When it comes to high tech, we tend to wear blinders. We rarely look around to see how others succeed. This is especially true with organizations who want to look beyond basic BI and reveal answers to questions they never thought to ask. What would demand forecasting for a CMO in media mean to a CIO in banking? What would Proactive Customer Care in telecom mean to a Chief Revenue Officer at a global retailer? Let's dig into some cross industry use cases that will get you outside your comfort zone and allow you to take a different look at how applications of advanced and predictive analytics can help you act on new insights that transform your business.

1. Good evening!
Make yourselves comfortable for the next few moments because...

2. CROSS INDUSTRY USE CASES IN BIG DATA ANALYTICS @graemeknows

3. Hi. I’mGraemeNoseworthy.
My last namemeans“homesteadjutting out intothe sea.”I’m a
ContentMarketerat IBM Analyticsforthe Communications
Industry Sector.Thisismy2nd timespeakingatPAW.
I’ve beenworking in high-techfor20 yearsand working in the
fieldofbig dataandanalyticsfor 6 years.
You can followme onTwitterat @graemeknows.
When I’mnot working, I’m also:
• Father to the #AdventureMen (mytwo boys)
• YMCA Executive Board Member (secretary)
• Volunteer atYMCA CampTakodah (asummercamp)
• Chaplain ofTrinity Lodge (freemasons)
• Retrofuturist Super Geek (trekkie)
• Drinking too much coffee (cream &sugar)
• Not voting for DonaldTrump. (he’s insane.)

4. Let’s start with the most exciting stuff...
Hold on to your seats.This next slide is amazing.

5. The Legal Disclaimer
• © IBM Corporation 2016. All Rights Reserved.
• The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and
accuracy of the information contained in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this
information is based on IBM’s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for
any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing contained in this publication is intended
to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of
the applicable license agreement governing the use of IBM software.
• References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates.
Product release dates and/or capabilities referenced in this presentation may change at any time at IBM’s sole discretion based on market
opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way. Nothing contained in
these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales,
revenue growth or other results.
• IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion.
• Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a
purchasing decision.
• The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or
functionality. Information about potential future products may not be incorporated into any contract.
• The development, release, and timing of any future features or functionality described for our products remains at our sole discretion.
• Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or
performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in
the user’s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an
individual user will achieve results similar to those stated here.
• If you are actually reading this entire legal disclaimer, you’re either a lawyer or you enjoy text heavy slides. Or both.

6. Point of Clarification:a“usecase”is not a“casestudy.”
I’ll share a few customer stories without all of the boring exciting details.This is NOT an IBM commercial.

7. By now, it should be glaringly obvious...
Big data analytics is here to stay. Like water. And electricity. And email. And... super hero movies.

8. And yet, big data is still like outer space.
It’s massive, on any relative scale, and it can be overwhelming at first.

9. z
CDO/CIOs Line of Business
Data Scientists
& Developers
Needs:
• Self-service applications
• Pre-packaged solutions
• Insights as a service
• New revenue streams
Needs:
• Governance platform
• Data architecture
• Security & privacy
• Tools, talent, technology
Needs:
• Cloud data services
• Open source environment
• IoT foundation
• Red Bull & Pizza
Lead a data-driven
transformation
Deliver new business
outcomes
Innovate faster
and scale securely
Transforming organizationsand industries
Big data analytics reaches every role in every industry. Or… at least, it should.

10. But, much like DarthVader’sstormtroopers...
We tend to keep a narrow focus on our own little piece of the action.

11. LET’S IMAGINETHIS:

12. NOTTHIS:

13. The Advanced Analytics Comfort Zone
Create new
business models
(CEO)
Attract, grow, retain
customers
(CMO)
Transform financial
& management processes
(CFO)
Manage risk
(CRO)
Prioritize IT investment
for innovation
(CIO, CDO)
Optimize operations
(COO)
Systems of
Engagement
Systems of
Record
Systems of
Insight
Fight fraud and
counter threats
(CSO)

14. The AdvancedAnalytics ComfortZone
Create new
business models
(CEO)
Attract, grow, retain
customers
(CMO)
Transform financial
& management processes
(CFO)
Manage risk
(CRO)
Prioritize IT investment
for innovation
(CIO, CDO)
Optimize operations
(COO)
Systems of
Engagement
Systems of
Record
Systems of
Insight
Fight fraud and
counter threats
(CSO)

15. Don’t be a chicken!
There’s nothing to be afraid of.

16. Let’s pause here for a moment:
How would you define your analytics comfort zone?

17. A quickstory from the
IBM Business Connect Summit
inWarsaw, Poland. October 2014.
Global Banking CIO fascinated by Demand Forecasting in M&E? Sure!
Overly excited sales rep? Not so much.
http://bit.ly/1L6v2RP
Did someone say
spreadsheet?

