HR Transformer Blog


Managing Attrition - Are You Looking Backwards or Forwards?

Glass Bead Consulting - Attrition

How do you manage attrition?

Most companies will review last month’s attrition figures, long after the star employees have had their farewell leaving do. This is the equivalent to looking behind in the rear-view mirror, whilst travelling at speed - you may know what’s behind you but it’s too late to do anything about it.   Or do you look forward, anticipating trends of employee flight risk and making small adjustments as you travel down the road?  After all, if you can see the possible obstacle ahead you have a better chance to avoid it.

As wages continue to rise, we see more employees dipping their toes in the welcoming water of the job market.  Keeping our best employees with us on our journey is going to be hard and managing the cost of unwanted employee turnover is going to be even harder.

Marc Andreessen, co-founder of Netscape and early Facebook investor, has said,

“Five great programmers can completely outperform 1,000 mediocre programmers.”

So how do we quantify the cost of losing our best employee? 

The calculation for the cost of losing an employee varies from one organisation to another, but typically includes hiring, on-boarding, training and ramp-up time to peak productivity. Other costs that need to be factored are loss of morale due to high turnover, higher business error rates, and a possible impact on a company’s culture and customer reputation.

Deloitte estimate the cost of losing an employee can range up to two times the employee’s annual salary.  Given the significant financial impact, it is surprising that 40.7% of UK organisations do not measure the cost of attrition, according to XpertHR.

This prompts some basic questions organisations should be asking about attrition such as:

  • Do you have a good idea of what your attrition levels will be over the next few quarters?
  • Do you calculate the probability and the impact of losing an employee?
  • Do you know the actual cost of attrition in your business?
  • Can you prove which factors cause unwanted attrition in your organisation?
  • Do you know which interventions are more likely to keep the higher performers (the five great programmers) and let the laggards leave?

Looking at attrition in the rear-view mirror

Many HR teams measure who has left the company in the last period, in which division, and what type of role as a way of broadly measuring attrition.  However, looking in the rear-view mirror only describes what’s behind us, it doesn’t tell us what is coming up, which makes it harder to prepare for unexpected change.   By the time we have realised it is too late.

Looking forward using predictive analytics

What we really need is to manage attrition more proactively by understanding who is more likely to leave and what the impact of them leaving would be on the business.  In a smallish company this is straightforward, but where you have larger teams, spans of control and distributed teams this becomes much more difficult.

Credit Suisse found that a one-point reduction in regretted attrition saved the bank $75 million to $100 million a year.  So building an attrition prediction model is one way for HR to make a substantial impact on the bottom-line.  See “The Algorithm that tells the boss who might quit”.

For those interested in more People Analytic case studies, including attrition, go to David Green’s excellent summary “20 People Analytics Case Studies

Using an evidence-based approach, we need to critically assess different sources of evidence.  Building your own predictive model is one way of building up a reasonably strong source of organisational evidence.  It is also worth reviewing the scientific research as another source of evidence, see this meta-analysis for example and reference below.  

Tej Mehta from Owen Analytics, explains the benefits of using predictive analytics,

“A typical approach will brainstorm all the potential factors that might cause an individual to leave. These are then used as inputs into machine learning algorithms that can predict flight risk with a high degree of accuracy which is often over 80%.”

The attrition landscape needs to be revisited if organisations are to remain competitive as they make their respective journeys.  Predictive analytics can be a step change for the HR community, at the very least providing some useful dashboard controls to enable better decision making.

I hope this article has given you some useful ideas and maybe some inspiration.  As always I would be interested in hearing about your examples using predictive analytics to better manage retention and attrition.    In response to our clients’ request to provide this service, are delighted to announce that we have launched a new service “Managing Attrition using Predictive Analytics”.

Some other useful resources to improve attrition management

Why Do Workers Quit? The Factors That Predict Employee Turnover (19 page PDF from Glassdoor)

Turnover: Predicting Attrition - A great free training resources from University of Pennsylvania | Coursera

Whether your company has 500 or 120,000 employees, there are many things you can do to improve retention and manage attrition, see Managing attrition using simple analytics

Meta-Analytic Review of Employee Turnover as a Predictor of Firm Performance (2011)    Julie I. Hancock, David G. Allen, Frank A. Bosco, Karen R. McDaniel, Charles A. Pierce

 

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Let Them Eat Tech

@AndySpence

The HR Tech Congress, the second held in Paris, was yet again a splendid mix of stimulating speakers, great organisations and brilliant technology.  However, the smell of revolution was in the air…

Professor Gary Hamel made a rallying cry that was so loud it could be heard 17km away in The Palace of Versailles,”Kill bureaucracy and you’ll unclog the arteries of business,” whilst Dr.Daniel Thorniley warned us about the economy, and it was not good news.  Debt, low growth and a rising populist tide in politics means soon we will all be working in the gig economy, whether we like it or not.

