Partnering with a more human resource

FAQ: Your questions for Dr. Fermin Diez on embracing your HR data

Posted by: The ADP Team on 28 November 2018 in Business Strategies, Human Capital Management, Human Resources, Payroll

Dr. Fermin Diez, HR expert, professor and author recently joined ADP in our webinar HR Analytics: Embracing your HR Data with Confidence, discussing how you can achieve greater insights and data-driven decisions with your HR data.

We ran out of time for audience questions, so here are Fermin’s answers to the ones that were submitted:

1. How do you identify and collect relevant data to reveal real insights, such as in the case of exiting employees?

There may be several ways to accomplish this, here are two ideas that have worked for me in the past. You send a survey, or even do a phone interview, with people who have left the organisation 6 months after they have left. This helps to take away some of the reservations and emotions from the employee’s final days at the company. The other way is to hold a focus group for people in the company and ask them why they have stayed.

2. What practical steps / options do you recommend for turning bad data to good quality data?

In the webinar, I did say that bad data is better than no data. There’s no magical formula for squeezing bad data into good. However, you can use bad data as a starting point to develop your hypothesis. If your data is bad because it’s a small sample, expand and diversify your sample across the organisation. If it’s bad because of the context (exit interviews with people who have been made redundant), find a way to answer your question in a less emotive situation. Or you may be aware that the data is not exact (e.g. annual reports that show executive compensation in bands as opposed to actual figures); in this case, make allowances for the fact that your results are “in the ball park”, as opposed to “precise”. The bad data can act as a signpost, directing you to which way to focus.

3. How can organisations automate HR data more efficiently?

It depends on the size of the data you are managing, but generally new-generation HR information systems will have a way to warehouse your data. Or your outsourcing vendor may be able to do it for you as well. If you run a small enough operation (including, say, a subsidiary of a big MNC), Excel – and Tableau – for doing analytics may be all you need. Download your data from where it is residing, your financial system or your employee engagement vendor, for instance, into and run simple analytics from there. In bigger cases you will require “data lakes” and powerful statistical software.

4. What are the implications of data privacy on the ability of organisations to do analytics?

Moving data across is an issue. Coding becomes challenging. Getting signatures may be cumbersome. But in the main, the results we want will be in aggregate form.

5. In the webinar, you talked about breaking down a business problem into hypotheses and variables to gather on, with the example of compensation. What kind of measures and variables are used to measure other HR challenges, such as the return on investment of training?

Let’s review the steps, as they are the same for any kind of HR problem that you wish to tackle. First, build a clear and simple statement, not a question. In the case of training, your hypothesis could be “our current training program for sales associates is ineffective.” Next, how do we prove/disprove that? What data is required? Perhaps you should survey current sales associates (anonymously) and ask if they feel that the training provided helps them to be successful in their jobs? You could supplement this with retention reports, how long does the typical sales person stay? How many make their quotas in their first year? Second year? One example I used in the past related to Quality Assurance training for the manufacturing employees. We used “yield” (amount of raw material that ended in an approved finished product) as the Y-variable, and hours of training as our hypothesis, meaning that more training, up to a point, would lead to better yield. We did, in fact, find an inverted-U relationship, but more importantly, were able to justify the cost of additional training by the improvement in yield, which was in line with manufacturing objectives of becoming world-class.

6. What trends are you seeing in the collection and use of Employee Diversity data? Our organisation wants to focus on greater diversity and inclusion, however we do not have the employee information (beyond gender) to build a data-driven business case. How are other organisations you have worked with in APAC addressing this?

The collection of personal information such as disability, sexual orientation, etc. must be done in a way that builds trust with employees and is compliant with in-country legislation. My advice is to be clear with leadership on what will be done with this information once you have it. Employees will sense if this is a box ticking exercise or if they think your organisation would use this information against them. Perhaps start with a voluntary question on the employee engagement survey (run by an external third party) to get a benchmark of where you are at as an organisation.

7. How do we balance the need to experiment in HR versus the need to deliver “business as usual”?

This is a question that most departments grapple with – not just HR. Think of it this way: everyone knows of a company that fails to recognize a change or shift in the world and goes out of business as a result. Failure to innovate in HR, or recognize that the world of work is changing, including the expectations of employees, will make HR less valuable in the eyes of leadership. If you have a good business case, and enough wins to ensure the management team trusts your judgement (even if you have a few misses), then you should be well on your way to help the business improve revenue and profitability through people strategies. I hope that my webinar has given you the language to present to your leadership the sorts of insights that you could be offering with a laser focus on data-driven conversations and insights, rather than focusing entirely on the day to day work.

Thank you, Fermin! Did you miss the webinar? You can still listen in on the recording, which includes Fermin’s contact information for further conversation, just click here.


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TAGS: Design thinking HR innovation leadership