of Analysis
Line
Managers

Business
Users

Financial
Analysts

Business
Analysts

Business
Managers

Executives

How are we doing?

Why?

What should we be doing?

Immediate, visual insight into
business performance

Self-service analysis of
trends and patterns

Insight to determine
strategy, allocate resources and set
targets

Business Analytics Application Components

Dashboards Scorecards

Reports

Queries

Analysis

Content
analytics

Predictive
modeling

Planning/
budgeting

Business Analytics platform

Loans
Systems

Banking
Systems

HR Systems

Marketing
Systems

Financial
Systems
Business Analytics Continuum

Scenario
Modeling
Trending

Analytic
Reporting

Predictive
Analytics
Business Analytics Applications
Analytic Reporting
 Provides full breadth of report types
 Delivers consistent information across all types of
report output
 Can be personalized and targeted
 Enables collaboration across users, communities
and with IT
 Provides access via email, portal, MS-Office,
search and mobile devices etc

Multi-Dimensional Analysis
 Provides guided exploration across multiple
dimensions of information
 Performs complex analysis and scenario modeling
easily and quickly
 Gets to the “why” behind trends to reveal
symptoms and causes

 Moves from summary level to detail levels of
information effortlessly
Business Analytics Applications
Dashboards
 Provides at-a-glance, high impact views of
complex information
 Helps quick focus on issues that need attention
and action
 Are highly visual and intuitive
 Combines information across disparate sources

Scorecards
 Provides instant measurement relative to
targets and benchmarks
 Aligns decisions and tactics with strategic
initiatives
 Supports scorecarding methodologies
 Ensures ownership and accountability
Scenario Modelling
 Model and compare
scenarios
 Reorganize, reshape
 Multiple versions
 Financial and profitability
analysis

 Exploration and „what-if‟
scenario modeling
Predictive Analytics is Transformation Technology
• Analyzes patterns found in historical and
current transaction data
• Analysis into attitudinal survey data to
predict future outcomes
• Enables more proactive decision
making, driving new forms of competitive
advantage:
– How do I predict outcomes resulting
from my decisions?
– How can I predict demand and
allocate resources to ensure I am
delivering services effectively?
– How can I find the patterns in vast
amounts of data?
Summary – Business Analytics in Context
Planning, Budgeting,
Forecasting & Consolidation

Analysis & Reporting
What happened?

What will happen?

Report

Forecast

Single
Data Model
What is happening?

Scorecard

Why?
Analyze

What do I want to happen?
Plan
Move from “Sense and Respond”
to “Predict and Act”
Predict and act
Velocity

Lack of
Insight

Inefficient
Access

Volume

Sense and respond

Instinct and intuition

Skilled analytics experts
Variety

Inability
to Predict

Back office

Real-time, fact-driven

Everyone

Point of impact

Automated

Optimized
How can Business Analytics address
the Key Issues in Credit Unions?
Key Business Issues Facing Credit
Unions
1.
2.
3.
4.
5.
6.

Address Margin Compression
Develop a strategy for consolidation
Enhance regulatory compliance
Prepare for industry transformation
Attract new members
Leverage IT to improve productivity and
profitability
7. Attract, manage and retain top talent
8. Protect your members from fraud
Credit Union What ifs…
Payments

Branch management

... predictive analytics could detect
and prevent a wire transfer identified
as high probability of fraud?

...could understand which
branches or products were
performing the best?

Executive leaders

...could make better business
decisions using accurate data
across all time horizons

Relationship
management

...could consider
the risk and
profitability of the
entire member
relationship when
pricing new deals?

Risk and finance
Marketing

...could predict the right
offer for the right
member at the right
time?

...could streamline
compliance and
understand risk
exposure across
businesses and
regions?
The Irony is…
• You probably have more than enough DATA to
get the answers…
• But you can‟t access it, analyze it, or
communicate it well enough
• You understand people who have already done
business with you vs those that have not
• “Myth Busting” – many assumptions may not be
supported by the data
No Shortage of Internal Data
Member Data

Financial Products

-

-

# of members
Demo Information
Location
Accounts

Issue – How to
transform it into
INFORMATION
and ACT on it

Revenue
Costs
Location
Accounts

Financial Transactions

Branch Data

-

-

Deposits/Withdrawals
Loan Pmts
Interest

Members by Brach
Revenue by Branch
Product Mix by Branch
The Data isn‟t always where its needed
Executive
- Strategic Planning

Middle Managers
- Management Control
Front-Lines
- Operational Control
The greatest challenge of the computer
industry is to learn how to build
information bases, not databases. The
really important information cannot be
easily quantified and exists outside the
organization.
- Peter Drucker (1993)
The Analytics-Driven Credit Union
Increase flexibility and
streamline operations

Optimize
enterprise risk
management

42

$

Create a
Memberfocused Credit
Union
The Member View
How do I retain my
best members?
Who are my ideal
members and how do I
attract them?
How can I ensure that our
pricing is competitive and
profitable?

What products/services
attract mass affluent
members?

?
How do I find the optimal
balance between service
and cost of delivery?
How can I improve service

Why are my marketing
response rates so low?
How do I make more
members highly
profitable?