How will we survive this extended downturn?

“What will we eat?” they ask.

 “Let them eat cake!” the response of the ancien régime.

(Or as Marie Antoinette did not say “Qu’ils mangent de la brioche”. But ‘let them eat brioche’ doesn’t have the same ring to it – anyway I digress)

Gary Hamel told the HR audience to “to stop fiddling at the margins” and take up arms against bureaucracy, the biggest barrier to productivity in business.  Hamel even invented a word for this corporate disease “Bureausclerosis

If you can spell it, surely you can destroy it, right?

The symptoms of bureausclerosis Hamel described were: added management layers, isolation of leaders, longer decision cycles, increase in formalized policies, rule proliferation, increase in power of staff groups, organization becomes primitive, loss of ‘voice’ from staff, increase in legal processes, decrease in risk-taking, and the politicization of it all.

Ready or not, here comes the Gig Economy

If Professor Hamel gave us some examples of what was needed to transform business, Dr. Daniel Thorniley provided us with the big picture on the economy.  We are living in an unprecedented period of low growth where 63% of youths in the Eurozone do not have proper contracted employment.  Many will be forced into the Gig Economy, and this doesn’t just mean a nation of musicians and artisans, but also hosts, drivers, plumbers and (of course) humble HR consultants. Many will struggle to make a living or have the security that the previous generation have taken for granted.  I read Thorniley’s latest 46-page report, Global Business Outlook 2016-2020, with the cheery subtitle, “Why there is no future for your children.”

Now all this makes for gloomy reading and we might expect delegates of HR Tech Congress to dust off their Édith Piaf records and get out the whiskey,

but many could be heard asking, “OK, it all sounds terrible, but does this impact me?”

“Mais oui, bien sur!” (my franglais is improving)

In HR, changing business models and global economic drivers will determine whether we are scrambling for candidates, sweating our employees for discretionary effort, or working on clever algorithms to automate work.  I would guess a larger proportion of the 3,500 delegates will be joining the gig economy over the next few years.

One thing’s for sure, we might not be able to guess where the economy is going, but there are plenty of technology developments to get excited about.

Software is eating HR

So, if our business models and organisations are changing before our eyes, this raises some big questions.

How does this affect the way we think of work, organisations, and society?

Do our old people management practices still work?

How does HR respond to this? “New systems anyone?”

There is nothing so useless as doing efficiently that which should not be done at all.” – Peter Drucker

This message seems to resonate with the HR Technology industry and is especially true now.

My concern is whether we have the right set of people management practices for the type of organisations that Hamel says will flourish?  Are we in danger of simply crystallising the processes that served us well in the last century?

These and other questions present the challenge for HR and the technology industry today.

I had the pleasure of introducing some excellent presentations in the well-attended HR Tech stream, so could not attend as many presentations as usual.  However, my fellow blog squad comrades have done a great job of sharing what they saw.

-> Reinventing HR: 12 key takeaways from #HRTechWorld from David Green

-> My top 10 disruptHR’ers at HR Tech World Congress from Faye Holland

-> Accelerating Gender Balance in Tech from Dorothy Dalton

-> And this is a great resource – all the presentations from Paris (and previous conferences) in one place: HR Tech World Congress Presentations

I was also fortunate enough to look under the bonnet of some of the latest tech tools, and I am particularly interested in the use of predictive analytics and artificial intelligence in solving business problems.  I saw some useful tools that work as a stop gap for current recruiting/ATS software, e.g. tools that help prioritise recruiters workload using simple algorithms.

There were some nice looking visualisation tools that sit on top of current HRIS systems showing historic data.  However, I was disappointed that I didn’t find any genuine machine learning or pattern recognition in this space, despite some of the marketing claims.   People Analytics is an exciting area in the early stages of its development.  However we need to overcome some key challenges to be successful, see my recent post, “7 Challenges That People Analytics Must Overcome”

Building the new HR Republic

There were many great stories of companies building the new republic, making progress, solving business problems and embracing technology.   Technology is indeed being used to transform whole industries and the biggest impact on HR will not be on how we operate, but on how we manage work in the future.

