Career in analytics in a KPO
Do you love to explore and investigate information? Do you find spreadsheets to be a useful ally rather than the scary monster people make them out to be? If the answer to both the questions is yes, you should consider a career in analytics.
Analytics is a fast-growing field that promises exciting careers for those with strong quantitative skills. In his bestselling book ‘Competing on analytics’, Thomas Davenport defines analytics as “the extensive use of data, statistical and quantitative analysis, exploratory and predictive models, and fact-based management to drive decisions and actions.” Analytics can range from a simple exploration into how many sales were made last year to a complex neural network model predicting which customers to target for this year’s marketing campaign.
Analytics is used in a variety of industries. Industries like financial services, retail and travel are naturally amenable to analytics as they generate a lot of transactions and hence a lot of data. No wonder these industries were among the leaders in adopting analytics. However, less obvious industries like manufacturing and sports are also making innovative use of analytic applications to drive competitive advantage.
India has become a global hub for analytics. Most US companies that have a significant analytics team have a presence in India. In addition, several Indian companies are providing analytic services to companies throughout the world. With increasing opportunities, the demand for analytics talent has grown strong.
| Career pathThe entry level role in the field of analytics is that of an analyst. This role offers you a chance to work on projects in a team, building expertise in the domain as well as the analytical tools and techniques. Basic knowledge of statistics is mandatory. You need to be familiar with widely used statistical concepts like p-value, probability distributions, chi-square etc. In addition, knowledge of common analytical techniques like logistic regression, clustering and decision trees is highly desirable.You will spend anywhere from 18 to 36 months in your first role before moving to the next level i.e. a senior analyst. If you have a PhD, you could directly join at this level. In this role, you will be expected to work independently on projects, even leading some of the smaller ones. You will continue to learn new methodologies as well as build domain knowledge.After spending another 2 to 4 years in this role, you will move to a team lead or lead consultant level. At this stage, many people will move into a people management track where they get to demonstrate their leadership and people management skills. However, some people with a more technical bent may choose to become subject matter experts (SMEs) instead. As an SME, you will provide leadership in defining and executing analytic methodologies for specific projects as well as develop new techniques to improve current processes. At this level, you will also be expected to manage most of the communication with clients regarding the projects you are working on.The next role in your career will be that of a manager. As an analytics manager you will be responsible for a team of 5 to 30 people. You may have 1 or more team leads working under you. If you are on the SME track, you may not have a permanent team assigned to you but you would be expected to provide thought leadership on individual projects.The next role is that of a senior manager followed by the Associate vice president (AVP).
Growth in analytics is largely merit-based. You would need to demonstrate strong quantitative skills and an analytical aptitude in the early years. However, as you move up the communication and people management skills become stronger differentiating factors.
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Popular domains in analytics
- Marketing analytics – Market assessment, Product feasibility study, Response / Profitability modeling, Sales Tracking & Sales Force Effectiveness, Customer Segmentation, Cross-Sell/ Up-Sell Strategies, Marketing mix modeling & optimization, Price and promotion analysis, Churn Management, Loyalty analytics
- Risk analytics – Acquisition strategy, Underwriting Support, Credit Line Management, Fraud Analytics, Collection Strategy, Portfolio Monitoring, Simulation, Loss Modeling, Product Mix Optimization, Demand & Residual Value Forecasting, Life Cycle Profitability, Liability Asset Modeling
- Biostatistics – Clinical trials, Pharma research
- Market research – Consumer Surveys, Industrial Surveys, Customer Satisfaction Scores, Segmentation Analysis, Trend Analysis
Studying analytics can lead to a high-paying career. Because it is an emerging discipline, there are still very few programs available to potential students. Those with advanced degrees in the field can differentiate themselves very easily.
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