Big data, data scientists, BI, modeller and countless other fancy roles continue to scream out loud to anyone who is scanning any media today. The excitement of challenging times, the lure of big packages and career path, the possibility of hobnobbing with the decision makers, the tag of “genius” and many more silver linings adorn the profession. The insatiable demand for talent in the data space is no hogwash either. Reports from analysts, sectoral studies, recruiter briefings and the horizon gazers – all endorse analytics as the progression of the future http://www.itwire.com/it-people-news/enterprise-staff/69065-data-scientists-in-hot-demand-in-ict-market . Endorsing the demand is also the fact that anyone and everyone has already launched a program in analytics or is planning to launch one soon. You can even find a series of open resources to learn the subject – http://www.analyticsvidhya.com/blog/2015/07/big-data-analytics-youtube-ted-resources/ . But then, a serious word of caution here, not all paths lead to the Eden of analytics.
Analytics today is more a core skill that cuts across any business discipline as it deals with better decisions. Any professional with an aspiration for growth needs to master this skill. As the information technology matures, more data is available to the manager to make a sound business decision. What seems to be lacking is the managers capability and understanding of the dynamics that impacts any decision. A course in analytics holds the promise to provide this competency, but there are a few caveat that need to be followed. This note attempts to highlight the same.
Decision making hinges on five critical pieces – understanding of the situation (context), influencing factors (variables), the controllable parameters (decision variables) the desired goals (outcomes) and finally the panacea – (actionable insights). While there are tools, technology, computational power, connectivity, algorithms and frameworks that enable this process, the most critical piece is an anxious, fertile and dedicated human mind – because Note 1: All analytics is not machine learning! Very simply put, a machine can only process the past data with identified set patterns. An insight can only be derived and recognized by a primed and willing brain. Unfortunately, there are no shortcuts to learning this.
Action insight – Chose a program that gives equal weight to the problem solving skills as the tools and technology side
Decide as a word has its roots in Latin dēcīdere; literally – to cut off. It is very similar to words like homicide, insecticide which primarily denotes pain. The process of decision making is really painful as it involves killing some of the options one has. Note 2: All about analytics is not enjoyable and rosy! It involves supporting some hard choices and making hard choices. Not always will you have the perfect information to make the perfect decisions, however, the outcomes will show no mercy if your choice was wrong.
Action insight – Chose a program that allows you practice in realistic scenario with realistic data sets and simulations
In businesses, decisions are very involved and a continuously challenging process. Do not mistake this challenge as any edge of the seat thrills or adrenaline pumping experience. Neither is it an experience of “eureka” giving you a high. It is rather repetitive, expansive and thankless experience. Every time you make a wrong decision, it would be known, but the right decisions would be expected and hardly acknowledged. You would need to ask seemingly obvious and stupid questions, you will need to revisit every detail multiple times just to ensure that you are not misreading or ignoring any facet. Note 3: Analytics is about getting into the murky details! It often needs one to sift through mountains of data which a typical mining tool has missed because of the assumptions made in writing the mining algorithm.
Action insight – Chose a program that helps you develop immense patience and attention to details
When one analyses, the interest is to be able to accurately predict the future. You would be surprised that the same data when analysed, would communicate at least 13 different things if there are 12 people in the team. We all carry our own biases and stereotype of the world. Note 4: Analytics is about challenging your own and other people’s biases! It requires a great degree of conviction to challenge the convention. It is also equally critical to be able to question every assumption and even the established norms. One needs to be able to see possible connections where none seem to exist to a less inquisitive mind.
Action Insight – Chose a program that pays equal attention to building your analysis and reporting skills
Last but not the least, the value a business attaches to any analysis is the impact of the action it leads to. Analytics is most certainly about actionable insights. One needs to be able to connect the models and mathematics to the reality and plan actions based on them. Note 5: Analytics is about action, it is equally important that the action is clearly outlined with the assumptions that have been made to implement the insight. What are the possible risks and challenges one could face in implementing it? Also important is to understand the actual performance of the process/decision affected by the action insights and ensure that adjustments, modifications or sometimes even drastic measures are planned based on the outcomes.
Action insight – Chose a program that clearly makes action the primary driver and the learning outcomes are clearly linked to the actionable insights
Having outlined the caveat, it is also important that I encourage you to gain a higher perspective to a career in analytics. Any decent analytics program would generally offer that as long as you have done your homework in fact finding, understanding and evaluating the analytics as a career option. It would give you a structure to make better decisions in general and it is your own efforts to learn to apply it to making a better decision about your career choice as an analytics professional!