HR Insights, HR Management

My Big Problems With Today’s Big Focus on Big Data

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As is becoming more prevalent, there are three emails in my inbox this morning, all with some post or webinar about “Big Data.”

TLNT is hosting a webinar titled Enabling Success With Big Data – Driven Talent Acquisition, Talent Management magazine has an article, Where’s the Value In Talent Analyticsand Chief Learning Officer magazine has The ‘Datafication’ of Learning.

Recently, LinkedIn published an article (Why We No Longer Need HR Departments) and a Spreecast (Is It Time To Fire Your HR Department?), both featuring Bernard Marr, described as a “best-selling author and enterprise performance expert.” The post had 19,000 LinkedIn shares, and 1,143 tweets as of 2 pm the day it was published.

A different approach to HR

In his post, Mr. Marr advocates changing the name of HR, and splitting it into a “people support team” and a “people analytics team.” The people support team would do the “taking care of the people stuff” while the analytics team would use big data to manage and predict human behavior, ideally leading to improved performance.

The reason for splitting HR in two? The conflict of interest between taking care of the people and looking hard at what the people are doing.

There is a fair point there, although I vehemently disagree with splitting HR. But that wasn’t what got my attention.

When asked about what he meant by using Big Data and data analytics,  Mr. Marr offered a couple of examples. He didn’t mention the industry, but he said that one organization found, through analysis, that those with a criminal record outperformed those without a criminal record.

The second example was of a construction company who provided wearable devices to their employees to measure stress levels, and when the stress was too high, they would pull them off for a rest. He contrasted this as a better way to gauge employee engagement, using real data instead of a survey which employees didn’t trust.

I’m going to skip over the criminal record and the stress test from an employee relations perspective, and just hit on the data issue. Maybe I’ll come back to the other at some point when I stop shaking my head.

A very basic problem

I applaud the attention to the use of data and analytics. I truly believe it is the single most important strategy for HR, because it is the only way to move to evidence-based decision-making about people.

And the tools and techniques these days are truly exciting. There are amazing organizations out there who, I’m sure are ready for predictive analytics, but most organizations aren’t, and HR, for the most part, is not.

But we have a basic problem: Our data stinks.

We can’t really measure performance because our performance management program doesn’t really measure performance. We can’t track voluntary turnover because managers put in whatever term code strikes them as appropriate  – or not. We can’t [easily] correlate individual performance to unit performance, because financials are summed to an accounting department, while individual performance is summed to a manager. Succession plans, in most cases, are static documents that are outdated by the time we need to use them.

And those are only some of the systemic issues. In addition, there is human error.

Manager and employee self-service have cast a huge shadow over the credibility of HR data, because neither group really understands the criticality of the work they’re doing. A manager who picks the first job code that seems to fit stands a good chance of picking the wrong one, and your “by job” data is now compromised.

Data must be credible to have value

Organizations that have basic employee data in their Human Resource information systems, and supplemental employee data in their Performance and Learning system, can’t easily analyze the data together unless data have been mapped carefully. And I wonder what percent of HR professionals are still chasing down performance plans after the deadline?

Data has to first be credible before it can be useful. That requires a strategic look at output requirements, accountability for the data accuracy, and an audit system to ensure quality. This is work that HR may see as tactical, but it is ever-so strategic.

Otherwise Big Data will be nothing more than big, messy data, and HR will spend more time than they’re already spending playing defense.

And I just can’t let this one go — criminals outperforming non criminals? Really? Do we care since — hopefully — we won’t be hiring criminals?

I can appreciate someone outside the field of HR providing helpful input, fresh perspective and innovating thinking, but I’d prefer that individual at least take time to understand the basics of the profession.

This originally appeared on the ….@ the intersection of learning & performance blog.

Carol Anderson is a Principal with Anderson Performance Partners a boutique consulting firm with the mission of helping the HR profession be as valuable to their clients as possible, intersecting performance and learning to actually drive organizational results. She has held HR leadership roles in health care, financial services, retail and the military. Most recently she served as Chief Learning Officer for a large health care system in Central Florida, with responsibility for talent development, leadership, professional and clinical education and team member engagement. Contact her at carol@andersonperformancepartners.com.
  • http://www.cultureamp.com/ Didier Elznga

    Couldn’t agree more!!

    You are absolutely right. Also I think there is a sort of strange dichotomy where people think that data is all “BIG” data and needs teams of analysts to make sense of it.

    If you look at parallels in the marketing world (and others) some of the best uses of data are just simple ways of implementing feedback loops so local managers can see what works and what doesn’t by getting ongoing feedback.

    It isn’t so much about high level overviews as it is about iterative learning.

    • Carol MacDonald Anderson

      Excellent point, well said. Your words iterative learning really cement that thought. We try to do so much, and do so much badly. If we could just chunk off what’s important and focus on that, it would be a much better approach. Thanks for your comment.

  • Carol MacDonald Anderson

    Absolutely Jon – both comments here use the word iterate and it’s a perfect guide for HR. I would also add that if HR could a.) realize that data is strategic and begin to fix it, and b.) pick work that really adds value to the organization, it would be a huge boost for HR. Thanks for your comment.

  • Jennifer Jordan

    Hiring someone with a criminal record does not necessarily equate to hiring “a criminal.” And in markets where competition for talent is steep, a statement like “hopefully we won’t be hiring criminals” is simply facile.
    Candidly, I’m not surprised if they do outperform. Many are grateful to have overcome that incredibly steep barrier to employment, and are willing to go the extra mile to keep that job.

  • Jim Rose

    Well said Carol; let’s assume for a moment that the data is accurate and relevant (a big leap for most); the elephant in the room is very few have the ability to:

    1) Interpret the data and

    2) Make recommendations based on the accompanying analysis;

    Jim