What we should do before investing in technology


We often think of technology as a good thing – surely having the latest version of something is obviously the best way and people who do that win?

Perhaps not.

Charlie Munger said – The great lesson in microeconomics is to discriminate between when technology is going to help you and when it’s going to kill you.

Most companies would benefit from new production technology that is more efficient and so uses less energy.

The deciding factor, however, is what that technology does for the business

Does it help it create more products, for example.

In a commodity business, being able to push more product out means that the market has more supply and so prices go down.

The cost and energy savings made by the more efficient technology is wiped out by the reduction in prices to customers.

All of the benefit goes the customer, with little staying with the manufacturer.

The Japanese are well-known for having slow upgrade cycles, using older equipment for much longer.

This is because changing things adds complexity and could reduce the amount of time the factory actually operates.

In addition, changes often introduce new problems, and Japanese companies value stability and continuity.

They invest in systems that help them reduce defects, by continually monitoring a number of parameters and warning them when things are going wrong.

This helps them maintain quality.

Having good monitoring systems lets workers manage more systems and machines each – while good working practices, maintenance regimes and stable technology let operations carry on without crisis or constant intervention.

All too often, we look for a silver bullet – a new technology solution that will solve all our problems.

We should start, however, by making sure that we are using what we already have well – and good monitoring systems are our eyes and ears into the operations.

It’s simple really – we need to do the basic things a little better, every day.

And that starts with looking and improving what is in place before buying something new.

What type of service model do you have?


The UK economy is dominated by the service sector, which makes up more than 80% of GDP.

Many industrialised countries are in a similar position, moving away from raw material extraction and manufacturing to an economy based on service and, increasingly, knowledge based activities.

How should we think about service businesses?

We often start by thinking of a service as something people do for other people but this doesn’t capture the full picture.

In 1978 Dan R.E. Thomas, writing in the Harvard Business Review, suggested that we need to ask two questions to understand the model used in a given service business:

  1. How is the service rendered?
  2. What equipment or people render the service?

Matching services with business models

Although the article is old, it can be adapted into a framework to help match services with business models.

On one axis, we can think of people and their skills, ranging from relatively unskilled to professionals with extensive qualifications.

On the other, we set out how they use equipment and whether it needs to be operated, monitored or can be automated.

Services that require a human operator range from mowing a lawn, which can be done by someone relatively unskilled with a mower, to heart surgery, which requires a team of professionals with specialised equipment and facilities.

Monitored services can range from overseeing equipment, such as a car wash to more complex plant operations and consulting services.

In these situations the people don’t need to get physically involved but use systems to keep track of operations and change settings as needed.

Automated services range from vending machines at one extreme that have a fairly straightforward task of dispensing products to expert systems such as a health website that allows us to diagnose ourselves and decide whether we need to go to a hospital or not.

Why knowing the kind of service model you have is important

The kind of service model we operate decides how we scale the business.

If a business depends on one person’s time to succeed, then scale can only happen by adding more similar people.

Think lawyers, accountants and management consultants.

There is a reason why most professional practices are small.

They can only grow by putting in more capital and pushing up their fixed costs base which, if revenue fails to grow as expected, means they eventually slide into failure.

There aren’t that many ways to get around this. A common solution is to find patrons – small or big.

Scaling equipment, on the other hand, may be an easier option.

As more of the service is automated, the same number of professionals can deliver a better service to customers.

Unless it spills over into self-service.

There is a crucial difference between service automation that makes things better and cheaper for users and service automation that makes things better and cheaper for providers.

Getting users to do more of the work can easily fall into the latter category.

The right blend of service and equipment

A good service business, it would seem, has a core of people with appropriate skills and scales by adding technology and automation that improves service quality to customers before adding more people.

As with most things, that’s easy to say, but not simple to do.

How to create the conditions for complex outcomes


The natural world is teeming with creatures perfectly adapted to their environment – that have ways of walking, swimming and flying, live alone or in social groups and participate in an ecosystem with their own unique niche and capabilities?

Where do we begin trying to understand how they do it?

We start by breaking things down into parts that we can understand.

Like blind people touching parts of an elephant, we find pieces – a snake-like tail, a fan-like ear, a tree-like leg.

If we bolted a snake, a log and a fan together with the other bits that we identified, would we get an elephant?

The answer is clearly no – but we persist in trying to build complicated things from simpler pieces.

Take most systems, for example.

An organisation is a system made up of people in roles.