For those in HR and leadership roles, there is plenty we can do before we even think of buy new software. We can start by asking, what is the evidence that this practice (e.g. performance, talent, hiring, learning, engagement) works in our organisation now, and will do in the future?

It was a dismal economist who gave our profession the name, Human Resources, rendering people as an asset to manage.

Maybe this term also belongs to the last century along with Bureaucracy?

As with many revolutions, there will be casualties, but change can pave the way for a new order and a better approach to people management.

So when managers in your organisation ask about the conference and the impact on their staff, you might mention defeating bureausclerosis, the challenges of low growth and the gig economy.

If they then ask, “But, what will they eat?”, just simply reply,

“Let them eat tech”.

À bientôt.

(This was a guest post on the HRN Blog)

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7 Challenges that People Analytics Must Overcome

People Analytics - Glass Bead Consulting

7 Challenges that People Analytics Must Overcome

I am excited about the role People Analytics will play in transforming organisations.  I have seen some real success stories where organisations have incorporated more data-driven decisions about people and work. 

David Green highlights some great case-studies in his article, 20 People Analytics case-studies, which includes, Virgin Media, who reduced sickness absence rates from 9% to 4% saving the business £750,000.

There is clearly a journey to be taken where we move from our current starting point, where we often distrust the data we have on employees, to a place where we can better predict sickness absence, attrition and productivity.

Most organisations are already on this journey to some degree. The percentage of companies that believe they are fully capable of developing predictive models doubled this year, from 4% in 2015 to 8% in 2016, according to research by Deloitte, “Global Human Capital Trends 2016”.   However this journey will have some challenges that we will need to overcome.

People Analytics can play a key role in reinventing organisations.  However we need to resolve some of the structural challenges to truly succeed.  I covered some of these themes in my recent presentation, The Role of HR in Reinventing Organisations: Embracing People Analytics, at the Workforce Analytics Summit in Sydney.

Despite the hype, there is low adoption of People Analytics at the moment – here are some of the challenges that I think we need to address and also some suggestions of how WE (in the broadest sense) can overcome these challenges.

As always, I would welcome your views on the challenges, and especially ideas, and examples of how to overcome them.

Challenge 1 - We prefer ‘gut feelings’ to make people-based decisions

"80% of HR practitioners say their company leaders still rely on 'gut feelings' to make people-based decisions"  according to a survey of Human Capital Institute members in partnership with Oracle.

What’s wrong with using ‘gut-feelings’ to make people-based decision?

Professor Rob Briner from Bath University explains in his article What’s the evidence for…Evidence-Based HR?  that “our intuition is a valid source of evidence, albeit a weak source.” 

Daniel Kahneman, in his book – Thinking, Fast and Slow described two main types of thinking well with their inherent biases.

When you are under time pressure for a decision, you need to follow intuition. There is nothing wrong with using our intuition or gut feeling, but as Kahneman has said “you should not take your intuitions at face value”

So back to the challenge for those with skills in People Analytics, if your business customers do not believe that data is useful then they will not ask for it, or use it, or believe in it.  Which is a fairly big challenge!

So how do we overcome this challenge? Maybe there is a middle way between the fast and slow lane?

What you can do:

Make sure the boss ‘gets’ using evidence-based data.  If you are the boss, then make sure your new hires also ‘get’ it.  

Make intuitive decisions more data-based AND our data-based decisions more intuitive

 

Challenge 2 – The Peak of Inflated Expectations

Emerging Technology Hype Cycle - Gartner Emerging Technology Hype Cycle - Gartner

In HR we have always had business problems, statistical knowledge and access to piles of data, so why the hype around People Analytics now?  Well the Cloud and Big Data sales machine is probably talking to your boss right now.  You know the pitch, “Analytics pays $13.01 for every dollar spent”.

Managing expectations on people performance with the CEO should be your job and as mentioned, People Analytics has delivered some good early results, but one of the biggest dangers right now is far too much hype.

Since 1995 Gartner has been measuring The Hype Cycle, the promise of emerging technologies, and shows five key phases of a technology’s life cycle.  Is People Analytics in danger of succumbing to the hype before it delivers benefits?

Peak of Inflated Expectations -> “Early publicity produces a number of success stories – often accompanied by scores of failures. Some companies take action; many do not”

Trough of Disillusionment -> “Interest wanes as experiments and implementations fail to deliver.”

