02 03 2015
door Inostix

What we learned about HR Analytics in 2014 – Part 1

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lessons learnedJust as in the previous years we have been rushing from HR Analytics project to project in 2014. It was the year with the highest number of HR Analytics projects ever and the projects became much more sophisticated. More and more large organisations are building capability for HR Analytics, either internally or externally. Meanwhile our blog has reached an incredible traffic which means that HR people from around the world are doing their home work in preparing for their analytical future.

Organisations seem to be in even greater distress than last year to gain insights into the relationship between investment in human capital and its impact on the results. As I did last year, I’ve been reflecting, together with the fantastic iNostix team, on a the most important lessons from the past busy year. Here you go…14 lessons in 2 blog parts…enjoy the learnings!

1. Start with a business question, not with data 

Whenever HR asks me how best to start with HR Analytics, I tell them: ‘Start with a pressing business question or issue, not with HR data.’ Sometimes HR finds the courage to ask: ‘We’ve got a whole set of HR data here, could you have a look if there are any interesting patterns in it?’ Remember Pasha Roberts saying in Part 2 of our blog The HR Analytics Value Pyramid: “Find business pain and solve it!”

Unfortunately, most of the time HR is not very familiar with core business processes, is not involved in the analysis of it and does not have a good level of credibility in the business of adding value to such processes. In my experience, that’s a huge challenge for HR. Developing HR Analytics capabilities is one thing, but getting involved in and adding value to the optimisation of core business processes is another thing.’

2. Mirror the marketing department

People often ask me whether HR should collaborate more strongly with Finance to get better analyses. My answer to this is that Finance definitely out-analyses HR and that good collaboration with them is certainly desirable. At the same time, that collaboration entails some risks: Finance looks at all analyses through the eyes of an accountant, while HR analytics primarily aims for organisational optimisation by analysing human behaviour in function of achieving organisational objectives.

In connection with our blog articles about the HR Analytics value pyramid, this is my experience: I see in Levels 1 and 2 of the pyramid that HR collaborates more with Finance (costs, reporting, metrics, ratios, productivity, efficiency, etc.). In Levels 3 and 4, I recommend working more closely with Marketing. Both HR and Marketing are trying to measure human behaviour. The marketing function uses predictive analytics all the time to predict customer behaviour and the methodologies they use (since many years!) can all be adopted by HR. Marketing has far less information about customers than HR has about employees, so HR even has an advantage over marketing in that sense.

3. Most HR Business Partners won’t cut it…

One of the most frequently asked questions in my workshops is how HR can train business partners to become more analytical. Until recently, I gave numerous workshops to ‘typical’ HR business partners: HR pros with a social-scientific background and – with all due respect – mainly a considerably low or completely absent analytical acumen. For years I tried to keep positive and worked hard with my clients to teach the analytical trade to these HR business partners.

However, in the meantime I’m sorry to say I’ve kind of given up hope. Awareness, yes! Managing analytical projects, maybe! Working with the business, hopefully. Doing analysis, forget it! It’s a totally different field of expertise with different people! You need unconventional profiles in the HR analytics function (see what Shell does about it) and if you’d like to understand this profile, have a look at a few such job descriptions.

4. HR Analytics is not a cost but an investment in competitive advantage

I often have discussions about necessary budgets for doing HR Analytics. HR’s focus in this is mainly on the costs aspect and I’m sorry to say, not so much on the investment aspect. I’ve noticed that HR leaders do not succeed enough in positioning HR Analytics as a necessary investment in the competitiveness of their organisation.

That often has to do with the lack of knowledge about the possibilities of HR Analytics. If you can catch the power and possibilities of HR Analytics entirely, I bet you will be able to present a strong business case just like a few more advanced HR analytics leaders already do. Some of them have even come so far that the business puts budgets at their disposal, because they firmly believe in collaborating with these HR Analytics experts.

