Video – Tech and Talent

Earlier this year I was asked to be on a panel to discuss how Talent teams use tech and how the rise of software has changed the experience for candidates and the companies recruiting them.

It’s a long one, but has some interesting observations from the participants.

Why Job Adverts Suck and What You Can Do About It.

At the start of this year, and many years before it the pundits of HR and Recruitment (yes, they really exist) make predictions for the year ahead.  As well as borrowing heavily from the mantras of Silicon Valley startups promising to be social, mobile and local there is always one persistent prediction that never seems to go away.

The mists in the crystal ball clear and a vision of the future appears, with absolute certainty, our forecasters declare “The Job Description will cease to exist!”.  Then, as if to mock that same prescient certainty, they don’t.

Despite the flaws of the formats on both side of the job seeker chasm things seem to stay the same.  Whilst the prognosticators may lament that their visions haven’t been proven right the world keeps turning, recruiters still want to see your CV and HR departments the world over keep posting banal job descriptions.  As much as recruiters may decry applicants for their terrible CVs or offer advice on how not make CV mistakes there doesn’t seem to be quite the same amount of concern for the job descriptions and adverts that they themselves post supposedly to entice those looking for work.
The average job description is currently a mishmash of an older version of the original specification, some amendments from an enthusiastic new hiring manager and some sexier phrases stolen from various other company’s career pages.  When you stop to consider the amount of work that marketers put into a banner or headline just to make a viewer click it’s mind boggling to think that recruiters expect people to consider making such an enormous change to their lives on the basis of bland copy and trite cliché.
There must be a better way… and there is…

In 1943 Abraham Maslow published his paper “A Theory of Human Motivation” in the Psychological Review. He posited a series of human drivers that worked sequentially, the lowest order of which must be satisfied in order to achieve the next. For example when starving to death we’re unlikely to be concerned with how our peer group thinks of us, until we meet that more basic need.

 Maslow used the terms “physiological”, “safety”, “belonging”, “esteem”, “self-actualization” to describe the pattern that human motivations generally move through.  If we are using the format of a job advert as a means to motivating an action from a reader, could we borrow from the Maslow model to ensure that we are writing a well rounded and engaging advertisement?  Without too much of a mental stretch it’s easy to see how these stages can be made applicable to pressing on the underlying motivations a person may have when wanting to apply or even moving from casual interest to intention and ultimately action.  At the very least we could use a model to broaden the appeal of a job advert and hit more of the motivational bases that Maslow identified.







The lowest order motivator for a job seeker has to be salary.  Whilst it is foundational and important it can quickly be satisfied and judged accordingly.  Try putting the actual salary range on your job postings and voilà the majority who apply will have some idea of how much you are prepared to pay for the role.  Assuming that your job is not unpaid or a front for slave labour stating a salary is a good idea.  Promising adequate or even fair pay for a candidate’s toil should never be the best motivator you have to play.  Put simply, cash should never be your “ace in the hole”,  if it is it’s time to rethink the role.  Try talking to some other people who already do the job and ask them why they like it. Try to gain a deeper insight into the persona of those who enjoy the job – chances are that their reasons are probably inline with a potential employee’s too.  It tends to be the third party recruiters who’s job postings feature salary as the biggest incentive. “Java Developer $90,000” is a great indicator that the poster hasn’t really understood the real differentiators or their target audience.
For a lot of job posts salary Screen Shot 2015-01-27 at 09.50.57is where we stop. There may be other details given about the company doing the recruitment or a technology stack but these will be generic and explanatory e.g. “You will write code and fix bugs” these are statements which would be true of the same role in another organisation.  How can we make this a little more personal? Maslow’s second step in the hierarchy is “Safety”.  For job seekers this may take the form of permanent vs. contract or the security of your company as an entity.  These can be addressed early on, from startups referring to themselves as “VC funded” or larger corporates stating successes “Safety” should be accepted as quickly as the salary stage.  If you don’t meet the needs of the job seeker here i.e. lower than expected salary and indeterminate contract length they will self select out of the process, and that’s a good thing at this stage.  Remember a great job advert isn’t about mass appeal it’s about gaining the interest of the right people.
A growing number of companies are following in the footsteps of the larger technical organisations and offering a bewildering number of perks and free incentives to their employees.  These are the hyperbolic tales of free food, dogs in the workplace, on site masseuses and hot and cold running champagne.  Who wouldn’t want those things? However a lot of job adverts fall at this hurdle.  Promising money and free things are are a great way to have someone make a small change. Switching a bank account or internet service provider maybe but surely not enough to change employers?  Job security should be implied in any job description and the benefits and perks are nice to haves – but don’t be swayed into thinking it’s enough.

