But today, as well as a couple of meetings, and a bit of time by the pool, I’ve been finishing off on an input to a UK client’s learning strategy, and have been reading some research and watching a couple of webinars as input to this.
One of these has been the CLO’S Virtual Fall Symposium which took place live back in October. (Quick reporting isn’t something I always do well eg I’ll probably only get round to posting on cuts, strikes and exec pay in 2012!).
There were a few interesting sessions at this, including:
- Another excellent session from Dan Pontefract
- What was probably a great if unrecorded conversation facilitated by Jay Cross and team (though I can’t say that playing hooky from the workshops sounds terribly conversational to me).
However, the one which most interested me was by Larry Israelite from Liberty Mutual. This suggested that measurement can (I would say should) be based on an organisation’s beliefs, not just on data or current goals:
- The data based approach is based on a cycle of data – information – judgements – actions. As well as being HR driven, focused on the current state and reactive, the main problem with this approach is that there’s a disconnect between actions and data – you can take actions but don’t know what led to the data in the first place.
- The goal based approach is based on a cycle of goals – measures – results – actions. It’s still HR driven, but focuses on refining the current state, defining outcomes and being more proactive. You’re looking for the impact of what people do but you still don’t know what these things are and they’re difficult to control so your ability to influence them is severely compromised.
- A cycle of beliefs informing behaviours followed by measures – results – actions addresses these issues because you can influence the behaviours, and if necessary revise the beliefs. It’s also business driven, focused on achieving the desired state and much more proactive.
It’s about faith – a firm belief in something for which there is no proof, and something that is believed with especially strong conviction. Eg Liberty Mutual’s beliefs include hiring the right people. Their talent management measurement reports focus on 34 measures which reflect these beliefs. Tracking against these strategic measures means they don’t have to prove how HR impacts the business: “We believe we’re effective and successful because the CEO believes we’re effective and successful.”
There were some good points in this – I agree that data without a strategic backdrop to underpin it is often valueless – which is why I am a firmer supporter of ‘big strategy’ than I am of the opportunities of big data.
And I also agree with the importance of beliefs, though I think we can push deeper and get to more unique needs than just something like recruiting the best people. It’s why I like Gary Hamel’s focus on ideology (definition taken from Hamel’s forthcoming book, What Matters Now):
“Here's a word that probably doesn't get much airtime in your organization: ideology. Do a search of your company's internal website and I'm willing to bet you won't find a single reference. That's a problem. As managers, it's our creedal beliefs that prevent our institutions from being more adaptable, more innovative, more inspiring, and more noble-minded. We are limited by our management ideology.”
Also see my post on HR scorecarding – an approach which combines some of the aspects of Israelite’s goal and belief based approaches, without restricting focus to behaviours, and which also makes the data which is collected make more sense.
The separation between outcomes and business impacts in my model is why I also don’t support Israelite’s suggestion that a business has to be performing in order to be a good case study. An organisation can have well developed behaviours and other human capital which, for a number of reasons, don’t result in the business benefits which are intended.
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ReplyDeleteA good post. However, I'm not convinced that beliefs necessarily are detached from having information, but rather that the supporting information may be seen as incomplete.
Measurement and reporting needs to happen as multiple levels including supporting strategic objectives. I agree that much in HR is data-led. The approach should be be the other way round:
What is the issue that I want to understand / decision that I need to make?
What information would help me make this decision?
What data is needed to create that information?l
Where can I get that data?
I wrote about such an approach in a post called 'the future of HR reporting': http://www.organizationview.com/the-future-of-hr-reporting.
The initial decision can be a strategic objective, and in fact a set of issues should include some at that level.
At the heart of the issue is how we make decisions based on evidence. Much of the (numerate part of the) HR profession when using data tend to come from a traditional statistics background, typical of what was taught in undergraduate (dare I say psychology) courses. An alternative, Bayesian, approach I find more appropriate for HR and more intuitive for the lay-person. The Bayesian perspective is much more accommodating to Beliefs.
Beliefs are necessary and useful. It's failing to refine your view (even to refine the probability that the belief is true) in light of evidence that's folly.
Thanks Andrew, interesting stuff as ususual. I need to spend a bit longer understanding Baysian, but I agree from an initial google search - and wikipedia - that it looks to be more a more appropriate approach.
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