There are continuing conversations in HR, about data, people analytics, AI and the data and insights we should be deriving. I often wonder whether these are the right conversations. This month I found some of those right conversations at the CIPD Analytics Conference #HRAnalytics17, chaired by Mark Lawrence.
Mark sits on the Analytics Advisory Board to the CIPD and has a convincing track record on analytics results as a consultant and for IBM, PWC and M&S. I will be booking my place for next year!
The HR profession is right to focus on getting information out of technologies, as well as the ongoing transformation of our roles from an operative function into strategic leadership (have we reached the C-suite yet?!). But we do not always know how to make those conversations effective.
Below I've outlined some key points from the CIPD Analytics Conference to help you make these conversations more effective.
How leaders in the field are discussing the data
In the HR tech field, I often have cause to point out the decreasing importance of organisational size (have a read here about choosing systems in their context). When it comes to analytics size matters.
Blue-chips, as well as juggernauts, presented case studies at the conference. (And convinced me too that case study sessions are not necessarily the workshops to skip, which is my naughty event secret!)
In big business, achieving capability and standards that apply to all parts of a disparate organisation is the hardest challenge. At Nestle, the mission is to share value from impressive insight over some 190 countries, of which only those in the UK and the US are lucky enough to have an analytics team.
Thank goodness that Mark told me the CIPD did intend a “shock factor” for HR here. Because the fabulous potential showcased, with clear strategic vision for HR to move on from that admin role based on grasp of data, was convincing.
Yet it was also frankly pretty scarily advanced on the maths, stats and tech. Frequent reference to R may have left many hoping session speakers would fill in the blanks. I sat thinking “uh-oh, we have an accessibility problem”. Even worse, whilst the majority of HR system providers will merrily tell us their solution is the real deal on analytics, you need to take this with a generous pinch of salt.
But things cheer up!
Firstly McKinsey were amongst others keen to underline that “domain expertise” is invaluable. In fact it is irreplaceable by tech.
Domain expertise simply means knowing about the people data; which means knowing the business and the people. There is always a place for the value judgements that HR must apply to insights.
Secondly have the confidence to know that the right approach is to start with the business questions to be posed and refuse to be driven by drowning in data you feel needs sorting.
And thirdly, later case studies began to show that there are some more achievable steps on the journey to an analytics maturity. You can start on the essential analytics before getting predictive or start to combine your HCM core data with information from other parts of the business (e.g. finance), for example.
Harder questions remain unanswered but they are the right debates to be having:
- How do we create the business case for the most progressive analytics possibility?
- Is best fit always and necessarily the trump card over best practice?
- What are the ethics of response to requests for data?
- How do we resolve the potential tussle that data security (think: GDPR!) presents to our field?
- How leaders in the field are doing well with their data
Andy Charlwood, Professor of HRM at the University of Leeds supported the CIPD in bringing to the day the research evidence for people analytics. He showed us how much difference creating influential relationships with senior stakeholders is the springboard to success. “Form a coalition of the willing”, Andy advised.
Research findings also prompted debate, fuelled by more sobering evidence of the real proportion of organisations as progressive as Nestle, McKinsey clients or the National Grid, about the shortage of people analytics skills.
It is the specialist consultancy to the business that is hard to find – take “HR” out of the job title and relatively easy to get hold of analysts, BI experts or even data scientists, but there was consensus that it is a rare breed who combines people and business consulting skill with data analytical capability too. So on the mid-scale resourcing is the most likely challenge.
So if you are upwards of something like 1,000 employees (a guestimate kindly volunteered to me by Jordan Pettimore and one I’d support from our own experiences at Phase 3 Consulting) there is still a route to leading on people analytics, like these larger players. Here are just a few clues from the day:
- See your intended people analytics function with direct reporting into the Head of HR, CHRO or CEO and focus on those top-level influences. Use consultants if you cannot justify the headcount.
- Answer the “so what” question when you present example information, which means taking a lead from a key business question rather than making the mistake of measuring the operations of HR.
- Generate a curiosity and intrigue about data outside of the analytics team with story-telling and visualisation. Don’t underestimate how much difference achieving attractive dashboards will make.
- Achieve a key step forward by ensuring direct correction of data at source with self-service HR solutions, and use this essential technology to capture new data that you don’t yet own.
The Coop turnaround story showed me quite how practical this all can feel.
There the analytics mission has been to date all about plotting clearly-linked relationships between headcount, contracted hours, skills requirements on the floor and rostering.
This old knowledge has been the input to work with people analytics. The outcome is an empowerment for managers with evidence-based confidence in how to plan for flexibility, cover, give permission for leave and achieve optimum store performance.
How conversations are to continue
The end goal is to arrive at analytics as a service to your business. This means an iterative investigation into key business drivers with data insight. The business-as-usual service in itself is an ongoing dialogue with data.
And the journey towards that analytics maturity is for HR a “long game”, concluded the expert panel.
We are right to be talking a lot about HR analytics and I suggest we could do with some more focus for those back-at-base debates. Even amongst the leaders, these are continuing conversations.
Many thanks go to an impressive presentation at the event, based on impressive achievement with analytics from: Jordan Pettman, Global Head of People Data, Analytics & Planning, Nestle; Keith McNulty of McKinsey; Andrew Webster, head of all things people analytics at the National Grid. For some very accessible tips applicable to small and mid-sized business have a look at my own blog features at www.phase3consulting.co.uk; and HR Zone here feature my review of an excellent 2017 textbook on analytics.
About Kate Wadia
Kate’s passion at work is for bridging the gap between technology and people at work, translating for HR professionals the language of HR systems and making meaningful their potential.
She believes that success with people technology is through people and that people are the differentiator. Using simple techniques drawn from HR experience, project management, business psychology and analogy with everyday life, Kate presents and explains how to work well with technology and technology projects in an HR leadership role.
With a background in contrasting private and public sector HR management, Kate developed her thinking in seeking for herself to understand her first HR systems project-work.
Currently she leads the Service Delivery for Phase 3 Consulting, offering an independent take on the HR systems market in the UK, through a network of experts. Kate’s guiding principle is that openness offers knowledge-sharing, credibility and trust.
Incorrigibly enthusiastic and up absurdly early for a working morning, she swears that she only drinks three good coffees a day, but nobody believes her!