Who would have thought that 2020 would bring us a ‘new normal’? In the Netherlands, the impact of the COVID-19 pandemic on Dutch Railways has been all over the news. Train traveling as we knew it will probably never return, which has big financial consequences.
It has also had an impact on our People Analytics department. As you would expect, data and information about absenteeism was an even bigger thing than usual. Absenteeism is entirely different than in other years. Ironically, this will probably mean that when we return back to normal, the data on absenteeism in 2020 will be pretty much useless when it comes to predictive analytics.
Instead of looking back on this strange year, I would like to look forward. What’s on our agenda for 2021? I hope we can inspire other People Analytics enthusiasts and that they will share their plans as well.
The Objective and Goals
At Dutch Railways, our People Analytics department’s objective is to deliver fact-based insights to improve decision-making and make HR more effective. To do so, we have set three goals for the next year:
- 75% of our HR data should be in our new HR Data lake and therefore does not have to be gathered manually anymore;
- 80% of our current ad hoc questions will be available as self-service for our HR colleagues;
- We will conduct at least 5 advanced analyses to help Dutch Railways make the right decisions on important HR matters such as absenteeism, productivity, and retention.
We will use four strategies to meet our goals:
- Data: data is up to date and available, in line with our definitions, and is safely stored at IT in a GDPR compliant way. Our HR systems are easily disclosed to assure we can make the right analyses;
- Fact-Based HR: HR is perceived as a serious strategic partner by both business and board of directors. By by using fact-based insights they lead the change and Dutch Railways can make the best decisions;
- Standardization: enlarging self-service for HR Business Partners and Business Managers by providing standardized and automated information;
- Advanced & Predictive Analytics: we use statistical techniques to discover meaningful patterns in (HR) data and to predict (HR) outcomes.
This makes sense: we want our HR colleagues to get better at interpreting and using information. If they are up for it, they need information without always asking our help: self-service. For self-service, we need the information to be standardized and automated. To have your information standardized and automated, you need your data to be up to date and correct.
If all this goes well, our People Analytics team will have more time to conduct more advanced research on HR subjects that matter.
Where the action is
We will be putting a lot of effort into getting more data in our data lake. Currently, we are implementing a new HR suite, so we need to make sure the right data will be available to us. We also have to complete the descriptions and definitions for some data fields we currently have in our data lake.
We will also be looking into creating a new data field: the distance between your work and your home. This data field will help us in calculations regarding compensation and benefits. Literature also indicates that this type of data might be useful in finding a driver for attrition.
Fact-Based HR will get a follow up: we have had some setbacks because of covid, but we still intend to advance our campaign with Frisse Blikken. At the same time, we will specify and create reports for Learning, a domain with a lot of data that we do not use to the fullest of its potential yet. We think that reporting on absenteeism during the pandemic will not be less.
We’ve also got a Strategic Workforce Planning project planned for our Customer Service, which I am really looking forward to. Last but not least we will be helping our Capacity department with better predictions of employee attrition that they need to specify how many train drivers and conductors we need to source.
We will be putting a lot of effort into standardized information. There are two options we see for next year. Either we source on the external market for a partner that provides us with tooling, or we ask IT to build such a tool for us. We will also be automating the reports on churn rate (failed hires) and Matching Satisfaction for recruitment.
When it comes to our advanced analytics, we are pretty excited about 2021! We will continue to build a predictive model regarding attrition and will conduct research on the effect of working in a preferred roster on absenteeism. Our yearly gender pay gap research is on the agenda too.
We are also really looking forward to working together (again) with the University of Amsterdam and the Data-Driven Business Master program in Utrecht. Finally, we will investigate whether Organizational Network Analysis is something that might be useful and whether our internal privacy rules allow this type of analysis.
A final word
These projects are just some examples of our list of 31 (!) projects for next year. We will not be able to do this alone. We need our colleagues and external partners more than ever to take the next step in People Analytics maturity. Focusing on this at least keeps my mind from the ridiculous current year.
I hope we all keep sharing our knowledge of People Analytics in the next year and wish everyone a wonderful Christmas and a Happy Fact-Based New Year!