Big data, statistics and decision-making

big dataBusinesses should always be aware that statistics can be manipulated and that analysis of so-called big data sets is a complex process that produce highly variable results.

Big data is defined as enormous amounts of complex information that can only really be processed using extremely powerful software using multiple servers.

While it can, over time, reveal trends, it is also subject to variability as data flows can be highly inconsistent with periodic peaks and troughs.

Interpreting the data

Then, there is the problem, as with all statistics, of drawing useful conclusions that are not skewed by what is selected and what people want the data to show.

A good example is the acceptance that a majority of the UK, 52%, voted in favour of Brexit. Actually, 52% of those people who voted were pro Brexit equating to roughly a third of the population.

There is no doubt that the vast amount of information available from big data collection has the potential to offer businesses power full insights on behavioural trends that can help them to make decisions.

However, this is only helpful at a broad level, such as driving general policy.

Business decision-making also needs to be underpinned by a much more granular analysis and understanding of its sector and its customers’ behaviour and desires.

Here, such factors as location, average income in that location, attitudes, personal tastes and preferences, are likely to play a significant part and are crucially important in determining how to pitch the marketing or sales messages at a particular target audience.

For example, US consumers appear to have no problem with repetitive, lengthy and “shouted” messages from businesses trying to market their products or services. In the UK, however, such tactics are seen as intrusive or even bullying and likely to have a negative effect.

Successfully integrating the broad brush of big data trends with the more granular and specific data collection is the key to business success, particularly for SMEs.

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