Chairman’s Notes, CIPD HR Analytics Conference, 7th October 2014
Quote of the day: “It’s changing the world. If you’re in HR Analytics, you’re in the right place. If you don’t like data, you’re probably in the wrong job.” Sue Foster, Global Head of HR Systems, Linklaters
Sometimes walking on a hilltop, you see a change in the weather sweeping across the land. A moment where the clouds are starting to clear, and the sun is starting to come through. That’s what it felt like at the 3rd CIPD HR Analytics conference on 7th October 2014 at the BMA. To me, the group atmosphere has brightened considerably since last year. It feels like things are moving in HR Analytics.
What has changed? It may be because the UK economy has picked up in the last 12 months. It may be because technology and skills are maturing. Whatever the reason, it seems to me that:
- HR people are more ready to get hold of data
- HR people are much more focused on business impact
- HR people are more confident that their organisation will be interested in the answers
There were over 120 attendees, the second time this year that the CIPD has organised such a big conference; and Max Blumberg’s 65 person CIPD HR analytics workshop the following day has been sold out for weeks. There seemed to be more people in the room than ever before who had come to HR challenges from an analytical background. People in the room were more senior and seemed more confident in what they could do.
A year ago, when people were asked what they wanted from HR analytics training courses, they emphasised gathering the data and getting it into shape. This year, there was more emphasis on conversion to business value, using People data to provide the business with a more lasting solution, integrating multiple systems. Attendees talked of wanting to:
- Connect HR data to business analysis
- Integrate with Finance
- Model scenarios
We see the big themes in analytics at the moment as being visualisation, data integration and data cleansing. The types of data being used are altering as HR moves out from its normal operational focus to using operational data for periodic reviews and transformational reviews.
It is clear that the data challenges grow as multiple sources of data are faced, but the tools, the skills and techniques are strengthening too. [download chairman’s slides]
Key recommendations from speakers and audience were:
- Build relationships with the business – for HR to develop its skills in converting a ‘gut feel’ about a business situation into a statement that can be tested using data.
- Build your data, either the slow way – as described by organisations that had spent up to 7 years getting the data into a clean shape and in one location – or the fast way, taking the 80-20 approach being guided by the insights in the data itself. (See our introduction to HR analytics)
- Build your team – using new skills, new recruits, including from unexpected places. Hat tip to Gavin Thomson, of Willis, who suggested teams needed to combine coder / cruncher / cartoonist skills. See also hao2.eu, who specialise in placing people with unusual skill sets.
Some great insights of the day:
- Data-backed results from a bank: at senior levels: quick external hires fail 3 times more often than ‘built’ candidates; it takes over 6 months to get a replacement up to the standard of the person you lost; there are a few key metrics it’s worth measuring: turnover in first 12 months, turnover in top performing groups, turnover due to lack of development opportunities.
- A sector study of law firms showing that apparently healthy overall employee turnover rates in fact masked a major retention rate issue for females once they reached a certain level.
- A sales organisation’s review of training, which found that although sales training appeared to be linked to increased sales, investments in training young males were essentially wasted: learning appeared to bounce off them, vs. training females, who doubled their sales.
- An HR team found that LinkedIn could be used as a datasource to benchmark the scale and roles of competitor businesses.
- Unused data is everywhere: exit interviews (periodic data, but only part-carried out, occasionally captured, rarely analysed) to the example of Learning Management System data (continuous, rarely used).
In all a great day, and I eagerly anticipate the next event in February!
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