5. Prove the concept, not the pilot

I always recommend that organisations wanting to start with HR Analytics begin with a ‘low hanging fruit’ pilot and I advise them not to make the mistake of only focusing on the analytical outcomes of the pilot itself, but rather (and foremost) on the wider context of why the pilot was organised. Analytical results are always impatiently awaited but as important as these results itself are:

  • gathering analytical experience in general;
  • gaining an insight into the data complexity, data ownership, data location (who owns the data, where are the data stored, how to get access to the data,…);
  • understanding the quality of the data (evolving from an administrative to an analytical data vision);
  • collaborating cross-functionally with the business; (see this great case study about such collaboration)
  • learning to work with data analysts (who do analysts report to in HR, where do they fit in the structure?);
  • organising the analytical activity: doing it internally or outsourcing it? (see our blog on this subject)
  • asking the right business questions;
  • understanding analytical methodologies; (see our blog on this subject)
  • presenting business cases and learning to improve the storytelling and visualisation of analytical outcomes;
  • learning to deal with data governance (privacy, legal, transparency,…), etc.
  • working with IT on data gathering, data integration, data protection, etc.

6. Risk is the language of the CEO

Risk concept.In order to get on the CEO’s agenda, I’ve had very good experiences with talking in terms of risk. CEOs have a gigantic number of priorities and everyone is trying to get their attention. To do so, I recommend making gradually better risk assessments of the most important business/organisation processes in terms of people. CEOs need to be able to trust that HR has been able to study and analyse the right (people-related) risks that could jeopardise business/organisation continuity or development.

If you can start conversations with explaining such identified (and analytically well-substantiated) critical risks, you’ll notice that you’ll gradually get onto the CEO’s agenda more easily, than when you discuss the list of leavers for the last quarter with him/her.

7. Build an ethical and transparent analytical practice

We often hear the wildest stories about all kinds of bizarre analytical practices, like reading and analysing internal email streams, for instance, trying to discover internal communication, network and performance patterns (to name just an example) from those emails. Although I’m fascinated by the technological evolution, how on earth will you explain this to your employees, works’ councils or employee representatives when you have to introduce action plans based on such spooky analysis?

We very often contribute to presentations to e.g. works’ councils and believe me, if you’re not willing to develop an ethical and transparent analytical practice in the long run, your projects will be either irrelevant or completely rejected overtime!

In part 2 we will discuss the following 7 lessons:

  1. Hiring a ‘just promoted PhD’ is not a good start
  2. Forget about big data at the start
  3. Don’t let bureaucracy and politics prevent from delivering value
  4. You can start tomorrow
  5. Think of analytics as a continuous exercise and not a series of projects
  6. Using ‘engagement-data’ for your HRA projects isn’t the magic solution
  7. Forget about using an analytical COE at the start

About the author

lukLuk Smeyers is an experienced senior HR executive who has lead complex transition projects for compelling Fortune 500 companies, such as PepsiCo, Starbucks and Nielsen. 

In 2008, Luk started a cutting-edge predictive HR Analytics consultancy, together with academic partner Dr. Jeroen Delmotte.

 Luk is widely recognized as one of the few European top HR analytics experts. He is revered as a leading thinker, educator, influencer and is a well-known content contributor, blogger, columnist and author of many articles. He is an invited speaker at international conferences and academic programs and helps clients set a higher ambition for strategic HR intelligence, leading consultative projects in the Benelux countries with such organizations as Ahold, ING, KPN, ABN-AMRO, Deloitte, Philips, Rabobank, UWV, RealDolmen, Acerta, NS, BASF, Besix, Strukton, Bekaert, Randstad, Eandis, AG, Postnl, AON, Raet, etc.

Interested in using predictive HR analytics as a key component in your HR strategy? Get in touch with CEO and co-founder Luk Smeyers for more information ([email protected] or via Google+). Or follow iNostix on Twitter and/or Facebook for exciting international articles on HR analytics. And don’t forget to register for this blog!




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