Maslow’s third tier was “belonging” or “love”.  For a job advert how can we convey a sense of somewhere a candidate might want to belong?  This is where a lot of job adverts fear to tread. We stop at the inanimate perks and don’t consider the social interactions that having a job will bring.  Belonging in job adverts is best conveyed through the people the candidate will be working with. Humans are (mostly) social creatures and benefit from interaction.  Who really wants to spend eight hours a day treading the same carpet as people you hate? At the other end of the spectrum who would want to work with an ex-colleague or former manager who was an inspirational leader? Who might want to join a team of renowned experts in their field?  If we make a job advert generic and impersonal e.g. “You will work with our team of developers” we risk becoming generic.  Talking about the team is an opportunity to sell successes to a candidate and gain engagement from selling the pedigree of a potential peer group.  In the world of startup it’s normal to see adverts proclaiming founders who are ex-Google or ex-Facebook in this way an employer borrows some of the perceived quality bar of their previous employers.

Another consideration for the “Team” level of a job advert is how the team organise and work together.  A job may be more attractive for a reader if it explicitly states that the team don’t like to hold lengthy meetings, or that they work closely with other parts of the business.  There are some great examples here that would make brilliant recruiting messages like Spotify’s excellent Engineering Culture video. For those who are harbouring frustrations about their current employer’s bureaucracy or lack of insight and innovation, referring to how the prospective employing company gets work done can be revealing and enlightening.  Moreover, talking candidly about these things can help convey authenticity and engender trust in the reader.

 

For his fourth level Maslow talked about “Esteem”.  This is the need for appreciation and respect.  People need to sense that they are valued and by others and feel that they are making a contribution to the world. When employees become unhappy and disengaged they slowly start to stagnate.  If they feel under appreciated or second best to others this happens all the quicker.  It may seem obvious to mention that  people like to feel valued but in a job advertisement it is wholly appropriate to mention how the role they will play will be important to the rest of the team or company.  It’s a certainty that some of the role you’re advertising will be similar to other roles at other companies – in these cases it’s important to differentiate at a personal level.  It’s a rare candidate that wants to be a cog in machine but still I see companies loudly proclaiming they are hiring “one thousand software developers this year!” the intended message is clearly designed to be one of security, though it’s hard to escape from a different “come and be one of a crowd” vibe.  Remember a good job advert spurs the correct audience into action and acts as a self selection point for those who are not right.  A job advert should not be generic enough to attract all comers – if it does you just ensure that someone will have to wade through the mire of terrible candidates and machine gun applicants that apply to everything.

Knowing that the role you are performing is worthwhile and needed is a far better motivator than the lower level “carrot and stick” incentives of salary and mock “benefits” of legally mandated holiday entitlements.  The better job adverts will mention those truly motivating factors – autonomous working, results driven environments without the reliance of rules and policies.  This further adds authenticity and can be a real differentiator for a reader.

 

So what’s left?  You have an advert for a new job that tells a candidate they’ll be adequately financially rewarded, they’ll be given a great set of benefits and the company is secure so their job will be too.  You’ve told them about the great team they they get to work with and then you’ve gone on to tell them how they’ll fit into that team and why the work they will do is important and needed.  If you said that was all a job could do it’s still pretty compelling, but Maslow has a further tier on the road to fulfilment.  “Self- actualisation”. This is the final level of psychological development that can be achieved when all basic and mental needs are essentially fulfilled and the “actualisation” of the full personal potential takes place. Research shows that when people live lives that are different from their true nature and capabilities, they are less likely to be happy than those whose goals and lives match.

In job advertising terms how can we then offer this form of greater fulfilment to a prospective candidate?  A majority of job descriptions fail in the balance of power they portray.  Despite the current market for hires becoming tighter, in far too many posts on job boards there is a weird “you should be thankful that we deign to allow you to read this” holier than thou language choice that only the most spirit crushed drone would find engaging.  However, this has become the accepted convention for weird mash-up of job description cum advert that employers post. Part internal HR document, part external facing “sexed-up” hyperbole.

