siliconindia | | April 20188HIGH TIME FOR YOUNG COMPANIES TO INVEST IN A ROBUST DATA SCIENCE TEAMBy Subodh Kumar, Chief Technology Officer, MagicbricksHeadquartered in Noida, Magicbricks is India's largest online real-estate platform that enables both buyers & sellers to locate properties of interest across India, and source information about all property related issues.IN MY OPINIONH ave you ever realised that how a certain brand of mobile phone that you missed out during a bumper online sale suddenly pops up `as available' in your online shopping cart after a week or so. All thanks to data science. The sudden proliferation of the online market place has certainly put more power in the hands of the consumer. In an era of digitisation, brands, which have succeeded are the ones that have made the right kind of investment in making the best use of the data that is available at their disposal.Thanks to this data, brands are now moving from instinct driven marketing to data driven marketing. Successful e-Commerce brands have started to value data more than even before. This has helped the brands to talk individually to the consumer making the interactions far more personal and engaging. Brands are sitting over tons of consumer behavior data that in turn gives them a deep insight into consumer minds. What is the consumer looking for? How is he looking for? When is he looking for? Where is he looking for? Why is he looking for? and what not. Addressing these questions with tech-driven solutions seems the way ahead in creating a robust business for the future. But the fundamental question remains ­ How to find these questions? The answer is simple ­ create an efficient and robust data science team that will build a business for future. Global internet companies like Facebook, Google and Amazon have been created on the back of a good data science team. New emerging brands also want to make the best of data science, but due to lack of knowledge and clarity in how to go about doing the job they have faltered. Till now, most of brands haven't been able to match expectations and outcome from data science, hence they ended up losing crucial business opportunities, which otherwise would have been a game changer. So, before setting up a data science team, it is important for organisations to map expectations, outcomes and role of this team in organisation. The first steps towards will be: 1. Organising Workshop: It all starts with a bit of self-introspection. It is highly important for brands to find out:· Is the organisation ready for adopting data/driven approach,· Identify top (at least 10 to start with) business problems that data science can help to answer· Right from the outright, set the right expectations and clear the roles of data science and the value that this team will bring on table to leadership · Is organisation ready to invest in data science 2. Define Roles & Expectations: Once you know what value can data science bring to your organisation, define the JD for a data scientist, who can head that team. The role must by inspiring and attractive and must give a clear idea to the prospective candidate on the data at disposal. Since the candidate will be leading a team it is very important for him/her to be technically hands-on and also visualize challenges for the business.3. Understanding Data: Once the lead data scientist joins, his first month should go in understanding various data and people/process (in regards to data source). He needs to spend time in meeting with each department to get this information as this will help him understand data in easier and better way.4. Bringing Value to Organisa-tion: Now that he understands data, people and process, he needs to pri-oritise problems. Within 3-6 month time depending upon nature of com-
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