18. Let’s illuminate
some interesting
analytics use cases,
shall we?

19. But, before that, we need to
considerthe scale and reality of
analytics solutions because...

20. There are no magic boxes.
There are no magicians.
There are only ecosystems.

21. OK, bro, let’s get to the use cases.

22. Demographic
data
Transaction
data
Interaction
data
Behavioral
data
In-store
POS
Kiosks
Website
Search
Online
Advertising
MobileEmails
SMS/
MMS
Social
Media
Customer
Service
Call
Centers
Events
Direct
Mail
Kiosks
Transactions
Orders
Payment
history
Usage
history
Purchase
stage
E-mail / Chat
Call center
notes
Web
click-streamsIn-person
dialogs
Opinions
Preferences
Desires
Needs
Characteristics
Demographics
Attributes
USE CASE: Customer of One exeperiencein Retail
The journey is personalized, social and increasingly mobile.
Question:
Does this applyto
your industry?
Point:
Of course it does.
B2B. B2C.
Public.Private.
It’s all H2H.*
http://bit.ly/MnS6hM

23. USE CASE: Financial Counter Fraud Management
It’s not just for insurance and banking anymore.
Question:
Who has to deal
withissues
relatedtofraud?
Point:
WhoDOESN’T
have to deal with
issuesrelatedto
fraud?

24. USE CASE: Driving value through engagementin M&E
Connecting the individual to the experience is the name of the game
Question:
How doyou connect
development to
customer needs?
Point:
We’reway past offline
focus groups and
surveys
(althoughthey’restilla data
source too!)

25. USE CASE: ProactiveCustomerCare
Turning costly call centers into revenue generating centers of excellence
Question:
Do you connect with
your customers on a
1-to-1 basis?
Point:
Wouldn’t you rather
speak to them on a
1-to-many basis?
(BONUS: it’s a hell
of a lot cheaper.)

26. USE CASE: Predictive Maintenance.. beyond the machines
Increasing availability and throughput while reducing maintenance costs? OMG YES PLEASE.
Question:
Are you expected to
meet aggressive
productionand/or
uptimegoals?
Point:
This goes beyond the
manufacturingplant or
the jet engineto, say...
MMPO
videogames?

27. USE CASE: Behavoir Based Fan Insights in Sports
From the sofa to the stadium, there’s more than just a few clicks to what your customers are doing.
Question:
Have you gone past single
source clickstreams to
understand actual
behavoir?
Point:
Customer behavoirs are
comprised of many
different actions at any
time. Can you identify,
measure and predict them?

29. USE CASE: Improving Quality of Experience for mobile
Are you sensing the pattern here? Everything revolves around the customer.

30. Apps are consolidating large
data sets and capabilities
to engage new audiences
Insight from nontraditional
sources of data are being infused
in business processes to create
new business moments
Innovations are composed
leveraging digital services from
a new ecosystem
New channels
and business models
Digital Innovation
at it’s finest
Real time insight
driven processes
USE CASE: Industry disruptors are utilizing IoT
They are recomposing their businesses through data-driven transformation

31. Let’s pause here for a moment:
How do youplan to get outsideyour comfortzone?(hint:talk to each other!)

32. “Go Outside”to gain brand new insights
Analytics is no longer a competitive advantage. It’s a business requirement.

33. IBM ANALYTICS PLATFORM
Discovery &
Exploration
Prescriptive
Analytics
Streaming
Analytics
Business Intelligence & Predictive Analytics
Content
Analytics
Information Integration & Governance
Data
Management
Content
Management
Hadoop
System
Data
Warehousing
Breadth & depth
of analytics
Data integration
& governance
Hybrid & fluid
architecture
Open & unified
platform
Create a new data
foundation that goes
across the business
Prepare data
for advanced
analytics
Predict the future
for the business and
adjust in real time
Align data management
strategy with customer
expectations
Delight customers by
understanding them
better than ever
Derive business value
from unstructured
content
The IBM AnalyticsEcosystem
Proactive. Predictive. Precise.

34. The (even better)Analytics Enterprise
Boldly go where no one (in your organization) has gone before.

35. Let’s pause here for a moment:
So... now whatdo youdo?Read.Attend.Explore.Discuss. Review.Challenge.

37. Please, don’t just take my word for it.
Now is the time when I get to use the word “Harvard” and instantly sound smarter.
http://bit.ly/2ajjIzR
First, be honestwithyourself.
Then, makethe behavioryour own.
Finally, take the plunge.

38. gnoseworthy@us.ibm.com @graemeknowsibmbigdatahub.com
Let’s connect!
You can find me on: