Decision Management Solution Blog
IBM Big Data & Analytics: Watson and Cognitive Computing
Continuing the IBM Big Data and Analytics event we come to Watson. Watson is designed to understand natural language, human-style communication. Watson then trawls through a potentially very large amount of material to create and score some hypotheses as answers for these questions and returns them. With each interaction it also learns what works, what the better answer is. IBM has been commercializing Watson through their transformation plays where they work with large numbers of companies to try and solve big problems, by selling it to their enterprise customers and through the Watson Ecosystem where they have some thousands of use cases submitted and under development.
Watson’s ecosystem includes the Watson Developer Cloud, the Watson Content Store where IBM is adding new content sources to the pool and the Watson Talent Hub with subject matter experts. The Watson Content Store is being driven both by IBM and by requests from partners. The content is focused in di
IBM Big Data & Analytics: Transform adoption with cloud
Cloud, says IBM, is changing people’s expectations – they want the same kind of pricing, time to value, flexible access, ease of install for analytics that they get from other cloud applications. IBM is therefore very focused on delivering analytics in the cloud through a mixture of private, public and hybrid clouds. They are going to use IBM Bluemix to deliver some Platform as a Service capabilities as well as their solutions running as a service.Plus they are releasing BlueInsight.
- Bluemix services focused on analytics include databases and warehouse services, analytics for hadoop, reporting, geospatial and time series analysis (see this post from IMPACT on Bluemix and cloud).
- More IBM products run on cloud all the time. Many products already run in the cloud – social media analytics, Cognos TM1 and incentive management, Algo Risk services amo
IBM Big Data & Analytics: Deepen Business Relevance
Glenn finch and John Murphy talked about deepening business relevance. The challenge, he says, with much of the work around analytics and data is how easily it drops into discussions of security, integration, scalability, performance etc. What clients care about though is business relevance – business value – being created by the use of this plumbing. To make data, or analytics, relevant takes channels and strategy not just technology. This is why IBM has created its new Strategy and Analytics group.
This kind of business relevance is a journey – it takes time, multiple projects,new or changed processes and organizational change. Enterprises can be transformed one business area at a time as part of a journey to being an analytic enterprise. Where IBM has invested is in getting to these more analytical processes fast – 30 days to change a manual process to a more automated, analytical one. This is where the Watson Foundation is applied, using Watson te
Upcoming Webinar: 6 Opportunities for Business Improvement with Decision Management
Live Webinar June 25, 2014 9:00 am PDT, 12:00 pm EDT Register here. What opportunities are you looking for to improve your business performance? In this webinar you will learn six opportunities that are readily available when you adopt a decision management approach to business rules and predictive analytics. These are opportunities to: Simplify business […]
IBM Big Data & Analytics: Customer Panel
Next up is a client panel with Verizon, FleetRisk Advisors and UBS AG.
- Verizon has created a specific Big Data and Analytics R&D group to diversify their portfolio of services, looking for new opportunities in data and analytics to leverage Verizon’s DAILY 12PB of data.
- FleetRisk Advisors is a business founded on predictive analytics for the trucking industry that rapidly focused on solutions to prevent the problems it was predicting – generating remediation plans.
- UBS’s e-discovery technology team is focused on delivering data in support of regulatory and other inquiries. In particular supporting (and understanding) unstructured data is critical.
As always I will try and capture the nuggets from the panel without attempting to transcribe it:
- Examples include personalized recommendations/advertising across many channels, intelligent network management, telematics-driven closed loop mitigation, detec
PegaWorld – McKinsey on digitization
McKinsey came on stage talking about digitization. They see that different industries are at different points in the digital disruption. New trends begin and early adopters grow, start transforming mainstream companies and then a tipping point is reached where some incumbents die. So, for instance, disruption of retail banking is just starting while traditional media/video stores, for instance, have already seen the death of incumbents.
Meanwhile consumers are changing. Average customers are increasingly worth less than they used to be while good customers are worth more. Consumer behavior is also changing in unexpected ways, with heavier online banking customers for instance also being heavier users of other channels – they are more multi-channel.
As customers become more omnichannel McKinsey has seen that 77% of satisfied customers use 3 or more touch points while over half of all customer interactions are part of a multi-channel interaction. Increasingly
PegaWorld – PayPal and Innovation
Brad Strock of PayPal presented on innovation. He laid out the three stages of money:
- Money 1.0 is what you might call traditional coinage and notes.
- Money 2.0 was the credit revolution with revolving debt, credit and debit cards etc. These have become the pre-eminent means of payment for many people.
- Money 3.0 is what PayPal sees coming – Digital and Mobile.
Brad polled the audience to demonstrate how rapidly people update their phones – hardly anyone is using an iPhone that is more than a few years old for instance. This pace of change shows up with competitors also – Honeywell never thought they would be competing with Google but Google’s acquisition of Nest means they are. Brad and PayPal consider the changes happening now have a lot in common with the industrial revolution. The industrial revolution changed the world dramatically in 100 or so years – urbanization, power, manufacturing, steel and more.
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