When it comes to analytics the limiting factor is not the software, but rather the shortage of skilled people required to make sense of the data.
As is often the case when demand for a particular resource outstrips supply, it's only a matter of time before a much wider variety of services based on applying data analytics within various vertical industries starts to emerge.
In the case of IBM, which has anchored much of its Smarter Planet strategy around the broad availability of quality analytics, the general shortage of analysts skilled in using analytics software means that the company will package a number of analytic services to its portfolio in select niche areas in the years ahead.
According to Frank Balboni, global business lead for business analytics and optimization, IBM will proceed cautiously into the services sector given the sensitivities customers have about making proprietary information available outside of their own organization. But he expects to see a fairly large number of third-party service providers emerge in any number of vertical industries to provide analytic-based services.
As the cost of computing continues to drop, the ability to provide these services becomes more feasible. But the limiting factor is a current general lack of professionals skilled in analytics. IBM has been partnering with a variety of universities to help train students on how to master analytics software, but it will be at least a decade before any of those efforts would have a meaningful impact on the current shortage.
According to Balboni, IBM in the last five years has spent $11 billion acquiring companies in the area of analytics in addition to another $2 billion on internal research and development. In addition, he said that the analytics category is growing three times faster than traditional transaction proccessing applications.
But while interest in analytics is growing rapidly, customers are trying to limit the expense associated with these applications by embracing emerging technologies such as the R programming model and the Hadoop data management systems that, while not as fast as proprietary systems, allow IT organizations to embrace analytics in a more affordable manner.
The challenge, however, is not aggregating the data, but making sure that the data itself is reliable and that meaningful correlations can be made in real time. Only then is the data actually going to considered trustworthy enough by the business to be actionable information, versus just data in another long series of reports that nobody ever uses.