A few weeks ago, our founder Richard mentioned that everyone in a tech company should be striving to create intellectual property that would outlast them. The important message is that this applies to everyone. Not just tech and product where it comes naturally, but in all departments, roles or responsibilities. No matter that it gets increasingly difficult the further you get from the primary intellectual property that a company creates.
This philosophy of “Everything as a product” is something that resonates with me due to my tech/product background and therefore I try to apply it even in my current role which is mainly management. A great example is how we built our career framework like an RPG, bottom-up, from skills, levels, competencies and career directions. In this article, I’ll describe the rest of the career framework, especially the parts that are touching on compensation and are important for people managers. In this case, we’ll go top-down, starting with the dashboard that we’ll break down into individual components which are tied to the career framework we use.
2022 Update: we open-sourced our career framework, so you can find its up-to-date version on our GitHub.
People Manager Dashboard
As a manager, I want to be one-step ahead and avoid uncomfortable situations like forgetting about someone’s pay-raise or unfair compensation. Also I believe it’s a manager’s duty to monitor this and ensure that everyone is treated fairly and in a timely manner. In the end, compensation is given for the work and contribution that the person delivers to the company. Compensation should not be dependent on negotiation skills and the boldness of the employee to ask for more. The exception, of course, is when the job description of the employee is negotiator or something like that when negotiation skills are the main competency 😃.
Another aspect is that more introverted people are naturally hesitant to go into uncomfortable discussions about salary. Especially in tech, it’s not uncommon that a developer would change their job and ask 30% more in the interview rather than asking the same thing of their manager. All of this boils down to being proactive, not reactive when it comes to compensation. For that purpose, we’ve built a “dashboard” for all managers of managers, that encourages proactivity.
As you can see, the word “dashboard” is bit of an exaggeration. It’s an MVP of a dashboard in the spirit of the product approach, represented as a simple table with all the employees, calculations and conditional formatting that serves the purpose of alerting. As an example, I’ve used a bunch of scientists as employees, salaries in Czech crowns and some basic tech career tracks. However note that all data is fictional and does not represent the realities of Mews.
For each employee, we track when they joined the company, when they last got a pay-raise and when they last had a performance review. We highlight the ones who have been with the company for long time and the ones that haven’t gotten a salary increase lately, as those are important to review and consider.
This section is pretty much technical; managers fill in dedication (full-time vs. part-time) and monthly salary or hourly salary depending on the type of relationship we have (employment, contract, other agreement). Based on this, the sheet calculates estimated net income of the employee and costs for the company. Both of those are important aspects when determining compensation, especially when hiring a new person. The most important column is
Investment which is a virtual value that represents normalized investment of the company into a unit of employee’s time. The purpose is to somehow normalize all the different conditions into a single number. We use it during hiring to determine where the new person would fall based on the offer, and whether their skills correspond to it.
Do you agree compensation should not be dependent on negotiation skills?
Avoid (at least some) uncomfortable situations…
The investment is highly opinionated and gets more complex when you employ people across multiple locations. When we were in such situation, we were using a Cost of living index as another variable used during the normalization.
In order to calculate overall career progress we need to record a career track and level in all the competencies for each person. This gets updated during the performance reviews. Career track implies responsibilities, job description and direction of the person. For example, “Developer” is a career track in the “Individual contributor” direction. Or “Data Science Manager” has “Functional Lead” direction.
The last part is the most interesting one, since it puts together compensation and progress and addresses the problems presented in the introduction, mainly the compensation fairness. On the other hand, it’s important to recognize that this system is not exhaustive and cannot capture all the aspects, therefore we use it more for indicative purposes. Because of this, we don’t have standard salary bands, but rather salary lower bounds which ensure that nobody is underpaid.
The minimum salary curve is our guarantee. That means if anyone increases in their career progress and appears below the minimum salary curve, we immediately see it within the
Minimum column in the sheet and resolve this. However we acknowledge that it may take a long time to increase overall progress, for example from
1.2 to above
2. That doesn’t mean there should be no raise during that period – managers are reviewing compensation much more frequently. Plus they’re taking other factors into account. In order to capture this, we also look at the indicative salary curve, which is an indicator, not a guarantee of how the salary should be progressing continuously.
There is another side to it as well – thanks to the indicative curve, we also get alerted within the
Indicator column if and how much someone is overpaid. Or if someone was over-assessed or under-assessed by their manager during performance reviews, which might be the other explanation for the discrepancy. Whatever the reason, it is something worth looking into in more detail.
We use a similar shape to our salary curves as depicted above. As you can see, between progress
3, the growth of the curve increases. The reason is that getting to this level is not an easy feat and can take long time. Levels above
3 are not common and such people have a big impact on the whole organization or even industry and therefore their compensation should reflect it and grow faster. Above
4, we just define the lower bound since in this area, it really gets individual.
What about open salaries?
Our salaries are not open yet and might never be open – we did an internal poll and actually the company is pretty much split 50:50 when asked whether we should open the salaries. On the other hand, they’re not 100% closed, we have a single “dashboard” where all managers of managers and above within the technical department have access. That helps keeping the balance across functions or teams.
In my opinion, open salaries are one of multiple possible solutions for how to ensure compensation fairness, which is the root problem and use-case that everyone cares about the most. The framework above is our answer to the problem in an environment where salaries are not open. It’s not a bulletproof solution, but it at least sends the message that we look into it, act based on the “alerts” and take fairness seriously.
Is there any application or software that does this out of the box? Do you see any loopholes in the scheme above? Or do you have any other question? Let me know in the comments or via direct message on Twitter or LinkedIn. You can check the sample dashboard including all the calculations, career tracks and salary bounds on Google Drive.