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Earlier this year I provided approximately 25 HR Directors with a return on investment calculation for a training initiative, and it worked amazingly well. While the calculation was only part of the ten-page proposal on why we should carry out this initiative in the way we were proposing, it received great feedback and helped our argument.

Now return on investment in HR doesn’t have the greatest history, indeed Latham & Whyte in 1996 published an article titled ‘The futility of utility analysis’ (for all intents and purposes utility analysis and ROI in this context are the same thing), and the article was damning, they found not only a lack of managerial support for ROI but that its inclusion in the presentation disengaged managers from the wider proposal. Now to be fair no one else has been able to replicate their findings, however, no one (including yours truly who did a master’s thesis on ROI) has really been able to find strong support for it.

Typically the way ROI is presented, is that a percentage is given that shows the return on investment. For example, if you invest $30,000 in training you’ll receive a 150% return on investment within the first year. And with ROI there can be some pretty impressive percentages thrown around, I think they need to be read with caution, the calculations for example aren’t designed to take market or economic conditions into account. Now the problem I had, was that presenting a percentage return in a Government environment didn’t make sense – Governments typically spend money. I was however keen to include ROI in the discussion, so what I did was operationalise it.

As a quick backstory to the training initiative, we were proposing to provide an amount of time that employees could access per year to undertake on the job training, be it peer-led learning, job rotation, acting up opportunities, etc. So in the proposal managers were free to providing training opportunities which matched the needs of their employees, some might take up training in Excel for example, or taking minutes of meetings, writing policy or a variety of other tasks. The commonality was time, so what I did was to present ROI as a break-even calculation in terms of time. In the proposal, we put forward that employees could access one week of training, and what we needed to break even on that training was for employees to complete in 44 weeks what they used to complete in 46 (the 44 weeks represented one year of work, taking leave, public holidays, etc into account). Essentially employees needed to improve to the point that they could complete more work within the same time period.

As I mentioned above, this approach worked really well. The people involved could understand the metric we were using – time and could make an informed decision as to whether front line managers could provide training that would have this level of impact.
Typically the training return on investment calculation looks like this:

U = (N)(T)(dt)(SDy) –C

Which many people don’t really connect or identify with, and once I start talking about standard normal distribution curves well, people leave the room. The important part however wasn’t the calculation, but rather the presentation of the breakeven point. For this to be a very little cost to the organisation, employees need to complete an extra two weeks of work within a working year. HR Directors and their managers can work with that, it makes sense.

I was really encouraged by the responses that I received, and will use this approach again in the future. While this post isn’t intended to be a guide, I’m hoping that it will provide some insight for those interested in ROI within the training realm, on how ROI can be configured to gain more traction than perhaps what it has experienced in the past.

By Brendan Lys

Operating at the intersection of Human Resources and Data Science, I leverage extensive specialist experience within Human Resources, with the methodologies and approaches of Data Science. This focus on the discovery of actionable insights from data, has been applied to areas such as: remuneration & benefits, workforce planning, recruitment, health & safety, diversity, and training. But what does the application of data science to HR challenges and opportunities actually look like. Within an HR framework the data we work with typically comes directly from our HRMIS, an advantage of using data science methodologies is that we can bring in additional data either held within the organization or from external sources - data which is out of reach from a pure HR analytics approach. Consider for example position descriptions, these contain a wealth of data that we typically ignore as its not in a analysis ready format. A side project I'm working on currently (April 2019) is using text mining on job descriptions to provide insights into which job family the position may fit into. The insights of my work have been enjoyed by organizations across a diversity of sectors including: Government (Australia and New Zealand), ASX and NZX listed companies, utilities, not for profit and higher education.