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Business Value of Big Data and Analytics #BDA13


Fred Balboni came up next. Fred, of course, was early in IBM’s Business Analytics and Optimization service line with its unique focus on analytics. This service line has grown to 9,000 consultants and has conducted thousands of – 30,000 – analytics engagements.

Fred began with a little history. ERP, he says, took about 20 years to transform business value. The e-business cycle, which followed, took about 10-12 years to drive business value. Analytics he says is tracking for a 7 year cycle to business value, with companies increasingly transitioning from technology implementation to business value.

IBM’s  analytic projects have several elements:

  • Analytics Asset Solutions – business use cases, signature solutions etc
  • Domain Capabilities – fraud, customer, finance, operations, risk and information management
  • Core Delivery Capabilities – strategy, BI, analytics, Big Data etc.

All of this matters. Particularly interesting were the focus on delivering domain expertise drawn from other industries and the focus on using both IBM and third party software.

Accelerating clients’ ability to transform with analytics, he says, is driven by IBM GBS’ investment in:

  • Industry use cases
    BAO has over 60 of these, 75% use Big Data, and each is a fairly detailed set of business value assessment, cost estimates, implementation accelerators etc.
  • IBM Signature Solutions
    These combine multiple IBM technologies and include Next Best Action, Anti-Fraud Waste and Abuse, CFO Performance Insight with Predictive Asset Optimization and Risk Management being announced. Over 75 such engagements since last year.
  • Big Data
    IBM is investing in its Big Data skills, particularly by extending their information management foundation capabilities to include big data.

IBM is finding that the best place to start with analytics is with a business value accelerator project that looks at strategic alignment, customer insight, risk/fraud/finance, big data and industry-specific elements. Each is unique but these are the common elements.

Fred ended with an interesting, if busy, chart.


Fred emphasized the importance of all the elements – from managing data, to understanding data, gaining operational insight and driving customer value.

Fred was then joined by a customer – Gueillermo Guemez of Banorte (a national bank in Mexico that has gone from 19th to 3rd in 20 years) -and Glenn Finch from IBM’s BAO service line. Interesting points form the discussion:

  • Analytics is seen as a key to driving growth by improving the customer experience and getting more products per customer
  • Customer experience requires the end of silos – decision-making must be customer-centric
  • Not about big data, about big data analytics so that a customer is treated as an individual
  • “Yes we have the data” – we just don’t necessarily DO anything with the data….
  • Critical to have really strong executive sponsorship for this kind of analytical transformation, or indeed any kind of transformation.
  • Also sustaining this kind of transformation requires a team focused on that, with senior full time resources assigned
  • Clients want business value, not “big data” or other shiny objects
  • This kind of project requires people in the bank to rethink their processes, the way they think about customers
  • Want to move to real Markets of 1 and that means underpinning everything with Big Data analytics and a customer focus
  • Fewer KPIs work better for value-based contracts – focus on 5-7 KPIs and not dozens (and I would add use these to identify critical decisions)

Great insights from Guillermo, not all of which I have captured here.


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