43

levels and the knowledge
of my front-line
employees?
Which are my best
performing branches?
Member Profitability Analytics
 Create profitability analysis and forecasts

 Perform “what if?” scenario analytics
 Calculate profit and loss (P&L) at the
account level
 Increase cross and up sell opportunities
 Analyze historical information to:
 Predict customer propensity to buy
 Develop lifetime value models
 Create account retention strategies
 Develop strategies to improve retention
and wallet-share of profitable customers
 Reduce servicing costs by matching
service levels to customer value
Marketing Optimization
 Mine historical member information to
determine patterns and segmentation
 Use predictive models to determine
likelihood of response to offers or
defection
 Generate reports and alerts on
customer interactions and portfolios
 Incorporate unstructured text data into
the analysis to better capture customer
sentiment
 Predict which customers are likely to
leave and what will keep them
 Use marketing dashboards to track and
monitor response and sales created
 Improve marketing cross-sell efforts and
reduce execution costs

45
Relationship Pricing
 Delivers an intuitive, centrally controlled
pricing tool that considers complete
relationship value and risk to improve pricing
consistency for both credit and non-credit
deals
 Provides bottom-up and top-down planning
capability and automated approval workflow
 Enables quick changes and consistent roll out
with centrally controlled pricing model

 Provides dashboards for relationship
managers, lending officers and senior
management
 Enables relationship managers to quickly and
consistently evaluate risk and profitability of
new business and increases management
visibility into lending book
Client Servicing
 Includes paperless, real-time selfservice reporting and analysis of
account holdings and recent activity
 Delivers Wealth Manager dashboard
with service process
monitoring, reporting, analysis and
forecasting
 Provides online or mobile client
statements with portfolio
summary, performance analysis and
asset allocation
 Improves relationship manager
knowledge and customer service
Risk Management View
How do I inform
business users about
the risk impact
of decisions?

How do I integrate
governance, risk and
compliance
processes?
Could I benefit from
fraud detection and
credit risk analytics?
Can I perform risk scenario
analytics?

48

How do I eliminate
operational silos to get
an enterprise view of
risk?

How do I operationalize
risk appetite?

?

How do I respond more
efficiently to evolving
regulatory requirements?
What operational risks
can be reduced?
How do I ensure that
pricing models are risk
adjusted?
Governance, Risk and Compliance
Provides an integrated enterprise risk solution to
help reduce risk exposure and simplify
regulatory response with a single system of
record
Enables the identification, management,
monitoring and reporting of operational risks and
regulatory compliance initiatives, including policy
management and IT
Improves processes with fully integrated risk
and compliance data
 Risk control self-assessments
 Scenario analysis
 Key risk indicators
 Loss event database
 Policies and regulatory mandates
 Harmonized control framework
Provides root cause analysis
Risk Insight & Optimization
 Includes business intelligence to provide
finance-integrated, actionable risk
dashboards, scorecards, and reporting
 Enables risk adjusted financial
planning, business modeling, strategy
selection and initiative planning
 Scenario analysis for all risk classes
(credit, market, liquidity, operational, counterp
arty)
 Risk optimization through risk and finance
integration, risk appetite management and
communications, strategic planning, and riskadjusted relationship pricing

50
The Streamlining View
How do I provide better
executive visibility into
enterprise performance?
Where can I cut costs
without affecting
revenue?

?

How do I improve tracking/
monitoring of high-value
payments?

What branches and
relationship managers are
my best performers?
Why?

How do I streamline
my financial
planning/budgeting
process?

How do I deliver real-time
insight at the point of
impact?

What’s the best
approach for IT cost
allocation?
Branch Performance Management
 Enables driver-based, rolling branch financial
planning at the product and customer segment
level
 Provides staff planning so headcount expenses
can be easily understood and controlled
 Monitors and analyzes key revenue, cost and
profitability measures by branch, product type,
product, member segment and even household
Payments Monitoring and Analysis
 Monitors transactions by
counterparty, geography, asset class
and transaction type
 Identifies trigger events for interventions
 Implements governance of key
performance measures and targets
 Predicts traffic, counterparty weakness
and bottlenecks
 Builds agile, fully costed plans and
forecasts to optimize pricing/chargeback
tariffs

53
Is there an App for That? (Mobile
Business Analytics)

-54-
Is there an App for that?
You‟ve seen the headlines…
• Today, over 80% of the Fortune 100 are
already deploying or piloting iPad -(NetworkWorld
2011)

• “Mobile BI has the potential to significantly
expand the population of BI users to include
a much more mainstream audience” -(Gartner
2011)

• “Forty percent of devices that information
workers use to access business applications
are personally owned” – (IDC 2011)
Why Mobile Business Analytics?
• Very broad reach
• “Real Time” accessibility of information
and decision making
• New, immersive experiences and
visualizations
• New possibilities for Collaborative
Business Analytics
How to Get Started with Business
Analytics projects

-60-
How to get started with BA?
• First and foremost – You need to realize that
Business Intelligence is not „Out of the Box‟
unless plugging into ERP or other „Single
Application‟ Solution
• There is typically design and development
work involved
• Depends heavily on your data and application
mix as well as your objectives/metrics
• Invest in “Up Front” planning and “selling” of
the project
What has to go Right on BA
Projects?
1.
2.
3.
4.
5.
6.

