Article: Staring down the barrel? Is HR set to fail the Big Data challenge?

HR Analytics

Staring down the barrel? Is HR set to fail the Big Data challenge?

With data becoming the new norm, the HR fraternity needs to change its game. A look at how the HR can embrace and integrate technological changes that are constant in the business world.
Staring down the barrel? Is HR set to fail the Big Data challenge?

Predictive analytics, power of HRIS systems, focused HR branding, leveraging social media have not yet morphed in the ways and norms of HR deliverables


Predictive trends through tools like regression analysis would be relevant to investigate the relationships among the indicators and outcomes of interest


John W. Boudreau (2015) defined the paradox facing the HR community as akin to issues like climate change, global hunger or socio-economic inequality. There is a general awareness that all is not well, that the “old order changeth”, however the HR community has not yet seen the disruptive effects, which allows for complacency. The HR fraternity is viewed with lens as polarized as a function which could well be redundant to being well regarded, but perceived as acting in isolation. We have all seen the periodic tsunamis catching our attention and driving the focus of the HR fraternity. However, an all concerted effort to embrace and integrate emerging genres of predictive analytics, power of HRIS systems, focused HR branding, leveraging social media have not yet morphed in the ways and norms of HR deliverables.

The changing eco-system

The exponential pattern of technological change is resulting in breakthroughs which are in turn, creating disruptions in markets and business models. Business is required to demonstrate flexibility, work with distributed and transient workforces which morphs to the rapid cycles of business reinvention. Employees are being required to engage with automation, deal with rapid skill obsolescence and hence constant upskilling, transitioning of low end or repetitive work to robots, increasing dependence on artificial intelligence etc. The social and organizational reconfiguration is resulting in increased democratization of work. Hierarchical organization structures are devolving into balanced communities built upon relationships which are short –term, for the periods of project. Long term alignment has given way to “shared purpose” and short term engagements. Talent is now looking for diverse work arrangements, beyond traditional full time employments and moving to freelance, outsourced or crowd sourced workers. Enhanced connectivity has accelerated global real time communication, product development and speed of go-to-market. Organizations that support and create trust cultures and purpose built networks are the ones slated to survive in this new world. An all-inclusive global talent market implies seamless distribution of the work across the globe. Enhanced life spans, talent availability in diverse talent pools etc. will necessitate the segmentation and direction of work to the “best” talent, either inside or outside the organization.  A differentiated leadership and engagement approach will require talent to be engaged through flexible approaches towards policies, practices, work designs, pay and benefits. The comfortable paradigm advocated by erstwhile HR organizations of “one size fits all” will be as relevant in the emerging environment as the mammoth!

Are they really HR Insights

The implications for HR are many. The rapid technological breakthroughs involving global collaborations would imply that HR needs to leverage artificial intelligence and machine learning to improve efficiencies in sourcing and reducing fulfilment time. Most HR practitioners have included “VUCA” and “SMAC” into the normal jargon of daily speak. Recruiters will no longer spend the bulk of their time and effort in mining job portals, but leave this work to smart algorithms which complete this in a fraction of seconds. The focus will shift to building talent relationships, mapping, identifying and engaging talent in specialized communities of practices and closed groups, focusing on the skill trend analysis and feeding these insights into talent forecasting and skill development initiatives.  However, providing an engaging recruitment experience will remain a fundamental task of a recruiter, since talent will have multiple options and without providing this experience, they would take their skills to another organization which would respect and value them more.

The enhanced connectivity of distributed and global workforce would require developing high trust cultures and purpose-built networks. The role of HR business partner will evolve to enhancing employee experience, community engagement, enabling collaboration and providing purpose and meaning in work. The increased thrust on employee and manager self-service would necessitate an enhanced employee technology experience. From an organization and performance architecture, the focus will be on aligning and driving performance, facilitating work-driven network management, community development and facilitating boundary less careers.

With work segmented and directed to the best talent (inside/outside the organization), a differentiated leadership and engagement approach will address the varied cultural preferences in policies, practices, work designs, pay and benefits. Learning functions will focus more on curating the content, delivering through app based games and simulation exercises and enabling collaborative social learning. Organization development teams will add to the arsenal of tools in their repertoire (360 degree feedback, psychometric assessments etc.) and work on identifying critical leadership competencies of decision making, social intelligence, learning agility etc. from outcomes of online games played internal/external talent and use these insights to position the “right person for the right job” in the normal scheme of succession planning.


