What's New in Predictive Analytics IBM SPSS
- 1. What’s New in IBM Predictive Analytics
IBM SPSS & IBM Decision Optimization
Fuel for the Cognitive Era
Jane Hendricks, Portfolio Marketing Manager, IBM SPSS Predictive Analytics
Ioannis (Yianni) Gamvros, WW Technical Sales Leader, IBM Decision Optimization
- 2. Session Topics
Analytics in the Cognitive Era
IBM Advanced Analytics
Conceptual Overview
Product Alignment
Key New Features
IBM SPSS Predictive Analytics
IBM Decision Optimization
Demonstration
Next Steps
Q&A
- 4. Analytics Driven Organizations Reap Rewards
Business outcomes
(69%)
Revenues
(60%)
Competitive
advantage
(53%)
Front Runners outperform on
Source: IBM Institute for Business Value (IBV)
by using data and analytics
- 5. Breadth of analytic use,
as reported by respondents:
In 2014,
10%
of organizations were
using advanced analytics
in three or more
functional areas of their
business
In 2015,
71%
of organizations are using
advanced analytics
in three or more
functional areas of their
business
and
33%
of organizations are using
advanced analytics
in six or more
functional areas of their
business
Advanced analytics are defined as the extensive use
of predictive, prescriptive or cognitive analytics within a business function
Organizations have rapidly expanded the use of advanced
analytics across business functions
Source: Analytics: The upside of disruption. IBM Institute for Business Value 2015 Analytics research study.
© 2015 IBM Institute for Business Value.
- 6. IBM Advanced Analytics Today
Data
Preparation
Analytics at
Scale
Insight to
Action
ALL Data
(Structured, Unstructured,
Streaming)
All Decisions
(People, Systems,
Strategic, Operational,
Real-Time)
• Predictive models
• Machine Learning
• Statistical Analysis
• Decision Optimization
• Real-Time Scoring
• Optimized Decisions
• APIs & services
• Dashboards / Interactive
apps
• Data models
• Data connectors
• Data Wrangling
Analytic
ServerModeler CPLEX StudioStatistics
IBM® (SPSS®) Predictive Analytics IBM® Prescriptive Analytics
Decision Optimization
Center (DOC)
DOCloud
- 7. Torchbearing CEOs look to predictive analytics in a changing
business landscape
More digital interaction
More competition expected
from other industries
82%
60%
60%
40%
Business landscape changes (in 3 to 5 years)
+37%
+50%
2015
2013
2015
2013
Insights from IBM’s Global C-suite Study – The CEO Perspective
ibm.com/csuitestudy
66%
50%
Use Predictive Analytics
Market Follower CEOsTorchbearer CEOs
more
32%
- 8. Predictive analytics can use virtually any data to
improve virtually any decision
Donor
management
Fraud
detection
Student
success
Sales
forecasting
Employee
turnover
Insurance
claims fraud
Cross-sell
and upsell
Customer
retention
- 9. Oak Lawn Marketing, Inc. employs a predictive analytics solution
to understand customer buying patterns and to target infomercials
Fourfold increase
in total revenue expected over a
three-year period as a result of
infomercials and other campaigns
Targets marketing
messaging and campaigns to
enhance the customer
experience and encourage
retention
159% boost
in the average monthly rate of
customers who return to shop
compared to the previous year
Solution components
• IBM® SPSS® Modeler
• IBM Training
• IBM Business Partner AIT
Business challenge: Although Oak Lawn Marketing, Inc. was gathering and
generating enormous amounts of data about its programs, the company couldn’t
conduct a thorough analysis of customers’ buying patterns using its outdated
business intelligence tools or unwieldy spreadsheets. Oak Lawn Marketing
needed a predictive analytics solution that would accurately portray and predict
customers’ buying trends and help it drive marketing campaigns.
The smarter solution: The solution combines predictive analytics, rules,
scoring and modeling algorithms as it analyzes transactional and demographics
information to help Oak Lawn Marketing understand which products customers
are most likely to purchase and to guide the company in its decision-making
processes. Using this information, the company can customize its multitude of
infomercials with messaging appropriate for various TV channels and time slots
and tailor other marketing campaigns, such as Internet and direct mail.
“We want to establish a brand that is used by our customers over a long period
of time.”
