http://www.personneltoday.com/hr/big-data-hr-needs-stop-reporting-start-predicting/

Big data offers HR some major opportunities to increase its strategic influence within the organisation and add value to its processes at all levels, by delivering predictive analytics.

Big data might seem like an HR buzzword, but it is one that will not go away – and one that HR should not ignore. The phrase refers to the huge volumes of data being generated in the modern world, and how we use it. Helping HR use big data to its advantage was the topic of a recent webinar from US blog Fistful of Talent, hosted by HR tech bloggers Steve Boese and Kris Dunn.

To harness big data, HR needs to change how it collects data, and to hire more data specialists, said Dunn. HR must also change how it uses data – it needs to stop reporting and start predicting. The biggest opportunity that big data offers to HR is in predictive analytics around high-volume, repeatable processes, such as recruitment.

Dunn and Boese offered practical suggestions for ways in which HR can start to use big data right away.

First, HR must identify the data it has. A good initial step is to draw up a schematic of available data on former, current and potential employees (within the boundaries of data protection legislation, of course). This creates the necessary volume of data to enable data modelling.

Second, make sure the data is relevant to the target audience. What metrics do the senior executive team need to see?

Third, scoreboard the data. Create tables that break down what big data has to say about how specific departments are performing, and are likely to perform. Fail to do this and the view of HR will never change, says Boese. To get the organisation to care about data, set up scoreboards and be ready to use the data they provide – against people, if necessary.

Turnover data is an ideal starting point for HR big data use, says Boese. Traditional turnover reporting is backward-looking. HR can take turnover data to the next step by annualising the data it already has to produce predictive analytics, projecting turnover for the coming month and the coming quarter. Employee age and tenure are likely to emerge as the two key factors influencing turnover. HR can use big data here to create a “relative risk of turnover” score for all departments.

How HR can harness big data

Accessing data should not be a problem for most HR departments, said Dunn. HR has plentiful access to data, for example payroll records, or data on absence and staff turnover. It needs to be more purposeful in collecting this data.To capitalise on big data, HR needs more data specialists. There are two types of HR professional, Boese suggests: “the cop” (specialising in compliance and enforcement); and “the assassin” (agents of change and disruption within HR). HR is conservative by nature, thinks Boese: around three-quarters of HR professionals are “cops”. He argues that “the assassin” is better placed to harness big data – but HR needs an even mix of both types if it is to function.

For HR to master big data, the profession needs to learn how to handle data in both structured and unstructured formats, he continued. Structured data is data stored in a system in a defined, orderly way (such as traditional absence records). Unstructured data is data spread across multiple media and lacking unifying structure (such as video CVs and social media discussions).HR needs to consider the three “Vs of big data”, said Dunn: volume (the huge amount of data being generated); velocity (the need to analyse and act on big data insights quickly); and variety (the ability to handle data in a range of formats). Others also introduce a fourth V, veracity, which ensures that the data is reliable and accurate.

COMMENTS

A very interesting article and some great comments that reflect some of the insights included in ADP’s new report – 'Big Data in HR: the big questions being asked'. Our discussion also focuses on the need to up-skill HR professionals to be able to handle, analyse and use data effectively, as well as ensure it is structured in the right way to be useful. Relating to the skills debate mentioned, Matt Stripe the HR Director at Nestle, told us that his organisation has introduced a team of big data specialists, whose role it is to feed data insights to the core HR team – so this could be one solution, as Adam has suggested in his comment.

Another challenge we identified is business integration, which is crucial for HR big data to be useful. HR data is scattered across the organisation and its insights are valuable to every department. HR must therefore work closely with others to obtain a truly holistic view of performance, and then use this information for the benefit of the business as a whole. This could also help pool skills in terms of analysing and interpreting the data, as Michael has suggested in his comment.

But despite its undoubted potential and the current hype, our report is clear that data is not the whole story and HR professionals must continue to maximise their experience and networks to understand what the data is telling them. Our panellists agreed that if they are able to do this effectively, they will further build their strategic influence on the boardroom and the business.

Annabel Jones, HR Director, ADP UK

I had a bit of a think about your last question overnight, two thoughts came to mind.