Is HR ready?

There is unanimous agreement among the fraternity that HR analytics is a “must have” capability. However, the central argument espoused by Angrave (2015) is that this goal is hampered by a lack of analytical thinking by the HR profession and that the profession “is set to fail the big data challenge”. The increasing trend, he argues, will be for analytics to be an embedded wing in the finance or operations functions, or enabling the boardroom decision, but this would then imply that HR will seal the exclusion from the strategic board-level influence. 

The perception among most practitioners is that insights that come from “big data” and sense making from few dozen terabytes to multiple petabytes would require skills beyond the scope of their domain. However, I disagree and contend that the fraternity needs to demonstrate “smartness” with respect to data and the ability to connect the dots, built insights from trends and patterns.  However, it pains me to see our understanding of trends coming from data represented as “52 percent want compensation, 31 percent want professional development and 31 percent want work life balance”, an insight report provided by a leading professional social network site giving the talent trends for India for 2015.

Organizations are increasingly deriving insights from data to make better decisions, with maturity levels differing widely. Starting with descriptive analytics (hindsight view of what happened), few have moved to predictive analytics, wherein advanced forecasts are made with the ability to model future results.

The need of the hour is to get away from “lag” data reporting and build insights from the lag data to predict trends which are relevant to the business. Herein, effective HR metrics would imply doing more predictive analytics.  So instead of mean data, which indicates how well we do, correlating what we do and how it impacts what we want to have and happen becomes important. Predictive trends through tools like regression analysis would be relevant to investigate the relationships among the indicators and outcomes of interest. For instance, instead of limiting to general analysis of employee satisfaction indicators, analyzing which employee attitudes affect customer attitudes and investor confidence outside the company would be relevant predictive analytics.

What's Next for HR

HR business partners can take initial steps in using data by presenting the Anova analysis across business units or levels of commonly available HR measures of assessment results, speed to competency, productivity, retention/turnover within 90 or 365 days, engagement survey results, profitability per employee etc. The cherry on the top would be if HR initiatives can be monetized and our HR fraternity present their initiatives in the language of “An XYZ investment on training will increase productivity, resulting in manpower reduction and saving in SG&A expenses to the tune of PQR%” etc. Prescriptive analytics would be the top-tier level of analytics, wherein machine learning techniques would both interpret data and recommend actions. The road to insights is built on a foundation of good data, one that is consistent, integrated, easily accessible, accurate and relevant.

Climbing the ladder of analytics requires the HR function to change from the current “inside/outside approach” to a more "outside/inside" approach. Ulrich & Dulebohn (2015) summed up the overview of what’s next for HR, which is summarized in the table above.

      Analytical Tools

Attending a few industry conferences and seminars, hearing a lot of the senior practitioners sharing their experiences, best practices and ruminating over their challenges, I was strongly reminded about the scene from the famous animated movie “The Jungle Book”. This iconic scene involves the vultures sitting on a tree, wondering what to do? While some employees in many organizations may be in agreement with the analogy, given the largely prevalent disenchantment with the HR community, I can already hear the dissenting arguments from my brethren in the HR fraternity, who would strongly object to being compared to vultures. However, the point about this article is not whether HR function is part of the family Accipitridae, but what has changed for us and what do we now need to do to change our game? Unfortunately, unless we wake up to need to become relevant and upskill ourselves to talk, think and leverage data, we run the imminent danger of getting dis-intermediated by technology while we continue to pontificate on “What do we do? Let’s do something! Ok –so what do we want to do?” 


  • Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics : Why HR is set to fail the big data challenge. Human Resource Management Journal, Vol.26, No.1,1-11.
  • Boudreau, J. W. (2015). HR at the Tipping Point: The paradoxical future of our profession. People & Strategy, Vol.38, Issue 4,46-54.
  • Harris, J. G., Craig, E., & Light, D. A. (2011). Talent and analytics : new approaches, higher ROI. Journal of Business Strategy, Vol.32, Iss 6, 4-13.
  • Ulrich, D., & Dulebohn, J. H. (2015). Are we there yet ? What's next for HR. Human Resource Management Review, Vol.25, 188-204.



Read full story

Topics: HR Analytics, HR Technology, Technology

Did you find this story helpful?



How do you envision AI transforming your work?

Your opinion matters: Tell us how we're doing this quarter!

Selected Score :