The Mis-Match of Algorithmic Recruitment

It's the not so distant future.

A mobile app linked to a wrist mounted wearable wakes you, at precisely the right moment.  It monitors your sleep patterns and pulse rate and greets you each morning with a chipper "Go get 'em!".  You dress and get ready to leave the house, the fridge has emailed to remind you that you'll need to buy milk on your return.  You lock the door behind you with a swipe of your cell phone, keys are no more.  Outside, you step into a self driving car and take a different route to the usual commute - the car knew about the traffic before you did.  You arrive at work and boxes are moved into the previously vacant office next to yours.  You weren't aware of a new co-worker. There were no interviews. They were algorithmically selected from the passive talent pool.  Kept warm on a diet of Pinterest photos of the office and Youtube videos of kittens selected to be the most humanising for the Mega Corp you happen to work in...

As far as predictions of the future go the vision I offer above is hardly advanced.  The technology exists for the wearables, the Internet of Things and the self driving cars, it's just that last part that seems incongruent.

In the growing adoption of technology for HR departments seeking to differentiate their sourcing efforts, the idea of algorithmic matching is seen to be the magic bullet in the "War for Talent".  Beyond the clichéd war metaphors and gullibility of HR Tech buyers is the future of recruitment to be left to the robots?

Technology has made the discipline of talent acquisition better.  We've moved far beyond the data entry and green screen databases of a decade ago.  As a modern workforce migrates to online services so their digital footprint increases making them all the more easy for the new breed of sourcers to find.  Now the future, according to some, looks set to be the automated addition of new workers and a touted increase in the skill of selection.  I'm no Luddite but I can't help thinking this is a version of a technological utopianism whose primary supporters are those that seek to benefit financially from the adoption of the technology in question.

So many of the products available that claim to have solved matching are the same providers who don't recognise some of the fatal flaws that their products exacerbate. The primary example of this is the reliance on the quality of data on both sides necessary for a match.  The majority of matching systems are parsing CV's and then matching against a job description analysed in the same way.  This is exactly the limited key word matching that these systems say is so weak.  Even when other data are relied upon to beef up the input, suggestions of LinkedIn profiles and even LinkedIn endorsements are laughable. Especially in the case of unverifiable LinkedIn endorsements like mine for "Midwifery" and "Cheese Making".  Of course I'm totally brilliant at both of these things...

Even the more advanced of the matching algorithms that incorporate some elements of semantic search (context of search, location, intent, variation of words, synonyms, generalised and specialised queries, concept matching and natural language processing) are constrained both by the data the candidates provide and the job description or criteria the employer matches against.  Anyone who works in recruiting will be able to quickly see that both of these sources of data are flawed and subject to constant change.  Data in both these areas can be knowingly falsified, incomplete and always out of date.

This data is inherently flawed because people themselves are inherently flawed.  Candidates will always seek to portray themselves in the best light, hiring managers will always add some extra "nice to haves" or even make the work of two people into one mythical job description.  A matching algorithm is forced to make sense of too many moving parts and results will suffer.

In moving towards this style of recommendation the people in the processes are reduced to the status of commodities.  Subtle nuance is lost and the chance for innovation curtailed by inelastic parameters.  People are not a product.  When Amazon presents you with a book based on your buying preferences it has only to reckon with your fickle, transient tastes.  A book doesn't reject you because it feels it's too far to get to your house, or because the other books on the shelf don't feel your reputation is strong enough, a book doesn't want to work from is own home or have a counter offer from a series of rival readers...people do.

Recruiting is a constant stream of edge cases.  Whilst a matching engine might work for less complex roles at large numbers, it won't help you compete in winning that all important "War for Talent" you were so desperately spending your way out of.  The current level of technology is no match for the ability of a good recruiter.  This is not an indictment of the technology, it's an acknowledgement of the greater problem that exists in the institutionally flawed HR departments and Recruiting processes the world over.  Using a tool like this to gain another datapoint to inform decision making is a valid use - it's the shame of HR Tech that every new tool is paraded as "the answer".  If the industry could wean itself off it's obsession with the novel and shiny we might be able to tackle some of these issues at the root cause and realise that the skills we learnt whilst toiling at our green screens might not be entirely redundant.

