The Theory

– When you calculate risk, you examine the cost and probability of something going wrong. If you were put it into an equation, the equation would look like this:

RISK = PROBABILITY x COST

You like to think that things will go well, you will meet the best-case scenario and reap maximum benefit, you like to think that the probability of something going wrong is less than .01, so you put a low likelihood on that event.

So you get: Bad Outcome = .01 (1%) / Good Outcome = .99 (99%)

This is what ‘you like to think‘ in an ideal world. But the world is less than ideal.

– It’s that Simple – or is it?

You’re already over-estimating that things will go right due to the ‘overconfidence principle’. Because of optimistic expectation you don’t see the true risk.

You’re also typically overconfident about your returns too…

To endure risk is low, you typically use, ‘best of breed technology’. This is usually at high initial outlay, but you expect a high return on investment – so that’s OK. Or is it?

Let’s create a scenario.

You invest £500,000 on a technical specification for the project. The tech is brilliant and does way more than you need. That extra tech you never need – but have it there ‘just in case’ – costs you. So you have already spent probably an extra 20% on tech you simply did not need. Even though you don’t realise it, speculating funds on something that is superfluous – is risk. Likely returns on this cost are zero.

You invested £500,000 on a project where your expected return exceeds £2,000,000 so feel confident this is money well spent.

You have a high expectation of good return, but expect minimum payback to be at least £80,000 – which covers costs and gives you a little more besides. With excellent marketing, press coverage etc the initial outlay will reap the anticipated far higher return.

A Touch Of Reality

Using the above equation, a scenario of failure has little possibility.

This is your prediction:

• £200,000 success                                                               50% probability
• £80,000 moderate                                                             49% probability
• £-50,000 failure                                                                  1% probability

Looks good doesn’t it?

Upside Down Bottom Line

What if, instead, we turn this equation on its head?

Instead of risk being viewed as ‘probable success’, it’s seen as reducing  potential cost.

What we’re saying here is, “OK, you know what you want – eventually – but instead of listening to all the hype of what this great solution can do (for you and your competitors equally), you focus on the real cost of the solution (in monetary terms as well as labour, time and other factors) and decide, instead of going for the ‘best solution’ (reducing risk by increasing probability of success), go for best-fit and least costly solution – before committing to any huge expense.”

Take the example of, a camera or phone. You get lots of functionality on your equipment these days, but you don’t typically use it all. Lower cost cameras will do the job you need perfectly adequately. Typically you don’t use all the filters – some look so awful we would ‘never’ use them, even though you paid for them ‘ as a package’. Do you see where I’m going now?

The same goes for high-ticket solutions to a problem in business, much of what’s paid for is ‘insurance money’ when you could have gone for a lower cost solution that would have done the job as required – and saved money (or risk).

Recalculating and Rethinking Risk

Now back to the initial (more realistic) scenario – you thought the project had a risk of .01 – still a risk. Factoring overconfidence into the equation would make failure more likely. In fact it’s well documented that, certainly in IT, 30% of projects fail – so change .01 and move it up to .3. Why put a heavy investment into something that has 30% chance of failing?

As well as that risk, you also lose the extra 50,000 over-investment initially put into the project that wasn’t needed.

Standish reports that only 9% of projects are actually successful, therefore the equation looks like this instead of the previous graph:

• £200,000 success                                                               9% probability
• £80,000 moderate                                                             61% probability
• -£50,000 failure                                                                  30% probability

This is a very different scenario than was looked at initially, but more realistic and less over confident.

“When you are eager for a project to work, you are more inclined to be overconfident, yet oddly enough overconfidence decreases as knowledge increases, we become less sure as we get better at something.” (Plous 1933)

This is why it’s always important to look at a best-fit solution (usually a hybrid), to minimise risk by reducing initial cost of project outlay. Bearing in mind the true likelihood of failure, it’s always wiser to limit initial outlay.

New technology is prey to overconfidence. The more proven a technology is, the more we rely on the probability of it working because teething problems have been dealt with and there is more experience in that technology to be hired. This is a false reason for using a best-of-breed solution.

With new technology, don’t overlook the ‘little guy’ – he may just be the market leader of the future!

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