The rising dominance of analytics

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Analytics has become an indispensable tool that helps in corporate decision making. Read on for more details from Gautam Munshi, on how to crack the code as a data analyst

The last hundred years have witnessed a rise and dip in various professions, professions that have fuelled revolutions of their time. Pre-independent India saw lawyers at the helm of the independence struggle. The mid-sixties saw the rise of the engineer and the scientist which led to some of our greatest revolutions such as the green revolution. The eighties and the nineties saw the domination of information technology and financial market professionals. The 21st century is now at the onset of an analytics revolution.

Analytics is the art and the science of comprehending data in its enormity and discovering patterns in them and using these patterns to predict specific performance indicators to a very high level of accuracy. Statistical techniques and sophisticated algorithms, when applied on the enormous amount of data that is generated today can identify patterns, correlations that would otherwise be lost in the dataset. On analysing these patterns and correlations, new, powerful and game- changing insights can be garnered, giving decision- making a whole new dimension. Therefore, analytics in its sophistication nullifies decision-making based on gut feelings, and instead allows one to make data- driven decisions. It is this aspect of analytics that will bring about a transformational revolution in the present business sphere.

Big Data, as the trove is called, has given rise to a new profession, that of the analyst. A profession that a McKinsey report suggests will see a huge increase in popularity and demand as organisations are increasingly depending on data-savvy analysts to gather their data and turn it into meaningful information from which powerful insights can be garnered.

So what makes an analyst? A curious and detail-oriented mind with a working knowledge of software tools such as SAS, SPSS, R, Hadoop and analytical techniques such as correlation, regression, cluster and factor analysis, etc., makes a good data analyst.
Advancements in the analytics industry are closely related to the advancements in technology. This  in turn requires a data analyst to have a good grasp of the latest technology. But a great analyst is one who is also committed, one who goes the extra mile, one who is creative and has a good business sense, all of which, put together, will help him/her make an informed and intuitive observation.

The rising dominance of the analyst can also be explained by the fact that analytics is not limited to any one field or domain; instead an analyst’s expertise can be applied across the board from education, manufacturing, marketing to HR, finance to travel and tourism. There simply is no boundary to the industry eligibility of an analyst.  

In the pharmaceutical industry, analytics has been in use for a long time now, but the speed at which this data is collected, analysed and the insights executed has seen drastic change. When earlier it took about two months to collect, analyse data and derive insights, in the present day, the same tasks can be carried out on a weekly basis if not on a daily basis. As a result of which, the effectiveness of strategies can be measured almost in real time, customer trends can be picked up immediately, clinical trials are no longer lengthy processes, and it allows for resources to be allocated efficiently.

In HR, professionals are increasingly turning to predictive analytics to gain meaningful insights from the HR data collected from various sources. HR professionals are use analytics to predict the effectiveness of hiring, performance of employees and attrition decisions are now made based on data.

In the manufacturing industry, the Germans and the Japanese are pioneers in the application of statistics and analytics to innovate, design and improve the manufacturing process. Analytics built into the manufacturing process allows for continuous improvement, quick detection of defects, easy identification of customer trends, and all this has had a significant impact on saving costs.

In marketing, analytics is applied to identify potential customers of a product or service, the size of the market, the profitability of the market. The concerned team, or member analyses market data and supplies the information that affects inventory planning, procurement decisions, branding decisions, workforce planning, promotional programmes, etc.

Analytics is widely used in the financial sector too. Banking analytics solutions are designed to help banks with operational activities like customer acquisition, operations and risk management. Predictive modelling of customer behaviour and scoring techniques enable banks in answering key questions of profitability and minimising default risks.

The scope for growth in the analytics industry is tremendous. For example, every organisation today has a website, thereby making way for web analytics to measure their online performance and ROI (return-on-investment). Every organisation, thus, creates a need for an analyst. But the analytics industry is still an up-and-coming one and the talent pool that is available is not sufficient to meet the demand.

(The contributor is CEO of Redwood Associates.)