| | JUNE 20218CIOReviewFOLLOW THE MONEY AS ROADMAP FOR DATA ANALYTICSBy Hiek Van Der Scheer, Chief Analytics Officer, AegonData Analytics provides businesses a huge opportunityIt goes without saying that the opportunities with Data Analytics are huge. Even if you don't believe the promises that consultancies make, and you take the quote `data is the new oil' with a grain of salt, you cannot deny that data already has a huge impact on business models. Uber, Airbnb and Netflix are the obvious examples: They are not a transportation, hospitality or entertainment company but a Data Analytics driven companies.However, data are useless unless an organization is able to leverage these with (advanced) analytics to make better or faster decisions. Examples can be found across industries and across the value chain. Why is Data Analytics an opportunity NOW? The answer is quite simple:- Digitization of organizations: Making vast amounts of data available, which can be leveraged with analytics. This holds for the classical digitization of processes but also in new areas like health data (with health trackers), IoT and open source services (like PSD2). - Easy-to-use analytics tooling is available. To mention a few: DataRobot, H2O, Domino Datalab, Dataiku, and Sagemaker; all enabling automated Machine Learning. Be aware, a `fool with a tool is still a fool' but these solution make ML much more accessible to a wide range of Analysts and organizations. - Data savviness has increased in organizations. The possibilities of datafornew business models based on data are increasingly known. You don't have to study econometrics or computer science to embrace Data Analytics. IN MY OPINIONLack of alignment with the businessMany research reports indicate that organizations are still unable to capture the potential of Data Analytics. A major reason is the lack of alignment between Data Analytics and the business. It is not the unwillingness that causes this misalignment.On one hand, the business in typically unable to clearly articulate what they expect from Data Analytics. Often they expect the silver-bullet while the business challenge might be too complex to completely solve with only Data Analytics. Or they mistrust data and the analytical insights at forehand, and rely on their professional experience and knowledge. On the other hand, many Data Scientist get energy from building the most advanced Analytical Solutions without thinking about implications of using it in real-life. Only with an open mind-set and an iterative process between business and analytics, the best solutions arise. Boosting the effectiveness of Data AnalyticsAlthough the above findings are pretty universal and persistent, there are ample opportunities to make analytics work for your organization.First, focus on people over technology. The challenge of alignment between Data Analyticsand business is a people issue. Ensure that the technical people have sufficient soft-skills to listen to the business, translate the business opportunities and challenges into technical
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