So what if the CEO gets excited about HR once in a generation you might say?  What happens if we set expectations too high for People Analytics and do not deliver?  It will not be the first time that HR has over-promised and under-delivered based on “best-practice”.  At some point you will need new recruits in a competitive market which needs new software, but there’s only  so many times you submit a business case with a decent ROI.  What you really need is some early positive results.

What you can do:

Set realistic expectations on people analytics – aim low  and over-deliver.

Start with a specific business problem

Learn from the early adopters

 

Challenge 3 – HR doesn’t need Big Data, it needs Big Questions

“Without data you are just another person with an opinion” W.Edwards Deming

But, “Without questions, you are just another person with data”

There is a danger that People Analytics is a solution looking for a problem and in the “scientific method as an ongoing process”, the generation of interesting questions is a key step. 

To do this we need to know the business.

I had a client a few years ago, who trained a group of HR Business Partners as 6-Sigma Black Belts.  After the training, they demanded a data dump from Peoplesoft.  "What problem are you trying to solve?” and the reply was “We don’t know yet until we see the data…”.

The example highlights the need to solve business problems not analyse data.  Strategy is all about making choices, so if you run an analytics team, generate as many questions and hypotheses around a particular problem area as you can by casting the net widely.  

What you can do:

Generate many wide ranging questions and hypotheses which solves business problems

Coach Business Partners and HR into developing hypotheses and sharing the insights back to the business

 

Challenge 4 – We need the right tools to do the job

This paper is worth reading, “HR and Analytics: why HR is set to fail the big data challenge”  (Angrave et al, 2016)  published in Human Resource Management Journal. 

As you might expect from the provocative title, they don’t hold back :-

“the HR analytics industry, which is largely based around products and services, which too often fail to provide the tools for HR to create and capture the strategic value of HR data.”

In other words, our HR Systems, data and reporting tools might not help us answer the business questions we have.  Many HR operational systems were simply not designed for analytics, and although they are improving, I expect to see more sophisticated analytics functionality in subsequent software releases.

What you can do:

Keep discussing your needs with your Technology Partners

Collaborate with others in the industry to source great tools

 

Challenge 5 – No confidence in the underlying frameworks

To use a house analogy, there is no point having cameras & sensors, unless the house is structurally sound in the first place.  We need to have a roof, secure doors and running water before we can add sensors that optimise our heating, detect poisonous gas, detect intruders etc

As Max Blumberg says in his article, People Analytics: Who’s fooling who?   “if like most people you don’t believe in your organisation’s competency and performance management frameworks, then you certainly aren’t in a position to believe in the results of statistical analysis based on data generated by these frameworks. As the old acronym GIGO says, Garbage In, Garbage Out.”

What we are crying out for is a theoretical framework to test our hypotheses about people, behaviour, productivity and organisations.  We are not there yet, but I am optimistic that over the next few years we can develop the skills and knowledge to increase our confidence levels in people management.

What you can do:

Stop doing people analytics until you’ve fixed your frameworks.

Collaborate with academia and peers in other organisations

 

Challenge 6 – Show me the Money

The problem is, you can show the C-Suite pretty data visualisations of their organisation showing attrition, gender balance,  and average commuting time, but the hard truth is the CEO will only really listen when you link it to Revenue and Profits.  When it comes to employees, the holy-grail is increasing employee productivity.  We need to link as much as possible to employee Productivity to get ‘buy-in’.

What you can do:

Develop your own internal measures for employee productivity

Try and link your initiatives to improving employee productivity

 

Challenge 7 – Structural issues with HR Operating Models

I have been speaking and writing about some of the structural issues with HR Operating Models for many years (see for instance, Is your HR Operating Model Fit for the Future?  If the supporting structures for HR analytics are not in place, then the probability of success is lower.

A couple of structural issues with HR Operating models that many orgs sill grapple with are:

Working in silos.  In HR we have developed some great experts over the last few years (e.g. talent, learning, reward etc) yet we have also become a function of specialists creating more silos which makes it harder (not impossible) to work together as a whole to deliver HR (Business) strategy.

The role of HR Business Partner.  The role was introduced as a strategic partner and account manager for HR Services, however there have been challenges.  Many orgs are on their 3rd or 4th revisions of this role and HR BPs are key to solving business problems as key customers for an analytics service.   However we are in a transition phase, as described by “Most HR BPs won’t cut it…”   from Luc Smeyers and “Stop Hiring Data Scientists if you’re not ready for Data Science” from Greta Roberts.

