IBM Report on Analytics


In October, IBM released a report from their Institute for Business Value titled Analytics – A Blueprint for Value. IBM releases these reports on a periodic basis, and this one is focused on the growing importance of analytics to business success. Through their analysis, they came up with nine levers that represent the sets of capabilities that most differentiated leaders exhibit:

  1. Culture: Availability and use of data and analytics within an organization
  2. Data: Structure and formality of the organization’s data governance process and the security of its data
  3. Expertise: Development of and access to data management and analytic skills and capabilities
  4. Funding: Financial rigor in the analytics funding process
  5. Measurement: Evaluating the impact on business outcomes
  6. Platform: Integrated capabilities delivered by hardware and software
  7. Source of value: Actions and decisions that generate results
  8. Sponsorship: Executive support and involvement
  9. Trust: Organizational confidence

Continue reading

MIT Big Data Panel Discussion


In May, I participated in a Big Data panel discussion at the 2013 MIT Sloan CIO Symposium. The panel was moderated by Tom Davenport, Harvard Professor and co-founder of the International Institute for Analytics. The panel participants aside from myself were:

  • Annabelle Bexiga, CIO, TIAA-CREF
  • Jack Norris, CMO, MapR
  • Keith Collins, SVP, CIO & CTO, SAS Institute
  • Michael Chui – Senior Fellow, Mckinsey Global Institute

This was a very good discussion on the potential of Big Data and the possible direction it takes in the future. Michael Chui did a great job with his opening remarks, referencing this Mckinsey Report and using examples from it. This report, which I have mentioned previously, focuses on major disruptive technology. It is interesting to hear the perspectives (and sometimes biases) of these industry players. It’s an hour and ten minutes long, with some very good audience questions.

Thoughts on 2013


Another year is coming to a close, and that means it’s time for 2013 predictions. Blog posts and articles will focus on the possibilities that lie ahead in the coming year. With so much uncertainty in the global community, people predict at their own peril. So this year, I am focusing my thoughts on the journey that I believe will dominate the rest of the decade. That journey will span three very broad categories: the accelerated movement towards systems of engagement, operating model change, and Digital innovation.

So here it goes – my thoughts for 2013:

Continue reading

IBM Big Data Study


The IBM Institute for Business Value recently completed Big Data research and released a report titled Analytics: The real-world use of Big Data. As the report states, companies have been dealing with large volumes of data for years (think billions of call center records collected by Telecommunication companies). But the report also identifies the two trends that make this era of big data different:

  • The digitization of virtually “everything” now creates new types of large and real-time data across a broad range of industries. Much of this is non-standard data: for example, streaming, geospatial or sensor-generated data that does not fit neatly into traditional, structured, relational warehouses.
  • Today’s advanced analytics technologies and techniques enable organizations to extract insights from data with previously unachievable levels of sophistication, speed and accuracy.

Continue reading

The Social Ecosystem


I recently viewed a video titled The Future of Social Inside the Enterprise, a thought leadership presentation from the recent Dreamforce 2012 conference. The presentation is delivered by Dion Hinchcliffe of the Dachis Group, and Alan Lepofsky at Constellation Research. This is a fifty minute journey through the past, present and future of social business. You’ll find some content on the business value associated with social, and some good examples of how social is evolving to support the way we work.

You can start to see how systems of record may integrate with systems of engagement. Two examples are given by Mr. Lepofsky. The first describes a stream level integration, which allows system of record events to be broadcast into the activity stream. This stream level interface is envisioned to be the place where people spend time doing their jobs. It is pointed out however that stream level integration has its issues, the biggest in my mind being the loss of context. Comments made in the activity stream do not work their way back to the system of record, so context is lost. The other critical issue is the noise level associated with these streams. Without robust intelligent filtering, these streams become worse than email. This filtering – finding the actionable insight among the noise – is critical to the effectiveness envisioned by future systems of engagement. I had a discussion this week with senior executives from a large Financial Services firm, and the general belief is that this critical filtering will take years to develop and optimize. It took IBM four years to tune IBM Watson to compete in the Jeopardy challenge. This is not simply a sentiment analysis exercise.

Continue reading

Big Data and the Emerging Era of Engagement


I often tell the IBM Watson story as a way of describing the future of analytics. Watson – with a large quantity of Big Data behind it – beat the two biggest Jeopardy winners of all time. Although that became the story, the bigger story for me was the business application of what I had just witnessed. Watson showed us how analytics will mature from descriptive to prescriptive. Most companies I talk to are still in the descriptive stage – reporting on that which has happened.

Continue reading

Is Data and Insight a New Source of Revenue?


In this world of Big Data and advanced analytics, many companies are starting to wonder about the revenue potential of their data. An opportunity to create new revenue streams is an attractive scenario – if data assets can become information products. Although not new, the number of companies that pursue information related products could grow considerably. Most companies upon inward reflection will find that the analytic core competence required to deliver insight – the higher end of the monetization scale – does not exist internally.

This introduces some interesting scenarios that underscore the market need for analytic outsourcing and the establishment of analytic centers of excellence. The evaluation process for this opportunity involves a market analysis that identifies the value-added information products for the target market. Understanding the business outcomes enabled by insight is a critical step in determining which products make sense. In addition, the data required to enable these products must be clearly understood, available, and clean enough to deliver the required insight. The process is then enabled by the appropriate analytic methods, taking advantage of advances in computing power and in-memory capabilities. The ability to include insight from unstructured data through the use of text mining expands the opportunity for value creation.

I envision a number of relationships emerging between technology companies and value chain players. These relationships enable new, more insightful information products by combining traditional data related skills with deep analytic and domain expertise. Companies will look to supplement existing offerings with analytic oriented products and services, or pursue new innovative offerings altogether. Insight as a driver of business and decision processes will be enabled in the future by internal movement towards analytic excellence, the use of external information products and services, or some combination of both. This is a natural response to the “Big Data” phenomena and the need to improve the speed and quality of decision making. It introduces a new era of information brokers that deliver new innovative products and services enabled by business analytics.