Recap: Insight 2014 Day 1 General Session

I’m following the Insight Conference from home this year, but am going to still keep up with recaps of the general sessions, as I have done in past years.  If you want to do the same, head on over to InsightGO for access to the live stream and more.

Insight 2014 Day 1 General Session:  Seize This Moment – Transform Your Industry

Bob Picciano, SVP, Information and Analytics Group

  • Data is the what, cloud is the how, and engagement is the why
  • Over 4.5 quintillion bytes of data are being created every day.  Twice as much as just two years ago.
  • “Generation D” enterprises are 3x more likely to excel at developing insights regarding customers and markets
  • 136% growth of marketing analytics jobs over the past three years.
  • When data moves to the center of your business, that’s when real value is created

Q&A with Larry Volz, VP and CIO, Pratt & Whitney

  • Expect predictive and real time analytics to change everything across value chain at Pratt & Whitney.
  • Get a lot of data from engines – initial build, maintenance, on-wing measurements.  Up to recently looked at it for descriptive data, but it wasn’t really analyzed.  Had some indication of health, but was like looking in rear view mirror.  Transitioning with IBM partners to look ahead and be predictive regarding engine health.  Ability to look at an event that might cause delay or cancellation is an evolutionary capability.
  • On health side, looking at fuel burn analytics.  Tailoring work scopes by segmenting flight data.
  • Goal is optimizing customer’s in flight experience.
  • Looking at how can go after disruptions in supply chain.  Schedule assurance and product quality.  
  • It is a big shift from descriptive to predictive model.  Not just IT event.  Need to re-engineer business processes.  Had strong commitment from senior leadership team to make this shift.  IT team working with both IBM and internal business partners to get this launched.    
  • In order to get to opportunities quickly, needed accelerator to help on journey.  Needed someone to help accelerate move from descriptive to predictive.  Looked at all companies in the field, and IBM stood out as richest and deepest big data expertise in industry.

Deepak Dodani – CEVA

  • World class set of supply chain solutions in freight management and contract logistics.  (If you buy a TV on Amazon, CEVA is behind it.)
  • Underneath all processes, have platform that allows them to integrate supply chains for complete control of supply chain visibility.
  • A lot of unstructured content to deal with.  Order forms, bills of lading, etc.  
  • Undergoing a strategic move to utilize cloud based services in platform.  When it came to ECM, chose IBM Navigator.  Allows to expand cloud based services portfolio.  Gives leg up on predictive analysis and run business proactively.
  • Advice on moving from on premises to cloud:
  • Plan taxonomy before move the content.  Get the data hierarchy there early.
  • Get document retention policy at enterprise level drafted and approved.  

Bob Picciano – Cloud
People moving to cloud for agility, innovation, new business models.

Generation D:

  • Data-rich, analytically driven enterprises are 1.8x more likely to use cloud for data management
  • 1/2 of leaders deliver big data and analytics initiatives significantly through cloud
  • 80% are or will be leveraging public cloud for Big Data Analytics projects

Examples of companies using Cloud for big data and analytics

  • SunLife Stadium (Miami Dolphins) – Uses Softlayer to improve fan experience
  • Webster Bank – IBM Security to prevent fraud
  • Akamai – Cloudant to rapidly deploy application environment
  • DXL – retailer uses cloud-based incentive compensation

Marcus Hearne, Watson Analytics demo – Insurance marketer
(If you want to just watch the demo, fast forward the replay to around the 50 minute mark)

As a marketer, importance is:
Using analytics
Time to insight
Actionable insights

  • Solution is “walk-up intuitive”
  • Start with seeing an average data score for the data uploaded to the system, and Watson Analytics has identified some areas where could automatically clean it up further
  • Customer Value Analysis:
  • Watson Analytics provided suggested analyses that can run.
  • Or, can type in question in plain language.
  • “What is the rate of customer responses to my campaigns and offers?”
  • Will come up with suggested analysis as a result of the question that typed in.
  • Automatically returning visualization for the results that are generated
  • Can further refine data himself (e.g., only married people, rural vs. urban locations)
  • Can also customize the results (e.g., instead of responses, can look at employment status) and will change visualization on the fly.
  • Can drill into the top offer by State.   Will continue to make visualization updates (e.g., switch from line graph to map view.)
  • Drill further to see which policy type responds the best
  • Switch to “Predict and Explain” views
  • Which customers will have the best customer lifetime values?  
  • Can have it suggest the most predictive model possible – automatically combining multiple fields.
  • Then can drill into decision tree to view the customers step by step – understand what is leading to the highest value (e.g., while lifetime value is linked to having multiple policies, it doesn’t mean that the more is better – 2 policies is the magic number.)  Returns specific results so that can tailor marketing investment to where it will have the biggest marginal value.  (e.g., first invest in one area, then if have left over funds go to the next highest value).

Inhi Cho Suh, VP Big Data, Integration and Governance

Announcing IBM DataWorks

  • Business analysts get relevant data inside their applications
  • Application developers embed data services inside applications
  • IT enables self-service data access for all.

Dash DB – agile data

  • Easy to add data refinement to app
  • IT/Data Engineer can deploy warehouse himself.
  • Probabilistic matching

Watson Curator

  • Improve the relevance and governance of content collections
  • Increase user confidence in the quality of information sources in content collections
  • Integrated governance to improve and defend Watson responses

Can get started today with IBM DataWorks, IBM dashDB, IBM Cloudant, IBM Watson Curator.

Ian Story – IBM Navigator Demo, running on Softlayer
Navigator – Simplify file sharing for business users everywhere

  • Collaborate on content securely
  • Easy to use on any device
  • Extend applications with open APIs

Updating script Bob Picciano wrote for House of Cards, only it accidentally reads “House of Cars” instead of “House of Cards”

  • Can search content in repository for certain word (“car”)
  • Can check out content to desktop, fix it, and then check it back in.
  • All the metadata is there.
  • Can open Navigator app on phone, and there is the latest version of the file, available on phone.

Critical inflection point – either your part of the Generation D leaders, or you’re lagging behind.
A question for you:  Are you ready to seize this moment?

Client story video

  • Macy’s – Want customers to be able to shop online, on phone, or in store
  • Banorte – Want to talk to a segment of one.  A personalized bank for each customer, made with data

Bridget van Kralingen, SVP Global Business Services

  • The quest for personalized engagement: Customers expect personalized experiences
  • Intersection where big data meets personalization
  • Arrival of long awaited market of one is finally here, but that’s just stopover on way to real destination
  • Consumerization of experience for professionals and individuals in all industries
  • Example:  Imagine flying from Paris on flight that is running late, and flight crew can walk down aisle with mobile device with live access to each passenger’s itinerary so can rebook them before they land.
  • The info on individuals is the most valuable data any organization can have.  And need to provide access to that to get value.  This will be the new ERP.
  • The market of one is a way station.  Engaging that segment of one at level of action is the goal.  To get there, need to be very precise in how think about it.  Design and engagement are related but not the same thing.  Engagement is complete experience, and is dependent on astute use of data and analytics, in context.
  • Immersive – relevant, contextual and immersive.  Infuse physical world with digital interactions of all kinds.
  • Speed – Battles are won or lost in seconds
  • Tolerance for waiting is so much shorter than it used to be
  • Apple + IBM Partnership
  • Focusing on apps that are built for mobile, not a desktop app retrofitted
  • Targeted for specific industries and uses

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