Post Meeting Review Notes - Strategic Workforce Analytics

Deploying HR Analytics for Better Talent Management and Organisational Effectiveness PRESENTERS: Gillian Pillans, Research Director, Corporate Research Forum (CRF) Alec Levenson, Senior Research Scientist, Center for Effective Organisations Olly Britnell, Head of Global Workforce Analytics, Experian Pranav Chadha, Senior Manager Talent & Digital and Analytics, Adidas Tim Haynes, Global Head of Organisational & People Analytics, GSK Dr Nigel Guenole, Senior Lecturer and Director of Research for the Institute of Management at Goldsmiths, University of London Gillian Pillans summarised the research report, based on around 220 survey responses, 40+ interviews with practitioners, experts and consultants – plus a lot of reading! Whilst strategic workforce analytics is certainly a hot topic, for most organisations, it’s early days

Most people start with modelling and predicting turnover, but these may not be the most business critical issues. Unfortunately, there is still too much focus on ‘HR for HR’, rather than for business performance and benefits, and this is exacerbated by too much of a ‘silo mentality’.

Resource, data quality and HR capability are seen as the greatest barriers. HR is less data and evidence driven than the organisation more generally, but there has been limited investment in upskilling the function.

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Deploying HR Analytics for Better Talent Management and Organisational Effectiveness Action    

points for the function therefore include: Start with the business strategy and critical business questions Insights need to lead to decisions and behaviour change Collaborate better with other functions and analytics teams Upskill the function

Alec Levenson gave his insights based on his book, ‘Strategic Analytics: Advancing Strategy Execution and Organizational Effectiveness’, and the perennial questions that organisations wanted to answer. The three main challenges were: 1. Analysis is disjointed and uncoordinated 2. Not everything matters to the same degree, with tasks and behaviours that that do NOT improve strategy execution vastly outnumbering the ones that do 3. Too many people start with solutions around individual jobs and behaviours, rather than thinking more systemically The solutions?

Firstly, establish a holistic diagnostic or causal model – either your own, or the one here.

Then understand that causation runs from individual to team to business, and that human capital performance leads to enterprise performance and strategy execution. And probably most importantly, ensure your analytics are working on the right issues – work the priorities as shown in the following slide.

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Deploying HR Analytics for Better Talent Management and Organisational Effectiveness Nigel Guenole took us through the challenges and opportunities of workforce analytics.

These challenges have seen the average life of a S&P 500 company drop from 60 to 10 years, and to combat this, firms need to cultivate the right types of assets: valuable, rare, inimitable and nonsubstitutable (VRIN). Assets such as land and factories are predictable, but people are less so – but analytics can help in making HR more predictable.

Nigel showed a checklist for preparedness for success in workforce analytics; within Europe, the top third had 8 or over, middle third 5-7, and the bottom third 4 and under.

He finished with 5 ‘truths’ about workforce analytics, the first one of which pointed out that you don’t always need it anyway!

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Deploying HR Analytics for Better Talent Management and Organisational Effectiveness The four other ‘truths’ were:  Research design compromises are costly  Date novelty is inversely related to utility  You can’t manage your workforce without knowing who they are, and this needs to include more psychological understandings as well as the usual demographics  Workforce analytics need to include two way influence; worker attributions about organisational intentions and analytics really matter Case study 1: Experian Olly Britnell, took us through how Experian are using predictive workforce analytics. He gave us a snapshot of the business for context.

The organisation itself uses modelling and propriety data sets extensively in building credit risk solutions for clients, as exampled here.

The team identified that the ‘hamster wheel of recruitment’ was a business issue with significant bottom line impact – every 1% reduction in unwanted attrition (running above industry benchmarks) would produce $3m in savings – so they focused on building predictive capability, using the tools and techniques that they would use with clients. © Corporate Research Forum 2017

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Deploying HR Analytics for Better Talent Management and Organisational Effectiveness He showed the model in action with the flight risk example.

They then built an application that gave a headline profile for every employee, based on these key demographics; it’s simple, intuitive and usable. The data can be used to drive appropriate interventions.

Olly stressed that this was not a ‘silver bullet’, but more of an aid to be having the right conversations – ‘a toolkit to drive a different debate’.

And has it worked? Evidence so far shows that is has, reducing attrition in some high volume areas.

However, the paradox is that as interventions improve, the power of the model will decrease.

Experian is exploring options for making its predictive attrition analytics model available to other organisations. If you're interested in taking part in a pilot, please contact Olly at olly.britnell@experian.com.

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Deploying HR Analytics for Better Talent Management and Organisational Effectiveness Case study 2: Adidas Pranav Chadha gave a real-time demonstration of the Adidas Talent Acquisition Analytics tool. The aim is always to make data simple, sexy and playful.

The tool was built in-house, with a 3 person team fuelled on pizza and beer, with no budget. It provides a single source of truth about what’s happening right across talent acquisition globally; everyone has access. It’s agile, transparent, and enables transfer of learning across the organisation.

Candidates can give feedback about the whole hiring experience, and hiring managers have realised that this feeds back into potential customer buying expectations too.

Case study 3: GSK Gillian interviewed Tim Haynes covering 108,000 employees in 160 countries. Insights included:  Progress is never linear, and also don’t underestimate the value of reporting  Ideally analytics teams include people with a variety of skills e.g. organisation psychologists as well as HRIS experts. Don’t forget political savvy too!  Work on business critical issues e.g. for them, manufacturing in the US has a large supply chain and heavy regulation – any quality issue could lead to shut-down. They have built a predictive tool, incorporating workforce data (e.g. adherence to technical training) to look at potential quality risks across sites.  Don’t get taken in by ‘watermelon dashboards – looks green all over on the outside, but it’s all very different and red inside’!  The new CEO sees behaviours and culture as hugely important, and she is using Tim’s team to help look at the mood. They worked with internal communications to use both qualitative and quantitative (e.g. employee surveys, Yammer comments) to put together a clear picture.  HRBP’s are key – they need to be helped and encouraged to use analytics, and not leave it to the central team.  It is important to have a sponsor who asks the business critical question, and then be able to produce the insight to make a difference as the answer.

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