Well, I think that…
Thinking is good; few of us think often enough. Too many of us follow learnt behaviours without questioning whether they are effective or appropriate to the task at hand. But launching a statement with “I think that…” doesn’t guarantee any real thinking has been performed – and even where it has, “I think that…” usually means “I believe that…”, and belief is a strange beast. Belief takes us into the realm of faith; and so “I think that…” sounds an alarm for me which makes me hypersensitive to the words that follow; are they really the results of critical thought, or a regurgitation of ill-considered opinion?
Many organisations are being seduced by the hoopla whipped up and labelled as Big Data. A popular meme has evolved which suggests that the existence of huge volumes of extremely detailed data enables insight into human behaviour, needs and motivation; if we just tap into Big Data we can learn everything we need to know about our customers, potential customers, competitors, employees and any other group we’re interested in. The truth is that very few organisations have the capability to generate such insight from Big Data, and these organisations are utterly data-driven; they collect, create, collate, cultivate and consume data – it is woven into all of their working practices, powers measurement of all their activity and the information reaped from its effective management drives their planning, execution and thinking. These data-driven organisations eat, drink and breathe information and to enable this they place a high value on data and treat it is as precious asset.
The vast majority of our businesses, however, are not data-driven; instead we are opinion-operated – that is, we hold beliefs about our organisations and argue our case for change, or maintaining the status quo, based on these opinions. Some of these opinions may well accord with reality – they may be accurate, rational representations of our world – but many may not; and rather than reaching for evidence to support or deny these beliefs, we often posit them with false certainty and strength.
Opinion-operated businesses have little if anything to gain from Big Data.
If we desire the insight, certainty and vision of the likes of Google, Facebook and LinkedIn, and we covet their ability to divine success from Big Data, then we need to understand the forces at work within them; we need to appreciate the scientific approach that they deploy and learn to utilise it to become data-driven like them. After all, Data Science is just that; a scientific approach to the use of data, yet opinion-operated organisations prefer to consider it alchemy and entertain tales of data transmuted into insight through mysterious, powerful software tools. The IT industry has a long and ignoble history of building bandwagons and then jumping on them; Big Data is certainly the high-profile vehicle of choice for many at present, and much of the hyperbole simply serves to remind just how many false idols IT has served up over the years. The reality is that the scientific method – observe, hypothesise, test, measure and repeat – is neither mysterious nor magical and can be applied to any aspect of business. The problem is that it demands imaginative exploration of data, rigorous and critical thinking, falsifiable experimentation and carefully detailed measurement – requiring creativity, tenacity and perseverance.
In short, it is hard work without quick fixes.
There are no shortcuts to data-driven business; it is a culture, an attitude, which pervades an organisation and influences all resources, all processes and all decisions. It doesn’t replace opinions, but the difference between the opinion-operated and data-driven business is evidence; data-driven business can back up their opinions with a rich selection of information drawn from analysis of evidence, explaining the cases for and against, and presenting the reasoned understanding behind each opinion. Too often, the opinion-operated business relies on the legends of its industry, its own organisational mythology and an assortment of ancient texts – the vestiges of religion, rather than the continuous test-and-measure of science. Building a body of knowledge takes time, effort and effective management; data is collected and validated, information is synthesised from its careful analysis, and knowledge emerges from shared understanding of information once it has been appraised, considered and communicated.
This is a dynamic, continuous process; scientific knowledge is always on the move, seeking greater understanding through challenging the status quo and looking for better answers to questions posed. Data-driven businesses understand and accept this – there is no sitting back on a job well done, carving lessons learned into stone tablets – assumptions are challenged, new hypotheses derived, tests defined, evidence gathered, results measured and analysis discussed. The process goes on; the body of knowledge is refined, understanding evolves and results continue to progress.
So to move from opinion-operated to data-driven takes time and commitment, but it makes little sense to dabble in Big Data without such a commitment – oases of evidence-based reason amid a desert of faith-based superstition are weak resources and prove too little sustenance for our travels. The spectacular rise of data-driven businesses over the past fifteen years suggests that whilst the journey is arduous, the destination is more than worthwhile.