—Harry Hill, president and chief executive officer
- 10. • IBM® PureData™ System for
Analytics (powered by Netezza®
technology)
• IBM SPSS® Collaboration and
Deployment Services
• IBM SPSS Modeler
• IBM SPSS Modeler Desktop
• IBM SPSS Modeler Server
• IBM Training: SPSS
80% reduction
in serious accidents among
trucking company customers
Solution Components
Business Challenge: To meet customers’ demands, FleetRisk Advisors needed
to extract even deeper predictive insights regarding truck driver safety from an
ever-growing range of measured parameters and get it done faster so that
customers would have the time to take truly preventive action.
The Smarter Solution: For each of the company’s customers’ truck drivers, a
powerful new predictive modeling solution translates some 4,500 data elements,
from a diverse and ever-growing range of sources, into quantitative risk ratings
related to the likelihood of on-the-job accidents, giving operators the cue they
need to intervene proactively to prevent such accidents and to save lives.
“Our new solution has enabled us to push the boundaries of predictive risk
analysis, which has translated into real value for our trucking operator customers
that rely on it.”
—Patrick Ritto, chief technology officer
20% reduction
in the incidence of minor
accidents
30% increase
in driver retention rates, with
commensurate decreases in
recruiting and training costs
FleetRisk Advisors helps trucking operators prevent more
accidents by building stronger and faster risk prediction models
- 11. What’s New in IBM SPSS Predictive Analytics
Empower
every user
Unlock
more data, faster
Ground to Cloud
deployment options
Code optional, open
to open source
Big Data for the
desktop
Predictive
everywhere
- 13. Uncover the Value of the Silent Data Majority
80% of data is unstructured; therefore, invisible to
computers and of limited use to business.
By 2020, 1.7MB of new information will be created
every minute for every human being on the planet.
Incorporate GeoSpatial Data
Text Analytics with
Sentiment Analysis
Entity Analytics
Massively Parallel Algorithms
…delivered to your desktop!
- 15. Code-Free Deployment at Scale: Activating Analytics
Parallel In-Database
Optimized for Big Data environments
Reduce network traffic
Improved processing speed
Reduce data movement SQL pushback
Optimize performance with in-database
adapters
Increase analytic flexibility with in-database
mining
Advanced Model Management
(including A/B Testing, Champion/Challenger)
In-Database/In-Hadoop
Batch/Real-Time/Streaming
Point of Impact
(Analytical Decision Management)
- 16. Ground to Cloud: Deployment Flexibility
• Full breadth of analytical
capabilities
• Collaboration and
enterprise-wide best
practices
• Customize for (virtually)
any use case
• On-premises, hybrid and
software-as-a-service
LOB &
Personal
Analytics
Developer
Tools
• Analytic tools built for
business
• Digitally delivered, digitally
fulfilled
• Variety of licensing and
packaging options
• Available for Windows or
Mac
• Build smarter data
applications -- quicker
• Endless possibilities
• No installation, no
configuration
• Mix & match components
Enterprise
Analytics
IBM SPSS Modeler Gold
IBM Cloud Marketplace
(SPSS & DOCloud)
IBM Predictive Analytics on
Bluemix
- 17. Predictive Analytics on BlueMix
https://www.ng.bluemix.net/docs/#services/PredictiveModeling/index.html#pm_service
- 18. IBM SPSS & Decision Optimization in Marketplace
https://www.ibm.com/marketplace/cloud/us/en-
us
- 19. Open Source and IBM Predictive Analytics
First R, then Python,
now Spark
Make coding optional
FacilitateEmbrace Extend
Make it massively
useful
- 20. Extend Capabilities through Open Source: R
R Integration
R Build/Score, Process and Output node support
Scale R execution by leveraging database vendor
provided R engines
Custom Dialog Builder for R
Provides the ability to create new
Modeler Algorithm nodes and dialogs
that run R processes
Makes R usable for non-programmers
- 22. NEW! Python for Spark
Data Scientists can create extensions for
novice users to exploit R, MLlib algorithms
and other Python processes
Spark & its machine learning library
(MLlib)
Other common Python libraries
• e.g.: Numpy, Scipy, Scikit-learn,
Pandas
Abstracting code behind a GUI makes
Spark usable for non-programmers
- 24. IBM Decision Optimization for Python
Model & solve optimization
problems writing pure
Python
Notebook ready.