The Talent Hacker's Manifesto

Nick Marsh of Makeshift recently introduced the term Talent Hacking.  His contention was that hiring was broken and there existed a movement towards a new way of thinking.  How did it come to this?  Why is it that the world of recruitment can be called out as broken with no argument to the contrary?

Long ago in the mists of time and still the case at some less progressive organisations, recruitment was owned by HR.  From behind the dull-warmth of privacy screens and bloated software that referred to people as resources, recruiters began to stir.

Often regarded as the "noisy ones" on the HR floor, recruiters slowly began to emerge and be recognised as having a legitimate skill set.  A skill set that was distinct from their agency counterparts and yet not in keeping with the silo'ed silence of HR departments.   Moreover it was a skill set that was distinct from those of the HR generalists.  Over time the recruiters in more progressive organisations moved further away, diversified further and were allocated distinct budgets.  The dual pressures of speed from the business and for frugality from the finance department meant that in-house recruiters had to adapt the way they worked and began to become introspective - there wasn't just one skill of recruitment but many.

The role of a recruiter has been split in many organisations and so to reflect this and also to highlight there particular skills there are now many different job titles in use - from Sourcer, Headhunter, through Talent Acquisition Specialist, the Orwellian sounding Staffing Officer to Talent Scout there seems to be a new way to describe yourself each day.  So is "Talent Hacker" doomed to become the next in a long list of buzzword-like titles?

I hope not.

Hopefully we can avoid the pitfalls of buzzwordism if we make a clear distinction as to what a "Talent Hacker" actually is.  Firstly, I don't believe it's a job title at all.  Talent Hacking is a methodology.  At best it's a philosophical stance taken by a recruiter to adapt and experiment and at worst it's the sharing and usage of a number of disparate tools to expedite hiring.

In Nick's original article I was quoted as saying that “Hiring is still waterfall in an agile world”.  What I meant by that is that a "traditional" hiring process is slavish in adherence to accepted dogma. A job description is produced, it's disseminated through advertising channels, resultant applications are pushed through a pre-defined process and those lucky enough to have impressed will be hired.  In this process, there is no feedback, no learning and no space for creativity...worst of all there is no scope to delight the candidates.

With the Agile/Waterfall divide in mind, I propose that the Talent Hacking outlook can be formalised by borrowing (stealing) from the Agile Manifesto.  The Agile Manifesto is a statement of values for software developers, reinforcing those elements that are of greater value when developing software.  Similarly we can list those things that we feel are important when hiring, like this...

While there is value in the items on

the right, we value the items on the left more.

Hires over Processes

Too often in large recruiting organisations the pressure to maintain robust process and measure the performance of recruiters in the organisation means that we lose sight of the reason we're all there in the first place.  Measuring and rewarding things like number of candidates contacted or the number of contacts who made it to second stage is good practice but if the team isn't hiring it's all just "busy work".  A robust and fair (free of bias) process is important. Processes are ways of doing things that are more efficient - they must make a workload easier to complete or faster, you can think of them as collections of efficiencies.  If they do not add benefit they are no longer of value.  A lot of larger organisations hang on to process as though it was a life raft in a rising ocean of change, once the process is no longer effective (which you should periodically test for) abandon it and find a new more effective process.  A point here on "Best practices", to paraphrase Mary Poppendieck, author of "Lean Software Development" - Best practices are solutions to other people's problems that you may not have.  So much of the processes of recruitment are done simply because "it's how we did it at x company" or worse still "it's how I've read x company do it".  Process is great to ensure a level playing field and to expedite the flow of a candidate towards being hired - if it isn't doing either of these things it should be questioned and if found to be lacking changed.

