Eiffel Over

Tag: Optimisation

  • When the joke isn’t funny anymore

    I’ve been writing this week about when is and isn’t a good time to optimise. And also about the way a street theatre clown uses feedback to keep them close to their goal of making the audience laugh. 

    Well, the clown has another trick up their sleeve, which I learnt from clowning teacher Holly Stoppit, which is called the Drop. 

    Usually a clown can whip up an audience into a frenzy of laughter by doing silly, unexpected things on stage. They will find a gesture or a game that gets the laughs rolling. But then usually, at some point, the joke will stop being funny. The tide turns quickly, and the audience isn’t laughing anymore. 

    This is when the clown should use the Drop. They simply forget all about what they were doing and invent something new. The surprise keeps the audience engaged. It reanimates the clown, giving them a new creative opportunity. It reconnects the clown and their congregation. And the game of improvised laughter-making starts again.

    The reason the clown can do this is they have no resistance to changing the plan. Few deeply held plans about how the session is going to go. Few carefully created props that wouldn’t get used if they took the show in a different direction. And critically, no ego.

    With none of this baggage, the clown is freed of sunk-cost fallacy. Sunk-cost fallacy is the often-held belief that we must continue doing the same things as before because we have invested so much in our existing ways of doing things, even if in the long run changing plans would lead to better overall outcomes. 

    One of the reasons we continue to do the same thing as before rather than change approach is because we feel we have so much invested in the status quo. It could be investment in physical infrastructure or personnel. It could be more personal than that and be an issue of reputation. Or a fear of challenging the powers that be.

    But if the approach we usually take is no longer working for the system, we need to have the confidence to drop and explore something new. Because when the audience stops laughing, the joke isn’t funny anymore. 

  • When optimisation is a good idea

    There are times when optimisation is a good idea. For example:

    When the technology involved is mature. With a rapidly changing technology, process optimisation may not keep pace with technological evolution.

    When the environment is stable. It is easier to optimise a structure for a prevailing wind than for blustery conditions. 

    When customer behaviour is constant. If customer demand is broadly unchanging, then we can optimise around how we carry on giving them the same thing.

    When you have good feedback. This is critical. Without good feedback from the system you are operating in, you don’t know if what you are putting into that system is meeting your aims. And you can’t see if the system conditions are changing.

    When there are no disruptors. These disruptors could be technological. Or they could be a group of engineers (or other humans) with an approach that is changing things up. It is too late for optimisation when no one needs what you are offering.

    In short, optimisation is good when the conditions are steady. 

    But if our operating environment is changing, then we need to dedicate at least some of our resources to asking, do we need a different approach?

  • The trap of the same way as before

    It is easy to do something the same way we did it before. 

    The previous time acts as a guide.

    Using the same approach as last time gives us something to improve on. We can see the shortcomings and improve on them. 

    We need to do less mental work when we use a tried and tested and optimised approach.

    Using the same way as before avoids us challenging whether the way we’ve been doing things for all these iterations is still fit-for-purpose.

    The same way as before gets us out of difficult negotiations with the other people who are also invested in the same-way-as-before approach.

    And it avoids us having to do the hard work of imagining and creating something different.  Something better. Something more appropriate. Something that the system we are working in needs more than the same way as before.

  • A suboptimal walk in the hills

    Here’s a made-up story I usually tell in our How to Have Ideas workshops at Constructivist. It is a story from the distant past when humans lived without phones in their pockets…

    Imagine you and a friend agree to meet for a walk in the hills. You agree to meet at the bench on the top of the hill nearest the carpark. It’s easy to see from the carpark, and it is a nice spot to sit and wait for each other. 

    But when you arrive, you find a thick fog has descended upon the valley. You have no idea which way the hill is. So you start walking and notice that you are going uphill. Feeling encouraged, you carry on finding your way through the fog by following the line of steepest slope. Eventually, this method brings you to the top of the hill, where you see the bench and sit down. 

    The fog begins to clear.

    Gradually you begin to see that on the other side of the carpark there is another hill, with another bench on it, and there is your friend waving back at you.

    Ok, it’s quite a crude story, but it serves as a lesson in constant optimisation. Sometimes, following the line of steepest slope – making what seems like the optimal decision at every step – only gets us to the top of the nearest hill. But to reach the top of the tallest hill we might need to stumble around in different directions in the fog before the best way forwards becomes clear. 

  • Convergent poem

    Zero in

    Figure out

    Tidy up

    Manage down

    Validate

    Mitigate

    Prioritise

    Optimise

    Strip it back

    Keep it clear

    Make the risks 

    All disappear.

    These all sound like good things to do on a project, and are what engineers (and other humans) spend a lot of time being trained to do. And it makes sense – we manage projects that come with big risks and sometimes big budgets. 

    All of these processes are forms of convergent thinking: ways of working that take a situation with many possibilities, inefficiencies and uncertainties and reduce it to something more refined, more singular, more known.

    This approach is fine if what you are starting with contains the elements of the right answer. You can take some approximately right answers and iteratively improve them to make them better and better. 

    But if the starting point isn’t the right approach, optimising it won’t make it better. You just make the wrong answer more efficient.

    So we need to balance convergent thinking with divergent thinking that opens up the problem, that sees what else might be possible. But first, let’s go for a walk…[to be continued tomorrow].

  • The wrong (moment to put on your waterproof) trousers

    This is a post for the cycling decision-makers among you. It may resonate even if you don’t cycle. Variations on the question of whether, if it starts raining when cycling, it is worth stopping to put on your waterproofs.

    How late am I running? Have I got time to stop? How heavy is the rain? Will it carry on? How quickly could my clothes dry? Will I get wetter stopping to put them on?

    If I do decide to carry on, is it wetter to go quicker or slower?

    Do I have all the facts? Do I know all the unknowns? Is this a complicated or a complex problem? Am I able to make a good decision? 

    Is there an angle I can cycle at in which my rain shadow protects my lower half sufficiently? 

    Is how I’m framing the question limiting the result? What opportunities am I not considering? If I stop at a random location to put on my waterproofs, what might I notice that I might never have discovered had I ploughed on?

    What happened last time? Was it the right decision? What are other people doing? What would my future self advise?

    Am I even in the right frame of mind to make this decision? What could I be thinking about instead?

    What happens if I get it wrong? How much does it matter to me if I get it right? Am I deluding myself that I’m in control?