Instead of using language straight out of the mouths of the mill owners of the Industrial Revolution why not let candidates know what they stand to gain from being an employee.  What are the experiences they will have that will let them grow as individuals.  Will they gain new skills or be trained in new areas?  Will they get to mentor or be mentored by other employees leading to more rewarding interactions? Will they have the scope and the freedom to be truly creative? Are they empowered to innovate? This is the future facing final tier of any great job advert and if you can hint at a brighter future for those who come and work for you it might just be the tipping point for them to hit that big red apply button.

The Next Big (Data) Thing: Awaiting the Robo-Revolution

As the quest for the shiniest silver bullets in recruitment continues the fields of artificial intelligence, machine learning and “Big Data” are proving to be a great hunting ground for salesmen and sensationalists alike. To the trained eye these fields are distinct and separate, yet when selling a solution that makes a claim in one of these areas there’s a wealth of content that shows us that our industry is capable of misunderstanding them all equally.  Whilst the misrepresentation of technology by those that are selling it is nothing new in the recruitment industry the coverall terms of A.I and “Big Data” have become imbued with a special power.  Part of this magical thinking has increasingly led to loftier and loftier claims for technology that, though still in their infancy, can be skewed for more clickable headlines.

In journalism there’s an eponymous “Law” for this kind of headline. “Betteridge’s Law of headlines” is an adage that states: “Any headline that ends in a question mark can be answered by the word no”.  It is intended to be humorous but seems to work in the overwhelming majority of examples. “Is This the True Face of Britain’s Young?” Sensible reader: No. “Have We Found the Cure for AIDS?” No; or you wouldn’t have put the question mark in. “Does This Map Provide the Key for Peace?” Probably not.  I propose a similar adage for content covering technology and its application to recruitment and HR.  Betteridge’s Law still applies in this area for example “Does AI Mean the end of Graduate Recruitment?“. Nope, it doesn’t.  What about those headlines that aren’t posed as questions? For those I propose Ward’s Law “The more often an article about recruitment uses terms associated with A.I., Machine Learning, and ‘Big Data’, the more likely the results of any study quoted will overstate the efficacy of the technology“. In other words, the more often recruitment is thought of as being “solved”, the further that will be from the truth.

Let’s look at an example.  Recently I saw this headline “Big Data research predicts which CV’s will be invited to interview by recruiters”, which sounds fantastic! It continues with “New research has discovered a way of telling which CV’s are most likely to be picked out from a large pile of job applications by recruiters.”  This type of press release has become formulaic. Characterised by a claim to the potency of the algorithm, some slightly spurious statistics that don’t entirely hold up to further research or misrepresent the original intent of the research, make some other claims where the algorithm hasn’t been tested but would be an amazing disruption “…make it possible to predict a candidate’s future performance simply by scanning their uploaded CV..”, and ending with a sooth-saying doomsday quote from someone in the industry – “In the future we’ll all be fed by tubes and robot overlords will tell us what jobs to do”.

In this example we are given the sample size a “staggering 441,769 CV’s” and the percentage accuracy of 70-80% when graded against human recruiters screening the same 441,769 CVs. That means that in 88,354 to 132,531 cases the algorithm disagreed with the human recruiters and rejected the candidate. That’s quite a number of false positives/negatives, even more so for any company that values a candidate’s experience and values how applicants might be treated in their processes.  Where this element of humanity breaks down even further is that when given another source of data – a cover letter – the algorithm performs worse, the strike rate falling to 69%.  How many of those 132,531 the algorithm did not invite to interview went on to be hired? We’re not told.  The other aspect of this any many similar stories to consider is that humans aren’t great at dealing with large numbers.The reason for this is that our sense of number is based upon two innate systems which essentially deal with small numbers accurately or large numbers only approximately.  We don’t often encounter large numbers, so when we do, it can be easy to struggle to know if that number is statistically significant.  LinkedIn boasts 433 million members and Facebook has 1.65 billion monthly active users but at this scale those numbers are almost meaningless when applied to the hiring goals of one company. Our inability to connect large datasets with real people is rampant. Big numbers dehumanise us, and the bigger the numbers, the worse the effect. If these raw numbers alone aren’t enough for a little doubt to be cast we can look to those elements that the decisions are being made upon.

