Orchestrating symphony from noise

The Big Data debate rages on. But while it’s good to talk, noise is not something we need more of. It’s time to get smart – and to orchestrate the data you have.

The siren call of big data has convinced the majority of marketing leaders that data holds the key to success in the digital age. Yet few believe they’ve had success in delivering on the promise, citing as the main obstacle the difficulty in wrapping their arms around the vast amount of customer and marketing data needed to provide a true one-to-one customer experience.

Moving from quantity to quality to action
Of course, data is indeed an immensely powerful force in contemporary marketing. But an ongoing debate about volume, velocity and variety misses where the value lies. Given that the quantity of data will only increase exponentially as digital development continues apace, aiming to embrace it all is an unrealistic expectation.

Asking the right questions of relevant data is smart – orchestrating data from selection through collection to application of insight is smarter still

A more effective strategy focusses on asking the right questions of relevant data – and most importantly of all, applying the insights gained to improve the customer experience.

The need to acquire and analyse relevant data places ever greater importance on the human aspect of the data analytics process. From collection, to segmentation, to the creation of models and the application of insight, interpretation is as important as the data itself.

Who is interpreting the data?
If one accepts that the ever-increasing quantity and complexity of data means one can rarely see the whole picture, it is just as true that one is unlikely to get a clear picture.

So, the data has been collected and processed and modelled and analysed. Now everyone wants to know what the data is saying, and more importantly, what it means.

Each time the question is asked, the story changes a little. At every stage of the data journey, interaction adds another layer of interpretation. By the time the output arrives, it’s been cut a hundred ways and more, each cut colouring the picture to a greater or lesser degree – a shift in emphasis here, some subtle shading there.

Visualisation – the art of data analysis
Which brings us back to human interpretation and the benefits of a skilled operator. We’ve said it before: a data artist (rather than a data scientist) takes the output and turns it into consumable theories and hypotheses that can be tested and applied, delivering fresh insights that actually help an organisation meet its goals.

Data and human insight are not mutually exclusive. Any data is only as valuable as the information and insights we can extract from it – only these interpretations will help us make the right decisions to meet our objectives and secure a competitive edge.

Asking the right questions of relevant data is smart – and orchestrating the data from selection through collection to application is smarter still. Some look to the data geeks to fill this space, others advocate those with a more entrepreneurial bent, perhaps even a dash of flair. A choice which essentially boils down to whether you want monitors to watch over the data and report anomalies, or a conductor to orchestrate the data, someone who can shape symphony from noise.