There are some at the top who see themselves as the brains and controllers of the outfit and many people who do work.

Organisations are often designed – made up of structures and hierarchies and reporting lines – held together and moved in a particular direction by incentives, punishments and guidance.

Does organisational behaviour come from the particular arrangement and positioning of people?

Or does it emerge from somewhere else?

The study of emergence looks at how complex behaviour arises from the interaction between simpler elements.

There is a difference between complex and complicated.

Complicated may be something like a steam train – with lots of moving parts. When the parts move in the way they should, we get something complicated like a moving train.

An example of a complex thing is a flock of birds flying in the sky together. Each bird maintains its distance from another – and the whole flock can swoop and move like a single living thing – but there is no one bird that plans or controls the action.

The complex thing that we can relate to easily is the Internet.

We are all connected by a vast decentralised network that has only a few simple rules about pages and links – but is so much more than that now.

Emergence is sometimes seen as the border between order and chaos.

In an ordered world, everything has its place – we put a rock on top of another rock and eventually we can get a building.

A chaotic world is dynamic – as elements combine randomly with feedback to create new conditions that – and range from the weather to swirls in a coffee mug.

As we move from order to chaos – we pass through emergence – and that is where life and the behaviour we see in the natural world seems to be.

But how can we use this in daily life or business?

With knowledge work in particular, a strict rules based approach is unlikely to create anything particularly interesting or innovative.

Instead, its the interaction between people with capabilities working together that creates output from the organisation that is “greater than the sum of its parts”.

Managers should try and do just a few things.

  1. Find good people.
  2. Remove as many barriers as possible that stop them working together.
  3. Set a few working practices
  4. Get out of their way.

Then, wait to see what emerges.

What kind of approach is best for a new project?


What is a good model to use when setting out on a new project or venture?

Is it to design for size from the very beginning – to plan for scale and explosive growth?

Or is it better to start small and build on little victories?

The answer, as in most cases, will be it depends.

The approach we take is contingent on the situation – what the environment around us looks like, what capabilities we have, the resources we can muster and what moves other players are making.

The challenge is that we don’t know what works.

If we look around at examples of what has worked, we see survivors – firms, systems and people that dominate the economy.

That doesn’t mean that how they did it was the right way – it means that the way they did it was right for their time and they were lucky.

It also doesn’t mean that they will continue to survive.

Size brings with it problems – the dinosaurs were perfectly adapted to their conditions until the conditions changed, and they couldn’t change quickly enough.

Viruses, on the other hand, may have been around since the dawn of life – and continue to spread and replicate themselves.

A often quoted post talks about this in the context of software design.

A good software solution needs to be simple, correct, consistent and complete.

The right way to design it to solve a problem completely, implement it on the right platform, use the right tools and maintain it in the right way.

Or we can get half of it working and available, get people using it, get them hooked and then worry about making it better.

Keeping it simple is the most important thing. It needs to be correct as far as we can see. Consistency and completeness are nice to have, but they can be sacrificed in the interests of keeping thing simple.

In addition, the fewer things we have, the less effort it is to be consistent or complete.

For many of us, then, it comes down to a personal world view.

Some of us will be comfortable with the idea of a large project, a big plan and the will to go with the big win.

Others will prefer small, even austere approaches.

In an ecosystem – there is place for both types of creatures.

It is the same with markets.

Why we need to get tactile with data


We often put a lot of effort into creating a good looking dashboard or reporting system – but then what happens?

All too often it simply becomes background noise.

We get it every day and ignore or simply tune out – going blind to it while we get on with whatever is latest and loudest.

We tend to fall into patterns and things like data and information displays can simply become pretty pictures rather than being used for reflection and action.

Unless you work in a lean organisation, that is.

The Japanese have a word for a big room – Obeya – that they use to call a dedicated space that is where people come together, can see what is going on and collaborate.

A way to think about this is like a command centre, a war room or the bridge of a ship.

Japanese companies like Toyota use this every day – or even several times a day.

It starts with a simple idea – we have to hit certain targets every day.

We get together during the day and go through the numbers and see if we are on track or not.

If not, we can make changes and correct our course. Being in the same space helps with having that conversation.

The space doesn’t have to be physical – it can be a digital space where we can get together, share and modify information.

But the important bit is that we need to engage with information we get.

At Toyota they make updating information a manual activity – writing numbers by hand, drawing charts and updating status indicators.

