As a sector, media & entertainment has a lot to gain from the use of analytics in decision making. As M&E professionals, we have to be malleable, nimble and open-minded if we have to continuously delight our consumers.
‘…but you don’t understand, how do I quantify my instinct? I run a business that’s creative; all about heart-felt passion and human emotions. What mathematical model can predict the magic of a smile?’
As a former management consultant and software programmer, this is a response I’ve come across only too often. As counter-intuitive as it may sound, it’s actually the best spiel I’ve heard in favour of big data and analytics.
It’s a lot like riding a motorcycle on a winding road. The wind is perfect, the traffic minimal, and you’re immersed in a therapeutic experience. If you’re an enthusiast you’ll know the gears without even looking at the display panel. Why, then, do most motorcycles come with elaborate panels and indicators? The answer is two-fold: (1) there’s simply too much at stake to rely purely on instinct, and, (2) an objective, real-time data point is far more accurate and reliable. It’s not a competition between man and machine but a confluence of the machine’s insight with human judgment to arrive at the right decision at the right time.
Let’s start with the ROI
A recent McKinsey & Co. study across Europe, Americas and Asia found that companies championing the use of customer analytics are 7.5 times more likely to outperform their competitors on sales and nearly 19 times more likely to achieve above-average profitability. Media is fundamentally a consumer business. Just imagine the impact for the sector, if only half of the above stats are true.
The Big data conundrum
A big challenge that media companies face today in their analytics adoption journey is in their ability to draw ‘coherent and actionable’ insights on their consumers from large sets of unstructured data being captured every minute across multiple touch-points.
For example, in the case of a TV broadcaster, consumer data is fed from multiple sources in various forms – viewership ratings, social media preferences, primary research surveys to name a few. While the quantum of data is a challenge on one hand, it is the sheer variety of this data set - GRPs vs. textual comments on social media vs. survey responses - that presents the bigger challenge to derive a coherent set of insights. Remember, the ‘Big’ of big data is as much about variety as it is about volume. The result – media executives end up looking at a subset of this data, which they find convenient to interpret, to draw insights for their decision making.
Thanks to technology advancements, it is now possible to solve this conundrum through the adoption of advanced analytics & visualization tools, and generating insights on the click of a buttons, yielding high power to decision makers.
Success lies in cultural embedding
But people have tried in the past. Some have succeeded while a large number have seen their analytics initiatives fiddle out within the mesh of personal egos, poor execution capabilities and resistance to change. What can be done differently?
First and foremost, big data analytics needs to be pursued as a CXO-level agenda. It is important to have a senior executive sponsor – someone who can traverse through the organizational breadth and depth and act as a true evangelist. Secondly, those driving analytics should be able to appreciate business nuances and always keep sight of the business impact – the moolah – rather than being caught up with mathematical models. Finally, investment in training frontline employees on the effective use of data models is vital. It is they whose life gets affected the most and without whose appreciation and understanding, any such initiative is bound to struggle for breath.
The M&E sector is undergoing a paradigm shift in this new-age, data driven economy. It is time that we shed our inhibitions around big data analytics and look beyond our self-created cocoons – our friends in other consumer sectors, e.g., telecom and banking, have already made big strides in this space. What can we learn from them? It’s the same consumer they are targeting, after all.
Creativity forms the bedrock of our profession. That said, we exist to serve and delight our myriad audiences. Mathematical models may not be able to predict the smile on our consumers’ faces, but they can certainly help us in getting more of them to smile, more often!
The author is Strategy Head, Viacom18 Media