In my latest webinar with #NewToHR I covered an introduction to HR analytics including how to build a data and analytics driven business case. Thanks to all the attendees who joined. As promised, I have come up with some responses to the questions that were asked during the session. If you have further questions please do comment on the blog and I will get back to you.
1. Do you have any suggestions on how to present “unwanted data” that happens to challenge the performance of the “big guys” in the company, who consequentially resist it, yet is critical to business success?
That’s a good challenge, because any data you present should be adding value. This means two things:
- Find the value: Start by always thinking through which questions you are looking to answer and which data will help give you that answer. This will give your enquiry focus.
- Communicate the value: If the data encounters resistance from the “big guys”, the classic reason for this is usually a lack of understanding about the impact your insight could have. So, don’t necessarily go for wholesale change immediately. Focus on a small element where you know you can have an impact, track the outcome, and use that to support the business case.
If you can focus on and demonstrate value you are much less likely to be ignored.
2. How can we find out more about our employee retention across our international workforce?
This is an interesting question, thank you. First of all, I’m wondering why this is an international issue?
My guess is it’s because the basic facts are hidden away in multiple source systems with data that don’t match. I would suggest getting the HR teams from the various countries together and ask them to work together for one day to come up with the following:
- A definition of an employee
- A definition of retention
- A way of getting 20 other standard terms agreed (e.g. department, job family, role, gender, age, tenure, performance)
- A way for them to state the value of answering the question, ‘How does our employee retention differ across sites?’ and ‘How much would it be worth if they could take different actions and achieve a different outcome?’
I would expect that by the end of that one day, the HR team could come up with an agreed definition across multiple countries, and that at the end of 3 days, a delegated HR analytics team could offer insights on:
- The range of retention by country, by site, by department
- The cost of attrition in recruitment fees, recruitment effort & time, lost productivity
- The value of improving all under-performing sites to the 75th percentile
- Stage of attrition (0-1 month, 1-6 months, 7-12 months, 1-2 years, 2-4 years, 5 years+)
- Check for relationship between attrition and movements in unemployment by country over the last 5 years
- Five hypotheses about actions that could lead to higher retention
- Based on these findings, you could then put in place an improvement programme, owned by managers on each site, or each country.
3. When you discuss training and the impact on performance, do you have any more solutions/ideas?
First of all, you need to ask questions from three different perspectives:
- From an analytical point of view: What are your data sources?
- On the input side: Do you have a system in place to record when your employees attend a training course, the duration, and cost of the training course?
- On the output side: How do you measure performance?
Assuming that you have good data sources for both the input and output sides, then it is easy to create a scatter plot of inputs (training) vs outputs (performance), and to start exploring it. But not all training courses are equal. You need to collect feedback from trainee on course quality, ideally right after and 1-3 months after the course is conducted to understand the impact.
If your sample size is large enough, you can also run a regression on the correlation between training and performance. You can look for inadvertent experiments, when real life has created a quasi-controlled experiment. For example, with a good-sized dataset, we could compare the populations of people who went on training, with people who didn’t go on training, and with a third group: people who signed up for, but didn’t attend training.
4. In one of our plants we want to see how the Quality team can more effectively use HR metrics, how do we address this?
What is quality? Ideally, your Quality team will focus on metrics that Customers would agree to represent true Customer value. For example, in logistics this might be on time / in full delivery (OTIF), for customer service it could be net promoter score (NPS), and meanwhile for a hospital, mortality rate. The HR dataset is unlikely to have these metrics, but your Quality team can get lots of value by working with the HR team to merge the Customer Value data with the relevant HR data.
The Quality team should use HR data to contextualise results:
- Where are the positive deviants – the areas, sites, departments or teams that bring unusually good customer outcomes?
- What are they doing right?
- Are there any distinguishing features of these groups – demographically, by location, by training, by management?
You can also look at organisational questions:
- Where are the people adding the most Customer Value?
- How does this compare by level?
And you can look at Input questions:
- From where do we hire the people who are delivering the highest customer value?
- What training have they received?
- Which training courses seem to have greatest effects?
Now a word of warning. You’ll probably find some differences in demographics, but these may well be by chance. The sample sizes in companies are often small. Usually the sites that are doing best are not distinguished by features like age, sex, or recruitment channels. In most cases, they are actually doing different things. This is where detailed operations understanding and root-cause analysis will be required. At this point, forward thinking HR teams will be able to help through:
- Supporting activity analysis
- Showing areas on where time and cost are spent
- Allowing experts to zoom in on the working practices in activities that are truly creating a
This represents an overlap between HR, Operations and Strategy. Regardless of who does it, it is a very useful way of thinking through the real impact on quality.
Any more questions? Please comment below and I will get back to you.
Latest posts by Giles Slinger (see all)
- HR Tech World 2016: How to make the case for investing in analytics - October 26, 2016
- IBM HR Summit – Future HR Tech Insights to Watch Out For - June 27, 2016
- The Art and Science of Organisation Design - February 15, 2016