Community-based
documentation and samples
Solving on cloud or
locally is invisible to
APIs*
Access the
Technology Preview at :
pypi : docplex
Github : docplex
IBM market leading Decision
Optimization technology,
CPLEX, is now accessible as a
Pure Python package
under the
Apache license
(*) Solves the same program for free with IBM DOcloud free trial subscription or
IBM CPLEX Optimization Studio Community Edition installation
- 26. Beyond Predictive
Capture
price,
product,
location and
date for each
transaction.
Historical
& Master
Data ETL
Determine
important
variables,
predict trends,
seasonality
etc.
Predictions
and Insights
Allow multiple
users to
experiment with
multiple
scenarios.
Collaboration
& What-if
Set policies,
promotions
etc. Allow
reviewers and
auditors to
have a say.
Rules &
Process
Managemen
t Automatically
generate
decisions, allow
user interaction
with decisions.
Decision
Making
Key steps for a mature decision support application leveraging
advanced analytics
Descriptive
Predictive
Prescriptive
- 27. Advanced Analytics Solutions Documented Value
2 Chilean Forestry firms Timber Harvesting $20M/yr + 30% fewer trucks
UPS Air Network Design $40M/yr + 10% fewer planes
South African Defense Force/Equip Planning $1.1B/yr
Motorola Procurement Management $100M-150M/yr
Samsung Electronics
Semiconductor
Manufacturing
50% reduction in cycle times
SNCF (French RR) Scheduling & Pricing $16M/yr rev + 2% lower op ex
Continental Airlines Crew Re-scheduling $40M/yr
AT&T Network Recovery 35% reduction spare capacity
Grantham Mayo van
Otterloo
Portfolio Optimization $4M/yr
Source: Edelman Finalists, http://www.informs.org or http://www.scienceofbetter.org
- 28. Uncertainty is everywhere …
Each planning cycle is
afflicted by future
uncertainties - prices,
demand, supply,
weather effects…
We get caught in a costly reactive cycle where we fix issues after the fact, instead of
anticipating and planning for them.
We don’t have a
clear vision of
possible future
scenarios, and their
effect on plans.
Plans are out of
date as soon as
they are created
- 29. A new approach to planning
Contingency Planning
Create multiple scenarios
using averages
Evaluate each as a separate
what-if
Pick a conservative scenario
and act conservatively
Robust/Stochastic Planning
Create multiple scenarios
using confidence intervals
Create a single plan of action
that balances all tradeoffs
- 30. Benefits – stability, profit
Supply chain planning for a motorcycle vendor
2% increase in profits vs. deterministic optimization
Inventory optimization for IBM Microelectronics Division
Greater than 7x increase in feasibility vs. deterministic
optimization
Energy cost minimization for Cork County Council
30% value-add in cost reduction vs. deterministic optimization
Leakage reduction for Dublin City Council
10 times increased stability vs. deterministic optimization
- 31. One of the Largest North America Logistics Companies
Size of operations:
Over 15,000 loads per day
Over 10,000 trucks and drivers
Over 30,000 trailers
Over 150 facilities world-wide
Looked at intermodal operations and resource placement across 2014
Key challenge is to ensure enough resources are allocated to rail yards on a
weekly basis
Allocating 50 trailers to Chicago when only 30 are needed
Allocating 100 trailers to New York when 150 are needed
Repositioning resources takes time and costs money
- 32. Latest Comparison
Start
12 instances
1st of every
month
20 day horizon
Deterministic
Single existing
forecast
Stochastic
Create multiple
forecasts by
varying demand
forecast by +/-
10%
Deterministic
Make decisions
based on single
forecast
Stochastic
Make decisions
based on multiple
forecasts
Deterministic
Compare with actual
demand realization to
determine revenue
and cost
Stochastic
Compare with actual
demand realization
to determine
revenue and cost
- 33. Taking Uncertainty Into Consideration
-0.1%-20% improvement
~5.1% on average
~$23.9M annually
~$1.3M
on average
over 20 days
- 36. Please contact us for further information:
Phone: 800-543-2185
E-mail: salesbox@us.ibm.com
Website: www.ibm.com/tryspss