Week of December 16th, 2024
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Pareto Optimality in RecOps by Jeremy Lyons
More than likely you have heard about the Pareto principle, though you might have heard of it by its more commonplace sobriquet of the 80/20 rule. The Pareto principle, named for economist Vilfredo Pareto, states that for many outcomes, roughly 80% of consequences come from 20% of causes. Some examples of this are 80% of sales coming from 20% of clients, 80% of issues are caused by 20% of the causes to quality issues, etc. However, while many people know about the Pareto principle, in RecOps we deal predominately with Pareto optimality and Pareto efficiency. So, let’s dive in.
What is Pareto Optimality?
Pareto optimality, is an economic state where resources cannot be reallocated to make one individual better off without making at least one individual worse off.
What is Pareto Efficiency?
In economics, a Pareto improvement formalizes the idea of an outcome being "better in every possible way". A change is called a Pareto improvement if it leaves everyone better-off (or at least as well-off as before). A solution is Pareto efficient or Pareto optimal if after all possible improvements, there are no longer any ways left to make one person better off without making some other person worse off.
But ok, you didn’t come here for an Econ lesson, you came here for RecOps knowledge.
In your RecOps role, you have likely been working to create Pareto efficient solutions from the minute you started by balancing tradeoffs so everything feels equal. If you came up as an RC (or still are), you likely did this without even knowing when it came to scheduling. For example, you worked on load balancing or placing your interviewers in their preferred times so that candidates had got their interviewers at their best. Vice versa, you took into account candidates’ preferences for interview times or locations and, if you couldn’t accommodate them, you did what you could to make sure they weren’t too inconvenience.
Why is understanding Pareto optimality important in RecOps?
Because it is about efficiency and proper resource allocation. For example, if you are about to implement a new tool or process, but only a certain number of users will receive it, the non-receiving group will be disadvantaged. This likely means that you will want to think of ways to ensure that the disadvantaged group is given an advantage in the next round of improvements or that you make other changes so that they are less inconvenienced (e.g., a comp increase, etc.).
What are some other situations in RecOps that articulate Pareto optimality?
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Until next week, Regulators 😊
CEO @ Talentful | #1 Global RPO designed for technology companies
1wThanks for the mention Jeremy A. Lyons 🙏
CEO, Performance-based Hiring Learning Systems. Author, Hire with Your Head and The Essential Guide for Hiring.
2wJeremy A. Lyons - we're working on study to determine first year turnover and engagement by source of hire. Do you have any info regarding this or interested in helping collect it?
Conversational AI | AI Strategy | AI Governance | AI Policy | Specialist in AI Transformation of Recruitment and Talent Functions
2wThanks for the mention, mate