Whenever I read about a potentially revolutionary algorithm I’m always keen to understand how it is arriving at its results. In particular in these screening algorithms, what is the programmer choosing to include, what do they exclude and what weighting are they giving those elements on which they are basing those decisions? In this example experience, workplace and education are all measured. We’re also told that “Contextual factors were also taken into consideration, such as ‘did the candidate apply in time’ and ‘was the candidate already employed by the company?’”.  Then potentially more problematically, as alluded to in the full version of the PhD thesis this press release is taken from, demographic factors like “age, gender, nationality, marital status, and distance from the hiring companies” are also included.

This post is to comment on the representation of emerging technology and its application to recruitment, and it’s not my intention to speculate on a possible future of robots replacing humans, but there’s an algorithmic future that’s being neatly swept under the carpet by those who are “pro-robot”.  Research from Harvard University found that ads for arrest records were significantly more likely to show up on searches for distinctively black names or a historically black fraternity.  Research from the University of Washington found that a Google Images search for “C.E.O.” produced 11 percent women, even though 27 percent of United States chief executives are women. (On a recent search, the first picture of a woman to appear, on the second page, was the C.E.O. Barbie doll.)  Google’s AdWords system showed an ad for high-income jobs to men much more often than it showed the ad to women, a new study by Carnegie Mellon University researchers found.  Those who advocate a perfect future will have to confront this research and much more like it.  Whilst it’s often cited by overzealous salespeople that algorithms based on data are free from bias, software is not free of human influence. Algorithms are written and maintained by people, and machine learning algorithms adjust what they do based on people’s behaviour.  All this is even before a well meaning but industry-novice programmer opts to include factors like “age, gender, nationality and marital status” which are explicitly protected in discrimination law. Would an organisation deploying such an algorithm to sift candidates have to expose how the selection was arrived at?  Would candidates still be afforded the same protections?

The problem here is that programmatically applying a simplistic model doesn’t allow for any degree of nuance, and when we’re seeking to measure humans, nuance is everything. Sorting and ranking algorithms for stock in a warehouse have a great advantage over those that seek to catalogue people, and books on a shelf or a can of baked beans in a supermarket don’t have the free will to opt out of the process at any time, but humans do.  Historically, humans have opted out of over-automated processes. I remember a UK bank luring customers back to the fold with the “promise of no automated call centres” and several websites offer the opportunity to “talk to a real person”.  For those companies unwilling to interact at these early stages there may come a time of reckoning when candidates opt instead for a more human process, and not to become a human to be processed.

So how did we get here?  Why is it that the future is either an electric nirvana or a desolate dystopia? Like a lot of science reporting in the media the rise of technology is held up as a scare story, a robo-bogeyman to frighten HR.  Uniquely in the world of HR and recruitment a wealth of the content on the rise of technology is written by those who are selling the products. We have a discourse owned by the vendors, and an audience that doesn’t want to, or hasn’t invested the time to learn about the tech.  It’s no wonder that somewhere in the middle of all this, there is misunderstanding, acceptance and skepticism, and for some money to be made in this new wild west frontier.  For the rest of us there is plenty of content filled with wild claims and spurious statistics, you might not agree with the findings of studies of the claims or the vendors, but I’m sure someone somewhere is ready to tell you that “60% of the time, it works every time”.

Screen Shot 2016-06-01 at 15.18.28

 

 

Podcast – Innovation and The Future of Recruitment

Another podcast, and a return to talking with the brilliant Matt Alder.  Matt continues to compile a series of excellent perspectives on recruiting and HR called Recruiting Future, you can listen to the whole series here.

To listen to me try my hand at some futurism and badmouth clumsy attempts to use Snapchat for Recruitment hit play below!

Data and HR – Numbers are Nothing Without Insight

Managing employees and an HR function requires a more holistic approach than exploring issues from the surface.

People use statistics as a drunk uses a lamppost – for support rather than illumination. – E. Houseman (1903)

Our online activity has meant a ubiquitous lens is shone on our lives where the accessibility of data leaves leaders believing every metric can be measured, compared and leveraged, contributing to a curious new world of seemingly ‘crystal clarity’ that was seldom thought possible. The problem, however, arises when data collection occurs without the insight required to take contextual influences into account. Leading the way for deeply consequential misinterpretation and misjudgement to arise. This ubiquitous lens, unless harnessed correctly, stands to confuse as much as it will clarify.

