Forward-Looking BI
Fern Halper
TDWI Director of Research, Advanced Analytics
September 9, 2014
@fhalper
2
Speakers
Fern Halper Research Director for
Advanced Analytics,
TDWI
David Clement Product Marketing Manager,
BI and Predictive Analytics,
IBM
Agenda
• Industry trends for predictive analytics
• Use cases for predictive analytics and forward
looking BI
• Getting started
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Predictive analytics
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A statistical or data mining solution
consisting of algorithms
and techniques that can be used
on both structured
and unstructured data to determine outcomes.
Popular predictive analytics techniques
• Decision tree
• Regression
• Clustering
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Classification, segmentation, association
Market trends shaping forward-looking BI
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1. Democratization
2. Consumability
3. New data sources
4. New platforms
New Users Driven By EASE OF
USE
1. Democratizing BI
To extend the deployment of BI and analytics
tools to more users in the organization
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Democratization
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0% 5% 10% 15% 20% 25% 30%
70-100%
50-70%
30-50%
10-30%
<10%
Don't know
70-100% 50-70% 30-50% 10-30% <10% Don't know
Series1 15% 16% 13% 24% 24% 8%
What percent of your organization's employees is using BI and/or analytics tools on any platform?
31%
2. Consumability
Able to be used…
More accessible results…
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Ease of Use
• Point and click visualization
• Software suggests models
• Collaboration/Sharing
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Easy for Individual
The business analyst will build models
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(source: TDWI 2014 Best Practices Report on Predictive Analytics)
Embedded Predictive Analytics
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An example:
model
3. Data sources evolving
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72%
76%
61%
4. Platforms are becoming popular
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The Result
• Platforms offered:
– Relatively easy to use
– Incorporate disparate data types
– Extend the functionality of BI to predictive
analytics
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Use case 1: Predict product levels
• Reactive: Tracking product purchases
To
• Proactive: Predicting product inventory
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Reactive to proactive
• Reactive:
– Query to produce
reports and
dashboards
• Proactive
– Predict product levels
– Optimize inventory
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Use case 2: Predict churn
• Reactive: Knowing when customers drop a
service
To:
• Proactive: Predicting when a customer will
drop a service
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Reactive to proactive
• Reactive:
– Query: Number of
customers dropped per
month
– Query: Dollars lost per
year
• Proactive
– Outcome of interest:
Dropped vs. Retained
– Characteristics of
customers with that
profile
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Use case 3: Identify fraud
• Reactive: Knowing how much fraud is
happening
To:
• Proactive: Predicting when fraud will occur
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Reactive to proactive
• Reactive:
– Query: Dollars of
revenue lost
– Query: Number of
fraud attempts
– Query: Number of SIU
cases per year
• Proactive
– Outcome of interest:
• Fraud vs. No Fraud
– Characteristics of
customers with that
profile
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Getting Started
• Pick a project with a metric
• Develop a POV
• Build your skills
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Poll Question
• Are you performing predictive analytics today? – Yes, we are doing this today
– No, we are not doing this today, but are planning to do it this year
– No, we haven’t even started our predictive analytics efforts yet,
but we’re interested in predictive analytics
– No plans
– Don’t know
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© 2014 IBM Corporation 24
Predictive Business Intelligence Forward-Looking Business Intelligence Predictive Business Intelligence Forward-Looking Business Intelligence
© 2014 IBM Corporation
Forward-Looking Business Intelligence
Know the past, understand the present,
shape your future
David Clement
IBM BI and Predictive Analytics
Product Marketing Manager
@DWClement
© 2014 IBM Corporation 25
Predictive Business Intelligence Forward-Looking Business Intelligence
Key trends are fueling the need and urgency for analytics
The emergence of big data analytics
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35% of businesses use big
data for business
advantages.
Increasing consumer expectations
2
84% of consumers rely on
social networks for
purchase decisions.
Accelerating pressure to do more with less
3
32% is the higher return on
invested capital for
those organizations
using advanced
analytic software.
© 2014 IBM Corporation 26
Predictive Business Intelligence Forward-Looking Business Intelligence
Challenges faced by business units
“We need to understand why
events are happening within our
operations and allow managers to
respond faster.”
“We need to better measure
business risk and reduce losses in
order to provide superior pricing
and increase profits.”
“We need to understand our
customers and prospects as a whole
and at the individual level to better
target our services and products.”
© 2014 IBM Corporation 27
Predictive Business Intelligence Forward-Looking Business Intelligence
With business intelligence and predictive analytics from IBM, transform data into useful
insights. Help make confident decisions and improve operational efficiencies with historic,
current and predictive views of your business.
