Equity, Diversity & Inclusion - With Intent - Understanding Diversity Metrics
How serious are companies really about Equity, Diversity & Inclusion?
How serious are companies really about Equity, Diversity & Inclusion?
What if, during the discovery phase, you had live robust external labour market data that instantly helps you to craft the perfect go-to-market strategy, positioning yourself as the expert voice on the target market?
Let me take a couple of the above challenges and explain how Horsefly can help in a matter of minutes:
One of our UK-based financial services clients struggled to fill a position they titled as Quality Engineer. Simply entering this job title in Horsefly, and looking at the results, it took less than 15 seconds to identify the problem:
It wasn’t that there was a lack of candidates; in fact, there were plenty of Quality Engineers across the UK:
The problem was that quality engineers work at the following companies; therefore, the job title chosen was not relevant for the audience that they wanted to attract.
What if, during the discovery phase, you had live robust external labour market data that instantly helps you to craft the perfect go-to-market strategy, positioning yourself as the expert voice on the target market?
Let me take a couple of the above challenges and explain how Horsefly can help in a matter of minutes:
One of our UK-based financial services clients struggled to fill a position they titled as Quality Engineer. Simply entering this job title in Horsefly, and looking at the results, it took less than 15 seconds to identify the problem:
It wasn’t that there was a lack of candidates; in fact, there were plenty of Quality Engineers across the UK:
The problem was that quality engineers work at the following companies; therefore, the job title chosen was not relevant for the audience that they wanted to attract.
Horsefly Analytics is excited to announce our latest value add feature - you can now create customised micro regions within Horsefly!
What is a Micro Region? This is your own, customised search area based on a city and a radius distance of your choice, for any set of job titles and skills. For example you can create a single location such as ‘Manchester + 50 miles’ and compare that with another location such as ‘Mumbai +20 miles’, and then compare candidate supply and demand in these unique regions.
A further breakdown of each individual micro region, including the candidate location by city view is available upon clicking on the individual micro region. Please see below for examples.
How do you recognise a data dinosaur within Talent Acquisition?
Being a dinosaur means believing that you are collecting and using information that informs and measures but in reality the world has moved on. You have been left behind and are no longer evolving. You are marking time, probably keeping everyone happy until that moment when your organisation realises that their competitors seem to have an advantage, they don’t seem to have the recruitment and attraction problems you do and they take a look at why!
It doesn’t seem possible that anyone can make a comment in any of the recruiting Facebook groups without being asked for the source and validity of the data. This is understandable, given that so much data is shared in a debate, often without reference to where that number has come from. Recruiting, in particular, has also suffered from urban myth syndrome. Popular truths, that said enough times by enough people become accepted law, even though they don’t necessarily stand up to a data sniff test. I often find myself asking: “Do you think that, or do you know that?”
Increasingly, talent acquisition leaders are being asked to become an expert voice within their organisations. I once heard a half joking quote in a conversation at a conference, when we had those, that has stuck with me for a number of years since:
“In God we trust, everyone else bring data!”
Google tells me that this can first be attributed to American Management Theorist W. Edwards Deming.
Whilst there is some dispute in who said the exact quote first, I think you get the point. This was quoted in a book in 1986 when we were first being asked to show some proof behind our proposals and statements. Jump forward to today, and we have a very different challenge. In a world where every click, task and action is digitally recorded, we often have the problem of too much data to navigate. Developing an “expert voice” around your area of interest is less about bringing data, and much more about defining the right data, applying context and being able to define and communicate meaning. This is a critical skill in establishing a credible expert voice in an organisation. The art of “big data analytics” is really being able to turn lots of numbers into meaning, and communicating why this is important, to someone who is probably not an expert in the discussion topic, and be sufficiently credible to get their support.
Over the last few months I have been speaking to the users of Horsefly Analytics, to understand how and why they use the labor market data available. One of the questions I always ask is what makes them confident enough to present Horsefly’s data to support their expert voice. They are, after all, staking their reputation and in some cases, careers, positively and negatively on actions resulting from their recommendations. The source data has to be right.
The answer that I’m continually getting is that although there are sometimes surprises (and that’s healthy), the numbers, trends and conclusions feel right to someone working in the market day to day, and come from a broad enough range of sources to present real trends, whilst picking up on variances globally.
My challenge was that I was hearing about trillions of data sources, and that felt too big to imagine. Kind of like trying to picture infinity. I asked Horsefly CEO Will Crandle to break down for me how they acquire so many data points, extract what they need and derive meaning in a fast time frame. Answers to queries need to come quickly. This is Crandle’s answer to my question on why I should trust the data:
As part of the work I’m doing with Horsefly Analytics, I get to ask for labor market reports that provide background data for some of the questions I have. Just recently I have been digging into the job market as we exit lockdowns across the globe. I understand that each nation will have a different pace to this, but at some point soon we will be able to pick up trends, and link job openings to exit from lockdown restrictions, in order to forecast what might be coming down the road.
I was prompted into this research when trying to understand the trends impacting jobs advertised on job boards and aggregators. Whilst I understand that not all jobs are advertised, this data does give a good indicator of how the market is moving. The value of the job board market is forecast to continue to grow year on year in most analysts' forecasts. I found this forecast a bit strange. Not because I believe that the much hyped “death of the job board” might come about, but the wider adoption of programmatic technology, means job ad buying has, and will continue to get much smarter. The trends I’m seeing today is that this is resulting in advertised jobs staying public for much shorter periods of time, with companies buying visibility only until a fixed number of applications have been achieved. My question was that if hiring companies were paying for jobs to stay live for shorter durations, then the spend would be less. That is, after all, one of the main reasons for adopting programmatic advertising. Even if the number of jobs advertised remained at a similar level, I would expect a forecast of market value to decline, as spend per job decreases.
I have had quite a few discussions with recruitment leaders, job board heads and others on this topic. One of the themes I’m constantly hearing is that companies are now advertising more roles, as the cost per role decreases. This is certainly what I was hearing from the job distribution companies, and aggregators. Companies are using job boards to attract candidates for a broader range of jobs, relying on programmatic technology to ensure they are spending in the most efficient way. This should not come as a great surprise, as it has marked a decrease in the cost per application, and improved the ratio of applications to hire (by reducing total volumes.)
At the same time, relying on traffic from other sources via aggregation, has seen organisations reducing the number of job boards they are using in any one campaign. I’m tracking the data on this at the moment to prove the theory, and will share it with you over the next few months, when I have a conclusive trend line. Early indications are that both of these conclusions look to be correct.
To start off this research, I wanted to understand how the advertised jobs market has been performing over the last few months as we come out of COVID restrictions across much of the globe. I asked Horsefly to come up with this data, and think some of the trends provide some new insights into what is going on. A snapshot of this data for a few selected countries in Horsefly's database is below and at the top of the page.
I have been working with data companies like Horsefly's CEO, Will Crandle, over the last three months to try to properly understand labor market insights, and what is actually useful to recruiters when it comes to filling roles. I know that there continues to be a lot of talk about how recruiters are, or could use data to perform better, beyond adopting a rinse and repeat approach to hiring. We understand and acknowledge that data in decision making is important, as we try to move from reliance on “gut feel” based on experience, to something a bit more provable.
Email: info@horseflyanalytics.com
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