Posts filed under ‘Measurement’

What HR data can’t tell you

What HR Data cannot tell you

HR data and HR analytics is becoming increasingly popular – and with good reason.  Good data and clever use of the data can make HR better. Data mining, charts and data reports are used to guide innovation and process optimization.  All good things.

There is an argument among some people in HR that “you cannot measure people and convert people (and feelings) into hard facts”. They somehow see HR analytics as reducing people to something objective, deprived of feelings and being non-human. That is simply not correct. Objective facts and observation about human behavior has guided management and psychology for many years and has increased our understanding of human behavior. Our increasing technological powers will improve our insights in human behavior and hopefully assist us in making better HR decisions on the back of these insights.

BUT the advocates of HR analytics sometimes forget the limitations HR data. HR analytics face many challenges – many of which are psychological and rooted in the mindset of HR – and some misunderstandings about what HR data can do persist. Let me express three common ones;

  1. The data will speak for itself. The views expressed in statements such as “the data will speak for itself”, “HR data will make decision-making easy” and “numbers will express the law of causality so clearly that you will have to stupid not to understand that a will lead to b” are all naive if not dangerous. HR data will only get you so far but they cannot take away the fact that you will need to make subjective decisions, that all data requires subjective input to be meaningful and that HR data will only take you so far. The data will not speak for itself, the conclusions will continue to be in the eye of the beholder.
  2. More data will make it easier to interpret. This statement is not correct –  in fact the opposite is often the case; interpreting data is not getting easier. The more data you collect the harder it is to see the meaning of them. True, our capabilities to arrange them, visualize them and to publish them are getting better all the time. But interpreting data is not about arranging them, it is about finding out what they mean. Our obsession of collecting ever more data actually makes it even more difficult to find their meaning. And visualization techniques will not help us there.
  3. Data is objective. In one way HR data is objective but we should not be fooled that it is the same as getting a true representation of the world. The datasets are representations of the world gathered, generated, selected, put together, analyzed and adjusted for the particular purpose they are created for. Not only that, but in real life most HR Data is often incomplete, inaccurate or simply outdated.  So instead of treating data as objective and non-debatable understand that HR data is nota true representation of the world – it is a subjective representation of the world. But a good one nevertheless.

But perhaps the most important thing that HR Data cannot tell you is that they cannot tell you why people react as they do. Even the most predictive HR data can ‘only’ give you better information for your predictions and probabilities to forecast what will happen. That’s all. HR Data will not tell you why it will happen or how the people will fell about it. But it is frankly also quite enough.

HR Data will do a lot and hopefully it will make HR better. But it will not take the human element out of HR. And for that we shall be happy.

09/11/2012 at 15:47 2 comments

Are you measuring performance or results? HR is often measuring the wrong one.

It is impossible these days to open a HR magazine, go to a HR conference or read a HR book without being overwhelmed by terms such as ROI on HR, HR analytics, KPI’s, measurement and Human Capital Management. These buzzwords which are trying to make HR ‘harder’ have really gained acceptance in the HR world today. In many ways, this is a good thing.

The problem with metrics and KPI’s is however, that they actually do work. That is, if you start to measure people in certain ways and you link their pay to meeting those measures they will in most cases try to meet these goals (KPIs) at the cost of other things.

“What you measure is what get’s done” as the old saying goes. It is therefore imperative that you measure the right things.

I was recently inspired by a Ted-talk about measuring performance. The talk was given by Dr. Chris Shambrook who supports organizations with leadership development. He makes the argument that when organizations talk about performance they are usually talking about results. So when you ask a person about how his performance is, what most people think of is results – how well are you doing against the goals set for you. What performance really means is “doing the things you need to do in order to get the things that you want”. He argues that organizations should focus on performance more than results. I totally agree.

I recently wrote about something similar when I advocated that HR also should track effort in the performance management system. Inspired by John Wooden, arguably the best coach in sport’s history, who famously never talked about winning games and wasn’t focused on the points on the board but instead for him it was about sticking to the fundamentals and making an effort to reach your potential. If you do that, he argued, the points will come.

Jon Ingham is a big more cynical when he state that “the easier something in HR is to measure, the more likely it is to be pretty low value”, but I agree with him. It is easier to measure results but HR should be more focused on measuring performance. However just because it is more difficult does not mean impossible. It just means that you should look somewhere else for your best KPI’s.

I freely admit, that I believe  HR can add significant value through good analytics, metrics, ‘true’ evaluation and cleaver KPI’s. However I also believe that they are difficult to get right, and if not done properly you can actually do more damage by using ‘ugly’ KPI’s. If you want to do it, make sure you do it right. In that sense I am not a true ‘Demming’ who believed that “In God we trust, all others must bring data”.

By focusing on performance instead of results you focus on how much potential you have and how you need to develop that. That in return will give you more control over delivering your results. Isn’t that what we are supposed to do?

04/06/2012 at 21:49 2 comments

Should Human Capital be fully capitalized on the Balance Sheet?

Book value accounts for about 20% of a company’s market value today. The rest – 80% – is down to immaterial ‘assets’. This makes valuing companies very difficult indeed.

There are many good reasons why book value always will be lower than market value. However one way to close this gap – and thereby making the value more transparent – is to capitalize more of the immaterial value. This could be ‘Brand Value’, ‘Customer Loyalty’ or ‘Innovation’. All of these things obviously makes a company worth more. However, one candidate stand out to me – people or ‘Human Capital’.

Why ‘Human Capital’ is a strong candidate is because it accounts for the bulk of the cost for most companies today. For some it is about 75% of total costs. It is also universally recognised, that people and their ability to perform, is the single most critical reason behind value creation today.

