Making your data work for you - analytics in a big data world

Data analytics is taking hold because a spreadsheet simply doesn’t cut it in today’s business world. During an era when commerce and professional services were conducted in slow motion, the old real-time, knowing how your clients or customers behaved last month was probably fast enough (at least as fast as everyone else). Now the world acts in ‘internet-time’, knowing what your customers did last month is akin to having a doctorate in ancient history.

Organisations today look to an ongoing, dynamic, and flexible use of information to make better – faster – decisions. In short, the ability to make sense of your information, and that around you unlocks greater business value and enables you to know where and how to find your organisation’s ‘certain something’. With that objective in mind, it’s not hard to see why now is the time to set your data to work…

The Scale of Big Data
If you’re an average mid-sized firm, you’re likely to have around 20 Terabytes of live data storage capacity data in total. Yet, all that data is barely being put to use – some estimates suggest that 90% of all information in an organisation lies unused once 90 days have elapsed since its creation. That unused data is a goldmine waiting to be tapped to better understand your business opportunity and inform decisions. And it’s a big goldmine.

But when did plain old data become ‘big data’? As ever, in an IT industry that favours buzzwords and hype, definition is something of a moveable feast. However, if the amount of data you now have is greater than the capacity of the applications you’re using to try and make sense of it, it’s fair to say you have a ‘big data’ challenge.
The Speed of Knowledge

That ability to rapidly understand and act is the key. Organisations of all persuasions need to act quickly; a sales team needs to know when prospects are at their warmest, humanitarian NGOs compete aggressively to be first at a disaster scene, automated trading systems need to know the signals that indicate whether to buy or sell stock and so on.

The objective here is to set the information free and make it work for your business, clearing the way for decision-makers to analyse it and enabling you to make the right choices. The organisation that can act quickest wins.

Predicting the Future
The holy grail of analytics is to move from analysing the past to predicting the future. That development is already a reality in many areas of our lives –used to predict everything from the likelihood that we will default on a loan, to the risks of us developing heart disease.

For business, this means informing better decisions and investment planning based on real insight, delivering value where it matters – in driving the business forward.

The key message for business leaders today is don’t ignore the data you already have or you risk being left behind. If you have all this data and you don’t reuse it for the benefit of your organisation in the future, then why did you create it in the first place?

Starting down the road
If we look at the basic approach, a great starting point is The O.O.D.A. Loop – the process that defines how humans react to stimulus. It’s a practice we all go through thousands of times in a single day and also holds true for how the business should react to information stimulus.

Observe: collect as much situational data as possible

Orientate: analyse to form a coherent view

Decide: use that coherent view to decide on a course of action

Act: enable your organisation to act as effectively as possible

However, trying to analyse a new world of big data with old tools diminishes the value of that data – and leaves those who can to observe, orientate, decide and act faster in a competitive situation.

The ‘right’ analytics solution for you depends on the nature of your organisation, your customers and the business imperatives that will define your success in the coming years. Ask yourself ‘what do we really want to use data for?’ and then find the tools you need to make that data work for you. In general, analytics tools are split into two solutions areas:
1. Those that consolidate existing information so companies can ask the ‘why’ question.
2. Tools that combine predictive analytics and business rules to optimise and automate the millions of small decisions made every day.

There’s no doubt that firms have to start down the road to analytics, not least because customers increasingly demand it. So, in the coming years, analytics will move from an ‘executive indulgence’ to a ‘must have’. The organisations that win will be those that use analytics intelligently to find out what their ‘certain something’ is and act upon it. Because it’s all in the data.