10/07/2014

By Huw Bristow, CTO, Silver Lining Solutions

We live in a world which was shaped by the first industrial revolution, which saw manual power eclipsed by the intelligence and skill of human craftsmen automated by machinery. Today we are in the midst of a revolution potentially just as momentous, often referred to as the ‘digital revolution’.

Few would disagree that our ability to gather, manage and manipulate data on a previously unprecedented scale is already altering the way we live, work and play. The proliferation of embedded devices and the shift to online and mobile communications are enabling the gathering of masses of data at low cost and little effort. This has led to an explosion in the interest in data and its use by organisations.

Research conducted for Gartner earlier this year revealed that their most senior clients once again identified Business Intelligence and Analytics as their number one priority. For many organisations, this means big data. But whilst big data is the current ‘must have’, with companies enthusiastically harvesting more data than ever before, far too often they do not consider how to do anything meaningful with it before they start collecting it.

There is certainly a lot of data out there to collect. As consumers, we now generate vast - actually unimaginable - amounts of data. In fact, to give you an idea, I read recently that as consumers we generate 5 exabytes of data every two days (an exabyte is a billion billion bytes and if printed would fill 20 billion four drawer filing cabinets).

Just because there's huge amounts of data available, if we don't understand what we're looking for and why we're looking for it, it can confuse and mislead. Without a business focus and a specific problem to be solved, data of this nature is an ever-increasing distraction (and cost) to the business that isn't generating any related benefits. This is why we need to focus on “little” data: segments of data that are accurate, personalised, in context and aligned to business outcomes. Data that enables users make better decisions.

So where do you start? As with any performance improvement initiative, it is important to first understand your current position and define your objectives. You then use 'big' analytics to identify the drivers of positive business outcomes that will help your organisation achieve its aims. At an individual employee level however, knowing what those drivers are won't immediately allow you to understand what you need to do differently to get your own performance to the requisite benchmark. Individuals need to see data that is important to them, picked out for them from the big data.

This is where little data comes in, as it delivers the intelligence that pinpoints the specific skills, knowledge and behaviours that will help to improve those drivers. If you understand these links, you can pinpoint gaps in current skills, understand how employees compare to the average and what they have to do to improve and deliver the appropriate training and coaching. And if you are able to provide employees with the capability and autonomy to see where they need to improve and by how much, and access to resource to allow them to self-manage that improvement, this is a great example of Little Data in action.

A really important thing to remember is that this focus should be a continuous journey, not a one off. As individuals improve, and as a result the organisation's performance improves, continual analysis will show the measurable link between employee and business performance. It will also show how these drivers of positive outcomes change over time as the bar gets raised ever higher and will allow you to create a focused, continual professional development platform that equips your employees with the all the relevant resources and allows you to understand the return on investment of learning and development initiatives.

As an example, we were tasked by a global mobile telecommunications company to help them improve their employees’ performance. As a result of anaylsing the big data, the business achieved a 20% increase in sales conversions, a 16% decrease in customer churn, a 30% increase in same plan resigns and a 12% reduction in call handling time. The big data alone would not have achieved these returns.

This was achieved by pinpointing the causal factors of positive outcomes and by focusing performance improvement on the things (skills, knowledge and behaviours) that really made a difference.

Big data may be good at an organisational level, pulling together structured and unstructured data sources and "datafying" previously unrelated points, but at a more granular level, providing individuals with nuggets of timely, individualised and contextualised data that allow them to do their job better will have the more significant impact.

So rather than defining data by size, at Silver Lining Solutions we prefer to think in terms of Better Data, which is combination of insights generated at an organisational level (Big Data) reinforced and supplemented by specific, personalised data (Little Data) that allows organisations to understand and improve the link between employee behaviour and ultimate business outcomes.