Payroll and Parity...art or science?
I once met a CFO who ran his own payroll and that of his peers and the CEO. They were growing fast and I asked him if he intended to continue running the payroll himself. He answered that he would do it till he finds someone who looks at payroll as just numbers and not as people. While one could mark that off as paranoia, it has to be agreed that it is not all that uncommon to build fortresses around payroll. However 'walls have ears' and 'who-gets-what' continues to be freely discussed in elevator chats and washroom gossips. And as the figures float in the grapevine, we all seem to hold a magic equation in our head that quickly computes the value of an individual and maps it to their pay or pay rise... and that computation happens in a jiffy to place a FAIR or UNFAIR pin on the case before leaving the elevator! :-)
The point in question is the objectivity behind payroll figures and...
...if payroll figures are guided by science or by emotions?
...is it possible to look at payroll as just numbers and not at the people behind?
...is objective payroll parity a myth?
In the HR & Recruitment Technology space there have been many interesting attempts at deriving a scientific model to compute the CTC of a candidate. From semantics to text based analytics to machine learning, most of these attempts have ended up nowhere while few came out with a statutory warning about 'potential outliers' to whom the method would not apply. An expert in the recruitment domain once helped me with a rough benchmark CTC per year of fulltime experience on a resume. The formula seemed just fair till some of the big boys of ecommerce and funded startups started their direct hiring and tilted the scales. The formula failed, yet I continue using it occasionally and favorably in parity discussions!
Legend has it that experienced recruiters can gauge a resume in 10 seconds or lesser and finish an interview in the first 90 seconds. True or not, fact remains that the recruiter is not done until the CTC question is thrown at the candidate. The second look at the CV is almost always linked to how far or close the CTC is, when compared to the computed value in the recruiter's head. There are young prodigies in the technology space who make recruiters fall off their chair with their CTC figures and do not get their callbacks despite having given their best interview. The dissonance created by the age of the candidate, years of experience and their CTC turns out a tad too difficult to comprehend even to the seasoned recruiter.
While prodigies do come by often these days, a lot has been observed and written about how nepotism and 'glass floors' can contribute to skewed paychecks, making prodigy identification difficult. Reading a CV would in no way let anyone in on such cases of being a blessed candidate. And no analytical model known to man can identify or tackle these exceptions. We also have the case of line managers and department heads who pitch the case of their staff better to a pay revision committee as compared to those who struggle at pushing their own case. From feeding progressive data to seeding positive images, pitching to the committee is an art to master.
The industry has for long played with the idea of Balanced Scorecards, KPIs, OKRs and other tools to scientifically track and measure performance. The tools have evolved and technology has progressed, yet the efficacy of these tools remains debatable. Though the intent is to objectively capture and translate performance trends to remuneration terms, these tools often become a manager's journal to trace the origin of a bias for or against an individual.
It's true that the left brain and the right brain have their own assigned duties and the heart versus mind conflict is an undeniable aspect of a day's work. It's interesting how these differences and conflicts play during recruitment decisions and payroll parity discussions. After all its not easy to find someone who looks at payroll as just numbers and not as people!
