|By Adrian Bridgwater||
|December 10, 2013 12:00 PM EST||
As an industry, information technology is fond of relabeling, reclassifying and renaming things.
Part of the art of innovation is the reinvention of those things that we know we need to fix. But true innovation is argued to be the reinvention of those things that we don't think we need to fix - and this is often called "disruption".
Obstreperously hostile, or not?
The IT industry has effectively reclassified the term itself; where we might naturally think of disruptiveness to embody obstreperously hostile entities, actions or "things" even - we now use the term "positive disruption" to explain where technology is bringing new efficiencies and functionalities to us.
Disruption can be positive and progressive then, that's great - we get it... but there's a problem, i.e., disruption of the technological variety brings with it a need for reskilling.
Take the Hadoop software library framework for distributed processing of large data sets across clusters of computers. Hadoop uses simple programming models, but it is still said to be a complex implementation task that requires new and specially developed skills.
Also then, take analytics, for want of a second pertinent example.
Technology vendors from HP to smaller niche players have carefully nurtured their Business Intelligence (BI) offerings over the last decade and more so that we now view data analytics as an almost natural antidote to Big Data. It's true that often quite sophisticated predictive data analytics is moving into the realm where every so-called knowledge-worker could potentially start to use these tools.
Skills-to-innovation trade off?
But is the skillset there for these analytics functions? The short answer is of course no, not fully by any means. Is there a skills-to-innovation trade off that CIOs will have to make?
In the very near future, a large proportion of any firm's workforce will have to start using predictive analytics (in some capacity or other) as part of their daily routines. This means that we need to think about how we deliver those functions now, i.e., we need to build application interfaces (many of them on mobile one suspects) that will be just as easy to use whether we are talking about a data scientist, a business analyst or a normal end user.
"We've seen a real shift in the skills employers are looking for," said Aidan Anglin, chairman of the Recruitment & Employment Confederation's Technology Sector Group.
"The most important qualifications for these types of data analysis roles might not be academic degrees, certifications or job experience but so called ‘softer skills' - curiosity, creative flair, the ability to visualize and to communicate clearly with non-technical people throughout the business."
HP says that its own Information and Analytics Services (IM&A) aligns the right people, processes, and technology to create the right information management and analytics strategy. "We provide the right engagement, the right environment, and the right management to analyze and understand your information and how to act on it," says the firm z but it may often be the HP consultants who need to step in and help with skilling up to start with.
As to whether this translates to a skills-to-innovation trade-off for CIOs might be stretching it a bit, but the point stands, i.e., we have to consider the wider effects of disruption even when it is the positive kind.
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