Executive Sponsorship and Commitment
Planning
Trust in the Data – Data Validation
Proper Roles
Change Management
Sustainment
Strategy Based Analytics Approach
Plug Into CU Management Process
1. The strategic management process where
strategic issues are refined and implications
discussed.
2. In the operational management process
corrective actions are taken and implications are
discussed.
3. In the daily management processes corrective
actions are taken.
In all three processes, there is an „evidence based‟ or
analytics-based review of performance indicators
Getting Started with Analytics
Projects
1.
2.
3.
4.
5.

Start with an Executive Discovery Session
Review Business Strategy
Build the linkages from Strategy to Measures
Determine success indicators
Identify process and project fitness –
Readiness Assessment
6. Build the scorecard/measurement process
7. Gather Data from Operational Systems
8. Build the Views, Reports, Analyses, and
Dashboards
Readiness Assessment
Asks the following questions:
1. Do you have executive support?
2. Are the goals defined?
3. Can your staff handle the change?
4. Do you have the data needed?
5. Can your systems support BA?
6. Can your IT staff handle this?
Avoid Common Pitfalls
1. Lack of Planning You need a map of where you're
hoping to go – and the team to get you there.
2. Under-Estimating the Data Access/Validation phases
of the project.
3. Lack of Resources – You will need:
• Business Expert
• Data Expert
• Business Analytics Solutions Expert
Avoid Common Pitfalls
4. Lack of responsibility. If you are going to make critical
decisions on the data in the BA system, you need at
least one staff member who takes responsibility to be
the „Data Validation Cop' of content.
5. No Change Management. You need to get people
prepared for the change in their roles and
responsibilities as well as the challenges of having
data/results more visible.
6. Lack of Ongoing Sustainment. You need to constantly
feed the solution with data and adjust the metrics as the
business changes.
Interactive Session
• Business Analytics – Credit Union
Examples
• Mobile / iPad Analytics Solutions
Questions

-71-
Thanks for Participating

-72-
Follow Up
•

Brian Beveridge
•

(204)-775-3500 ext 4602

•

Brian.Beveridge@mnp.ca

• Shelley Legin
• (778)-772-8009
•

Shelley.Legin@mnp.ca

Weitere ähnliche Inhalte

Was ist angesagt?

Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business IntelligenceRonan Soares
 
Business analytics
Business analyticsBusiness analytics
Business analyticsDinakar nk
 
Business Intelligence-v1.pptx
Business Intelligence-v1.pptxBusiness Intelligence-v1.pptx
Business Intelligence-v1.pptxRandhirShah3
 
Business Intelligence - Intro
Business Intelligence - IntroBusiness Intelligence - Intro
Business Intelligence - IntroDavid Hubbard
 
Business Intelligence And Business Analytics | Management
Business Intelligence And Business Analytics | ManagementBusiness Intelligence And Business Analytics | Management
Business Intelligence And Business Analytics | ManagementTransweb Global Inc
 
Better decision making with proper business intelligence
Better decision making with proper business intelligenceBetter decision making with proper business intelligence
Better decision making with proper business intelligencemadhavlankapati
 
Business Analytics and Decision Making
Business Analytics and Decision MakingBusiness Analytics and Decision Making
Business Analytics and Decision MakingExcel Strategies LLC
 
Business Intelligence Presentation (1/2)
Business Intelligence Presentation (1/2)Business Intelligence Presentation (1/2)
Business Intelligence Presentation (1/2)Bernardo Najlis
 
1. Data Analytics-introduction
1. Data Analytics-introduction1. Data Analytics-introduction
1. Data Analytics-introductionkrishna singh
 
Business Intelligence
Business IntelligenceBusiness Intelligence
Business IntelligenceHank Lin
 
Importance of Data Analytics
 Importance of Data Analytics Importance of Data Analytics
Importance of Data AnalyticsProduct School
 
Foundations of analytics.ppt
Foundations of analytics.pptFoundations of analytics.ppt
Foundations of analytics.pptSurekha98
 
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
 
Introduction to Business Analytics Part 1
Introduction to Business Analytics Part 1Introduction to Business Analytics Part 1
Introduction to Business Analytics Part 1Beamsync
 
Business Intelligence and Business Analytics
Business Intelligence and Business AnalyticsBusiness Intelligence and Business Analytics
Business Intelligence and Business Analyticssnehal_152
 

Was ist angesagt? (20)

Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business Intelligence
 
Business analytics
Business analyticsBusiness analytics
Business analytics
 
Business Intelligence-v1.pptx
Business Intelligence-v1.pptxBusiness Intelligence-v1.pptx
Business Intelligence-v1.pptx
 
Business Intelligence - Conceptual Introduction
Business Intelligence - Conceptual IntroductionBusiness Intelligence - Conceptual Introduction
Business Intelligence - Conceptual Introduction
 
