Using a biblical quote ("Lift up a rock and you will find me there"1) as a metaphor for big data may seem farfetched yet it is a surprisingly fitting description of the omnipresence of data in businesses. Understanding that businesses and their customers generate a digital footprint at every touch point is an important starting point but linking these prints to solve specific problems is the true magic of the big data revolution.
The challenge is how you get from raw, incomprehensible data to information that offers a basis for making smarter, more precise decisions that can have a profound effect on the business.
Another reason for using a biblical quote is that analysing information for the purpose of decision-making has existed since the beginning of time. As a former investment analyst, data crunching for the purpose of arriving at buy and sell recommendations was my norm. But just like how the majority of business decisions are made, my decisions were as much based on gut and intuition as they were on data and rigour. The influence of qualitative data over quantitate data more often than not resulted in sub-optimal decisions. The big data revolution has changed the playing field and created exciting opportunities. With it, however, come challenges.
Our goal is to solve specific problems better, faster and more efficiently than we were able to before.
Ninety percent of business leaders expect that big data can dramatically change how they do business according to a recent survey conducted by Accenture2. Yet despite the fact that big data is a mainstream idea it is not mainstream in practice.
The reason for this? Very few companies have the in-house expertise to translate all this data into actionable insights. The experience of managers wrestling, often unsuccessfully, with the ever increasing amounts of data and sophisticated data analyses is often the rule rather than exception. "Traditional” businesses often disregard the power that analytics could have on their own businesses because they were not born digital.
To extract real value from a big data strategy, buy-in is required from the top of the organisation. This might require a mind shift in the traditional sense but it is fundamental that the organisation aligns their goals with that of their digital strategy. Big data is often mentioned but rarely actioned. Implementing a big data strategy is no mean feat. There is an obvious investment required in resources, technology and tools.
Successful data analytics stories are often found in surprising territories; we just need to turn the right stones to see them. One of the most interesting applications I found has been in law enforcement. In the Memphis Police Department analysing historical crimes to predict where future crimes are likely to happen cut crime by 30%3 and in the Detroit police department analysing slang used by criminals on social media led to a noticeable reduction in crime.4 Both these examples started with the precise goal of reducing crime. The means to achieving their goals was through a well defined big data strategy.
In summary then; implementing a big data strategy starts with commitment from the top that runs through the entire organisation. We need to understand that big data is not a magic bullet with the solution to our problems but rather the means to an end. Our goal is to solve specific problems better, faster and more efficiently than we were able to before. We do this by identifying what problems we are looking to solve and then work backwards by identifying what data has the potential to give us the answers and where that data resides. While it is easy to get lost in the detail and get overwhelmed by the volume and velocity of data and the skillsets and technologies that are required there is definitely help to be had.
What data is hiding under your company’s stones?
1 The gospel of Thomas saying 77b