Looking across the hype, we can see that analytics has been around for over 30 years now. Data-intensive organizations such as banks have been relying on insights into these data to predict trends and customer behavior. But these analytics were performed in a dark corner of the organization and thrown across the department wall when ready. There was not much interaction with the business departments, and even less integration with the transactional systems.
When big data arrived, the expectations were extremely high. Not only would we be able to integrate more data than ever before, from whichever internal or external data source, we would also create brand new business models from this wealth of available data. That was the theory.
Then reality sank in. Most organizations realized they would not become the next Airbnb or Uber. They have a couple of experts - the so-called data scientists - playing with Hadoop in about the same corner as the analytics experts were playing all those decades before. They did generate interesting insights once in a while, but the result could hardly be called a data-driven organization.
Time for action
It is now time to move beyond this phase of hype and isolated experiments. Time to integrate the possibilities of big data into the transactional systems. This is a necessary step in order to improve the countless real-time decisions that must be taken every day, rather then enabling that one ‘magic’ insight which would lead to new business models. You cannot change your company strategy every month. But you can take better informed decisions every day, using those big data that you have successfully captured and integrated.
This does not only mean re-architecting your ICT infrastructure, it also implies a radical re-thinking of the role of big data. You should no longer start from ‘what have we got available as company data and insights?’ but rather from ‘what business problems are we trying to solve?’. Only when taking this approach, you will be able to successfully integrate big data with your transactional systems and decision support processes.
And the data scientist?
In this new era of big data, the data scientist needs to be de-mystified as well. We don’t need a technical wizard who also perfectly understands business language. Nor do we need every business person to acquire enough analytical skills to become a data scientist. But we do need the business to understand the potential and possibilities of analytics as a decision-support tool. Only then will the business departments be able to help design the best possible system which uses analytics and big data to its fullest. We will gladly help you in reaching that level of understanding, and ultimately in turning big data into ‘small’ day-to-day actions, which will then lead to big business.