“Talent is now the most scarce and valuable commodity on earth, so companies who really understand how to attract, retain, and manage people will win”.
– Patrick Coolen, 2015
HR analytics is more than simply data mining on employee efficiency. Beyond this it ultimately aims to provide tangible insight into the processes that define the day-to-day business operations – the pre-set actions taken that ultimately lead to the pence and pound on the bottom line. At its heart, it is about improving strategy and processes.
For many, the challenge that threatens the firm footing that HR analytics may provide, comes in the form of knowing what data to capture, and what data model to harness. Get either or both wrong and the envisaged optimal return on human capital is going to go unrealised. Here’s exactly what is entailed in this all-encompassing process – and here’s why corporations should be investing in what is analytics around their most invaluable resource.
Analytics achieves some great results – so why do some refer to a “gloomy landscape”?
Before I dive into the details of people analytics, I want to outline what some refer to as the “gloomy landscape” that is the current outlook.
Deloitte research suggests only 4% of HR departments have any form of predictive analytics in place, whilst more than 60% are still grappling with a mass (and when I say mass, read mess) of systems, even to get the most lacklustre of reports.
So, just what do I mean by lacklustre? Well that would be the fact that, for the most part, this 60% struggle to know how many people are on payroll on any given day, whilst most also fail to track hourly workers.
This is all despite people analytics delivering staggering results, as I’m just about to show you…
So, just what can be realised, when you get people analytics right?
One USA healthcare organisation achieved $100 million in savings, whilst also securing the Holy Grail in relation to its workforce – more engaged employees.
Bon-Ton identified attributes that made cosmetic reps successful – something that has led to an increase in sales per rep of $1,400, whilst driving down employee churn by 25%.
Wells Fargo, with predictive model in hand, has been able to select the most suited of candidates for teller and personal banker positions – this program has, within 12 months, achieved an increased retention rate in tellers and personal bankers of 15% and 12% respectively.
And one company (unnamed under NDA) reduced its retention bonuses by $20 million – as well as its employee attrition by 50% – all thanks to predictive behavioural analysis.
An appropriate analytics solution – The crux of the matter
Choosing the right analytics solution comes down to this, and this alone:
Businesses must know, upfront, what outcomes are sought from the tools used.
From this strategic standing start, a process as mapped out by Giles Slinger (2015) may be followed:
1. Get the questions clear
2. Get your data clean
3. Understand the ‘as-is’
4. Design the ‘to-be’
5. Understand the organisation as a system
HR analytics solutions: The options that lie before you
– The cloud based HR system – providing powerful integrated features pre-built and ready to go (such as Oracle, SAP, Rosslyn Analytics, ADP, IBM, Ultimate Software, Saba, Skillsoft, CornerstoneOnDemand, Workday).
– Smaller, creative providers – for more customised, targeted solutions (such as HiQLabs or iNostix).
– Purpose built data analytics systems – for systems designed completely around reporting and analytics (such as Google Analytics, Hadoop [IBM, HP, Microsoft, and Intel], Amazon, and Teradata).
HR analytics benchmarking: the latest thinking
“I shall try not to use statistics as a drunken man uses lamp-posts, for support rather than for illumination.”
– Andrew Lang, Scottish Novelist, 1937
Sage words indeed, and one that covers many of the most recent notions to emerge from HR analytics. These thoughts include: a focus on data that is combined with external data (social profiles, employee job history and more); analytics that is combined with the oft forgot gut feeling; decisions built upon more than purely data – for the protection of ethics; and analytics that is less about data crunching for the sake of it, and more about answering a pre-defined question or challenge.
These strands of thought continue to evolve, yet one of the strongest opinions in this realm is that Human Capital Analytics, doesn’t belong in HR at all. It’s for this reason that this branch of analytics is better called “People Analytics”. When we consider that this realm of data science can relate to sales, productivity, turnover, retention, accidents, fraud, and even the people-issues that drive customer retention and customer satisfaction, it’s clear that the expansive goals of People Analytics, span far beyond HR.
Ultimately, it is argued, removing People Analytics from HR can allow for better cohesion between the core departments that are responsible for these goals and objectives – finance, operations, and sales – for a truly end-to-end approach.
A matter of metrics
People analytics is far from a ‘one glove fits all’ task – organisations must tailor their approach and, of pivotal importance, benchmark their metrics. In layman’s terms this ensures that their analytics is achieving ‘bang for their buck’. That said, here are the most commonly harnessed of all metrics when it comes to people analytics:
– Staff advocacy score
– Employee engagement level
– Absenteeism Bradford Factor
– Human capital value added (HCVA)
– 360-degree feedback score
Not sure where to even begin?
If you’re unsure as to where to begin, it may be wise to start with recruitment – the realm of people analytics where the highest revenue growth and profit margin impact can be found.
“Recruitment is a good place to start, because if you can start to provide some predictive analytics about when and where we’re going to need people with whatever capabilities – way before people actually leave or we have vacancies, then that has a really significant impact on an organisation because there’s now downtime especially in critical roles”
– Andrew Lafontaine, senior director, HCM transformation, Oracle APAC
How well are you (really) managing human capital?
Let’s put some tangible numbers to the process – work out your human capital expertise by any one of the ten following suggested efficiency ratios:
1.) Revenue Factor = Revenue / Total Full Time Employees
2.) Voluntary Separation Rate = Voluntary Separations / Headcount
3.) Human Capital Value Added = (Revenue – Operating Expense – Compensation & Benefit Cost) / Total Full Time Employees
4.) Human Capital Return on Investment = (Revenue – Operating Expenses – Compensation & Benefit Cost) / Compensation & Benefit Cost
5.) Total Compensation Revenue Ratio = Compensation & Benefit Cost / Revenue
6.) Labour Cost Revenue Ratio = (Compensation & Benefit Cost + Other Personnel Cost) / Revenue
7.) Training Investment Factor = Total Training Cost / Headcount
8.) Cost per Hire = (Advertising + Agency Fees + Recruiter’s Salary/Benefits + Relocation + Other Expenses) / Operating Expenses
9.) Health Care Costs per Employee = Total Health Care Costs / Total Employees
10.) Turnover Costs = Termination Costs + Hiring Costs + Training Costs + Other Costs
People Analytics: Think you have what it takes?
People analytics is a demanding and complex role – and one that commands a wide variety of skill sets. Here’s a rundown of just what it takes:
– A degree and experience in mathematics, statistics, computer science and engineering
– Strong ability in Excel (such as macros, dashboards and pivot tables)
– Commercial acumen, analytical and interpretation skills
– Relationship building, influencing, intuition, and timing
– Clear storytelling skills (Ulrich and Rasmussen)
Looking toward the future
The future for companies that embrace people analytics is unequivocally bright – and already there is an increasing uptake in hiring for HR analytics professionals. As the axis of the world of commerce turns, we’re increasingly becoming an ever more knowledge-based economy. The result of which will be increased demand for ever more specific skillsets in the people analytics realm.
Yet the divide between this, and the current lacklustre performance amongst corporations is a staggering one – and one that is often compounded by people analytics incentives that start first with the data, rather than the business challenge, objective or goal. Just how the outlook of today, and the promise of the future, is to be bridged will be an interesting story to see unfold.