predictive analytics roadshow

© 2015 Software AG. All rights reserved.

PREDICTIVE ANALYTICS

OVERVIEW

© 2015 Software AG. All rights reserved.

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THE ANALYTICS SPECTRUMALL ANALYTICS ADD VALUE BUT ANSWER DIFFERENT QUESTIONS

Difficulty

Value

DescriptiveWhat

happened?

PredictiveWhat will happen?

DiagnosticWhy did it happen?

StreamingWhat is

happening?

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STREAMING ANALYTICS AND PREDICTIVE ANALYTICS

…while they can still change the outcome

BOTH TECHNIQUES COMPLEMENT THE OTHER

Predictive Analytics allows organizations to build models that represent patterns of behavior

Streaming Analytics uses these models to enable organizations to respond intelligently

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PREDICTIVE ANALYTICS FOUNDATIONS

All predictive analytic methods and models are based upon one common premise:

What has happened in the past will likely happen again

So once we learn from the past, we know what to look for in the future

And all of this is driven by the data itself, so:

The more data you have, the more you need Predictive Analytics

A FEW SIMPLE PRINCIPLES MAKE THIS POSSIBLE

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BUILDING A PREDICTIVE MODEL

Primarily, we are looking for whether a relationship exists between two variables

THE DATA DRIVES THE INSIGHTS

Dark Clouds Clear sky0

20406080

100

77

17

UNEven DIS-TRIBUTION

% did it rain

There is a likely relationship between dark clouds in the sky and whether it rained

Monda

ys

Tuesd

ays

Wed

nesd

ays

Thurs

days

Friday

s

Saturd

ays

Sunda

ys0

20

40

60

23 22 22 24 23 24 26

EVEN DISTRI-BUTION

% did it rain

No relationship between the day of the week and whether it rained

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BUILDING A PREDICTIVE MODELTHE LOGIC CAN BE SIMPLE OR COMPLEX

An example of a decision tree showing whether it is likely to rain

8 |Time

BusinessValue

Business event

High valueresponse

Time to act

Low valueresponse

Forrester Research calls this “perishable insight”

TIME VALUE OF DATATHE LONGER THE REACTION, THE LOWER THE VALUE

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PREDICTIVE ANALYTICS IN USE TODAY

Entertainment: recommendations suggest new movies based upon your viewing history

– Leverages your tastes and the tastes of others like you

ALGORITHMS ARE ALL AROUND US

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Finance: consumer credit scores model the likelihood of your paying the loan back– Models your probable behavior based upon the defaults of many, many others


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Health: heart monitors warn of undiagnosed heart problems– Watches for known pulse irregularity patterns


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THE BUSINESS VALUE OF PREDICTIVE ANALYTICS

Fraud detectionBank detects unusual spending pattern on your card Retail

Making relevant offers at the right time

Predictive MaintenanceDiagnosing a failing pump

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SMART LOGISTICSSUPPLY CHAINS CAN RUN MORE EFFICIENTLY

• Enable shippers to plan activities efficiently in the harbor

Objective

• Change Transport Mode or lane

Automated action

• Arrival time

• Route failure prediction

Predictive Analytics

• Position, Status, ETA

Always On Analytics

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SMART STORE MONITORINGMERCHANTS CAN MAXIMIZE REVENUE

• Traffic density

• POS data

• Shelf sensors

Always On Analytics

• Increased revenue

• More effective merchandising & service

Objective

• Proactive staff re-deployment

• Offer updates

Automated action

• When offers adjusted

• When queues appear

• When shelves need replenishing


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PREDICTIVE MAINTENANCEFIELD SERVICES CAN PREVENT OUTAGES

• Real-time conditions

Always On Analytics

• 99.999% uptime

• Increased 1st Call Repair Rates

Objective

• Technician Dispatch

• Field Service Automation

Automated action

• Failure prediction

• Remaining useful life of components


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PREDICTIVE MAINTENANCE EXAMPLEPREDICTIVE ALERTS ALLOW MORE TIME TO REACT

CLEAR SIGNAL LEADING UP TO FAILURE…

– But reliant on human intuition to interpret in real time?

CONDITION MONITORING CAN ALERT ON THRESHOLDS:

– Tells you something might be wrong, but not what or how urgent

– Ignores machine-specific differences

Condition Monitoring Alert

Predictive Alert

Visual Identification

FAILURE

TIME $

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OPERATIONALIZING PREDICTIVE ANALYTICSREAL-TIME PREDICTIONS NEED TO BE EASY TO DEPLOY

Data-bases

Event Feed

Event Feed

Event Feed

Actions

Alerts

Notifications

ApamaApplications

Dev

elop

men

tR

untim

e

PMMLPredictive

Models

DataManagementApplications

USE CASES ANDCUSTOMER EXAMPLES

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SOFTWARE AG USE CASES FOR PREDICTIVE ANALYTICSSolution Industries Predictive Use Cases Enhancement Core

EnablerPredictive Maintenance • Manufacturing • Failure Prediction

• Remaining Useful Life x

Connected Customer

• Retail• Hospitality• Financial Services• Telecom

• Next Best Offer• Churn Detection• Queue Prediction• Path Analytics• Facial Recognition

x

Smart Metering & Manufacturing

• Utilities• Manufacturing

• Electricity Theft Detection• Quality Anomaly Detection x

Smart Logistics • Logistics• Manufacturing

• Route Failure Prediction• Arrival Forecasting x

Fraud Detection • Financial Services• Retail • Probabilistic Models x x

PARTNERING

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THE SOFTWARE AG STRATEGY

• Partnering with organizations with data science skills– This stuff isn’t impossibly complex– But it does need specialist modeling skills

• We are building on the Software AG platform– Gives us a fantastic integration message– Includes new OEM components such as Predictive Analytics for Apama– Along with components we resell such as KNIME and Predixion

• Open approach means we can work with the customer’s preferred modeling tools

© 2015 Software AG. All rights reserved. For internal use only

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GO-TO-MARKET OPTIONS BY CUSTOMER TYPE

Standardized on SAS/SPSS/etc

Export models in PMML and execute via

Apama

No preferred tools yet, R

Propose KNIME or Predixion as

a platform

Willing to build DS skills

Offer KNIME’s or Predixion’s

simple, graphical

approach along with trainings

Unwilling to build DS skills

Introduce services

partners like Mosaic

Customer has in-house data science skills

Customer does not have in- house data science skills

OPPORTUNITY BRAINSTORMING

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MARKET OPPORTUNITY

• Streaming Analytics worth $2 billion* by 2020 (Markets and Markets)

• Predictive Analytics worth $7 billion by 2019 (Transparency Market Research)


PREDICTIVE ANALYTICS IS EVEN BIGGER THAN STREAMING

*Arguably, the value of streaming analytics has been underestimated as predictive analytics drives growth of streaming analytics Transparency Market Research © 2012

Market size by type of application:

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HOW TO SPOT AN OPPORTUNITY

Anywhere where an organization could benefit from knowing an event is likely to happen before it happens!

– Are they using SAS, SPSS, or R?– Are they using Apama?– Do they have a Big Data initiative?


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ACCOUNT DISCUSSION


predictive analytics roadshow

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