We at Aspirant Analytics love data. In our ideal world, all decisions are made on sound rational foundations. But sometimes, you don’t have the data or the time to analyse it. Here’s how to make good decisions without it.
Our numbers show that BAME (Black, Asian and Mixed Ethnicity) lawyers work on fewer client matters per year than their white counterparts. But by adding one crucial ingredient to staffing decisions, the numbers even out.
There’s plenty of hypothesis testing and reliance on data in the hard sciences (medicine, physics, chemistry). In contrast, talent questions (hiring, retention, development) are rarely subjected to rigorous scrutiny.
People Analytics is the toolkit to change this and place talent decisions on a rational, data-driven foundation.
Many people use the terms Reporting and Analytics interchangeably — showing numbers and discussing them. But not all numbers relating to a business activity are created equal. Here’s the difference, and here’s why you should care.
If Bill Gates walks into a bar, does everyone in the bar become a billionaire on average?
In this week’s instalment of People Analytics Demystified, we explore the subtle (and sometimes stark) difference between the Mean and the Median and discuss when to use which.
Imagine this: You look at your population of Oxford graduates, and compare their on-the-job ratings with non-Oxford alumni. You see that Oxford grads have, on average, higher on-the-job ratings. Does this allow you to conclude that Oxford grads are better lawyers? Well, it depends on the p-values of this data set.
And this is what we’ll cover in this week’s instalment of the People Analytics Demystified series.
How do you know whether the psychometric tests you’ve been running with your job candidates predict their performance? The answer is: You run a linear Regression analysis. This is what we’re covering in this week’s instalment of our series in Demystifying Concepts in People Analytics.
This is the first in a series of posts requested by some of our clients on demystifying concepts in analytics.
Dealing with trainee allocation is a three week exercise in frustration for everyone involved. One of our clients has aptly described it as “three weeks during which I age by three years”. Now, there’s a better way!
The time has come when law firms may lose business because they don’t have enough women and minorities at the senior level. Aspirant Analytics’ Gender in the Partnership Analysis clears the path towards the 30%.
Law firms need trainees like a society needs children. Yet in an era of increased lateral movement of associates and partners, the importance of a firm’s homegrown talent is often underestimated. Successfully recruiting and retaining trainees is a key factor in a firm’s success, not only in financial terms, but also when it comes to building a home-grown cohort of new company leaders.
A 30/70 split of women to men in partnership positions by 2020 has long been held as a laudable goal for the UK legal industry — but unless things change, it’s unlikely to happen anytime soon.
Does a better performance at A-levels predict a better performance as a lawyer? If they had to bet, most people would say yes to that proposition. Well, most people would be wrong, as our data shows.
Having the best people is vital to any company. However, hiring the best staff is difficult — you can’t know if your hiring decisions are right until several months (sometimes years) after the hire has been made.
In recent years, there has been a significant increase in the number of tools used to help assess candidates, including personality tests, cognitive tests, and gamification. Notwithstanding the insights these tools may yield, interviews are still at the core of recruitment, and especially of the final decision. However, little has been done to assess how effective people are at conducting interviews, and whether they are able to correctly make the critical hiring decisions.