The full power of big data and analytics is still not realised by many HR leaders. Why is the function still apprehensive about employing data to make decisions? Akankasha Dewan delves into how to overcome the perils of data management.Adapting and dealing with change is perhaps one of the most fundamental challenges facing corporate executives today.
But navigating change is made even more herculean when it involves a shift in your primary ethos, and for human resources practitioners, this means the inclusion of data when making business decisions.
“Earlier, the focus on, and inclusion of data was more in the sales function or operations or finance, but now business leaders are asking for data on different levels across all departments,” Nidhi Das, APAC HR leader for shared services and delivery at Autodesk, says.
“They ask questions such as ‘how did we leverage on HR related norms such as giving and receiving timely feedback?’ They explore issues along the lines of ‘after agreeing to improve a specific gap by 10%, did we achieve our target or not?’ and say things like, ‘we will improve our employee engagement by 10%?’”
And it’s because of questions like these that companies like Autodesk and others are currently sitting somewhere between being able to complete advanced data reporting and understanding strategic analytics, because they are starting to recognise the need to use data effectively.
But why does reaching the point of robust data analysis for people decisions still seem like such a far away concept for many organisations?
Acknowledging the power of analytics
Having the willingness and right attitude to participate in data conversations is something HR undoubtedly needs to be credited with.
This is especially because the function’s traditional association with the human element of the business now dictates a precarious balancing act between developing an emotional engagement with employees and translating their effectiveness into units of measurement.
“The power of analytics is going to transform HR,” Leena Nair, senior vice president of leadership and organisation development and global head of diversity at Unilever, says.
“In Unilever, we explore issues such as how exactly is your quality of appointments improving. You can do a complete analysis to see which are the most effective parts of your organisation and which are not. You can correlate talent with results and see what are the appointments that are making sense.
It’s about using the magic of data and analytics with the human element. Combining people scores and the human touch, and relying on both together is what will make an HR person special.
But accepting that the advent of data will lead to a more grounded and thoughtful HR strategy is winning only half the battle.
Reactive vs. proactive usage of data
The recent Asian HR Big Data Survey 2014 by HRBoss found 98% of HR professionals in the Asia Pacific region have no big data strategy in place.
This is despite close to 80% of those surveyed acknowledged big data’s importance in driving organisational growth.
“If you look at the whole maturity model in the way talent analytics are being used right now, different companies are in different stages,” Das says.
“Most of the organisations are in the reactive stage, which is mainly operational reporting because what they’re doing is collecting data and metrics on different things such as training or retention or attrition. But the use of data is not proactive enough at the moment. It could move to proactive, and then strategic and predictive analytics.”
Clearly, a chasm still exists between what organisations want out of spending their time and resources collecting data, and what they actually achieve out of this process.
But perhaps the most worrying issue is that the problem is inherently fundamental at heart: it is impossible to implement effective HR strategies from data collected, when the very collection of that data is a daunting task for HR professionals.
The HRBoss survey revealed 92% of HR personnel are frustrated by their reporting process and how long they need to take when creating these reports.
According to the poll, 88% of respondents spent two days or more making reports and 22% spent a minimum of six days per month on reports.
“The biggest challenge is not being able to collect and provide right information in a cost effective and timely manner,” Chauhan says.
Admittedly, technological advances have inflated the range and depth of information that’s available, making it difficult to handle such large amounts of data. But the difficulty stems not only from the range of data available, but also from the plethora of tools present to collect this data.
HR practitioners get routine access to data from IT systems, surveys, interviews, excel-sheet records and even corridor conversations.
In such situations, the data interpretation process gets complicated.
The importance of a clear vision
Because of this, establishing the specific purpose for which data is being collected is absolutely necessary, according to Das.
“The most important thing is to consider why you’re collecting what you are collecting. Having clarity within your mind as to what is the data going to be used for helps the collection of data to be more logical,” she observes.
This includes considering a bird eye’s view on how data is going to be employed within a global organisation.
