Prof. Madhu Viswanathan, Associate Professor and Research Director at IIDS, interviewed Saurabh Agrawal, SVP, Analytics, and CRM Lenskart.com to understand learnings from his experience as a Data Science Consultant and a Data Science Practitioner. Sharing snippets of the ensued candid chat between the two on ‘Analytics and More…’
Saurabh has worked in Digital Analytics in companies across varied industries - Fintech, Automotive parts supplier, and now Eyewear Retail. In his talk, he pointed out that, contrary to popular belief, there are more similarities than differences in how varied industries conduct data analysis. There is a pattern to data analysis that follows a common framework - Organizing the data, Drawing Insights from it, Building Models, and Applying the insights to solve Business Problems.
A crucial step towards solving Data-driven problems, he observed, is a deep understanding of the product & the customer. Also, driving data-driven solutions can be a long, exhaustive iterative process. Often, solutions do not come in one go. Hence, he emphasized the need to acquire under-credited soft skills like passion, patience & endurance, alongwith the necessary hard skills of Data Engineering and Coding required to solve them.
When probed if the 'Culture' of a company can encourage data-driven solutions, he accentuated the importance of a company's belief and a mindset that data can offer business solutions. A unified spirit to willingly look at data in everything can be transformative for the organization. The process will be riddled with challenges and failures, too, but the common mindset will enable the organization to look at data-driven solutions. He urged the audience to try and experiment with the data to get meaningful, sometimes surprising insights.
So, What does Saurabh do when posed with a statement like “Iss data se kuch karo?” (In this reference, please do something to get valuable insights from this data) Saurabh said it is a good strategy to undertake a mental checklist of “what do I want to do with the data?” It is essential to establish clarity around what can and cannot be done with the available data. Data Cleaning is another significant step that needs to be undertaken. Saurabh said it is significant to bring more people on board with data-driven decision processes across the organisation. Its critical to create an ecosystem in the organisation to allow data to prove itself right rather than proving people wrong. It is beneficial to find champions within the organisation by enabling all employees to work towards offering a better customer experience at minimal economic costs. He suggests doing analytics for shop floor managers and Business Unit Heads rather than for CEO/ CXO might have deeper entrenchment that will drive real change.
A significant impediment, he observed, can be convincing the non-believers. A good start can be to identify the believers early on and forge partnerships with them. Anyone struggling to grow will be easier to convince and is more likely to take help from data sciences to develop actionable insights. The possibilities that emerge with Data will then create a FOMO with the non-believers. Funny as it sounds, it has worked in some cases.
So, it is crucial to get started first. Focus on what is doable, even if it has a small impact. Small wins help build credibility to take on larger projects subsequently. It may not be a great idea to take on a challenge that’s a holy grail. Sometimes, data may not be available, or data may not be good quality. Other times, senior management may not have the patience to put the data collection system together. In such cases, waiting it out for some time and collecting data for analysis is a good strategy.
Given the rapid digitization & automation, more roles & jobs are getting analytical. Should then everyone aspires to be a Data Scientist? Not really. He reiterated the need to adopt a data-driven mindset to solve business problems and equip oneself with some necessary tools imperative to make astute data-driven decisions- Knowledge of a basic computer language though not an essential skill, is a handy tool for better understanding of data. He opines that Analytics is unique in that it combines both hard-core technical skills and business understanding.
Data-driven organizations have traditionally hired Data Engineers and Business Intelligence Developers. There exists a gap between the people who translate business needs and what the technology team needs to deliver. Business Translators can fill this void. While the role does not necessarily require hard-core coding skills, it is helpful to understand how to code. Saurabh suggests being open and flexible to learning to stay agile with changing skills in the future. The world, he says, will increasingly see more Citizen Data Scientists.
Insights from Saurabh, who has worked in financial analytics, manufacturing analytics, and retail analytics across B2B and B2C industries, offered attendees a holistic perspective of the importance of being a part of Data-driven Organisations and how to upskill in that direction and the hurdles one could face.
The participants engaged with Saurabh in a very interactive Q&A session. His mantra to use analytics as brahmastra (In this reference, A celestial weapon that never misses its mark) to transform a job onto the next level resonated well with the audience.