Big data seems to have been everywhere this year, every media outlet, pundit and business seems to have latched on to the concept, or at least the term, many without really comprehending what “big data” means, how it is collected and how it could be used. In all of the discussions however, the individuals who are either the source, the users or potentially the unanticipated collateral damage of attempts by businesses to adopt or use “big data” have either been forgotten or ignored.
So, in this post, I though I would spend a little time considering some of the things big data is, what it isn’t and how it could be used. I will also spend some time considering the real value of the personnel who may be impacted by the use of big data and, why we still need to value them for their contributions as humans, instead of casting them aside in our pursuit of the fashionable, shiny new concept.
What Is Big Data?
I will qualify this section of the article by stating that I am not a data specialist or a computer engineer, but, when dealing with such broad terms as big data it is not necessary to be too much of a specialist, specialists will develop the tools and techniques to use the data but we all need to have a working knowledge of what it is. In essence, what we are now referring to as big data is the vast pool of electronic data that is generated globally, generated from pretty much every source imaginable. This includes data created from sources as diverse as commercial transaction records, computer monitoring of jet engines, personal mobile phone usage, our travel habits and the data produced by industrial plant everywhere.
In the past, we lacked the computing power to both store and manipulate much of this data, resulting in the great majority of it being discarded, but, as processing and storage capacity and capability has increased, we are finding we are now in a position to try to distill some of this pool of data into useful and meaningful information.
Not All Data Is Valuable
One thing to note in the whole debate is that the vast majority of the data generated and potentially stored is essentially noise, having little to no real present or even future value. The process is the electronic data equivalent of distilling a pool of sea water to extract the salt, the water represents the useless noise component of the data and the salt the potentially useful data, though even the raw salt is just that, raw, and still needs further processing before it has any real value.
Once the data has been extracted from the noise, it must be manipulated and interpreted to produce useful information that can be acted on, whether that is to recommend an engine for maintenance or to send an email to an internet shopper suggesting something they may be interested in based on previous searches. This data interpretation will eventually be fully automated, but to identify the potential uses, develop the algorithms, and build a business around this data requires a lot of work by humans, and highly skilled humans at that.
Where data analytics will eventually lead the human race is the subject of a lot of debate. There are many uses for well considered opportunities that will bring enormous benefits in health management, traffic management, control of process plant, maintenance planning of critical equipment, etc. But equally, there are a great many ‘grey’ uses such as personnel profiling based on personal and family health records, travel, friend networks, and so forth that may be undertaken, but which may change society for the worse. As time passes both the good and the bad will appear and decisions will need to be made over what, as a society, we want and what we don’t.
The Role Of The Little People
So, in all of this rush buy businesses to jump on board the big data bandwagon, just where does it leave the little people.
Little People Make Big Data Work
In the first instance, personnel are needed to identify the opportunities to exploit available and relevant data and to do so in an appropriate way, to bring to bear all of the relevant knowledge such as proven historical formula and understandings, such that the data can be leveraged in the appropriate ways. Having identified the opportunities the big challenge is to find ways to separate the data from the noise then to interpret the data into useable outputs.
Some Big Data Will Displace Jobs
Inevitably, some applications of big data will result in current jobs being displaced or, at the very least, disrupted. The insights that well delivered data analytics can bring to many traditional jobs will mean that, those performing the job will be better informed and able to focus on their work in hand. Some jobs will disappear and be replaced by the output of the analytics but equally new jobs will appear to exploit new opportunities made possible by data analytics.
Big Data And Virtual Teams
The direct impact of big data on virtual teams is as yet hard to say, there will surely be some areas where some roles will be impacted, sometimes for the better, other times for the worse. Virtual teams often operate on the fringes of a business’ operations, undertaking special projects that require the leveraging of specialist skills, so being able to move some of these skills from being held by humans to being undertaken by computer algorithms will definitely be something we will see.
Similarly, many virtual teams are assembled to access low cost, skilled, knowledge workers, using the reduced costs to deliver greater commercial value to clients or shareholders, again, many of the tasks assigned to these lower cost centres could be automated by these high end computers that use machine learning to perform tasks previously only possible by humans with many years of education and experience.
Whatever the eventual outcomes three things can be stated for sure. Firstly that the adoption of data analytics and modelling will impact virtual teams in some way. Secondly, that as the computers become increasingly adept at performing some of our more mundane tasks it will give opportunities for the skilled humans to concentrate on the more challenging and advanced work. Thirdly, that there will always be a need for the little people in organisations, regardless of how big, big data may become
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