“Having to know what to collect at different regions may vary, because at a higher level, you’ll have various different metrics on attrition, metrics on hiring, etc. These varying regional stats may pose some challenges regionally, so you need to know what you want to do in different countries as well.”
Das adds this is where streamlining tools of collection is necessary, so a common language is established.
“HR professionals are not always trained to use data. We are now using tools and coaching our people in the HR field to understand how they can pull out the right data, which data to use and then go ahead forward with it.”
Investing in skills training
But issues around accuracy and efficiency of data can still be resolved to some extent by making use of more robust HRIS/data management systems.
As the HRBoss report highlights, the biggest roadblock hampering HR big data initiatives are inadequate IT systems for data management and reporting (21%).
However, the second biggest barrier is a lack of in-house data analysis expertise (19%), a problem which cannot be as easily solved as simply investing in a better data management system.
This then begs the question about whether HR teams are equipped with the right skill sets to make sense of the data and convert it into an actionable strategy and tactical plan for the organisation.
While all three HR leaders unanimously agree on the presence of a skills gap here, Nair adds the ups-killing isn’t necessarily a complex process, but it is tedious.
The process of reading data is similar to building skills for any other process.
Certain skills are requird to do this, so equipping people to understand this and teaching them how to move from collection to analysis to insight to action is necessary.
“I do think that HR teams in most places, certainly in Unilever, are investing and improving their skills to read and understand data. It is like any other skill, you have to learn it, you have to deep dive into trends,” she adds.
Developing a comprehensive action plan
A key element involved in learning how to translate data collected into actual business policies is knowing what exactly to collect.
Das explains the four strands of data which Autodesk collects very categorically. These include employee engagement index and metrics, manager effectiveness, talent brand score index and data on customer satisfaction index.
However, everyone spoken to for this feature agrees there are no particular metrics in place which are significantly more impactful to the business than others.
“Talent acquisition data, headcount statistics, tenure, attrition statistics, employment trends, recruitment statistics, gender diversity statistics – you name it and HR teams somewhere are working on it,” Chauhan says.
Importantly, the key element is to consider how the collated data is projected when aligning data with organisational strategies. This means adding in the specific implications or impacts to the business as a whole in your action plan.
“For example, look at attrition. If your attrition is 10%, leaders will say, ‘great, that’s a nice figure’,” says Nair. “But if you convert it and say, ‘look, we’ve lost 10% of our people and the monetary value of this is 10 million euros’, then people sit up and take notice and get into action.”
This therefore leads to a much more significant return of investment when it comes to using data within the HR function.
“Any piece of data, relevant to HR, can be useful for business, but it is our skill in making it speak to the business which makes the difference. You can make leaders sit up if you add in the numbers there,” Nair adds.
Getting support from the top
Using data is particularly useful in getting HR divisions a ‘seat at the table’ and adding a certain credibility and stability to their policies. Precisely because data from HR divisions revolves around people capabilities and performance, it can simultaneously predict the way the entire organisation’s departments might function.
This makes HR data increasingly valuable for senior management.
“The leadership teams at Autodesk show a lot of interest in employee engagement metrics. For example, the data which comes out from the employee engagement surveys,” Das explains.
“Leaders deep dive into the survey’s results and evaluate what the main trends and territories are like. Because these results are manifested in the behaviours of teams across functions, these leaders try to collate and link back the data with the trends they have observed in other areas. And then they come up with a thorough action plan which is led by the head of human resources.”
In other words, data garnered from the HR function on, for example, how satisfied the employee is with the organisation may help in predicting trends on how well the employee might perform within his or her own respective team.
This paves the way for HR to be actively part of the organisation’s operations, rather than remaind divorced with targets and company objectives.
The fundamental consequence of such strategic inclusion includes the possibility of more resources being allocated to the function and helping to overcome the barriers to effective data collection and use.
“In addition to investing in sound data management systems, investing in the HR function to carry out data management is also important,” Chauhan concludes.
“Because in the end, as business partners, using data in the HR team is about driving a change which makes sense for the business.”