Data over Anecdotal Evidence

The Talent Hacking approach loves data.   Sourcing, screening and shepherding a candidate towards being hired calls for a lot of decision making.  Decisions are better when supported by data.  Even if you cringe or break out in hives whenever someone says "Big Data" there is little doubt that the digital exhaust trails that people now leave behind them have made them easier to find.  Ask a tame recruiter you know if they can find your email address, I'll bet they can and it won't be from anywhere you remember writing it... Data supports a hiring plan, salary benchmarking, advertising response rates, recruiter performance, process improvement - it's all around us as recruiters.  Building a living breathing data set from which you can answer the future unknown questions will be one of the best investments for success as a recruiter.  Even better, a recruiter's standing in the business can be improved from the simple provision of the raw data.  The Talent Hacker will go further and provide insight to hiring managers - affecting change and having a direct effect on the success of the business.  It is the data that will enable the wider business, as consumers of the recruitment service, to answer the all important "Why?".  Why do we value this more than our own anecdotal evidence?  Anecdotal evidence is only ever the outcome of a single case, often it informs a bias or shapes action in a way that may have been right in a prior instance but not for the current one.  A Talent Hacker loves to hear the anecdotes of others because in unpacking them you can ask those questions that reveal what is "true" to an individual. They do have value, but I'll take the data.

Candidate experience over Corporate Responsibility

Beyond external marketing and websites, a recruiter is often the first human interaction anyone has with a company.  When they are doing their job well they are exemplars for the brand - impassioned spokespeople it's their enthusiasm that will bleed through in both their communication and deeds. So many recruiters at large organisations are a product of their environment they hide behind turrets built from template emails, missed phone calls and a fear of feedback.  An in-house recruiter walks a tightrope between advocating for the candidate and for the company at the same time, straying too far in one of these directions will not be beneficial.  A Talent Hacker takes a third position.  We must be aware that the talent war is over and that talent won.  Too many recruiters want to take an aloof position leaning towards the institutional arrogance that permeates some companies - "we don't have to provide feedback", "you're only worth a bland template email", "we have hundreds of candidates".  I'm sure this was a perfectly reasonable stance to take...until it wasn't.  You only have to look at Glassdoor.com to see reviews of interview processes that call out companies for their broken internal communication, ignorant recruiters and interminable, arduous processes.  For the Talent Hacker reading Glassdoor reviews is like a family owned restaurant being reviewed on TripAdvisor, scary as hell and a potential powder keg.  A recruitment process should feel like a personal service, the realisation that organisations are no longer all powerful and that bad reviews will stop people from applying hasn't fully permeated a lot of companies.  As humans we love to share, and embellish, a juicy story of bad service and this penchant for negativity can be mitigated by a recruiter doing their job well.  Recruiters should protect their employers they do have a duty to them, but if it comes at the neglect of hundreds of individuals whose only crime is to have applied for a job then it might be wiser to limit the damage and stop recruiting altogether.  

Responding to change over Following a plan

In life there are always events that are outside of our control.  As a recruiter we are often either privy to insider information or at the mercy circumstances outside of our control.  From hiring freezes, through acqui-hires to redundancies there are many business events that impact a recruiter.  The Talent Hacker must be aware of this and work hard to ensure that all parties, hiring managers, team, wider business and candidates are given the information where appropriate.  Working at the coal-face of recruitment often turns up interesting information that could be of great use to other areas of the business, if you don't forge these feedback loops you are effectively losing out.  It can be simple things like competitor hiring strategy or market rates rising in demand for a particular skill, however it can also be large and impactful learnings that should be used to adapt and change strategy - mass redundancies at a competitor, a new product launch or even rumours of mergers and acquisitions, candidates reveal a lot of information that could be useful - not listening to this let alone not reacting to it is missing out.  Change can be a valuable tool and resistance stemming from traditional models of yearly planning can only leave an organisation exposed to risk.  A company I once worked for lost 32 senior developers within three months - did they stick to a static hiring plan?  Of course not! ...but the changes shouldn't have to be that drastic to trigger a period of re-evaluation.  The Talent Hacker doesn't seek to control but instead knows that change will happen, they are not wedded to alternate contingencies but rely on experiences to suggest different paths to follow if the need occurs.

I like the appreciation of a new wave of recruitment thinking.  There have been pockets of genius in the underbelly of the people hunting game that have been hidden for too long.  From the boolean greats who sift through data to find that one unknown diamond of a candidate to the recruiters who do so much more than their remit, trusted advisors to candidates, hiring, housing and relocating their candidate's families and pets as they go.  Perhaps the Talent Hacker flag is one we can all unite under,   recruiters and candidates might be all the better off for it.

This manifesto is by no means an exhaustive list of what is to be a Talent Hacker and I welcome input to clarify the definition further.  By offering a definition we can at least trigger the debate and hopefully give the label more meaning.  