How practically this should be done is quite difficult to say. One way is to capitalise the total cost of the people including wages, pension, recruitment, training etc. But many questions are difficult: Should people be depreciated? If you spend money training them, should this be capitalised as any other investment? What happens when somebody leaves – should a cost be booked on the income statement? Can you ‘buy’ people below their value and should this be a gain on the income statement? How do you measure the value of people (if you don’t just use the cost base)? Some people are clearly worth different to the company despite perhaps getting the same pay – how should that be accounted for?

Perhaps these questions illustrates why Human Capital is not capitalised today. It is simply too difficult to find a meaningful way forward. But I would like to see a good, public debate about this. Perhaps there is a way?

26/08/2011 at 13:15 3 comments

ROI is a dangerous tool – here is how to use it

ROI (Return On Investment) has become the tool which HR increasingly use to show that they are adding value to the company’s bottom line. And rightly so. HR has the potential to create a lot of value to a company – also Shareholder Value. And this value  should be shown and highlighted.

ROI is a very simple tool. Too simple in many ways. The calculations is:  (return-investment)/investment. The return is the monetary gain from a HR activity and the investment is the full all-inclusive cost of the activity.

Despite the obvious problems in actually measuring the financial benefits of say a leadership development program, the ROI calculation is something  in itself to be careful about.

When I worked as a financial analyst, we didn’t use ROI that much. We used more ‘sophisticated’ metrics such as Enterprise Value metrics, ROIC (Return On Invested Capital), RoOFCF (Return on Operating Free Cash Flow), CRONCI (Cash Return On Net Capital Invested). What is common about all these ratios is that they recognise that ‘return’ and ‘investment’ is something quite complex.

When I still believe that ROI has a lot offer for HR executives it is because that when used right, it has a lot to offer.

The advantages with ROI are:

  • Easy to understand
  • Focuses on input and output of an HR activity
  • Show the bottom-line effect
  • Gives HR a language to talk to top management (and CFO in particular)
  • Makes it possible to make better HR investment decisions
  • Connects well with HR Balance Score Card
  • Potentially show the important assumptions behind the activity

The weaknesses of ROI are:

  • It is very sensitive to a few assumptions (in particular about productivity gains)
  • Reduces complex things such as people and leadership skills to simple causal relationship and a single number
  • Difficult to see the most important assumptions behind the calculation

So when you use ROI to show the financial value of your HR activities please remember that it is a very simple tool which should be used very careful. When I help HR executives to use ROI in their business I always emphasize the importance of process, structure, explicit assumptions and base line data.

Good luck

19/08/2011 at 09:35 6 comments

Wrong assumptions lead to bad decisions

Human Capital is the ‘hard’ side of Human Resources. It is about making strategic decisions, measuring the impact and basing decisions upon ‘objective’ and measureable data. One of the most important things for a Human Capital Manager is therefore to get quality data. Without that you cannot make good decisions.

Daryl Morey writes on HBR’s blog that ‘Success Comes From Better Data, Not Better Analysis’. He argues that the right data is more important that hiring good analysts, who can interpret this data. He writes “Raw numbers, not the people and programs that attempt to make sense of them. Many organizations have spent the last few years hiring top analysts based on the belief that they create differentiation….But…real advantage comes from unique data that no one else has”.

I only partly agree with Daryl. It is definitely true that most HR managers are basing their decisions on poor and questionable data and even more questionable reasons for using that data. Poorly formulated satisfaction surveys are often the only data upon which expensive programs are initiated. Most HR departments, which I speak with, will benefit greatly from having better data.

On the other hand I believe that some of the underlying assumptions on which many HR managers base their decisions are also poor.  That many mistake correlations with causality and therefore don’t understand what drives what. The connection between Job Satisfaction and Productivity is a case in point. Better data will not help you with that. You will just have better data to make the same mistakes. The shift to Human Capital Management should also be about questioning some of the underlying assumptions in Human Resource Management.

Human Capital Management is about making better HR based upon strategic and measurable initiatives. This requires much more data of significant higher quality AND to challenge existing underlying assumptions behind how they should be interpreted.

11/08/2011 at 18:59 Leave a comment

Does job satisfaction lead to increased productivity?

Job Satisfaction is one of the most researched concepts in Industrial Psychology and in HR in general. And one of the most robust findings about it is that it correlates highly with productivity. To which degree varies quite a lot. A large meta-survey by Judge et al. suggests that the correlation is about 0.3, but I have seen it as high as 0.5. That is quite a lot.

I don’t dispute that ‘Job Satisfaction’ and ‘Productivity’ correlates highly. There is so much evidence to suggest that. I just wonder about the causality. I can think about three ways to explain the correlation:

  1. The more satisfied you, the more productive you are in your job
  2. The more productive you are, the happier you are with your job
  3. A third element drives both e.g. if the match between job and employee is high then this employee will experience both a higher job satisfaction and be more productive.

In the end I believe that all three of the above are true. Which one of them is ‘the most true’, well I don’t know. However it matters a lot for HR practitioners.

If you believe the first explanation is more true then you would work hard on getting your employees to enjoy their work by increase autonomy, skill variety or give more feedback. If you believe the second to be true you would work on things which can increase productivity such as process optimisation. If you believe in the third explanation then you would work on your recruitment processes to optimize job-fit.

Before you measure job satisfaction in your organization, you must decide which of the three explanations you believe in and therefore how you should use the results.

26/07/2011 at 10:57 1 comment

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