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Interview – Ujjyaini Mitra, Head of Analytics at Bharti Airtel


What do you do?

As Head Analytics of Airtel’s mobility business, Ujjyaini plays the role of Subject Matter Expert in Analytics with a special focus to consumer’s Usage and Retention (UnR) & Pricing across Airtel’s product family, Customer service Experience and Market Research.

Along with building highly complex marketing models in Big Data space to achieve high revenue growth via right contextual marketing and enhanced customers’ life cycle value, she mentors the business leaders to draw right insights from the structured and unstructured data or reports. At the same time, she hand holds the junior members to break the business problem into impactful and actionable business analysis and to story line the findings.

Can you tell us about your background?

Ujjyaini, who passionately loved solving Mathematics puzzles as a child, who left behind the opportunities to join IIT but chose to study Mathematics and Theoretical Computer Science at Chennai Mathematical Institute and then pursued Quantitative Economics at her Masters from ISI Kolkata, received an offer to join McKinsey, one of the world’s best management consulting firm as an Analyst, when she didn’t even know what is Analytics. McKinsey introduced her to the world of Data Science and she spend 6.5 years in travelling across the Globe and solving challenging business cases cross industry – FMCG, Telecom-Media- Tech, E-commerce, Logistics as well as Macro Economic Policy at Govt level.

What did you to after Mckinsey?

She then went on to build and lead the Advanced Analytics team of Bharti Airtel, India – where she built a strong team of analysts who delivered few time critical strategic projects in decision science.

Analytics is an integrated part of Business Intelligence in Airtel. Business decisions are confluence of data driven insights and external market knowledge. Be it measuring campaign efficacy scientifically or taking complex decision of where to open new Airtel Store – are driven analytically backed by data in Airtel.

Airtel follows an approach of ‘issue-to-outcome’, where Analytics is infused to draw right information, information driven insights and thus implementation. So, Analytics is used at every stage of taking business decisions. Airtel adopted Analytics around 2009-10 while Airtel tied up with a Globally acclaimed business Management firm to start their journey on Consumer Life Cycle Management factory (CLM factory).

Today this factory is the Marketing lifeline in terms of Marketing Operations and measuring Marketing Outcomes. Following is a slide to show how Airtel takes Business decisions infused with data driven Analytics. Thus Airtel got benefitted everyway, starting from right customer acquisition module, improving campaign hit rate through right targeting of customers, improved ROI through right pricing, enhanced Customer Satisfaction and thus ‘winning customers for life’.

Can you brief us about some of the analytical solutions you work on?

All my current works has few basic goal – a) improve ROI, b) improve customer life. Therefore, customer interactions through every touch points can be integrated towards more contextual, timely and easily adoptable campaigns or communications.

Airtel not necessarily do everything in house. In fact, Airtel has a great eco system of outsourcing the operation and partnering with world’s giant knowledge hubs and experts. We build the solution jointly, customized to Airtel’s expectations. So that complex models can give birth of simple solutions to implement seamlessly. All Analytic solutions are built keeping ‘Customers’ in focus, so that, every department work towards the same focus point and outcome become customer centric.

Can you brief us about a specific use case in analytics that has brought significant value to Airtel?

UM: Last year I established a world class and completely automated measuring tool for all Airtel campaigns. So, earlier, where, it was not easy to measure right efficacy of the campaigns due to leakage in calculation, I have made it scientific and water tight. It is being automated, no human effort is required in calculation.

CLM team, therefore, seamlessly prepare the ROI reports at any number of granular time frame. UnR team, Pricing team centrally and across circle can take a faster decision on which campaign is doing well, which is not, which one to continue, which one to stop, which campaign’s pricing needs to be changed vs which campaign’s content requires modification.

AIM: Please brief us about the size of your analytics group and what is hierarchal alignment, both depth and breadth.

UM: This year we have plan to grow the Analytics team. However, instead of just building a central analytic hub, we want to disseminate the Analytic knowledge to business managers, so that they can think and problem solve analytically.

We are therefore, investing a lot to train all the business managers and vertical heads to understand Analytics, Statistics and their implementation in Marketing and other Business domains. That way, the whole organization row towards the same goal – mapping Analytics directly to decision making, taking action and delivering value for improved business performance.

We are evaluating good Analytical S/W which can empower our Business owners with Analytical tool kits to take data driven insights. Alongside, planning to build a strong core Analytics hub to serve the whole organization with analytical rigor.

AIM: What kind of knowledge worker do you recruit and what is the selection methodology? What skill sets do you look at while recruiting in analytics?

UM: People with good knowledge of Statistics & its right application [e.g. knowing t-test is just OK, but one must know given a business problem whether to apply t-test vs F-test or Chi-square test], Big data tools, and basic understanding of business or market.

AIM: What are the most significant challenges you face being in the forefront of analytics space?

UM: 3 challenges:

  1. Shortage of right skilled people [most Analytic institution either train focusing only towards theory or tools without teaching the real life applications; while other institute teaches top level application of Analytics in Business without balancing with right technical skill building]
  2. Making people unlearn ‘ad-hoc’ decision making based on gut feeling and training to use Analytics to derive data driven insights, therefore slow adoption.
  3. Lack of organizational strategy to grow Analytics even though leadership realizes its incredible benefit.

Your advice to students?

As a part of her interest to mentor budding managers and data scientists, she joins hands with various institutions and organizations like IIM Ahmedabad, IMT Ghaziabad, SPM, Data Science Foundation etc where she shares her industry experience with students. Being a student at the core of her heart she speaks at various conclaves to share her learnings and learn in turn and thus help spreading knowledge with broader group of Analytics enthusiasts.

Please brief us about the requirement of talent in Analytics?

We are investing a lot to train all the business managers and vertical heads to understand Analytics, Statistics and their implementation in Marketing and other Business domains. That way, the whole organization row towards the same goal – mapping Analytics directly to decision making, taking action and delivering value for improved business performance.