Business analytics
Business analyticsBusiness analytics
Business analytics
 
Business Intelligence - Intro
Business Intelligence - IntroBusiness Intelligence - Intro
Business Intelligence - Intro
 
Business Intelligence And Business Analytics | Management
Business Intelligence And Business Analytics | ManagementBusiness Intelligence And Business Analytics | Management
Business Intelligence And Business Analytics | Management
 
Better decision making with proper business intelligence
Better decision making with proper business intelligenceBetter decision making with proper business intelligence
Better decision making with proper business intelligence
 
Data analytics
Data analyticsData analytics
Data analytics
 
Business Analytics and Decision Making
Business Analytics and Decision MakingBusiness Analytics and Decision Making
Business Analytics and Decision Making
 
Business Intelligence Presentation (1/2)
Business Intelligence Presentation (1/2)Business Intelligence Presentation (1/2)
Business Intelligence Presentation (1/2)
 
BUSINESS INTELLIGENCE
BUSINESS INTELLIGENCEBUSINESS INTELLIGENCE
BUSINESS INTELLIGENCE
 
1. Data Analytics-introduction
1. Data Analytics-introduction1. Data Analytics-introduction
1. Data Analytics-introduction
 
Business Intelligence
Business IntelligenceBusiness Intelligence
Business Intelligence
 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
 
Importance of Data Analytics
 Importance of Data Analytics Importance of Data Analytics
Importance of Data Analytics
 
Foundations of analytics.ppt
Foundations of analytics.pptFoundations of analytics.ppt
Foundations of analytics.ppt
 
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...
 
Introduction to Business Analytics Part 1
Introduction to Business Analytics Part 1Introduction to Business Analytics Part 1
Introduction to Business Analytics Part 1
 
Business Intelligence and Business Analytics
Business Intelligence and Business AnalyticsBusiness Intelligence and Business Analytics
Business Intelligence and Business Analytics
 

Ähnlich wie Business analytics workshop presentation final

HWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
HWZ-Darden Konferenz: Building a Sustainable Analytics OrientationHWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
HWZ-Darden Konferenz: Building a Sustainable Analytics OrientationHWZ Hochschule für Wirtschaft
 
The Softer Skills Analysts need to make an impact
The Softer Skills Analysts need to make an impactThe Softer Skills Analysts need to make an impact
The Softer Skills Analysts need to make an impactPaul Laughlin
 
Metrics to Maturity, Intelligence for Innovation: Your Value Proposition
Metrics to Maturity, Intelligence for Innovation: Your Value PropositionMetrics to Maturity, Intelligence for Innovation: Your Value Proposition
Metrics to Maturity, Intelligence for Innovation: Your Value PropositionCherwell Software
 
Making Money Out of Data
Making Money Out of DataMaking Money Out of Data
Making Money Out of DataDigital Vidya
 
WHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjn
WHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjnWHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjn
WHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjnRohitKumar639388
 
Self-service Analytic for Business Users-19july2017-final
Self-service Analytic for Business Users-19july2017-finalSelf-service Analytic for Business Users-19july2017-final
Self-service Analytic for Business Users-19july2017-finalstelligence
 
HR Analytics - PAaDS2016
HR Analytics - PAaDS2016HR Analytics - PAaDS2016
HR Analytics - PAaDS2016PanaEk Warawit
 
HR / Talent Analytics
HR / Talent AnalyticsHR / Talent Analytics
HR / Talent AnalyticsAkshay Raje
 
Integrating Digital Marketing Analytics
Integrating Digital Marketing AnalyticsIntegrating Digital Marketing Analytics
Integrating Digital Marketing AnalyticsDaniel Shea
 
BA Overview.pptx
BA Overview.pptxBA Overview.pptx
BA Overview.pptxSuKuTurangi
 
Building a Winning Roadmap for Analytics
Building a Winning Roadmap for AnalyticsBuilding a Winning Roadmap for Analytics
Building a Winning Roadmap for AnalyticsIronside
 
TA reporting metrics and analytics
TA reporting metrics and analyticsTA reporting metrics and analytics
TA reporting metrics and analyticscjparker
 
Enabling Success With Big Data - Driven Talent Acquisition
Enabling Success With Big Data - Driven Talent AcquisitionEnabling Success With Big Data - Driven Talent Acquisition
Enabling Success With Big Data - Driven Talent AcquisitionDavid Bernstein
 
August webinar - Data Analysis vs Business Analysis vs BI vs Big Data
August webinar  - Data Analysis vs Business Analysis vs BI vs Big DataAugust webinar  - Data Analysis vs Business Analysis vs BI vs Big Data
August webinar - Data Analysis vs Business Analysis vs BI vs Big DataMichael Olafusi
 
Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...
Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...
Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...Edunomica
 

Ähnlich wie Business analytics workshop presentation final (20)

HWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
HWZ-Darden Konferenz: Building a Sustainable Analytics OrientationHWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
HWZ-Darden Konferenz: Building a Sustainable Analytics Orientation
 
The Softer Skills Analysts need to make an impact
The Softer Skills Analysts need to make an impactThe Softer Skills Analysts need to make an impact
The Softer Skills Analysts need to make an impact
 