Predictive analytics enhances the value of deploying BI reports, dashboards
and scorecard capabilities across the enterprise with visibility into your
businesses past, present and future
Leverage data: Analyze information in any volume, combination and complexity
Provide insights: Use a trusted platform for
delivering forward looking business information
Make confident decisions: Complete
visibility into your business with
predictive analytics
Outperform expectations: Transform your business from a reactive operation to a proactive market leader
© 2014 IBM Corporation 28
Predictive Business Intelligence Forward-Looking Business Intelligence
• Understand the past and current state of your business, as well as future outcomes and their drivers
• Model your existing historical data to give you a guideline for future business behaviors
• Optimize business outcomes by tying predictive measures against
operation processes
• Deploy forward-looking business intelligence information on
desktops, browsers and mobile devices
• Provide users of different skill levels with the analytical capabilities
that can satisfy the needs of self-service data analysis
• Share results broadly from within a single BI interface,
extending data-driven insights across departments and into
frontline applications
This solution is designed to:
Forward-looking business intelligence from IBM helps you
overcome these challenges by validating business goals and reducing
the risk of bad decisions
© 2014 IBM Corporation 29
Predictive Business Intelligence Forward-Looking Business Intelligence
• IBM® Cognos Business Intelligence
• IBM® SPSS Modeler
• IBM® SPSS Statistics
• IBM® SPSS Collaboration and
Deployment Services
HCDE enhances student attendance, behavior and performance by turning big data into insight
13.6% increase in graduation rates since solution was implement
Solution Components
Business Challenge: HCDE had already taken the first steps in understanding the
signs that a student is at risk of under-performing – or even dropping out of the
school system completely. Now, it wanted to transform its ability to deliver this
information to teachers, social workers and others – giving them the right data to
make daily decisions that will help their students achieve a brighter future. The
Solution: HCDE chose to build on its existing predictive analytics solutions by
enhancing its reporting capabilities using business intelligence.
“We see analytics as an ongoing journey. We are constantly working to introduce
new capabilities. The first phase was predictive modeling of student performance.
Then we moved on to giving all 3,600 teachers and administrators access to that
student performance data via dashboards on their iPads or Android tablets. And
now we’re using text analytics and data mining techniques to look at professional
development too.”
- Dr. Kirk Kelly, Director of Accountability and Testing at HCDE
Top 5% in the Tennessee school systems
for performance
Top 10% in the Tennessee school systems
for progress, growth rate
© 2014 IBM Corporation 30
Predictive Business Intelligence Forward-Looking Business Intelligence
• IBM Cognos® Business Intelligence
• IBM Cognos TM1®
• IBM SPSS® Modeler
Elie Tahari harnessed predictive technologies to match production with customer demand
<2.5% The variance between
predictions and actual
items sold
Solution components
Business Challenge: Assembling the information needed to make key decisions
was an arduous and time-consuming task. For store replenishment decisions, the
lack of granularity in the reports made it impractical for managers to fine-tune the
product and size mix they shipped to each customer or outlet based on differences
in sales patterns from store to store or region to region.
The Solution: Business analytics tools now provide real-time insight, predictive
analysis, and detailed planning capabilities. Predictive analytics enables highly
accurate production planning, lower-cost logistics and more efficient inventory
management
“The ability to look four months into the future and know what our inventory levels
need to be on a weekly basis is absolutely key to our success... It allows us to
adjust production to a level that reduces our exposure and still gives us the ability
to supply our customer with close to 100 percent of their orders."
—Nihad Aytaman, director of business applications, Elie Tahari
30% The reduction in logistics costs
when addressing product shipping
Reduce risk Monitor production and inventory,
reducing exposure while
maintaining orders
© 2014 IBM Corporation 31
Predictive Business Intelligence Forward-Looking Business Intelligence
Why IBM?
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Unified workspace: Forward-looking business intelligence provides
a single vendor solution that integrates world-class capabilities
Integration: Forward-looking business intelligence provides optimal
data integration between past views of data and marketplace-leading
predictive technologies
Analyze relevant data: Forward-looking business intelligence
provides simple interfaces to ease the process of exploring all data
Platform: A purpose-built enterprise-class platform supports robust
metadata capabilities, advanced security and the ability to plug in
new solutions as the business grows and the needs of
users mature
© 2014 IBM Corporation 32
Predictive Business Intelligence Forward-Looking Business Intelligence
What to consider next: Visit AnalyticsZone.com and take a look at our Communities page • Try trial versions of our software in our predictive community • Learn about your analytics quotient in our Analytics Center of Excellence (ACE) community • Check out the extensive set of visualizations that come with IBM Cognos 10 – look at our
Visualizations community
© 2014 IBM Corporation 33
Predictive Business Intelligence Forward-Looking Business Intelligence
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Thank you.
© 2013 IBM Corporation
Turn your BI challenges into opportunities.
See how at the IBM Virtual Business Analytics Summit 2014!*
• Learn how to transform your organization with powerful, agile analytics.
• Attend insightful sessions including a key note presentation with Mark Smith, CEO
& Chief Research Officer at Ventana Research.
• Explore the latest business intelligence and predictive analytics software.
• Hear customer success stories, and network with peers.
Wednesday, October 1, 2014
11 AM to 2:30 PM ET
Register today! https://ibm.biz/BdFrHJ
*All attendees will receive a newly published Ventana Research Paper: Advanced Analytics
Enhances Business Intelligence—Robust New Technology Enables Better Decision-Making.
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Questions?
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Contact Information
• If you have further questions or comments:
Fern Halper
David Clement