People & Workforce Analytics Seminar 2018 – Day 2
I had some trouble falling in sleep after day 1, because I was still processing all the exciting stuff I heard. So many interesting case studies and inspiring views on the analytics field. Nevertheless, I woke up energetic and was looking forward to hear more on day 2. Let’s go!
Just like day 1, I would like to share my lessons learned on the second day of the 5th Icongroup People & Workforce Analytics Seminar in Brussels.
Be creative when internal data is suboptimal
As ABB’s Rodolphe Guerin told us: “Better data outweighs clever math”. Therefore it is important to have good quality data. And sometimes, you do not have the luxury to first improve the data quality, but you have to get started. There is a number of ways to perform the analysis.
Suggestion 1: use external data. Michael Rubas of Deutsche Telekom showed us how useful this can be for recruiting. The use of external data enables organizations to find out where the talents are the company needs.
Suggestion 2: take a renewed look at your available data. The chairman of day 2 Dave Millner showed interesting cases in which he used employee engagement data, not for usual purposes, but to find out how to improve collaboration within a certain company. It was interesting that David showed us that most of the time organisations already have the data they need. However, they don’t always know where to look and what to look for.
Suggestion 3: determine scope. Organisations tend to include every employee in the scope of an analysis. However, this is not always necessary and advisable. Jean-Paul Lucassen showed that for Strategic Workforce Planning (SWP) within the Dutch Railways, he focusses on the most important employees: “SWP is not a strategic planning, but a planning of your strategic workforce”. Scoping the project limits the variables you have to take into account and thus the risk your data quality is too low.
Let every HR professional embark on the HR analytics journey
Yesterday I told you about Stefaan Rodts’ mission to make his role – Analytics Translator – redundant, because HR employees should ultimately have a data and structured problem-solving mindset, and should be able to interpret results and insights from such analysis.
To make this happen, Ivo Vink and his team at Achmea are doing workshops with HR professionals to help them better understand the possibilities and pitfalls of HR analytics, interpret the results and getting to a structured business issue that can be answered with HR-analytics.
Of course, HR professionals should also have the tools to interpret results and insights. For that reason, Carsten Scheuba made sure Lonza’s HR professionals have access to a dashboard. He is experimenting between Visier (an off-the-shelf HR point solution) and Tableau (a configurable best in class visualisation/BI solution).
Be transparent and selective
In the panel discussion, led by Nathalie van Hooff of the Hogeschool Utrecht, the importance of transparency and ethics was highlighted. For employees HR-analytics might be scary. They heard horror stories about analytics in the news – e.g. Facebook and Cambridge Analytics – and they do often not know what their organisation is doing regarding (HR-)analytics. All by all, keeping employees in the dark might backfire and as such, it’s important to be transparent and to communicate pro-actively.
Moreover it is important to organize checks and balances. For example, The Dutch Railways (NS) has installed a data usage board and ING Belgium has an ethics board and does front-page checks.
Thirdly, it is also advisable to be selective in who gets to see and work with generated insights. For instance, Jan Billekens of Saint-Gobain shared that only a selected number of HR Directors allowed to work with the outcomes of the talent identification algorithm to prevent misinterpretation or undesired follow up actions.
Do not trust the data blindly and iterate
AnalitiQs preferably works with multidisciplinary teams on HR-analytics projects. It reduces the risk of tunnel vision and misinterpretations. Ivo Vink had a very rich illustration of this risk. In his journey to find out how Achmea can recruit the best call center agents, he found out the more customer centred the agent and the better the listening capabilities of the agent, the worse the performance of the agent. After some reflection it turned out the model focussed too much on factors like average handle time, while customer satisfaction was not (yet) taken into account (because of technical reasons). As a result, they are now going through another iteration of the project where they aim to include customer satisfaction into the model, thereby improving the analysis.
Lastly, many thanks to David Lanigan, Niall Doorley and Julien Salvi from Icon Goup for organising this wonderful event and thank you Dave Millner for hosting day 2. Please enjoy the aftermovie made by colleague Michel Pasman. Hopefully we see you all again next year!
Also read: People & Workforce Analytics Seminar 2018 – Day 1