Metrics to Maturity, Intelligence for Innovation: Your Value Proposition
Metrics to Maturity, Intelligence for Innovation: Your Value PropositionMetrics to Maturity, Intelligence for Innovation: Your Value Proposition
Metrics to Maturity, Intelligence for Innovation: Your Value Proposition
 
Making Money Out of Data
Making Money Out of DataMaking Money Out of Data
Making Money Out of Data
 
WHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjn
WHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjnWHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjn
WHAT IS BUSINESS ANALYTICS um hj mnjh nit 1 ppt only kjjn
 
Self-service Analytic for Business Users-19july2017-final
Self-service Analytic for Business Users-19july2017-finalSelf-service Analytic for Business Users-19july2017-final
Self-service Analytic for Business Users-19july2017-final
 
HR Analytics - PAaDS2016
HR Analytics - PAaDS2016HR Analytics - PAaDS2016
HR Analytics - PAaDS2016
 
HR / Talent Analytics
HR / Talent AnalyticsHR / Talent Analytics
HR / Talent Analytics
 
Integrating Digital Marketing Analytics
Integrating Digital Marketing AnalyticsIntegrating Digital Marketing Analytics
Integrating Digital Marketing Analytics
 
BA Overview.pptx
BA Overview.pptxBA Overview.pptx
BA Overview.pptx
 
Building a Winning Roadmap for Analytics
Building a Winning Roadmap for AnalyticsBuilding a Winning Roadmap for Analytics
Building a Winning Roadmap for Analytics
 
TA reporting metrics and analytics
TA reporting metrics and analyticsTA reporting metrics and analytics
TA reporting metrics and analytics
 
Hranalytics goodone
Hranalytics goodoneHranalytics goodone
Hranalytics goodone
 
1-210217184339.pptx
1-210217184339.pptx1-210217184339.pptx
1-210217184339.pptx
 
Enabling Success With Big Data - Driven Talent Acquisition
Enabling Success With Big Data - Driven Talent AcquisitionEnabling Success With Big Data - Driven Talent Acquisition
Enabling Success With Big Data - Driven Talent Acquisition
 
Business inteligence
Business inteligenceBusiness inteligence
Business inteligence
 
HR analytics
HR analyticsHR analytics
HR analytics
 
August webinar - Data Analysis vs Business Analysis vs BI vs Big Data
August webinar  - Data Analysis vs Business Analysis vs BI vs Big DataAugust webinar  - Data Analysis vs Business Analysis vs BI vs Big Data
August webinar - Data Analysis vs Business Analysis vs BI vs Big Data
 
SAS Institute: Big data and smarter analytics
SAS Institute: Big data and smarter analyticsSAS Institute: Big data and smarter analytics
SAS Institute: Big data and smarter analytics
 
Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...
Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...
Jeremy Adamson: Minding the Machines: Building and Leading Analytics Data Sci...
 

Kürzlich hochgeladen

08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsRoshan Dwivedi
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 

Kürzlich hochgeladen (20)

