It’s true that big data is changing the world like never before, and business are not leaving any stone unturned to get their hands on the best technology to collect data, gather information from it, and transform it into revenues. However, in this competitive world, the insight generation has to be a robust process, otherwise, there’s always someone who will be doing their homework better than you and snatching your market right before your eyes.
If you are wondering what else could be done, here are the six features of a robust, advantageous insight seeking process that you need to know about.
- Asking the right questions: It has been repeated so oft in the field of financial success that it is now a cliché, nonetheless, a cliché that cannot be dismissed by any means. To strike the most profit in the long term, businesses need to know what matters most to their stakeholders, their customers, and their employees. The know-how is good, but the know-who, know-why, know-where, know-when, and know-what have long been under-appreciated, but without which, a business can never be truly successful.
- Investment in technology is not enough: If you think that having the latest technology and the best data scientists for your business is more than enough, you’re wrong. Capacity development – which includes organizational design, processes, metrics, culture, and competencies – is the core of a successful business. In short, a holistic approach is required.
- Data is beautiful: A major part of failure in utilizing data is that it does not get the attention due to it. Operational data and its IT level functionaries have rarely been given the acknowledgement rightly due to them at the Board level, which leads to valuable information being side-stepped. The right insight will come from all data, regardless of where it is coming from. However, filtering practices can be adopted once all data has been checked.
- One-sided vision: Your customers are human, and so should be your data – or at least, with a human-like quality, which is to say that the engineering of data has to be aided with the skill of science and the craft of arts, i.e., a comprehensive and holistic view is again necessary. Though science has been gradually obtaining significance in board rooms of business organizations primarily through predictive modeling, the role of arts – which cannot be taken too lightly – is undermined. While an example of the role of arts at the basic level would be creating data visualizations to depict relationships and variation, at a higher level it could be generating ideas and identifying potential relationships.
As Einstein had once said, ‘Imagination is greater than knowledge,’ those in the business of using big data for their business must understand that creating a phenomenal success is not just data, technology, or even insight, but beyond all that – an imagination that can look ahead of the present, to create what is possible. All other things are just a means to reach that vision.
What do you think? What according to you is the value of insight and analytics in big data?
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