Can Big Data become a Big Bubble?

At LoQutus we guide our clients to become digital leaders. With Analytics & Insights we help our customers shape the right environment for leveraging data and analytics to become more data-driven. From a business development perspective we actively support alignment between Data Strategy and Business Objectives. We want to demystify the world of data and make it accessible for everyone.

As I was intrigued by Geert Noels’ recent article in De Tijd, I felt the urge to shed some light on his various statements. You can read Geert Noels’ original article here (Dutch).

In his column Noelsspeak in ‘De Tijd’ of september 13th, Geert Noels warns us about the risk of a bubble developing itself on the business potential of Big Data. Blind faith in artificial intelligence and the solid believe that data is an infinite source of wealth and fortune, much like oil to which it’s often referred, might lead to a big disappointment and loss. Think of the risk and the damage that can be caused by errors in data and models, leading to faulty outcome and wrong decisions. Data-driven means fact-based, so is there no need to question this? History teaches us that every invention or development is often first embraced by commercial interest as a new vehicle to push and pull business. This does not necessarily always contribute to correct use and application of these novelties. A rational approach is most probably the right way to find relevance in the buzz.

Obviously Big Data is becoming a catch-all term, but most associated matters can be reduced to using data to create and improve business outcome. This definition will prove to be the most reliable when judging the sense of initiatives in this domain. It will be no surprise that it is recommended to think big and start small. Keep the relation between data and business value in mind and look for the data in your organization. Companies and organizations use systems, processes, machines and tools to make their products, support their services and organize their internal workings. All of these generate data that is stored, processed and in some cases analyzed, is used to judge its performance or to support decision making. Even how obvious this all may seem, it can be hard to choose the right methods and tools to gather the right data and make it usable for a specific objective. Establishing a view on this helps to target value and identify low hanging fruit.

Most data resides inside systems and softwares and is often managed in function of these environments. It is not a logical function of an ERP-suite to prepare data for analysis, integration with other data for extended comprehension, least of all to feed Machine Learning projects. As Geert Noels correctly points out, the ‘Garbage In – Garbage Out’ principle has an enormous impact here. Just like oil, data needs to be refined by removing the junk and impurities, if it is ever to feed the high-tech solutions like algorithms that use it for processing. To achieve a sustainable data-driven environment, every level of maturity comes with its appropriate tools and practices.

In his conclusion, Geert Noels correctly puts that big data will not cure your business model. Data can play a role in operational excellence, it can drive business development and can even point you towards new value internally or in conjunction with external elements. A Data Strategy should investigate this before tackling technology or leading to organizational change. And the key components will be critical thinking and human creativity. A pragmatic approach to discovering your own roadmap will do just fine. Will Big Data prove to be a bubble? It does not have to be the case. The best way to find out is perhaps by investing in small data first…

Written by Richert De Vleeschhouwer, Business Development Manager Data Analytics & Insights

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