I’ve been re-reading a couple of books in preparation for another workshop on HR Metrics. One of these has been Calculating Success by Carl Hoffmann, Eric Lesser and Tim Ringo.
It’s a pretty turgid book, but then it does focus on measurement, which isn’t the most naturally entertaining topic area (I always struggle slightly to make my measurement workshops as stimulating as my other trainings).
But there are also a few other things which really irritate me about the book, for example I think the authors define analytics a bit too widely: “We see workforce analytics as a set of quantitative approaches that answer a simple, yet often overlooked question: what do we need to know about our organisation and workforce to run the company more effectively and (perhaps most importantly) how do we turn this knowledge into action?”
This definition leads the authors to including things like engagement surveys as example of analytics whereas to me, these are clearly measurement approaches rather than analytical ones (the analytics then follows the measurement of engagement). And scenario planning? It’s certainly a way of better understanding strategy, but its not an analytical approach!
Perhaps a better definition would be the process of asking and answering questions, to gain a better understanding of an organisation (ie being about the question, not the approach used to answer this)? Like these asked within the book:
- Based on the organisation’s strategy, what is the work that needs to be done, and are the processes, structures and roles designed to efficiently and effectively accomplish it?
- Is the human capital supply chain filling those roles with people capable of doing the work at the quantity, quality and cost required of the business model?
- Once in place, is the workforce fully engaged and motivated to meet or exceed performance standards?
- Finally, since change is ubiquitous, how can we detect the need for change, test innovations in the organisation and workforce, and disseminate those throughout the organisation?
I also dislike the complete absence of any focus on people strategy in the book. For me, analytics isn’t simply about developing insight into how people support a business, but how they support the people strategy which supports a business – a small but crucial difference. So analytics is about asking questions which provide a better insight into how people strategy leads to better business results.
And I’m largely unimpressed by the book’s case studies. Many of these are really about things completely unconnected with analytics, eg:
- Strategy (eg Circuit City –which really shouldn’t have needed to do any analytics to know that laying off 34,000 of its highest paid people wouldn’t be a good idea, Qantas, which also didn’t need analytics, just a little more ambition and determination to change, Sunglass Hut which was just about experimentation, and IBM which was about the need for a common language)
- Process and job design (ABC, the community college)
- Change management (the oil company).
However, there are some good examples too, eg I liked the CORP case study which concerns a case where measures showed a negative relationship between performance of the supervisors and the sales of a team, and a positive correlation between sales and team turnover. But ever here, the organisation only used surveys and focus groups to get a better understanding of the causes of these findings – not really something I would call an analytics based approach. The PHARMA case study is better – again involving an interesting situation in which some of the best people were being lost but also involving the use of regression analysis and stochastic modelling to gain a better understanding of the situation. This is the only example of what I would call a true analytics based approach in the whole book, but it is a good case study, so the book may be worth reading just for this (it’s in chapter six).
And then one of the most interesting aspects of the book, to me, is its discussions on people as widgets which concerns the importance, but yet also the perhaps over-hyped perception of importance, of this whole field:
“Other companies have a cultural bias against adopting a disciplined analytics approach to people, believing that people are not inanimate parts.
The authors quote from Boudreau’s Retooling HR:
“Is it because people are not widgets, and out of respect for their free will and humanity it’s unfair or wrong to use the same logic for workforce decisions as we use for decisions about more inanimate objectives like inventories and machines? No.
In fact, it’s arguable more unfair and disrespectful to employees and job applicants to make important decisions about where to invest in their development, performance and careers in less rigorous ways that those applied to more traditional resources.”
I don’t disagree with this, but I also think it misses the point. The reason why we don’t want to treat people as widgets isn’t about humanity and fairness, it’s about practicality. People are different to widgets. We talk to each other creating a complex and messy system in which it’s often difficult to disentangle cause and effect and in which a small change in inputs can have a large impact on outputs. It’s why HR analytics are so useful, but also why we must not overestimate their usefulness. We should never say this investment will result in this, just that it may…
So I dislike examples in which organisations seem to think they’re developed a full understanding of something which is actually impossible to wrap up this way. For example, an Asian airline apparently managed to develop a ‘clear picture’ of where instant messaging and other forms of social networking could have a significant impact on productivity. Well, I’m not so sure they did. There’s nothing wrong in trying to predict where the best use will be, but that’s very different to believing you’ve got the whole thing sewn up. Particularly with social networking, most case studies show that organisations will find a whole slew of emergent benefits that their people make up which they hadn’t thought about before.
And in fact the authors seem to come round to this perspective later in the book (in a chapter perhaps written by a different author?):
“However, we also believe that organisations sometimes take an overtly simplistic view of the complexities and interdependencies inherent in developing an ‘on demand’ workforce. People are not widgets; they cannot be comprehensively described within a ‘bill of materials’ or an ‘ingredient list’. Individuals come with a set of distinctive skills, preferences and requirements that motivate them to achieve well beyond their ‘specifications’ or that hinder achievement of their potential…. Given these differences, organisations should be wary of claims that they can manage the supply and demand for talent with the same precision as other commodities.”
Well quite, and in other areas of analytics too. This is all useful stuff, but let’s keep it in perspective – it’s the development and then implementation of a creating value people strategy that’s the most important – as well as difficult - thing, not the measurement of this, and not the analytics which may play a role in the strategy’s formation.
I like the point where the authors write “The value to the organisation and workforce of the access to these networks cannot be underestimated”. Right, and if that’s the case, let’s not go to the bother of estimating or analysing it. If it can be underestimated, you may need to use some analytical tools, but I’m afraid you probably won’t find them in this book.
Also see: The Five Most Important HR Analytics
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