- First, there is no shortcut to experience. Short term pain, is probably something that we'd have to accept. But we'd do well to really broaden our view of change to something a little more longitudinal. Real change is slow, and takes time, often generations. Look at where HR was say 30 years ago, big improvement. In our day and age though we want everything instant, and change is no different, it's just not realistic though and it causes a lot of unnecessary frustration in practitioners I think. (i.e. a lot of HR is dead type dramatisations)

If we accept that improvement in HR will take time, say thirty years for analytics to be where we want, then it's easier to accept that maybe the first five years of that will be a small regression as people gain the experience that will power future growth.

- Second, one possible alternative is seek to appoint data analytic staff from non HR related fields, and hope that their inferential ability is strong enough to cope with an unfamiliar data source. I'm really dubious as to whether this works though, as I think a big part of making sensible inferences is really understanding your data in the first place. Still, might work.

Other reads: http://www.personneltoday.com/hr/how-to-start-using-data-and-evidence-in-hr/ 

Evidence-based HR, the scientific approach to devising and implementing HR policies and practices, has gained traction over the past year. However, despite all the hype, there is still a challenge in implementing it effectively. The approach may be scientific, but the implementation needs to have an understanding of people at its heart, managing director of SharedXpertise Faye Holland says.

Data can greatly improve the strategy behind the HR function. However, many HR directors still lack the profile in their organisation to change established practices. So, while hoping to take an evidence-based approach, the reality is that many old habits and approaches remain.

Baby steps

HR is often seen as a business division that runs on “soft” skills, but data can help it to become a more strategic function. By proving a connection between engagement and productivity, you can create a business case illustrating that investment in data will allow you to measure these and therefore make improvements.

The key is to start small: begin by proving the merit of a more informed approach, demonstrating the findings that it can deliver and how the insights challenge the status quo.

After you have senior leaders on board with a small-scale data project, what next? The prospect of analysing reams of data can be daunting, particularly if data collection and analysis business-wide is in its infancy, as is the case in many fast-growing, mid-sized companies.

One approach is to be realistic about the levels of data the business can analyse.

Management consultancy Deloitte, for example, identifies four levels of business data analysis. At the most basic level is operational reporting. This is essentially reactive and involves looking back and comparing actual outcomes against what was originally desired.

The next level is advanced reporting real-time monitoring that is more proactive and is designed to assist with benchmarking and decision making, such as monitoring the impact of a change programme.

At the third level is advanced analytics. This comprises the ability to identify what makes a really good hire, based on the characteristics of those who have gone on to be successful employees in the past, for example.

Finally, there is predictive analytics, such as identifying which top performing employees may leave the business within the next 12 months.

Choose your tool wiselyChoosing the complexity of your data approach is even more important when considering investment decisions about tools to capture or track this information.

As Cath Possamai, the managing director for outsourcing provider Capita, says: “There are some very advanced analytic solutions offered by HR outsourcing providers. First of all, a proper assessment needs to be made of a business’ maturity level so that any tools and analytics can be tailored to extract useful and usable information.”

To get started, it is worth thinking about what level of data you and your business can capture and consider at the outset, and familiarise all key bodies with using and interpreting this data before migrating to larger and more ambitious data projects.

Billy Hamilton-Stent, managing director at Loudhouse Consultancy, says that data collection and analysis need not be difficult: “One solution is to run a monthly staff satisfaction survey. It doesn’t need to be complicated; one large business we work with simply asks its employees ‘are you happy?’ on a monthly basis and tracks sentiment based on the yes or no answers.”

Avoiding overloadThe flipside to all this is that sometimes we can face data overload. A pragmatic approach is needed to determine what needs to be sourced and what effectively will lead you down the equivalent of a data “rabbit hole”.

Laurence Collins, HR transformation and analytics director at Deloitte, says: “You have to be thoughtful about whether or not more data is likely to yield valuable insights. Research suggests that three-quarters of corporate executives in large companies aren’t getting value from half the data they already own.”

The key is to take a staged approach. Prove the value at each stage and take people with you. This will become crucial when it comes to getting support for mining ever more detailed data, securing approval for investment on supporting tools, and also taking seriously new policies and practices that result from this insight.

Faye Holland is managing director of SharedXpertise, organisers of the HRO Today Forum Europe.