Big Data 2.0 Will Be The Trend To Watch in 2017. Is Your Business Ready?

I’m pleased to see that Big Data is starting to become more and more like business as usual for many companies, including Hays. And, although the journey has undoubtedly been harder than any of us initially expected, it’s great to see how organizations are now taking the steps needed to develop and upgrade their staff, toolset and the amount or type of information they collect, to enable them to really take their data capabilities to the next level.

As a result, I believe that we’re on the threshold of moving from Big Data 1.0 to Big Data 2.0, and significant, real benefits will soon be commonplace across the business world. I see 2017 as a landmark year for data where those companies that take the right steps will be best placed to reap the rewards, both in the next twelve months and beyond.

Businesses that believe they can invest X amount in a data program and yield results within months must rein in their expectations and take a more realistic, measured and long-term approach

So what should your business do to ensure it’s ready to take full advantage?

Is Your Data Big Enough?

The most crucial issue to tackle will be to redefine our expectations – and understanding – of Big Data. Many companies that have experimented with data in the past have often been short-sighted, looking for an immediate return, or demanding an explicit business case for each data point being collected.

Data’s biggest opportunity, however, is to identify hidden patterns that allow a business to outperform in the future, and correctly highlighting these patterns requires comprehensive data that spans a long time. This cannot be built overnight.

For example, here at Hays, we first launched OneTouch, our single master database, back in 2008. OneTouch tracks and logs every aspect of our executive recruitment business, from our own day-to-day engagement with clients to candidate application history and interview success.

We initially intended it to serve as a global bank of candidates, but with seven years of data now available, we’re approaching the stage where we can begin using this information to identify patterns and answer complex questions about our business and market.

Based on years of previous behavior, we can get a deeper understanding of a likely outcome if we engage with a client in a certain way, or how candidates in different sectors are likely to react to job negotiation or perform in an interview, and ultimately enhance the service we provide to candidates and clients.

It has taken years to reach this point, and we’re still only scratching the surface of what we can do with this information. Businesses that believe they can invest X amount in a data program and yield results within months must rein in their expectations and take a more realistic, measured and long-term approach.

Big Data needs to be big, and many companies have simply been trying to change the world with a small pool.

Do You Have the Right People?

The extent to which businesses can take advantage of Big Data will depend on the people they recruit. This has sparked a war for talent. The value of data scientists is only set to increase in the jobs market.

But I believe that you can’t just drop these technically skilled employees into a silo department and expect them to revolutionize your business. The ability to analyze data and perform the hard, specialized role is obviously important, but these specialists also need to be able to communicate and translate what they have learned with the rest of the business.

Even more crucial, however, is that the wider company should be data literate and understand the potential and limits of the technology.

You need data-savvy people in all of the traditional functions – accountancy, marketing, sales – who can act as a bridge between this wealth of information and their own department.

Cross-specialism candidates are becoming increasingly common. Here at Hays, we have people working in our marketing or finance arms who come from hard data backgrounds. They have taken up a more traditional function, yet still have a foot in the world of technology.

By working alongside each other day-to-day, they help others in the department understand data, what they can demand and how they can implement it into their more traditional function. 

Technology works best when it complements, rather than replaces, the human element in business. AI is unable to judge cultural fit or soft skills, or negotiate with candidates

Do You Have the Appropriate Tools?

Many companies fear that, to achieve this cross-business understanding of data, they’ll need to invest heavily in training every employee. If your business’ data is only accessible via complex coding and processing functions such as SQL queries, then of course the average employee will require relatively intense training to be able to even input or extract data day-to-day.

On the other hand, if you invest in a modern analytics platform, your staff won’t need to know how to write code or program – they can often simply drag and drop items to log data, search the platform intuitively to identify specific information, or produce simple visualizations of complex data.

By focusing on making the most appropriate tools available, you can make data accessible for everyone in your business.

Developments in artificial intelligence (AI) and machine learning are also set to move the data debate on in 2017. Companies that invested in data years ago will now be looking at how they can make the most use of these large information banks, and AI provides the opportunity to set a simple end goal and have the computer learn and formulate the complex solution, whether that’s quickly analyzing mountains of information or scaling calculations or predictions accordingly.

For example, here at Hays, we can use our data to identify a client’s ideal candidate through patterns in job history and qualifications, and create a succinct shortlist of candidates from a database of ten million. Put simply, AI makes the impact of Big Data even bigger.

Of course, technology works best when it complements, rather than replaces, the human element in business. AI is unable to judge cultural fit or soft skills, or negotiate with candidates – vital workplace ingredients – and so at Hays there will always be a role for people.

But with the opportunity to scale activity to such a dramatic degree now possible, businesses can combine these tools with the tech-savvy personnel who can best utilize them, making both sides more effective and ultimately impacting bottom lines.

Big Data 2.0

Many may still regard Big Data as the latest example of business jargon, but I expect 2017 to be pivotal year that will go some way in silencing the data doubters.

Companies will begin seriously considering how they can accurately capture the information at their disposal, and those organizations that started the process years ago will turn to new developments in AI to make use of the wealth of data at their disposal, moving us firmly into the world of Big Data 2.0.

Those organizations that disregard data do so at their peril. If companies don’t use 2017 to hire vital tech natives, train existing teams or invest in the right tools to collect, interpret, analyze and act on the information available to them, they will only fall further behind their competitors.

Disruption never ends and I have no doubt that this year will see fresh, innovative ways to exploit data. But if your business isn’t even on the data ladder now, how will you keep up with your competitors when they grab the next rung? 

About the Author

Steve Weston is Chief Information Officer at Hays, a global executive recruitment firm. This article first appeared on LinkedIn’s Influencer blog.

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