08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 

Business analytics workshop presentation final

  • 1. MNP Technology Consulting Presents: Business Analytics: Top Line Growth and Bottom Line Results May 8, 2012
  • 2. Introductions - Facilitators Brian Beveridge Partner, Technology Consulting Leader MNP LLP Shelley Legin Credit Union Consulting Lead MNP LLP
  • 3. Agenda • 1:45 – 2:45 – Presentation • 2:45 – 3:00 – Interactive Session • 3:00 – 3:15 – Q & A
  • 4. Objectives Give Credit Union Executives and Board Directors an Understanding of: 1. What Business Analytics is 2. How could it be applied to Your Credit Union 3. How could you get started on a Business Analytics Project Does anyone have any other Objectives?
  • 5. Topics 1. Introduction 2. A Business Analytics Primer 3. The link between Business Success and Business Analytics 4. How can Business Analytics address the Key Issues in Credit Unions? 5. Is there an App for That? (Mobile Business Analytics)
  • 6. Topics 6. How to get started with Business Analytics projects 7. Interactive Session 8. Q & A
  • 7. What is Business Analytics? -7-
  • 8. We live in a Connected, Instrumented, Dat a-Rich World
  • 11. What is Business Analytics? “Business Intelligence” Term Coined by Gartner in 1989 – Simply defined as “using information effectively to make better decisions”.
  • 12. What is Business Analytics? Gartner‟s Emphasis Today: “Corporate Performance Management “ CPM means getting a better finger on the pulse of an organization to make a better, more accurate, and more timely assessment of how an organization is doing. Enterprises need to move away from asking, “How did we do last month or last quarter” to “How are we doing right now” as well as “How will we do next week”
  • 13. MNP‟s Definition of Business Analytics Improving our client‟s business results by providing business insights to all employees leading to better, faster, more relevant decisions
  • 14. The link between Business Success and Business Analytics
  • 15. Information is the Key to a New Wave of Opportunity… 44x as much Data and Content Over Coming Decade But Businesses are Challenged to Leverage it…. 1 in 3 2020 35 zettabytes Sources: • The Guardian, May 2010 • IBM Institute for Business Value, 2009 • IBM CIO Study 2010 • TDWI: Next Generation Data Warehouse Platforms Q4 2009 Business leaders frequently make decisions based on information they don’t trust, or don’t have 1 in 2 Business leaders say they don’t have access to the information they need to do their jobs 83% of CIOs cited “Business intelligence and analytics” as part of their visionary plans to enhance competitiveness
  • 16. Organizations embracing Business Analytics have the answers … 3x Organizations that lead in analytics outperform those who are just beginning to adopt analytics 5.4x Top Performers are more likely to use an analytic approach over intuition* *within business processes Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010.
  • 17. Winners in the Financial Industry Customer analytics Operational efficiency Using advanced analytics to profile and segment target customers, First Tennessee Bank improved marketing effectiveness by: Using financial analytics to streamline statement creation, First Command accelerated monthend updates by over: 600% Risk management Using business intelligence to create an online credit tool, Argos generated an annual business value for each customer of: 500% $855K
  • 19. Problems with Traditional Reporting and Analysis • Predefined Reports built into specific applications such as Financials, HR, Point of Sale, etc. • Some capability to customize layouts and parameters but typically limited • Biggest limitation has been the „scope‟ – i.e. You cannot easily combine and analyze data across application boundaries – i.e. HR and Financial information combined in the same report • Limited ability to „model‟ and try different scenarios • Changes often require IT to customize which costs time and $$ Page  19
  • 20. Traditional Reporting and Analysis Does a Pretty Good Job Typically not “real time” Typically – not addressed Page  20
  • 21. Business Analytics Helps with Corporate Performance Management How are we doing? What should we be doing? Analytics Why?
  • 22. BA Helps with Corporate Performance Management ■ Performance ■ Decision Making ■ Information ■ Data
  • 23. What if you had all the answers to win? Which customers are thinking of leaving? Which transactions are suspicious? How is Margin Compression affecting my credit union? The ultimate differentiator today… …is being able to make more informed choices with confidence, to anticipate and shape business outcomes. How can I extract insight from all of my information?
  • 24. A Taste for Analytics -24-
  • 25. Guided Exploration of Your Data • Enables guided exploration of information that pertains to all dimensions of your business • Continuous exploration and investigation of past performance to gain new insights and aid in business planning • Facilitates complex analysis and scenario modeling easily and quickly without requiring IT resources • Gets to the “why” behind an event or action to improve business performance. • Provides navigation from summary to detail levels of information effortlessly
  • 26. The Four Styles of Analysis Line Managers Business Users Financial Analysts Business Analysts Business Managers Executives How are we doing? Why? What should we be doing? Immediate, visual insight into business performance Self-service analysis of trends and patterns Insight to determine strategy, allocate resources and set targets Analytic Reporting Predictive Analytics Trending Scenario Modeling • Top down view • Drillable reports • Sort top & bottom • Review then query • Personal exploration • Compare & contrast • Rotate and nest • Work disconnected • Model scenarios • Compare scenarios • Save versions • Uncover patterns • Statistical calcs • Mine data/text • Predict will be” ”What outcomes • Budget Variance • Product ranking • Sales trend analysis • Market analysis • Financial analysis • Profitability analysis • Fraud prevention • Churn analysis ”Drill-Down” ”Slice and Dice” ”What if”
  • 27. The Four Styles of Analysis Line Managers Business Users Financial Analysts Business Analysts Business Managers Executives How are we doing? Why? What should we be doing? Immediate, visual insight into business performance Self-service analysis of trends and patterns Insight to determine strategy, allocate resources and set targets Business Analytics Application Components Dashboards Scorecards Reports Queries Analysis Content analytics Predictive modeling Planning/ budgeting Business Analytics platform Loans Systems Banking Systems HR Systems Marketing Systems Financial Systems
