Trends in Analytics

In the coming years business are to be more influenced by the presence of trends and some trends are here to stay. As is the case in any evolution, analytics trends also deserve a closer analysis and look in. The growth is so fast that it has reached a stage where before one can analyse these trends it becomes a reality. A classic example is the big data that is causing more strategies and substantial decisions on businesses taken based on this term “analytics”.

What are the trends in store for us then through the penetration of analytics?
There is this trend going that sooner or later the smart machines will ultimately take over the human centric jobs. But no case to fear for this as there is still a place for us to exist with a job to do. This is because we humans have always added value to these machines to work efficiently through inputs being designed by us while automation happens and this trend is likely to continue. This age yes does belong to us.

The analysts though predict the revenue from cognitive solution deployment to exceed more than $60 by end of 2025. So with this evolutionary growth of cognitive technologies it is expected to only better complement human decision making as we move on. So the result is that machine-men is both-and and not either-or as it may stand to be understood.

In fact such a futuristic trend shall mean smart people and smart machines are to gel well to create amazing results. All this means that humans are to build these machines to work more smartly. Another section shall work on fitting these machines more to fit processes and monitor the overall performance. The humans will ensure that certain machine aspects can never happen i.e sympathise, empathise or care. This way the pathway shall be set to paving way for a complementing association.

In fact this collaboration shall not happen on its own but happen once organisations begin to first examine the knowledge in-house, followed by the intensiveness of the processes to then accordingly determine which of these tasks are to be completed by humans and which needs to be executed by machines and were both can work in tandem. As a result of this assessment we may have 2 possible options emanating, one might require the work force within the organisation to undergo re-training and in the other case might mean making certain jobs performed by humans to be redundant leading to job losses! Companies that can spot this requirement more smartly in the earlier phase might take relevant decisions to bring the right mix of humans and machines on stage.

The transformation from taking a lot of efforts to bringing analytics to the organisation to a few departments companies are making it mandatory to have more top level executives also be involved in taking insight-driven decisions. Such organisations can be classified as insight-driven organisations. What is happening is organisations are bringing together the strategists, processes, key people and of course technology to work together to bring fantabulous results.

In reality we are beginning to see this transformation to analytics with leaders seeing it to weighing attention to building data warehouses in house to house the big data requirements to facilitate in decision making. This means either building infrastructure to support big data or else build a data warehouse thereby changing the scope of expectations. The viability of trying to fit smaller analytics build in certain may no longer seem to be great idea which is why the leaders will now look at fitting these analytics capability across the enterprise at all levels.