Finding an affordable, but decent place to stay in London is not an easy task. As an experiment I made a reservation at the easyHotel, family of easyJet. Perhaps I was a bit naive, but for business purposes it might not be the most suited hotel. As a result of my experiment I arrived at the conference less energetic than the day before and in a wrinkled shirt, lol. Luckily the presentations I attended were very interesting, so I didn’t have hinderance from my little experiment.
Nicky Clement – Data storytelling and demonstrating ROI from people analytics
A common theme at the conference, for those just starting, but also for those ahead of the curve, is the conversion of insights into action and true ROI.
Nicky heads up a team of 6. Which, in my view, is not an awful lot if you consider the headcount and geographic spread of Unilever. Subsequently one of the key questions for her and her team became: “how to maximize reach and thereby action with limited resources?”
At Unilever they have applied different techniques to create reach. They have lifted the floor by educating HR BP’s just so they can make better use of the available toolbox. They have pushed the ceiling up by working one on one with leaders and turning them into “converts”, for instance by sitting down with them and answering their questions on the fly with the Tableau people dashboard. Moreover, they create a provocation pack for senior leaders every once in a while to get and stay on the radar.
Apart from above mentioned items one other, seemingly simple, thing stood out. They have created a community. At the core of the community is the people analytics team. In the second ring are cluster leads. I imagine these to be ambassadors/points of contact within a BU. And in the outer ring are volunteers with a passion and/or expertise in the people analytics field. By building and maintaining the community the people analytics team has been able to make waves and turn a 6 person team into a 50+ coalition.
Vanessa Lammers – Engagement check-ins, a pro-active approach to enhance employee experience and retention
Continuous listening, together with Network Analytics, were the trending topics at the conference. The presentation from Vanessa shed a light on how Nestlé Waters went about in getting a better feel for the sentiment in the organisation.
The team started out with creating a research strategy. For instance, addressing questions like “which questions should we answer through research?”, “what to investigate in a qualitative and/or quantitative fashion?”, “which workforce segments should we target?” and “how can we create leading instead of lacking indicators?”.
To illustrate how they have answered some of these questions it is interesting to note that nowadays Nestlé Waters combines quantitative with qualitative research, low frequency (annual engagement survey) with high frequency (short pulse surveys about particular topics), they target segments of the workforce where high turnover would cause high impact (think scarce labour market, high performance and potential scores), they hold stay interviews (leading indicator) next to exit interviews (lagging indicator).
Apart from strategy they also diligently worked on research design because asking poor questions has an inverse impact on the value that can be created. This sounds obvious, but from experience I can tell many organisations let HR professionals design surveys, whereas these people have never been trained in research methods. To more vividly paint the survey design picture: instead of asking “what are the reasons for leaving?” they now ask top X reasons. Alternatively, a follow up question on “what are the reasons for leaving?” could have been “rank the earlier provided reasons for leaving”.
Swati Chawla – HR-analytics to drive business decisions
13 Asian countries, 150 meetings and 8 months of work. That is the context in which Swati executed her project. But it was worth it! Not only did the project successfully answer the business question “how can we grow sales?”, it also answered the underlying research questions “how can we organise, manage and utilise the salesforce?” and put HR-analytics more firmly on the map.
In my opinion the beauty of this case is twofold. First, only a handful of relatively simple statistical methods have been used, e.g. probability analysis. All else was based on metrics like sales and profit per sales, sales and profit per FTE, span of control, contribution to profit by employee tenure and scenario planning. Second, I can tell from experience almost all companies would have the vast majority of all input data available in existing systems and/or spreadsheets. The only thing that Swati and stakeholders had to manually create was a task/time allocation matrix for the sales staff in various markets.
On the back of this case a quote I picked up on day 1 popped back up in my mind: “the impact of analytics is oftentimes inversely related to the complexity of methods used”. Not sure if this is always true, but probably good to reflect on this quote when designing a project.
Another thought that surfaced and might be worth pondering about on the back of this case: shouldn’t all organisations have a HR controller in their team, just like finance has business controllers?
Steve Bianchi – The successful long game
Where I was starting to think network analysis is something everyone talks about it, but few have experience, Steve Bianchi appeared on stage.
He presented a case in which he and his team had scraped LinkedIn data for a number of purposes. (1) Calibrate job specs. If, based on characteristics in the job specs, profiles were returned that insufficiently matched, the job profile was adjusted. (2) Find candidates. As soon as there was a robust job spec the system would return interesting candidates. (3) Leverage the network of the workforce. If candidates had a connection with one of the employees that already worked at the organisation the employee could earn a referral fee in case of a match.
Unfortunately, LinkedIn doesn’t share its data any longer and GDPR will shortly kick in, so by now this example can’t be (easily) replicated any longer. In addition, the case above is only feasible if an organisation is sufficient in data management. And this doesn’t always hold true, because within HR the following lesson is little recognized: “great information management enables great management information”.
Next to my takeaways from the presentation there are several common themes that I did not incorporate yet. Below a succinct run down.
- GDPR & Ethics and the Extended Workforce (flex/core) are still hot topics. Perhaps the latter is one of the reasons why network analytics is hot.
- The Analytics Translator is a must have in all HR-analytics teams. The role is instrumental in educating HR peers and Line Management which helps to create impact. In addition, the role can shape and manage projects in a dedicated and hence more effective way. The function can turn the insights into compelling nuggets of information for customers (e.g. through visualisation and storytelling).
- As continuous listening becomes more common, text and perhaps even speech analytics will receive a lot of attention going forward.
Also read: Gido @ People Analytics World – Day 1