Category: Innovation

There are two traps we often fall into when developing something new:

1. We try too hard to plan ahead and come up with everything we will possibly need before starting any work.
2. We spend a lot of time making one part better and faster when it doesn’t help to make the overall performance better.

In software development the classic problem is one of requirements and specifications.

We usually don’t know what we need to do the first time we approach a problem.

It’s the process of engaging with and solving the problem usually helps clarify thinking – and when we have finished with our first solution we now know what we really need to do to solve the problem.

The idea of right first time simply doesn’t work when we don’t know what the right way is yet.

A better approach is to prototype our way to the right solution.

We ought to start small and simple – designing something we and others can understand.

Whether it’s a business process or a software program, once we can show others a working prototype we will be able to see reactions, get feedback and other useful information which can help us refine our ideas.

It’s also important we don’t get too fancy or try to locally optimise things.

Something very clever right now may be hard to understand in three year’s time by someone else, who might decide to throw out all our work and start again instead.

Local optimisation is the idea that we work very hard on speeding up one part of the process but miss the real bottlenecks in the system.

The overall time any system takes to work will be controlled by its slowest component. Making any other part work faster will not reduce the overall time.

For example, it doesn’t matter how fast we get ready in the mornings if the real bottleneck is how long it takes the bus to get to our stop.

We could be 20 minutes early – but it’s the bus time that will decide whether we are late or on time to work.

Our natural tendency, very often, is to try and do more – plan more, think more and have more.

In reality that leads to bloat – creating large unwieldy systems no one loves.

We would be better off following a few simple rules:

1. Prototype then polish. Get it working first, then try and make it better.
2. Doing nothing can be very constructive. Words that aren’t there can’t be read wrong. Code that isn’t written can’t fail.

If we must do something – then we should concentrate our time on the things that deliver exponential results, not incremental improvements.

Why is it that many systems – software applications, company policies, operational processes – are hard to use?

Take websites for example. How many company websites are structured in an easy to use, logical manner?

If we ask any company’s marketing team, they will probably say that their website is structured, laid out and easy to follow.

For them, that is.

This is an example of a principle called Conways’s law, which says that Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure.

In other words, the way in which we structure ourselves influences the systems we create.

For example, if we have two factories, one making bread and the other making jam, we are likely to advertise ourselves as having two product lines, the bread line and the jam line.

We’re unlikely to combine them and pitch ourselves to customers as the jam sandwich line – even though they might actually be looking for a sandwich rather than a collection of components.

This is a natural way for an organisation to behave – after all the way they look at themselves seems natural and normal – so why not show themselves to the world in that way?

Except to a user with little experience, it’s hard to work out what companies do, so they will pick the one that makes it easiest for them to understand.

The problem gets worse as we try and create bigger and bigger systems.

For example, a large software application that tries to do everything will find itself bogged down as it grows, constrained by previous decisions and choices about architecture and design.

One solution to this problem is to limit the size of teams – use multi-skilled individuals in small teams that have end-to-end responsibility for a product.

This is the principle behind work cells in lean manufacturing.

These teams tend to produce work that has clean edges and plays nicely with other teams.

Small teams are also fast – they can get together, come up with a plan, develop a product, test it and get feedback, and iterate and improve in the time it takes for a large organisation to do the paperwork needed to get permission to start.

Although, the size of teams is not a solution by itself – it simply produces systems that may be smaller, simpler and work more independently, and so be easier to scale.

The point is that our default approach when trying to design anything is to focus on what we think a user needs.

But, that thinking focuses on us – not on the user – who might actually approach the situation from a completely different point of view.

Perhaps that’s why some of the most useful tools have been developed by people who made them for their own use – they knew exactly what they wanted from the start.

Charlie Munger talked about competitive destruction – the process by which new businesses come along and destroy older ones – often built using new and different technology.

Being one of the first to market can be a good thing in this situation.

Using a surfing model, if a business can get up and catch the wave, they could ride it for a long time, making profits on the way.

Intel did it with microprocessors, Microsoft with desktop operating systems, Apple with smartphones and Google with search.

Products based on artificial intelligence (AI) and machine learning might seem good candidates for the next wave.

Take the way in which we use mobile phones, for instance.

Tools like predictive text have been around for a while – but phones are used for much more than talking or texting.

Navigation systems on them have gone from route planning to real time route optimisation, with suggestions on how to change routes in the middle of a journey based on travel patterns in the area.

Translation is another area being transformed by technology.

For gist translation – where what we need is an understanding of what a document says in a different language – the systems built into browsers and search engines do a remarkable job.

Machine learning may provide the solution to spam emails.

Microsoft Outlook’s clutter service means that virtually all spam type emails are filtered out and never hit the inbox.

Generic newsletter, marketing and sales emails simply can’t interrupt us any more.

Some of us don’t worry about scheduling or planning things – the entries turn up in our diaries and we can rely on our phones to tell us where we are going and when to set off.

These tiny changes to the way in which machines help to organise and optimise our days are happening in a barely recognizable way.

But they are becoming also becoming an inextricable part of how we go about our daily business.

These changes signal a groundswell that is expected to turn into a tidal wave as AI affects everything from law and medicine to transportation and sustainability.

The question that individuals and organisations need to consider is how they will fit into a world where work requires hybrid human-machine skills.

Robert Kiyosaki in his book Rich Dad Poor Dad has an elegant way to define assets and liabilities.

Assets put money in your pocket. Liabilities take money out of your pocket.

This isn’t the way accountants look at things – but it’s a good way for the rest of us to visualize where we should put our money.

Investing in a rental property that gives us income every month is good.

Buying a flash car that costs us hundreds in payments every month is bad.

It’s a clear and simple model that should increase how much money we have if followed.

We can tell what kind of financial health our life is in by looking at the pattern money takes as it flows through our hands.

If, when money comes in, we invest in assets and the money flows back into our pockets, that leaves us with more at the end of the day.

On the other hand if, when money comes in, we have liabilities, then the money flows out to pay for them and we are left with less when done.

And the same model, it turns out, can be used to think about activities that we do every day.

It’s a bit of a cliche – but even the Harvard Business Review is happy to use an article title like Manage your energy, not your time.

Our days are made up of rituals – things that we do from the time we wake up to the time we go to bed.

Some of these things are going to leave us with more energy than we started with.

Others are going to drain us of energy when done.

And, while it’s easy to fall into a victim mentality and argue that what we have to do is driven by the demands of other people like colleagues and bosses, recognizing the patterns that aren’t good for us is still the right starting point.

Like doing an audit.

There are a couple of ways to do this.

One approach is to log what we do over the day and then look back to see how our energy levels have increased or decreased.

Another is to make a simple list of things and give them a score.

Then it’s time to start making changes.

Usually this starts with creating new rituals.

For example, some people find their energy levels go up if they check email an hour after getting into work rather than first thing or in the afternoons.

Or we could do work sprints – 90-120 minutes of focused activity with a 5-minute break every 25 minutes followed by a longer break at the end.

We need to increase the number of rituals we have that are assets, which leave us feeling more energized when we are done doing them.

We might work on liabilities with high energy, but when we are done we’re drained – so we need to keep those to a minimum.

The last word on this goes to Scott Adams, the creator of Dilbert, who says –

Manage your creativity, not your time. People who manage their creativity get happy and rich. People who manage their time get tired.