Table of contents for IBM Insight 2014
- Opening #IBMInsight Keynote: Seize This Moment: Envision Your Future
- #IBMInsight Keynote: Envision you journey: Are you ready for real-time decision-making?
- #IBMInsight Powerful Analytics for Everyone
- #IBMInsight Keynote: Seize this moment – transform your industry
- #IBMInsight Internet of Things
Shanker Ramamurthy kicked off the session, describing how, as the world’s economy is digitized, the use of Big Data and analytics to compete in the new real-time economy becomes essential. The latency with which enterprises much develop and implement solutions is collapsing to zero. Customers are demanding more value for money at the same time, requiring not just faster but also cheaper and better services. Plus there is an explosion in the sharing economy with companies unlocking economic value using data, analytics, cloud and social. IBM’s contention is that growth and differentiation, efficiency and business resiliency are all required and that big data and analytics are central to this. Companies must be able to make multiple moves in the time that their competitors can do only one. The real-time economy he says requires execution with speed, tying business strategy to data and customer engagement.
Glenn Finch came on to talk about the sixth Institute for Business Value study on data and analytics. Four big shifts
- Most of clients report in-year benefits from analytics
63% say they are getting value in less than a year, even in the same quarter. Time to value is critical.
- Velocity has become the key driver of analytic value
- Customers are not the only focus for analytics any more
53% still focused o the customer but 40% focused on operational analytics
- Digital capabilities are being increasingly integrated into business processes
10% of the responders in the survey are “front runners”, doing analytics wide and deep while 75% are not doing very much yet. The remaining 15% are deep but in a narrow area.
Glenn introduced three themes – acquire, analyze and act – and brought some customers on stage to discuss them. These clients have identified big strategic pressures and interestingly one responded by looking for decisions that needed to be improved and driving back to analytics and data that will help – Begin with the Decision in Mind as I like to say – while the other began by improving the data and data access and pushing that up into better decisions. Beginning on the “Act” side – the decision – gives you an immediate tie to the business (one of the reasons I like it) and it’s clearly harder to make this business connection when starting on the acquire side.
Both emphasized the importance of business support and business engagement, however. In addition at least one of the companies was doing well before starting the effort – it was not about responding to current crisis so much as a future one. Not a lot of discussion of “real-time” though.
Mark Andrews of GBS came up to talk about how companies are changing the way they are generating analytic insight. These shifts are changing how analytics are being done:
- From samples to all data
Instead of taking a sample that is relevant and looking at it they are taking ALL the data in their big data infrastructure and analyzing it. More data, more fields, less summaries and more raw data. The role of cheaper infrastructure is key because the cost of analyzing more data has dropped while access to new data types increased the incremental value of this additional data.
- From hypothesis to discovery
Not sure I agree with this one but IBM sees companies that used to start with a hypothesis move over to letting the data speak. Personally I find this approach a little scattergun and still think you need to know which decisions you want to improve, even if you let the data tell you how.
- From analyzing data that has been stored to analyzing data in motion
Analyzing event streams, and scoring in real-time, rather than batch oriented analysis.
Mark brought up a panel of folks to talk about some of these trends. Some good examples of using less common data types and on analyzing / integrating all the data not just a sample of traditional data. A certain amount of unexpected insights too and some old stories about real-time responses like ATM fraud. Nothing worth noting particularly.
Mark wrapped up with an announcement of a new solution – Big Data and Analytics Solution Accelerator – that allows the various elements to be access
For me too much focus on long cycle time decisions and not enough on real-time decision-making. Too many GBS platitudes and not enough concrete anything.