Metrics that Matter

Firstly apologies to those of you that aren't quite as geeky about the numbers of recruitment as I am, I'll be back to ranting about the misuse of Pinterest for recruitment soon.  As I promised previously I wanted to give a little insight into those individual statistics that go to make up the metrics I use (or those I like to see) when recruiting.  Gathering this information isn't about producing a report simply to prove effort.  It is only the most unengaged stakeholder who can take solace in knowing that candidate and recruiters are somewhere in the building...  Gathering this seemingly disparate data points, in a consistent format (more on this later) is about creating a dataset that is alive and available to answer questions that may arise later... regardless of what those questions might be...

So what are the basics?  Those elements that you have to capture and whether that's in an ATS, a spreadsheet or typed up and popped in one of those old-timey filing cabinets.

Name, gender - All of your candidates will have a name, even if they have just one like a Brazilian footballer or Madonna they still have a name.  You should decide in advance on a format for writing these names capitalization, hyphenation etc this is to facilitate later use of names in mail merge or batch operations - candidates don't want to receive an email for "MAtthw BUCKLAND" so spell it right and you won't have to change 1000 name spellings at a later date.

Gender as a metric is of particular interest to me.  I've always worked in technical recruitment and it's an industry where females and transgendered people are under represented.  This metric can be combined with source to know which sources are productive for diversity goals and with the date ranges to know if and where candidates excel or fall down in your recruitment process.  This can facilitate later discussion and provide great evidence for changing processes later.

Role - the role the candidate applies for...this one really is basic to be able to slice numbers of total applicants by role, I hope everyone does at least this.  If not I guess they just tie CV's to the back of kittens and let them lose...

Gate Dates - Not Match.com for Farmers, this is the notation of the dates that a candidate moves through the hiring process.  Date of Application, Date of Phone Screen, Date of First On-site Interview all the way through to Date of Offer, Verbal Acceptance, Written Acceptance and Start Date.  GET ALL THE DATES!  So why track all these dates?  These date ranges can be used to answer a multitude of questions.  With values in these ranges reports can be compiled that show total length of process, drop-out ratios, expose bottlenecks in the process, expose waiting times and hold-ups, track notice periods... basically everything.  The date ranges and days elapsed are the bread and butter of recruitment reporting.  Do you currently know the average length of your interview process?  Does it vary a great deal?  Why is that? It's the interrogation of these dates that will give you those answers and perhaps when you have enough of an historical dataset predict time to hire of for future capacity planning... all for putting some dates in a spreadsheet or clicking those little calendar icons in your swanky new ATS!  Brilliant!

Source - Again a simple one, but it bears repeating, the source is how the candidate arrived in your recruitment process.  This should break down the source into broad categories that can tell at a glance what is a good source (a lot of quality candidates) a weak source (few candidates) or a bad source (lots of irrelevant candidates).  Example sources should differentiate between the "How" of the source too e.g. not just "LinkedIn" correct reporting should be "LinkedIn Search" and "LinkedIn Advert", this will enable you to distinguish between an active candidate application versus a directly sourced passive candidate.

Secondary Source - Some sources may require extra insight, you might need to know more for a later report.  If you have a primary source as "Event" this could be the particular Meetup, conference or pub you met them at.  A primary source of "Agency" might have the secondary source of the agency's name, for referrals it could be the refering employees name... remember they all have one...

Country of Residence -  I also like to track where a particular candidate is based this has multiple reasons, one might be for immigration purposes to highlight to internal teams where visa constraints may be an issue or delay a start date, a second reason could be to track individual sourcing efforts from a particular country... best of all most reports can include a lovely map showing where candidates came from...the prettiest metric :)

Contact Details - This should be the most obvious but still I see people finding value in the wrong things.  We all should know that a direct contact is better than a message delivered through a third party.  Simply put a telephone call or a direct email address are better than a LinkedIn Inmail.  If you only use LinkedIn to contact candidates and leaving it at that you're doing it wrong.

Last Employer - Want to know your pulling power?  Doing some competitor analysis?  Then you'll need to know where your candidates are currently working.

