Two heads are better than one

Whether you’re making decisions, innovating, developing plans or solving problems, the more the merrier is the go. Up to a point of course; too many cooks spoil the broth. But enough of cliches.

There is no doubt that people working together, directing their efforts towards the same endpoint, almost always do better than one lonely brain. Particularly when they are an assorted group, with different backgrounds, experiences, skills sets and all the rest of it. We all know that.

Why is it, then, that we so seldom act on what we know? Well, we’re all under pressure and involving people does take more time. But let’s face it, when you get a better result, that bit of extra time is worth it. Plus, the people you’ve involved have a better understanding of the situation and therefore greater commitment to the decision, innovation, plan or solution. Plus, when it’s your team you’re involving, it’s good for their development, both as individuals and as a team. ‘We’re all in this together’. ‘We the team’, in which there is no ‘I’. That makes your life a lot easier in the long run, too.

Of course, you don’t want to involve people when it’s just to rubber-stamp a decision or plan you’ve already made. Or so you get to lead a meeting that takes up everyone’s time and merely fills the room with warm, moist air. When people don’t care about the decision or plan or won’t be involved in implementing it or when it doesn’t affect them, don’t waste their time. And naturally, when time is really tight, you possibly can’t afford to involve people.

But that leaves a lot of other times when you are well advised to bring in the troops. When you have good people on your team — that is when you’ve recruited well, trained and developed them well, motivated and engaged them well — they probably have the skills and experience to help.

People often want to be involved, too. When you’re lucky, it’s because they care about the team or the organisation or their customers. Maybe it’s for their own personal development. Maybe it’s because they know they can make a positive contribution. Maybe they’d rather sit in with a group than get on with their own job. When that latter reason is the case, leave that person out of the loop, because you want people who can add value to your decision, innovation, plan or solution.

You should almost always include people who are affected by your decision, plan, innovation or solution and people who you need to help you implement it willingly and enthusiastically. When you need people’s acceptance and support, invite them to the party, too.

So there we are. You know it and I know it. Two heads are better than one. Act on what you know.



Every solution has a problem

Most parents take the view that problems are good for children. Problems teach children how to deal with life, how to fix things up, how to become more resilient, self-sufficient and self-confident. Problems help children to see themselves as problem solvers, not hapless, helpless victims.

What happens when you’re faced with a problem? Do you rub your hands and say ‘Oh, wonderful! A chance to take charge and exercise my brain to figure out how to solve it!‘ I don’t know too many adults like that. Somehow, what we see as a growth opportunity for kids doesn’t translate into adulthood.

Instead of welcoming problems and thinking: ‘I’m confident I can fix this up‘, we ignore them, put them to one side to deal with later, or foist them onto someone else to fix up. We might take them home with us and let them spoil our leisure time and turn our sweet dreams sour, but that doesn’t fix them.

Every solution has a problem. One goes with the other, just like steak and chips. As M Scott Peck says in The Road Less Travelled:

Problems call forth our wisdom and our courage.

When we let them.

But  when we let them tie us up in knots, problems paralyse us. Our brains freeze, we can’t think our way clearly through them, and we become ‘stuck’ and frustrated.

This is not a good game plan. Much better is to face up to a problem, look it in the eye, and, knowing we have the smarts and the strength to solve it, get started looking for a solution.

Discussion questions

Think back through the last few problems you’ve solved and messes you’ve fixed up: what did they teach you? How did they help you grow and mature as a manger?

How to use models

Models are representations of the real world. They help you better understand the real world by breaking it into pieces, making them good when you need to assess a risk or make a decision. But as Kevin Madigan points out, in an article on Property Casualty 360, a National Underwiriter’s website, no model can cater for every contingency and some models are better than others at helping us assess information about a risk or decision. The main thing is not to use models unquestioningly, for two reasons:

  1. Models are based on underlying assumptions.
  2. Models work on probabilities.

That means you need to understand both the assumptions models make and how they calculate probabilities.

First, ask yourself what your model’s underlying assumptions are and how correct and relevant are they to your organisation or decision. What contingencies are built into and left out of the model? Are the missing pieces important and if so, how can you incorporate them into your decision-making or risk management?

Next, find out how the model calculates probabilities. There are two ways: ‘classical’ probabilities and ‘subjective’ probabilities. You can be reasonably confident in classical probabilities because they are based on observation and experimentation; for example, flipping a coin or testing a drug on a target group and a control group. (Why not call them objective probabilities? Good question; too logical maybe.)

But you can’t experiment or observe elements of decisions about unusual events or problems or of catastrophic risks. That’s when subjective probabilities are used. Either you or the model need to estimate probabilities, perhaps based on observations about the past, informed assumptions about the future, and your ‘best guess’. That’s a long way away from classical probabilities.

So use models to help you make decisions and calculate risks but use them all with care, a questioning mind, and common sense:

  • Don’t take any model at face value.
  • Don’t interpret any model, especially those using subjective probabilities, as factual.

The statistician George EO Box put it well:

‘All models are wrong but some are useful.’

P.S. When you’re working with models, here’s a phrase guaranteed to impress: Don’t get caught up in delusional exactitude. In other words, be wary of models that claim to have a high degree of precision.

Discussion questions

What models do you use in your work? How accurately do they break information into pieces and represent the real world? What are their underlying assumptions and how relevant are they to the situation you’re applying them to? What type of probabilities do they use? In what ways might the models you use be wrong?