Archive for April, 2012


The internet is alight with blogs and articles about economic nudging, David Cameron’s ‘Nudge Unit’ and yet another economist (Richard Thaler) who’s recruited himself into the White House with promises to improve the effectiveness of government.

For the last few hundred years, a simple assumption has dominated thinking about human nature: when faced with a set of choices, people make the one that’s most likely to serve their personal interests. But behavioural economists say that people often don’t make decisions like this. People often make decisions which are downright irrational, such as taking out subprime mortgages or chain smoking cigarettes faster than Mad Men’s Don Draper (it’s 2012 now, so you don’t have his excuse).

This is interesting from Saffron’s point of view because we’re often tasked with trying to change employees’ behaviour when there may be no direct incentive for them to do so. An employee might wonder why they should bother engaging in cost saving tactics like switching off their computer at the end of the day or boiling one less kettle for tea when it’s not their money that’s being spent in the first place. And the far away reason that they should do so to save the planet and protect future generations doesn’t cut it for everyone. Saffron’s Nick Simons often repeats that you can’t change behaviour unless you can provide people with incentives or disincentives for doing so. But if people aren’t simply driven by their rational self interest, then it could be that we can change behaviour even when we can’t provide a Pavlovian reward or punishment.

And it’s definitely Saffron’s experience that not everyone behaves wholly rationally. One client told us that their employees fail to use their new online expenses system because they didn’t like the change. Clearly some people would rather forgo reimbursement for expenses than have to change the way they do things.

The idea of nudging is based on research that shows that you might be able to persuade people to make different (read, more responsible) decisions by tweaking their environment so that they perceive their options in different ways. For example, studies show that placing fruit at eye level in school canteens can dramatically increase sales. One experiment involved sending vehicle tax avoiders warning letters in plainer English. I haven’t seen the letter but according to The Economist, it went something like this: ‘pay your tax or lose your car.’

But is this easier said than done? Going back to my example about change management: if people don’t want to change, despite incentives, then to what methods should a hard working instructional designer resort?

Saffron recommends three alternatives:

1. A good relationship between the graphic design and instructional design team is a must for any good e-learning course

Next time you see several PowerPoint screens worth of text think about how it might be represented visually. Rather than writing a couple of screens telling users about a new project management process, why not represent it as a process flow or animation?

2. Forget the theory, focus on behaviour

We all know how easy it is to be hoodwinked by subject matter experts into filling a course with heaps of the theory behind competition law or data protection when what a learner needs to know is what they need to do better or differently in their job. Educate your SMEs so that they know that they’ll never change behaviour if you don’t show people what sort of behaviour they’re expected to perform.

3. Less is more

60 minutes of scenario-based questioning probably won’t be as effective as a 10 or 15 minute course, even if it’s less interactive. If you’re only selecting material that’s absolutely relevant to your audience then you shouldn’t really have any more than 30 minutes’ worth of content anyway. If you do, then consider whether the scope of your course is too large.

Whether or not nudging gets people to stop eating fast food or pay their car tax remains to be seen. But I’m still wondering: could we apply the insights of nudging to e-learning? Many companies already automatically assign courses to their employees’ online learning profiles and send out self-generated emails to remind people to take them. But is there any more that e-learning professionals could take from the economic nudgers? It could certainly work out cheaper than promising to give staff Amazon vouchers or a meal out for two in return for completing training courses.


When we take a look at compliance training, we often try to “justify” the learning to the reluctant user by listing the all of the empirical stuff that provides the context for the business case. “Data protection is important for us at Compuglobal Hypermeganet because in <insert recent year> there were <insert massive figure> breaches of data for our industry resulting in <insert inordinately large amount of money> in fines.” And yeah, it serves a purpose, to a point. Examples like this are an attempt at what we like to describe as a “war story” – using the worst case scenario to illustrate what a breach in compliance means.

But just trotting out the figures is a cop out for any self-respecting instructional designer; a massive disservice to what good e-learning should set out to do. Every single fact and figure should have to fight to prove its validity, rather than just being lumped in as a pseudo-supportive argument.

Here at Saffron we like to make a point about the “need-to-know” factor of data or statistics in our learning. Does everyone in your organisation really need to know how many cases were reported to the regulator in the past five years, or how many of those reported were prosecuted? It’s unlikely, because in most cases the training has been commissioned so that after you’ve completed it you can make the right decisions and avoid breaking the law. The focus of the training isn’t past performance, but future decisions.

Say you’re a small telecoms company that receives 250,000 calls from your 50000 customers per year. Last year, your staff logged 5000 suspicious calls, where the caller sounded like they were fraudulently trying to obtain personal account details. But it’s come to light in a recent court case that a private detective’s firm actually made over 10000 fraudulent calls, with a 50% success rate.

Some might just trot out this information as a bullet point list and leave the learner to it. But with just a little thought, we get our “need-to-know” number, where we can summarise the implications of the entire example and position it in a way that’s relevant to the learner by using just one figure.

From the stats, we can imply that 1 in every 25 calls made to the business is potentially fraudulent (total calls/fraudulent calls). This provides the context to the learner without going into overwhelming detail, and gets rid of the bits that aren’t really worthwhile. The learner can then relate this number to their everyday working life – if they take 50 calls a day, they can see that it’s likely that at least 2 of them could be fraudulent. With this information, the issue becomes much, much more apparent and resonates with the individual.

These “need-to-know” numbers provide context, whilst also arming the learner with knowledge that they can use in their daily routines. They aren’t hard to stumble across – you can often reach them by delving a little deeper into the data. They make the learning digestible, relevant, and can often be brought to life with supporting graphics or scenarios. So think about it next time you’re writing and ask the obvious question – what do learners need to know?




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