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Smarter Analytics Leadership Summit Opening #smarteranalytics


Table of contents for IBM Smarter Analytics Launch

  1. Smarter Analytics Leadership Summit Opening #smarteranalytics
  2. Pushing the frontiers of analytics #smarteranalytics

Steve Mills kicked off the IBM Smarter Analytics Leadership Summit. Business Analytics matter, he says, as shown by the focus of CEOs (8 out of 10 expect complexity to increase, enterprises applying analytics are more successful etc). The need for analytics is pervasive, with every industry seeing a massive expansion in the volume of data as well as an array of missed opportunities – such as the estimate $90B in missed sales because retailers don’t have the right products – and poorly managed risk – such as the hundreds of millions of dollars in healthcare fraud every day.

The key drivers of business analytics, he says, are the emergence of Big Data (price performance of hardware makes handling more data practical), the shift of power to the consumer (a focus on personalization and the increasing levels of social interaction between consumers) and continued pressure to do more with less (especially as the price of computing continues to fall). In response IBM is making massive investments – $16B for 30 acquisitions since 2005, 8 analytics solution centers, 10,000 technical professionals and 9,000 consultants and so on. Three example customers:

  • Best Buy with their focus on registered customers and analyzing their behavior to drive an 8-10x improvement in advertising effectiveness to these customers while spending 5-7% less (opportunity creation)
  • Alameda County Social Services using analytics to manage entitlements for citizens and identifying and eliminating fraud while better managing cases for a saving of $25M annually (fraud reduction)
  • A major telco analyzing system logs to improve overall system reliability with real-time root cause analysis (risk management)

These three – opportunity maximization, fraud reduction and risk management – are the three classic use cases for analytics and for Decision Management.

Next up Mike Rhodin and Bridget van Kralingen to drill into some details of the new Smarter Analytics initiative. Mike kicked off talking about the need for analytics to be paired with Big Data and the general trend towards more intelligent, cognitive systems (the purpose of Decision Management, of course). Analytics and Big Data, he says, must be at the core of all the smarter planet solutions being developed across every industry. Big Data and analytics are enabling a new wave of front-office transformation. Solutions have moved from enterprise data to big data, from a business initiative to a business imperative and from something that transforms a single organization to something that transforms entire industries.

From a client perspective, IBM sees a new agenda among many C-suite executives who see analytics as both the biggest threat and opportunity on the horizon. In addition there is a move from scarcity of data and insight to an environment where there is an abundance of data and increasingly of insight. This means that driving to take action on this insight, Decision Management, will become critical. In addition professions in the front office will change as it becomes increasingly digitized – CMOs, for instance, must learn how to market analytically to succeed. This change is reflected in IBM’s survey data where the number of companies seeing analytics as a competitive advantage increased by 57% between 2010 and 2011 while those who identify themselves as using analytics to compete are more likely to be outperforming their peers.

Companies are moving from seeing analytics as a potential opportunity to something that is increasingly essential – something that is core to the company’s strategy and operations. CIOs in successful analytic adopters are taking the position that data and analytics are abundant resources and seeing how they can drive those into new solutions. In particular they are seeing big opportunities to grow retain and satisfy customers and increase operational efficiency.

To do this companies need to:

  • Align their organization around data
    Create an organization-wide trusted platform for big data
  • Anticipate
    Focus on predictive analytics at both the transactional and portfolio levels. Predict fraud, risk and opportunity
  • Act
    Making real-time decisions where it matters – A Smarter Analytics Decision Management platform across text analytics, predictive analytics, optimization, business rules and entity analytics supported  by IBM’s Big Data platform
  • Learn
    Then you need to learn so you can transform over time.

IBM feels it is in a unique position with its platform technologies, 20,000+ analytics projects and 9,000+ consultants, and a research program that includes Watson as well as many other analytic research projects. Their experience has also resulted in three focused Signature Solutions:

  • Customer Next Best Action – a Decision Management solution
  • CFO Performance Insight
  • Anti Fraud Waste and Abuse – another Decision Management solution

Robert LeBlanc, head of the Middleware software group, came up to talk about the technology at the heart of these solutions. This technology has to deal with much large volumes of data from everywhere, data that changes more often – having higher velocity – and data that is of many new types an variety. This leads you to a platform that supports this kind of data environment – a Big Data platform – that handles both new and traditional forms of data and supports advanced analytics against it. This new environment will drive a need for new capabilities in much the same way that e-commerce and the web drove the creation of the WebSphere application server platform combined with a set of open standards and an ability to leverage previous generations of technology. Any Big Data platform must integrate with the current generation of data systems, must build on the open standards that exist and must be part of a robust ecosystem.

IBM sees this environment opening up new data sources (entity resolution from unstructured data for instance or network analysis) and new methods (adaptive analytics or optimization under uncertainty). New data sources and the ability to manage this data create new opportunities – 1.7B daily events at T-mobile or 1,000 buses being monitored in real-time across 150 routes in Dublin or sub-millisecond interventions to detect security intrusion in Brocade products. Of course one interesting example of this is in IT – the potential for using Big Data to improve the way IT operates across cloud provisioning, mobile enterprise and security.

IBM’s Big Data platform has several elements therefore:

  • Information integration and governance
  • Data Management:
    • Hadoop for new data sources
    • Stream computing (InfoSphere Streams) for data in motion
    • Data Warehouse for traditional data at rest
  • Accelerators layered on top of this data
  • Capabilities for
    • Visualization and discovery
    • Application Development
    • Systems Management
  • Analytic Applications to make this easy to consume

They are also working to bring new partners into this space with over 100 new Big Data partners and are determined to create the best possible Big Data platform.


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