For me, context is the cornerstone of moving from data to insight in a human way, which will clarify, rather than confuse. Nowhere is this more important than in the HR function, where the source of data; humans, operates in a fashion that led author Phillip Lieberman to label us as the “unpredictable species.”

This is best illustrated by highlighting a data source that is predictable, like books in a bookstore. For the bookstore, doing inventory is easy. The metrics needed are things like how many books are on the shelves and how many have been bought. Once a book is bought, there are no external factors influencing its behaviour not to be removed from that shelf. The book doesn’t decide that its commute is too long, or that its wife no longer wants it to work at its company, or that its pay packet isn’t satisfactory. Thus the likelihood of it leaving the bookstore, (unless I am seriously overlooking something) for any reason other than it being bought or stolen is highly unlikely. This is because the external factors surrounding it are predictable.

Humans on the other hand are a different story. Aristotle wrote that we are “rational animals” pursuing knowledge for its own sake. We live by art and reasoning he said. Whilst I’m sure many HR professionals would love to see their employee population be as predictable as books on bookshelves, myself included, the multiple external factors that make humankind human are unlikely to change soon. Which makes producing blanket metrics and chasing large numbers such a dangerous game, because in doing so, the individual is naturally rejected. It’s like saying “we have increased our likes on Facebook which means that we are doing better as a company.”

All that we get from this is a top line number. What do you actually mean by this? What does this equate to? If these questions aren’t followed up, then where does the return on investment come from? Is this useless? This problem becomes even more salient when you consider that HR systems for the most part aren’t built in ways that enable contextual data to be factored in. Nor will a majority HR systems allow data to be exported for further analysis, leaving you stuck analysing the top line, leaving retroactive approaches to remain.

Until contextual factors can be included within HR systems and data analysis, I personally believe HR isn’t critically equipped to have a discussion around data at all. Instead of building a data set from the ground up specifically focussing on important questions we want answers to alongside the external factors that influence them, we tend to take a retroactive approach by attempting to find data to support new questions. The same applies for the big data phenomenon (which by the way, unless you are Facebook or some other such platform are unlikely to truly have a big data set). Gartner’s definition of big data is “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” Playing with data sets of this nature without taking into account the contextual factors that directly influence decision-making processes as they happen will ultimately lead to skewed results and misinterpretation.

So my advice to those individuals taking the data approach is simple: ensure you keep the human in human resources. I am not ruling out this approach whatsoever, however ensuring HR professionals take a step back is key, especially if we are to glean the results required that are free of bias.

“You’ve got to have an Algorithm!” A Recruiter’s Guide to the A-word

Even if you only have a casual interest in the world of hiring it’s not long before you’ll encounter someone touting a magic bullet, a panacea for the “broken” world of recruitment globally.  Currently riding high on the buzzword bingo cards of these self-styled saviours is the humble “algorithm”.  This isn’t the algorithm you might know from maths or computer science however, the “algorithms” of recruitment are like a sorcerer’s incantations able to transform the world and imbue those that utter the word with sage like prowess and a cloak woven from the finest of Thought Leader hair…

In other disciplines the word algorithm is well defined (a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer), yet despite this there is a shift in understanding when we talk about algorithms for recruitment.  Because the discourse of recruitment is largely owned by those who wish to sell to practitioners the humble algorithm has become the magic in the box that’s too difficult to explain.  Algorithms are the elves who make the shoes whilst the shoemaker sleeps.  It’s because of this lack of understanding that each new tool that’s presented to HR, from personality quizzes based on dubious pseudoscience to true recommendation engines and all touted as having an algorithm with little or no distinction.

For the ease of understanding an algorithm is a set of well-defined instructions for carrying out a particular task. It must be sound and complete. That means it must give you the correct answer and it must work for all cases.  Usually, an algorithm is predictable, deterministic, and not subject to chance. An algorithm tells you how to go from point A to point B with no detours, it doesn’t stop to look at the flowers or to consider other factors outside of it’s available data along the way.

Does that sound like a recruitment process to you?  I’d struggle to find a recruitment process that supplies a “correct” outcome, and the notions of sound and complete aren’t interchangeable between organisations – what makes a developer a great fit for one company might be less relevant for yours. Recruitment processes are subject to chance and to that perfect serendipity of the right person available at the right time.  When a recruitment process is good for both the company and the candidate it bears the unique fingerprint of the culture of the company that created it.