We will never have the optimal HR Operating Model with managers, systems, HR experts working seamlessly together.  However we can strive to continually improve the model using People Analytics to help rethink many of our HR programmes and influencing how we deliver our people management.

What you can do:

Learn some of the lessons from others in HR Transformations over the last few years

Ensure Business Partners have good analytical skills and are inquisitive about the business. Provide coaching on basic statistics and people analytics where needed.

Continually evaluate the efficacy of our HR and Management initiatives

My “gut-feeling” is that People Analytics will help reinvent organisations.  We are in the early stages of a journey and we can all help by sharing methods, learnings and positive results.  We need to keep an eye on some of the near-term challenges as we move forward.   One key action within our control is to set realistic expectations and solve specific business problems.  This can get our business partners more interested into a different way of working.  The technology industry will probably evolve to roll-out improved offerings with time.  And our evidence base should get better as we improve data quality and start to ask better informed questions.  Although the ecosystem I refer to is complex, with diverse vested interests, we should continue to encourage sharing and collaboration as much as possible.  

Here is a presentation on "7 Challenges that People Analytics Must Overcome" I gave at HR Congress Amsterdam in November 2016.

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State of HR Systems Market Europe 2016 Sierra Cedar Survey Results

For the last 19th years, Sierra Cedar have been conducting a survey on HR System adoption.  This demonstrates admirable commitment to a market that ebbs and flows like the form of our star strikers in the European Football Championships (who are only on their 15th edition).  The survey is an invaluable resource to those working in the HR Technology ecosystem – the report can be downloaded here.  In this article I wanted to share some of the findings that caught my eye, but mainly to ask you to complete the survey for your organisation, before 8th July, so that this report is even more valuable next year!

The Big 2 still dominate – I am not talking about the Germany and Spain duopoly in Euro 2016, who have won most cups with 3 each.  In European HRMS adoption, the ‘Big 2’ tech providers, Oracle and SAP, dominate with 83% of the market.   SAP (HCM plus SuccessFactors) make up 52% and Oracle 31%.   ADP, Kronos and Workday make up 25%. This might surprise delegates who were at HR Tech World Spring 2016 in London, for example, noting the highly visible presence of CoreHR and Workday.  The ‘Big 2’ have their legacy customers, the onus is on the many challengers to prise them away and build their market share.

How much does this software cost? For large companies (with more than 10,000 employees), the average license cost per employee per year, is $116 (or €102).   For smaller companies with less than 2,500 employees, this cost is much more at $394 (€348).  This excludes implementation costs.  Now for this amount, you might even get you a ticket to one of the group stage matches in France.  In fact, why not spend the money on football tickets instead, your employee engagement scores will surely increase? *nervous laughter*.  When you have such highly paid employees on your payroll as Cristiano Ronaldo, who has a salary of €21m per year apparently, you want to get the most out of them.

Could wearable technology give us insight into players’ performance? 55% in the survey think using wearables will “increase workforce productivity”.  16% of organisations in the survey are using or evaluating wearable technology at the moment.  According to this article we might see Wayne Rooney cavorting around Old Trafford wearing a tracking device.

The most common pathway to an HR Technology Transformation, with 26.5%, is “Rip & Replace” which is basically moving everything all at once to the Cloud.  This is like selling your 3 most reliable players in a winning team – a tactic that is a bit risky!

Contrary to reading the industry press, not everyone is in the HR Cloud yet, it is estimated that about 50% of core HRMS is still on premise.  This might have something to do with the residual customers of the Big 2 taking their time on the upgrade path and working out options, and a rump of organisations where moving to the cloud brings more security and privacy issues.   One thing’s for sure, whichever country’s team wins in Paris will be in Cloud 9.

As you read the survey report, bear in mind the results are based on an adoption and do not represent market share.   In my view, it’s always useful to read these surveys for good background context.  This survey also highlights some of the trends the analysts are seeing and refers to useful frameworks used.  If you are considering making changes to your HR Systems, always go back a step to understand what your business really needs from HR and how this will support your HR Operating model. This article might also be useful – How to Earn your HR Cloud Tattoo.

Finally, make sure you complete the SURVEY before 8th July and good luck to your team in Euro 2016!

This article was a guest post on HRN Blog

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