Using Big Data to Make Better Business Decisions
Big data was traditionally thought of in the context of areas, such as sensor networks, call records, military surveillance, complex scientific research and the like. However, in recent years its definition has been broadened to include data arising from social networks, Internet search and large-scale e-commerce, which are the focus of this post.
McKinsey, Forrester, HBR and the Economist have offered expert commentary on the wealth of big data in this new, social context, as well as thought leadership on how it can be mined and analysed to create strategies that touch upon a range of business functions. The salient point all make is that big data impacts not only the usual players in social, such as marketing, PR, sales and customer service, but areas as diverse as supply chain, R&D, HR and much more besides.
We have been forced to broaden the definition of big data thanks to the growth of User Generated Content (UGC), the impact of which means we now create as much information every two days as we did from the dawn of man through to 2003. The unstoppable surge of content and data has contributed to what we are now calling ‘information obesity’ and led Edelman’s Steve Rubel to coin the term ‘Attentionomics’; focusing on the difficulty of cutting through the noise to captivate people’s attention, amid infinite content and finite time in the big data age.
But how do you go about using big data to make better business decisions?
Listening tools like Radian6, Sysomos and Synthesio are fantastic for reporting and evaluating external, digital marketing activity. However, there’s an unrealised opportunity for organisations to utilise these tools to mine data and extract meaning from online conversations to support their internal, operational and strategic decisions which can help them evolve from a social brand to a social business.
Navigating the complexity of big data and formulating social business insights is not easy though. It’s an emerging area that requires a broad and changing skill-set, meaning that all too often organisations can be data rich, but insight poor from their listening efforts.
Amongst all the discussion about big data there are already some fantastic examples of organisations leading the way and utilising it to make enhanced decisions for themselves or their clients.
Recorded Future is a software company with CIA and Google funding that specialise in web intelligence and predictive analytics. They have developed something called a ‘temporal analytics engine’ that scours the web to find relationships between people, organisations, actions and incidents so they can more accurately predict events, such as outbreaks of disease, terrorist threats and economic swings.
Another good example of tapping into social data to make better business decisions is that of Derwent Capital Markets. Using listening technology they compares fluctuations in the online national mood with stock market movements, the results of which help guide investments.
Thirdly, some major supermarkets are already using data mined from social media to enhance their supply chain. By studying local online conversation they are able predict demand and determine new products they should stock.
This trio of examples show how organisations are beginning to use big data to make better decisions and offers an exciting look into how online conversations may be used to predict offline behaviour in the future.
Although, we are only at the beginning of this journey, the potential uses of big data are wide, varied and exciting. For me, this is where things get interesting and it’s great to see big data rightly used beyond its traditional application in communications strategy to now guide the business one too.