Recruiter - Who found the candidate and who is shepherding them through the process?  It's important that I'm not noting this to provide a productivity report for managerial consumption.  Unless all the members of the team are hiring for the same role in the same geography there is little to be gained from a direct comparison.  Raw numbers alone, stripped of context are not an aid.  They are a great example of one of the great flaws in gathering data - quantity isn't always preferable to quality.

Date of Last Contact - One of the consistent complaints and killers of candidate experience is the lack of timely feedback.  Even giving a candidate a short "no news yet" will pay dividends if you later wish to offer against a less communicative rival.  To overstate, if you track the last date you contacted a list of candidates you can very easily automate an email letting them know what's going on and when they'll get feedback.

Status - Decide on a glossary of terms that best fit your process, get the hiring managers involved in this process too.  Phone Screen, First Interview, Second Interview..etc.  Have as many of these as you feel you need.  Counting each of these each week will give you a very rapid view of the overall pipeline.  Hiring managers will love this, full on warm and fuzzy feelings.  Too often the work of the recruiter can look like a dark art - they go and stare at a screen and people magically appear for interviews - a weekly pipeline report just illustrating the numbers of potential candidates at each stage will calm even the most rabid of hiring manager.

There are more things to track of course and when real value can be derived from the collation of this data you'll find it quite addictive.  Best of all, when you start to move on from thinking the collection of data is just to describe the current status to instead thinking that you are creating a living, growing dataset that can be used to answer questions that haven't yet been thought of... you'll start to see why metrics really do matter.

The Itchy Security Blanket of Recruitment Metrics

The rise of more intuitive technology enabling the recruitment process has made for an interesting corollary - a rise in an organisation's ability to collect and report data connected to the recruitment process.  The increasing data driven programmatic approach to recruitment can do much to aid in the design and selection of a recruitment strategy.  Seemingly small changes can be tracked to measure their impact on the success or failure rates of a decision.

The growth in our ability to collect these metrics has been matched by a hunger within the stakeholder set as a whole.  Once a hiring manager has seen a report that gives seemingly scientific insight into the hiring process it will be almost impossible to revert to something which grants them less insight.  I'm not advocating that we take away metrics for these managers rather than we give them the access and supply the relevant context.  The greatest danger of data collection lies not in the information, but in its interpretation.  

So what metrics are appropriate to measure? What metrics can offer us certainty without falling into the the traps of selection or confirmation bias?  There are already a lot of hyperbolic blog posts like "The Top 10 Metrics You Must Have" or "7 Recruitment Metrics to Win" these miss the point.  The metrics of recruitment are best used for experimentation - tied to the continuous improvement of the team.  If you are producing metrics that will sit unopened in a spreadsheet to appease a hiring manager you are guilty of security blanket metrics.  Whilst you will feel all warm and fuzzy because you can prove that some *thing* is happening they will be of no real practical value, like butterflies pinned to a board underglass, nice to look at but not useful.

So whats the alternative?  When done correctly the term "metrics" is a misnomer.  The gathering of data around recruitment will give you a dataset which you can apply to provide insight into historical performance and to measure impact of the specific efficacy of projects the team undertakes.  In this way it's possible to see results in real time - does that new advert copy lead to more applications? You can see that! Which website is best to advertise on? You can test that! Did that rival companies announcement affect your response rate? You'll be able to see!  Did adding that photo of a cat to your website make it better?  Of course it did! You don't need metrics to tell you that!

What can't metrics do?  Predict the future.  In many of the articles I've read about recruitment metrics I've seen a large number of lofty claims about prediction.  All the while these claims are made without noting the limitations of the dataset we have access to.  It's the measurement of this dataset that will be the most effective use of business value not on fortune teller style inference of outcomes.  Statements like "we had 1000 applicants in 2013, so this year we will have 1500" are always going to be more wishful thinking than informed prediction.  Metrics can help in planning for the future but knowing the limitations of the basis of those predictions is key.  If we aren't aware of the limits of prediction we risk undoing the good that data can do and reaching for the crystal ball.  

In a future post I'll list the what and why of the metrics I like to measure.  Both for tracking team and individual performance within the team.  Hopefully you'll recognise it's a list high on building a dataset with experimentation in mind and low on fluffy feel goods and blame dodging.