  • 29. Business Analytics Applications Analytic Reporting  Provides full breadth of report types  Delivers consistent information across all types of report output  Can be personalized and targeted  Enables collaboration across users, communities and with IT  Provides access via email, portal, MS-Office, search and mobile devices etc Multi-Dimensional Analysis  Provides guided exploration across multiple dimensions of information  Performs complex analysis and scenario modeling easily and quickly  Gets to the “why” behind trends to reveal symptoms and causes  Moves from summary level to detail levels of information effortlessly
  • 30. Business Analytics Applications Dashboards  Provides at-a-glance, high impact views of complex information  Helps quick focus on issues that need attention and action  Are highly visual and intuitive  Combines information across disparate sources Scorecards  Provides instant measurement relative to targets and benchmarks  Aligns decisions and tactics with strategic initiatives  Supports scorecarding methodologies  Ensures ownership and accountability
  • 31. Scenario Modelling  Model and compare scenarios  Reorganize, reshape  Multiple versions  Financial and profitability analysis  Exploration and „what-if‟ scenario modeling
  • 32. Predictive Analytics is Transformation Technology • Analyzes patterns found in historical and current transaction data • Analysis into attitudinal survey data to predict future outcomes • Enables more proactive decision making, driving new forms of competitive advantage: – How do I predict outcomes resulting from my decisions? – How can I predict demand and allocate resources to ensure I am delivering services effectively? – How can I find the patterns in vast amounts of data?
  • 33. Summary – Business Analytics in Context Planning, Budgeting, Forecasting & Consolidation Analysis & Reporting What happened? What will happen? Report Forecast Single Data Model What is happening? Scorecard Why? Analyze What do I want to happen? Plan
  • 34. Move from “Sense and Respond” to “Predict and Act” Predict and act Velocity Lack of Insight Inefficient Access Volume Sense and respond Instinct and intuition Skilled analytics experts Variety Inability to Predict Back office Real-time, fact-driven Everyone Point of impact Automated Optimized
  • 35. How can Business Analytics address the Key Issues in Credit Unions?
  • 36. Key Business Issues Facing Credit Unions 1. 2. 3. 4. 5. 6. Address Margin Compression Develop a strategy for consolidation Enhance regulatory compliance Prepare for industry transformation Attract new members Leverage IT to improve productivity and profitability 7. Attract, manage and retain top talent 8. Protect your members from fraud
  • 37. Credit Union What ifs… Payments Branch management ... predictive analytics could detect and prevent a wire transfer identified as high probability of fraud? ...could understand which branches or products were performing the best? Executive leaders ...could make better business decisions using accurate data across all time horizons Relationship management ...could consider the risk and profitability of the entire member relationship when pricing new deals? Risk and finance Marketing ...could predict the right offer for the right member at the right time? ...could streamline compliance and understand risk exposure across businesses and regions?
  • 38. The Irony is… • You probably have more than enough DATA to get the answers… • But you can‟t access it, analyze it, or communicate it well enough • You understand people who have already done business with you vs those that have not • “Myth Busting” – many assumptions may not be supported by the data
  • 39. No Shortage of Internal Data Member Data Financial Products - - # of members Demo Information Location Accounts Issue – How to transform it into INFORMATION and ACT on it Revenue Costs Location Accounts Financial Transactions Branch Data - - Deposits/Withdrawals Loan Pmts Interest Members by Brach Revenue by Branch Product Mix by Branch
  • 40. The Data isn‟t always where its needed Executive - Strategic Planning Middle Managers - Management Control Front-Lines - Operational Control
  • 41. The greatest challenge of the computer industry is to learn how to build information bases, not databases. The really important information cannot be easily quantified and exists outside the organization. - Peter Drucker (1993)
  • 42. The Analytics-Driven Credit Union Increase flexibility and streamline operations Optimize enterprise risk management 42 $ Create a Memberfocused Credit Union
  • 43. The Member View How do I retain my best members? Who are my ideal members and how do I attract them? How can I ensure that our pricing is competitive and profitable? What products/services attract mass affluent members? ? How do I find the optimal balance between service and cost of delivery? How can I improve service Why are my marketing response rates so low? How do I make more members highly profitable? 43 levels and the knowledge of my front-line employees? Which are my best performing branches?
  • 44. Member Profitability Analytics  Create profitability analysis and forecasts  Perform “what if?” scenario analytics  Calculate profit and loss (P&L) at the account level  Increase cross and up sell opportunities  Analyze historical information to:  Predict customer propensity to buy  Develop lifetime value models  Create account retention strategies  Develop strategies to improve retention and wallet-share of profitable customers  Reduce servicing costs by matching service levels to customer value
  • 45. Marketing Optimization  Mine historical member information to determine patterns and segmentation  Use predictive models to determine likelihood of response to offers or defection  Generate reports and alerts on customer interactions and portfolios  Incorporate unstructured text data into the analysis to better capture customer sentiment  Predict which customers are likely to leave and what will keep them  Use marketing dashboards to track and monitor response and sales created  Improve marketing cross-sell efforts and reduce execution costs 45
  • 46. Relationship Pricing  Delivers an intuitive, centrally controlled pricing tool that considers complete relationship value and risk to improve pricing consistency for both credit and non-credit deals  Provides bottom-up and top-down planning capability and automated approval workflow  Enables quick changes and consistent roll out with centrally controlled pricing model  Provides dashboards for relationship managers, lending officers and senior management  Enables relationship managers to quickly and consistently evaluate risk and profitability of new business and increases management visibility into lending book
