Algorithms, big data and analytics have made the old distinction blurred and no longer correct. Today, it’s really hard to know who ‘owns’ responsibility for all of the new technology. IT laid claim to smartphone technology and has Mobile Device Management to assist it in the deployment, tracking and upgrading these assets. Operational executives seem to ‘own’ the advanced technologies like sensors and Internet of Things enabled devices/machines in their capital equipment. But, does HR ‘own’ the advanced technologies creeping into the people management space?
I don’t think so:
- Is HR hiring additional HR staff with a different set of skills like data science, analytics, social science, etc.?
- Are they training operations people on how to use the results of the new tools correctly?
- Are they showing any signs of mastery around the new technologies and the underlying principles therein?
And the really big question is: Are they even buying the technology to cope with the emerging skillsets?
Years ago, while at the HR Technology show, I noticed record crowds in front of HR analytic vendor booths and in breakouts featuring these new tools. The more amazing a tool was, the bigger the crowd.
However, when I meet individually with the executives of these software companies I learned that HR teams were fascinated by the advanced technology but unwilling to buy any of it except for the most tame, simple tools.
In other words, they only bought tools that used familiar data, produced familiar results and offered few new insights.
These timid HR software buyers would look at one kind of technology but only bought modestly incremental ones. It’s like a car show – everyone marvels at the exotic, million dollar Italian sports cars but they continue to drive the Ford they’ve always owned.
I chalked this up to people being uncomfortable buying things they don’t fully understand. Who among us would buy, for example, a gas spectrometer if we didn’t know how to operate it or interpret the results?
But, the other reasons the crowd wasn’t buying these products could be HR’s unwillingness to change and HR’s inability to step out of its administrative comfort zone.
HR professionals could change – if they chose to do so. But, will they? They must if HR is to be relevant. Competitive forces will dictate needed upgrades to HR technology. Does HR want to be the last horse and buggy owner in world that’s adopted automobiles?
Here are some of the relevancy challenges for HR today:
1 – The Digital Workforce is made up of more than just human beings. Businesses are shifting from the Industrial Age to the Digital Age but is HR?
More and more processes are being completed and managed by bots. Bots analyze and co-ordinate the communication between two or more machine tools in an assembly line. Bots dispatch workers. Bots communicate with customers to solve simple and routine requests. In some firms, bots schedule work, route service personnel to complete the work, communicate with the customer to make sure the work was done well and then repeat the process, tirelessly, day after day.
Who should develop the personnel evaluation for the worker: an unfamiliar manager or the bot that has the most contact with the worker? Should HR evaluate the performance of these bots? Does HR know if the bots are contributing to work/life balance or engagement issues? Does HR even think about these questions? And, don’t forget that bots are doing a lot of repeatable HR tasks as well.
2 – Whose job is it to identify and resolve bias issues in the big data sets used in HR and Recruiting analytics? If HR doesn’t police the feedstock for its analytics, who will? Can HR make these evaluations if it doesn’t have the talent internally to do so?
3 – Believing that HR can defer its evolution to the Digital Age is delusional and unrealistic. Once upon a time, people were fearful of automobiles. Some thought people would perish if they travelled over 60 miles per hour. Some people thought the earth was flat and the center of the universe. There are even people fearful of cloud computing, too. Today, there is no place in HR for flat-earthers, cloud-deniers and the analytically ignorant. For HR people not to learn about, acquire, experiment, tune and use HR analytics is a disservice to their firm. As the Borg remind us, ‘Resistance is Futile’.
4 – HR needs smart, analytics-savvy people to discern the good from the bad analytics out there. There are bad analytic tools out there. HR professionals must become familiar and competent in analytics, correlation/causation, bias, etc. to decide if a particular analytic or its result is appropriate for the company.
Personally, I’m skeptical of many of the attrition/retention analytic tools out there as they provide too little advance warning of a potential departure.
I also question the lack of analytic tools to detect bad or pathologically defective bosses. Should an HR department create their own analytic tools for this use case?
And, I really worry about some of the team-building analytical tools that might morph into recruiting screening tools. If HR doesn’t get hip to these tools quickly, someone else in the organization might use these products and end up inadvertently creating liability risks for the firm.
5 – People are developing all new HR analytics whether you want them to wait or not. In a recent LinkedIn discussion board, commenters offered up a list of new ideas for new HR analytics. I’ve added their analytics suggestions to mine. Here’s a partial list of analytics that are potentially coming to an HR department near you:
- Predicting whether a job seeker will become a high performer
- Predicting when a worker will shift into becoming a high performer
- Understand what factors are appealing to high potential recruits vs. others
- Predict which employees will commit/are committing fraud in expense reimbursement, payroll, time entry, etc. *
- Predicting which employees may be more inclined to commit theft of company assets *
- Predicting when specific people are likely to retire and how that will impact succession planning and recruiting
- Predicting the speed and moves people will make in their career within the firm
- Predicting who the future leaders of the firm will be
- Determining what will drive enhanced levels of employee engagement
- Predicting when road warriors are about to burnout from too much travel
- Predicting when personal/professional life balance issues may occur and to whom
- Predicting what benefits (and participation levels) employees will enroll in
- Predicting potential ACA compliance issues
- Identifying potential adverse pathologies (e.g., narcissism, paranoia, etc.) in supervisors
- Identifying employees with a potential for violence in the workplace
- Identifying bad managers based on the short notice periods former employers are giving
- Identifying potential retention/attrition risks
- Identify changes in employer and competitors’ recruiting brands based on social sentiment time series analysis
- Correlate Glassdoor and other employer (and competitor) rankings to the employer’s ability and cost to attract new talent to the firm
* If some of this feels like the ‘future crimes’ detection in the film “Minority Report”, good. It makes me uncomfortable, too.
What all of this illustrates is that businesses and/or software firms have the ability, data and tools to develop powerful analytics. But, are HR organizations prepared to use these technologies correctly and effectively?
HR is no longer managing just humans. It is managing the software, data, tools, bots, processes, etc. that interact with external systems, external databases, other people, other tools, etc. The scope of HR has grown demonstrably and possibly outgrown the restrictive moniker of ‘human’ resources. It’s time to redefine the scope and name of HR.
The old moniker just doesn’t fit anymore.