ENGAGE

Some of us at Motivforce have been avid Star Trek fans since our early years. Mind you, not the super nerdy types who glue on pointed ears and pretend to chat via chest-fitted communicators at conventions. Nerdy enough though, to sometimes use the show as a frame of reference when confronted with the realities of work life. As we are in the business of client engagement, our favourite role model is of course Captain Jean Luc Picard. In virtually every episode, this charismatic leader gazes at the galaxy, lifts a finger to point it at a random planet and tells his crew to ‘engage!’ However, engaging does not always mean jumping to warp speed. Allow us to explain.

Many of our clients are warming up to the potential of Big Data, as they have an abundance of digital data from many sources, such as smartphones, sales databases, geographical production data, point redemption figures, social media opinions or even weather forecasts at their fingertips. Data that can be mined with smart analysis tools to provide data-driven insights (set to stun) for real-time decision making and tracking of shifts in customer sentiment. Indeed, Big Data holds warp speed potential for loyalty programs, but much of its progress has to be taken in foot-dragging steps, as important bottlenecks must be overcome. In our quest to debunk Big Data myths, may we draw your attention to an important fallacy that we sometimes encounter when talking to clients. The fallacy that one can deploy an algorithm on to a volume of raw data and have deep insights into program performance pop up automatically (there must be a button on the console for that!).

The reality of Big Data is that it needs to be cleaned, converted, wrangled and mangled, laundered and trimmed before it can be mined, analysed and meaningfully interpreted. This is a process that is sometimes painstakingly slow and, believe it or not, often involves a lot of manual labour. Client data is seldom ready to be analysed or put into our R-Cube to churn out those colourful plots and decisional pointers. For example, an unruly client data-base containing over 600,000 records and 22 ways of spelling a business partner’s name requires elaborate data janitor work. Moreover, verbatim data from social media posts about learning modules is unstructured and contains hidden and between-the-lines meaning. At Motivforce R&D, we constantly face the challenge of how to uncover this meaning. We refer to this as the Big Data’s gravity problem, alluding to the fact that while everyone’s attention is focused on exploring unknown worlds, there is a lot of unseen toll and hard work that drags us back to earth.

Just as spreadsheets have enabled non-experts to execute financial analysis, we are now witnessing the emergence of easy-to-use dashboard tools that enable our clients to monitor their programs in great detail and make real-time decisions. An important challenge is that we engage with our clients to make sure that they connect the right dots and obtain valid insights. While it’s exciting to boldly go where no loyalty program has gone before, our programs also need to live long and prosper, as Vulcan logic would dictate. That is why we feel it is important to keep treating Big Data in a down-to-earth manner.