  • 47. Client Servicing  Includes paperless, real-time selfservice reporting and analysis of account holdings and recent activity  Delivers Wealth Manager dashboard with service process monitoring, reporting, analysis and forecasting  Provides online or mobile client statements with portfolio summary, performance analysis and asset allocation  Improves relationship manager knowledge and customer service
  • 48. Risk Management View How do I inform business users about the risk impact of decisions? How do I integrate governance, risk and compliance processes? Could I benefit from fraud detection and credit risk analytics? Can I perform risk scenario analytics? 48 How do I eliminate operational silos to get an enterprise view of risk? How do I operationalize risk appetite? ? How do I respond more efficiently to evolving regulatory requirements? What operational risks can be reduced? How do I ensure that pricing models are risk adjusted?
  • 49. Governance, Risk and Compliance Provides an integrated enterprise risk solution to help reduce risk exposure and simplify regulatory response with a single system of record Enables the identification, management, monitoring and reporting of operational risks and regulatory compliance initiatives, including policy management and IT Improves processes with fully integrated risk and compliance data  Risk control self-assessments  Scenario analysis  Key risk indicators  Loss event database  Policies and regulatory mandates  Harmonized control framework Provides root cause analysis
  • 50. Risk Insight & Optimization  Includes business intelligence to provide finance-integrated, actionable risk dashboards, scorecards, and reporting  Enables risk adjusted financial planning, business modeling, strategy selection and initiative planning  Scenario analysis for all risk classes (credit, market, liquidity, operational, counterp arty)  Risk optimization through risk and finance integration, risk appetite management and communications, strategic planning, and riskadjusted relationship pricing 50
  • 51. The Streamlining View How do I provide better executive visibility into enterprise performance? Where can I cut costs without affecting revenue? ? How do I improve tracking/ monitoring of high-value payments? What branches and relationship managers are my best performers? Why? How do I streamline my financial planning/budgeting process? How do I deliver real-time insight at the point of impact? What’s the best approach for IT cost allocation?
  • 52. Branch Performance Management  Enables driver-based, rolling branch financial planning at the product and customer segment level  Provides staff planning so headcount expenses can be easily understood and controlled  Monitors and analyzes key revenue, cost and profitability measures by branch, product type, product, member segment and even household
  • 53. Payments Monitoring and Analysis  Monitors transactions by counterparty, geography, asset class and transaction type  Identifies trigger events for interventions  Implements governance of key performance measures and targets  Predicts traffic, counterparty weakness and bottlenecks  Builds agile, fully costed plans and forecasts to optimize pricing/chargeback tariffs 53
  • 54. Is there an App for That? (Mobile Business Analytics) -54-
  • 55. Is there an App for that?
  • 56. You‟ve seen the headlines… • Today, over 80% of the Fortune 100 are already deploying or piloting iPad -(NetworkWorld 2011) • “Mobile BI has the potential to significantly expand the population of BI users to include a much more mainstream audience” -(Gartner 2011) • “Forty percent of devices that information workers use to access business applications are personally owned” – (IDC 2011)
  • 57. Why Mobile Business Analytics? • Very broad reach • “Real Time” accessibility of information and decision making • New, immersive experiences and visualizations • New possibilities for Collaborative Business Analytics
  • 58.
  • 59.
  • 60. How to Get Started with Business Analytics projects -60-
  • 61. How to get started with BA? • First and foremost – You need to realize that Business Intelligence is not „Out of the Box‟ unless plugging into ERP or other „Single Application‟ Solution • There is typically design and development work involved • Depends heavily on your data and application mix as well as your objectives/metrics • Invest in “Up Front” planning and “selling” of the project
  • 62. What has to go Right on BA Projects? 1. 2. 3. 4. 5. 6. Executive Sponsorship and Commitment Planning Trust in the Data – Data Validation Proper Roles Change Management Sustainment
  • 64. Plug Into CU Management Process 1. The strategic management process where strategic issues are refined and implications discussed. 2. In the operational management process corrective actions are taken and implications are discussed. 3. In the daily management processes corrective actions are taken. In all three processes, there is an „evidence based‟ or analytics-based review of performance indicators
  • 65. Getting Started with Analytics Projects 1. 2. 3. 4. 5. Start with an Executive Discovery Session Review Business Strategy Build the linkages from Strategy to Measures Determine success indicators Identify process and project fitness – Readiness Assessment 6. Build the scorecard/measurement process 7. Gather Data from Operational Systems 8. Build the Views, Reports, Analyses, and Dashboards
  • 66. Readiness Assessment Asks the following questions: 1. Do you have executive support? 2. Are the goals defined? 3. Can your staff handle the change? 4. Do you have the data needed? 5. Can your systems support BA? 6. Can your IT staff handle this?
  • 67.
  • 68. Avoid Common Pitfalls 1. Lack of Planning You need a map of where you're hoping to go – and the team to get you there. 2. Under-Estimating the Data Access/Validation phases of the project. 3. Lack of Resources – You will need: • Business Expert • Data Expert • Business Analytics Solutions Expert
  • 69. Avoid Common Pitfalls 4. Lack of responsibility. If you are going to make critical decisions on the data in the BA system, you need at least one staff member who takes responsibility to be the „Data Validation Cop' of content. 5. No Change Management. You need to get people prepared for the change in their roles and responsibilities as well as the challenges of having data/results more visible. 6. Lack of Ongoing Sustainment. You need to constantly feed the solution with data and adjust the metrics as the business changes.
  • 70. Interactive Session • Business Analytics – Credit Union Examples • Mobile / iPad Analytics Solutions
  • 73. Follow Up • Brian Beveridge • (204)-775-3500 ext 4602 • Brian.Beveridge@mnp.ca • Shelley Legin • (778)-772-8009 • Shelley.Legin@mnp.ca

Hinweis der Redaktion

  1. Have Fun With ThisBy the by, if you went to our 3 hour workshop on Sunday, this session is a high-level review for you, but we’re better looking.
  2. Scott
  3. Scott
  4. Scott
  5. Scott
  6. Scott