Meaning and context of key words:
Analytics: The science of logical analysis. Study of patterns and other meaningful information gathered from the analysis of data. Methods could vary according to needs and objectives. Used to understand past performance or predict future performance.
HR Analytics: Knowledgeable, usable and actionable data to improve understanding of past, present and future of employee engagement, retention, satisfaction and experience.
People Manager: A business leader or manager from any function who is responsible to manage a team and its members. Line HR executives are included by default
Psychotropic: Affecting mental activity, behavior, or perception, as a mood-altering drug such as a tranquilizer, sedative, or antidepressant
Enterprises globally, are compelled to keep pace, if not a pace setters already with all the technological advances in the world. This translates to a growing need to take better decisions faster. Nothing more than analytics is gaining relevance and importance. In such fast paced ecosystem, analytics provides the necessary force-multiplier effect to take big decisions quickly in several critical functions of the company.
Analytics is fast becoming the cause, the enabler and the outcome of business improvement initiatives globally
The analytics tsunami has successfully transformed several several business functions such as marketing, finance, manufacturing and quality to name a few. Analytics are not used merely for hinting at what’s working well and what’s not and related diagnostics, but equally well to future actions and predict outcomes. As analytics becomes more easily available and user-friendly and cost-effective, one must expect that it is the way forward.
Good analytics directly and positively impacts quality of decisions made. Decisions made certainly depend on the quality of implementation and execution to deliver desired results.
Irrespective of outcomes, slowly but surely, analytics is assuming and acquiring mind & behavior altering capabilities with high levels of dependence and pervasiveness
Analytics resonates with “curiosity”, a basic instinct of the mind. Curiosity to know more and sooner on the one hand and, desirable outcomes or favorable news on the other, are mutually exclusive. Like a doctor reviewing a lab report. There is hope of good news but bad news does not mean the lab was wrong.
Analytics when deployed for troubleshooting marketing challenges or understanding future needs seems to provide adequate comfort to users. It allows cautious speculation and improves quality of decisions to be made and implemented. With time analytical methods have become reasonable, acceptable and popular decision support mechanism across other functions within the organization.
Like tools to a craft, HR Analytics can make good People Manager a better one. It cannot transform a bad People Manager into a good one
So if analytics is helping several functions in an enterprise, it should deliver all the greatness it can, across all functions. That seems like a fair statement except that, it comes with a caveat when used for understanding and decision support for employee management.
Caring for employees since origin of time meant carefully managing employee engagement, communication, experience, satisfaction and retention. Employers sought employees to create a journey that would be meaningful and satisfying for both.
This need has hardly changed. If at all, in keeping pace with the rest of advances in the world, employee lifecycle have shrunk drastically. The highs are higher and lows are lower. The experience of a 25 year career span seems to have been shrunk and force fitted in a 5 year window.
Particularly HR analytics tends to project employee management information in an evidently convenient, easily understood compartmentalized packets of knowledge. Everything looks right the first time its talked about. Within days if not in minutes and hours, the practising People Managers seem to have several reasons to believe that decisions made on the basis of data discussed seem inaccurate, insufficient. Irrespective outcomes combined with a strong tendency blame poor decision making & execution to HR analytics, it will be almost impossible to eliminate the need for HR Analytics.
HR Analytics will provide information about statistically significant clusters. Practitioners must exercise care to realize that sum of the parts created the cluster. Decisions based on clusters may not satisfy individual needs.
Be it performance management, comp and ben parity, team R&R or absolutely anything and everything that can impact employee engagement, experience, satisfaction and retention, individual employee needs and aspiration, can significantly vary amongst individuals and the same individual at different points in time and tenure.
Analytics resonates with one’s desire for curiosity. It may be completely in sync and even reinforce one’s preconceived inferences. All is Well if problems get resolved. If not, People Managers can soon be on a slippery slope of “I know what is wrong but there’s nothing much one can do about it”.
In an ideal situation, HR Analytics will confirm all your suspicions arising out of intuition, improves the quality of decisions taken and meeting desired objectives by carefully managing implementation of decisions.
Problems begin when outcomes are not as desired. Practising People Managers must carefully work backwards from outcomes to quality of implementation and execution of decisions to quality of decisions and the processes used to arrive at those decisions. More easily said than done.
In an attempt to correct and compensate for practices of the past, intuition, knowledge from person to person interaction with employees, common sense understanding what teams like and dislike seems to have been overshadowed by the appetite HR Analytics. Somewhere inadvertently, People Managers might have cornered themselves into believing that HR analytics alone would be sufficient.
Many companies run annual ESAT or Engagement surveys. More often than not they score upwards of 80-85% which indicates great levels of satisfaction or engagement. Yet even more surprisingly, they also seem to have high rates of attrition. How does one explain “we are a great company but people don’t hang around for long”?
This limbo of disconnect between what analytics suggests and the outcomes of decisions based on these analytics can be very unnerving and self propelling for many People Managers.
There is one way sure way to cut this negative spiral. It’s Back to basics for People Managers!
- Realize that team members don’t exist to create or enrich HR Analytics. Employees exist for good reasons and therefore the meta-data and consequent HR Analytics
- First, People Managers must question the quality and quantity of effort in understanding people issues through their own experiences.
- Time spent with team members must be far greater than the time spent away from them
- It is mission critical for line managers to spend at least 15-30 minutes a week with each of their team members and understand them better. Such discussions must necessarily educate managers to know more than just work related stuff
- 20 minutes per a week per team member still works out about 300 minutes or just 5 hours in an entire week.
- Similarly Line HR managers should try to spend no more than 20 percent of their time per week in front of excel sheets and power points. At least spend 3-5 minutes 101 with employees and with each employee under their management is mission critical.
- Connect with employees in a regularly, frequently and sincerely in a timely manner.
- Appreciate and Empathise at every opportunity and challenge