All this must be very disappointing for those fans of buzzwords but fear not! Here’s a new one for you! Whilst I don’t believe in an algorithmic approach outside of tools that aid human efficiency there is a way to describe the recruitment process and still get the reflected glory of using a lovely big word.

H-Bomb

heuristic is a technique that helps you look for an answer. Its results are subject to chance because a heuristic tells you only how to look, not what to find. It doesn’t tell you how to get directly from point A to point B; it might not even know where point A and point B are. Heuristics are a practical methodology not guaranteed to be optimal or perfect, but sufficient to accomplish the goals required.  Examples of the use of this method include using a rule of thumb, an educated guess, an intuitive judgment, stereotyping, profiling, or common sense.  In effect, a heuristic is an algorithm in a clown suit. It’s less predictable and it’s more fun.

There are many reasons that the application of technology can make recruitment so much better for all involved but the miscalling of the effects of these improvements won’t help the industry or recruitment as a discipline.  The exaggeration of the effects, range and successes of the “algorithms” is hyperbole at best and at worst a thin veneer, attempting to add shine to the same old business practices shunted online.  The majority of recruitment success stories that herald algorithms as earth-shattering go on to describe a single section of the overall recruitment process being automated not the utopian future in which we are awarded jobs by are robot overlords as they seem to suggest.

Remember that a first round online screen or adding an automated stage into an existing process is less advanced and has less effect than the introduction of the water frames and power looms of the Industrial Revolution, despite what the hyperbolic headlines will tell you.

In the blind solutionism of the HR Tech vendors and those who seek to build personal profile for their technical leaps-that-aren’t, there are real dangers.  Not least of all at risk is the candidate experience, the diversity of our organisations and the objectivity to think critically to improve these tools further.  That’s a high price to pay for the acclaim of an attention grabbing headline.

There are a great number of fantastic HR Tech tools and new ones are arriving all the time.  It is the skill of a modern recruiter to know when to utilise which tool, at what time, to have the maximum beneficial effect.  In seeking to replicate the processes of others or glorify ourselves for our own successes we aren’t embracing a bold new technological stance we’re contributing to the “broken” world we look down on.

Distopia

Podcast – Tech Recruitment and Why Recruitment Algorithms Don’t Work – with Matt Alder

Another podcast, this time with the excellent Matt Alder.  Matt is compiling a series of excellent perspectives on recruiting called Recruiting Future, you can listen to the whole series here.

To listen to me talk about Startups, scale-ups and sledgehammers hit play below…

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How to be Happy – Time to call off the “Engagement”

“Yes that’s right, we had a one hundred percent response rate to the survey.”

The speaker from a international airline proudly stated his results. His lovingly compiled pie charts labelled “Engagement” were resplendent in the Power Point behind him.  The audience were incredulous, a one hundred percent response rate how was it possible they asked?

“…well, of course, we made the survey mandatory”.

Whilst there are many different definitions of “Engagement” in the HR world broadly speaking and employee’s commitment to and involvement with their work and their organisation seems a decent place to start.  Like most HR initiatives the will to measure engagement starts out as well intentioned and a move towards concern for the employees themselves.  However, too often, in the application and the building of processes around this the notion of “Are our employees OK?” has been replaced with “Are our employees productive?”.  The change is a subtle one and has occurred as the results of surveys have been used as the answers to questions for which they weren’t intended.  Engagement, when measured effectively can be broken down into constituent parts.

  • Intellectual engagement – Does the person feel challenged in their work, are they thinking.
  • Emotional engagement – Does the person feel positive about doing a good job, is there an efficient emotional reward structure in place.
  • Social engagement – Does the role facilitate positive interaction with their co-workers.

When used incorrectly they are answering different questions.

  • Productivity – Is the employee producing the requited amount of labour that the company expects
  • Performance – Findings of surveys here are used as a proxy to explain results.

