Our company is based on people – they are the most valuable asset we possess. Taking care of various aspects of the employment in order to make them satisfied is what basically makes us live and breathe.
One of these aspects is the absolute necessity to attain fair performance reviews combined with adequate salary settings. E.g. If a peer gets promoted regardless of not respecting assigned work, demotivation can spread like a disease within any team, or even the whole organization.
There are various approaches to salary setting. Let’s name the two most common:
1. Let the human nature do its work and do nothing – wait for employees to ask for a rise.
The drawback is that you would be relying mostly on the employee’s self-esteem and confidence as the catalyst for the whole issue. This can easily lead to an unfair setting and promotions of wrong people, simply because they might have a strong character. Others might end up on the other side of the rope, feeling unappreciated despite fulfilling their tasks more than adequately.
2. As the boss, periodically sit down and review the salaries on your own, basing it on a mixture of self-elaborated performance opinion and gut feeling.
This method is better, but not good enough. One of the vulnerabilities is promoting people who are maybe not the top performers but know how to show off in front of you. This is especially risky within IT where clear KPIs are not easy to set up.
We have concluded a different method, based on something along the lines of crowdsourcing, and been practicing it for quite some time now – we have learned that the team members’ performance review provided by a single person is always subjective and unfair, obviously. On the other hand, the studies show that the output created by combining multiple reviews together produces a result that is very close to the truth.
We utilized this by having our team members provide numeric reviews for each other. Each review answers a question: how much value does this person give to the company, in comparison to others? We combine these reviews by using algorithmic methods within Nomtek Logic (http://logic.nomtek.com) and use the output as an important indicator that helps to achieve an optimal salary setting. This approach secures a satisfactory level of fairness and is used in addition to a more standard and detailed performance review methods like this open question survey (http://www.surveygizmo.com/s3/630017/Employee-Performance-Review).
Naturally, the task of reducing of all of the person’s output to some number may seem as dehumanizing, however in this world it’s a necessary evil and has to be performed by each and every company.
We are aware that the system is not perfect… It has its exploits, it might not be as efficient within larger enterprises, but in a moderate team size, where personal attachment between each member is present, from our experience, such input is improving the quality of performance data drastically and thus, our developers happily participate in this task and take responsibility for their and their peers’ future, and in the end, this is what this system should do, right?