It’s impossible to escape the terminology Big Data these days. It’s taken on faddish dimensions of popularity with various theories and ideas proposing the best way to tackle and manage the increasing amounts of information we generate and record. The reality is that most data is unusable to most businesses due to various regulations including privacy, intellectual property constraints and firewalls.

Even data in the public domain is hopelessly mismanaged and under-utilised. A recent (-ish, late 2012) report by IDC Digital Universe claims that only 3% of all potentially useful data is currently tagged at all, while less than 1% is effectively analysed. And that’s a global statistic. I can’t prove it, but I would guess Australia’s level of insight and analysis is much lower. It baffles me that we spend so much time on hype – let’s just roll our sleeves up and get on with it!

To borrow a concept from Nate Silver, we need to separate the Signal from the Noise.

All we need is analytics
Companies have never been able to manage their data effectively and technology has lagged behind the rate of data generation. Think about the effectiveness of every filing system you’ve ever worked with. When I started my career with a bank we had gigantic sliding filing systems which were operated by 4 people and even then I remember a constant pile of files and documents waiting to be organised or re-filed. And that’s only the data which actually made it to the filing system in the first place.

The potential of big data is immense, but it’s by no means clear or quantifiable. Think about the unstructured nature of data from sources like social media, customer correspondence, internal meetings, post-it notes and agile boards, and you’ll appreciate it’s no easy task. To truly harness the potential of data, companies need to associate all its sources of relevant data, both structured and unstructured, then analyse it and make that analysis accessible to the right people. In other words, it’s not big data, but analytics that we should be thinking about.

What is old and what is new?
The reality is that the key to any data management and interpretation problem has not changed. It’s simple: people. People create data, hopelessly mismanage it and then notoriously misinterpret it. To continue the earlier analogy, you may have the best filing system in the world but unless you have a document manager who can effectively lay their hands on the right file in quick time, your infrastructure is useless.

What has changed of course is technology. In the digital age we create such a broad variety of information through so many different platforms and we store and curate it in increasingly new ways. Much of it is useless to business but if you find someone with the insight and skills to work out what is relevant, you’re one step ahead of the competition. You can spend all the money you have on infrastructure but unless you have a culture and a team which values data, you’re wasting your time. Why spend time navel-gazing and contemplating the potential of big data when you could be doing so much right now with the right people.

Please don’t skimp on your people
Salaries are rising for analytics professionals. The prospects for someone with a strong mathematics and technology science education are amongst the best in the modern world. Check out this report from US Company PayScale which indicates that the top ten potential earning careers are all analytical. Both at the start and the middle of your career, you’ll earn more if you study science or engineering. Why should we be surprised by this? These people are eye-wateringly smart, they’re also becoming more worldly and confident in a boardroom.

So if you look at the facts of a digital business, data management and analytics should be your biggest cost. How effective every other part of your business is depends on how accurate, timely, accessible and relevant your information is. Your finance, HR, strategy, risk, operations, marketing and everything else hinge on the famous three Vs of information: Volume, Variety and Velocity. Yet so many companies undervalue analytics and pay better across almost every other function of a business.

We should be paying big salaries to analytics professionals and we should have a big budget for training and development. We should be creating more flexible workplaces and setting up paradigms which value analytical insights to encourage the best results for our businesses. So, what can you do with all these insights? Start by hugging your analytics specialist – tell them they’re doing a great job and give them a pay rise!