The shift is small and goes beyond just the semantic. For one set of employers “engagement” is now about measuring what we can “get out” of a workforce.  Like many other terms the human aspect has become distanced and now the people in the organisation can be reduced to a resource, counted and catalogued accordingly.  Even the manner in which these surveys are conducted can affect the results.  An annual engagement survey sent to everyone in the organisation is little more than the pointed stick poking at the bloated corpse of your organisation’s apathy.  Everything they measure has already happened, it’s post-mortem and the changes it would be possible to make are already too late.  A few click boxes on a website once a year is a chore not a meaningful interaction, regardless of the best intentions those questions are compiled with.

Some forward thinking companies have found a better solution.  In 2003, Fred Reichheld, a partner at Bain & Company, created a new way of measuring how well an company treats the people whose lives it affects—how well it generates relationships worthy of loyalty.  His Net Promotor Score or NPS was widely adopted and in use of companies of all sizes, segmenting the people into Promoters, Passives and Detractors with it’s simple one or two questions.  There are a great deal of benefits of adopting this approach and adapting it for employees.  When creating an eNPS (employee NPS) the annual laundry list of questions and ratings is replaced with a more frequent check-in, trends in happiness can be linked to real changes in the environment.  An entire team’s mood seems to be changing? Maybe it’s that new office space? Maybe it’s that new manager? Waiting 6 months to a year later to issue a survey is all too late.

ENPS-eng

So engagement surveys are too little too late and misused tools for measuring productivity.  eNPS is an improvement but in it’s attempt to be as answerable as possible still misses some of the larger aspects of the employee experience.  Some companies seem content to only measure those periods of time they are extracting effort from their employees, ignoring completely the fact there are external influences that might occur after 5pm.  The current toolset of HR is ill-equipped for the reality that the productivity and performance are great to measure but just as important are those things that employees themselves want to get out of work.

There is an alternative that more progressive organisations are adopting and in doing so re-humanising the process of collecting this data.  Instead of asking if an employee would recommend a place of work or waiting a year to prod at them with a laborious survey they ask a one question daily.  “How happy were you today?“.

Happiness at work and employee engagement are similar ideas but have unique and subtle differences in meaning.  Imagine you are managing a team and told to make them “more engaged” it might sound like a request for more meetings, for incentivising longer hours or an edict to start “cracking the whip”. Compare this with a manager tasked to make their team “happier”, this request isn’t about driving productivity. It feels more like a search for ways to empower the team, remove obstacles and better motivate them.

There are a number of new tools that seek to give a better insight into this broader question, at Forward Partners we use the MoodMap tool from Happiness Works. The tool asks the single question “How Happy were you today?” every day at 5pm.  I can answer in one click of the mouse.  Monthly “Climate Studies” probe deeper and allow more insight but not at the cost of provoking respondent apathy or the feeling that it’s all “too little too late”.  Better yet the tool allows respondents to offer “ideas” for improvements in the workplace.  In our use of the tool it’s been interesting to note that these ideas mirrored almost perfectly sections of Maslow’s hierarchy of needs.  The first suggestions were physiological or environmental – the air-con is noisy, my chair is uncomfortable etc.  In fixing these small, nagging, yet solvable items the “ideas” we’ve captured have evolved too.  There have been ideas for conference attendance, skill sharing, training budgets and social outing suggestions.  How’s that for “engagement”?

moodmap.io example

No software tool is magic and whilst it has been incredibly beneficial perhaps the biggest benefit is in facilitating the conversation around employee happiness.  For those companies looking for a way to gain insight into their employee’s well being and then empowering them to improve themselves and their environment these tools could be a great way.  Of course for the rest of you you have about 12 months to sharpen that pointy stick, or maybe wait to get that insight at the exit interviews?

pointy stick

Video – Employer Branding Panel at Stack Overflow Careers – London Tech Talent Week

Stack Overflow hosted a panel on Employer Branding in their shiny new offices and they were kind enough to let me offer some thoughts.  It’s interesting that when thinking about Employer Branding the panel often didn’t seem to be using the same definition.  With the growing interest in the area as companies seek to differentiate themselves via their “culture” hopefully you’ll find this of interest.

The entire panel is split over three videos so settle in… fetch popcorn…

Podcast – How To Shape Startup Culture Using Archetypes – The Lexoo Blog

Lexoo are one of the startups I’m lucky enough to work with at Forward Partners. They asked me to talk to them about the culture of Forward Partners and how we defined what that really was. We talked about Jungian archetypes, why Nike is the hero in their own story and why we have a whip and lightsaber in the office.

There’s a transcript and some other links to the workshop presentation here.