It’s the process of interacting with the data and information we have in front of us – of trying to touch and feel it – that transforms it from being a pretty picture on the wall to the source of our next action.

We are more engaged when we understand what is in front of us – and that makes for better conversations and more useful collaboration between colleagues.

It’s interesting that as we have more and more powerful ways to dissect and distill the data around us we humans become the bottlenecks in being able to use the information and insights more effectively.

And that’s no bad thing – constraints are good for innovation.

If anything – we need to slow down even more.

We need to look beyond the dashboard as a result and focus on the end result – what are we trying to achieve each day?

We should get our fancy algorithms and computers to do the number crunching they are good at and give us the figures we need – that’s not work people should do.

Our job to use our time to get a feel for the numbers – getting tactile with them.

That frees us up to use our creative ability to come up with solutions – and we need all the creative time we can get.

Because there are a lot of interesting problems out there to solve.

How to solve real-world management problems


We know we have to change things – but how?

A naive approach is to think that there is an engineering solution to everything.

Buy new software, change machinery, institute a new form or process and everything will fall into place and get better.

That approach assumes that business systems fit together like Lego blocks and swapping a new one in or moving them around will fix the problem.

It’s simply a question of knowing what systems we want.

We can then list out the options we have, model alternatives and then select the best one based on objective criteria – simple.

There’s just one problem.

The chances are that the people involved want different things.

The thing that the accountants see as an issue is different from how engineers would put the situation which is vastly different from the vision of the CEO and shareholders.

And, because its much easier to see things from our point of view, the decisions that get made say more about power and influence than impact and improvement.

Soft systems methodology (SSM), a programme of action research carried out by Professor Peter Checkland at Lancaster University, is an approach that helps us cut through such situations and have a structured debate about the problem situation and what we can do to improve it.

The principle that underlies SSM is that the one thing that we see in all real-world problems is that people are trying to take purposeful action.

Take carbon reductions, for example.

No one in any organisation these days would argue that it’s not better to be sustainable, reduce energy and emissions, and act in a more socially responsible way.

Why don’t we do more then?

The engineers blame the accountants for stopping projects.

The accountants point the finger at the CEO’s decision to limit costs.

The CEO points to the priorities of shareholders and the desperate need to meet quarterly numbers and support the stock price.

There are no solutions to such problem situations.

Instead, SSM teaches that there are accommodations – things we can do that reconcile conflicting interests.

It does not mean that everyone is satisfied – but it is a position that we can all come to that allows us to move forward and take action.

And that’s done through a structured learning cycle as shown in the figure.

We take a real-world situation, create models that describe a set of activities that enable purposeful action in that situation and compare them.

We use these models to talk to each other and see different points of view and figure out what accommodations we can make.

Then – we can take action to improve the situation.

But it doesn’t end there. This is a learning cycle – which means we can go around the loop forever, or at least as long as we’re still in business.

And it’s more complex – because we still need to think about culture and politics – that adds more layers to our analysis.

The thing is that real-life problems that involve people, their opinions and time aren’t simple to solve.

Let’s not pretend that they are – then we might start to make some real progress.

What is a thesis-driven approach to innovation?


Things are complicated now.

They also don’t stand still – the pace of change around us increases all the time.

One of the casualties of the times is our ability to know everything.

A few hundred years ago, all the useful information in the world could be contained in a decent sized personal library.

Now that’s no longer the case – we can hardly ever be certain that we know something – there are always complexities, nuances and new theories and evidence coming along that may cause us to reset our world view.

How can we make decisions – about investments, new products, lines of business – in such an environment?

We hear a lot about thesis-driven approaches these days.

What does that mean?

A thesis is an assertion – an argumentative one – that describes the conclusions we have reached about a particular subject.

It is a belief based on supporting evidence within a context. We must answer the question what do we believe and why do we believe it?

How can that help us develop a product?

A product here is a catch-all term for an innovative project that results in something that can be sold – whether it’s a new line of business or a new business altogether.

We start with a belief that there is a need for that product.

Then, traditional approaches might suggest starting with a business plan or a business model but what about those of us in an earlier, more experimental stage?

A framework for testing a thesis might help – as shown in the picture.

Testing a thesis starts with thinking about goals. What will success look like for this idea?

How many potential users are out there? What is the minimum we need for a viable line of business?

How can we get feedback? The number of sales is clearly a vital metric.

Ideally, we’d have a clear run in a market that needs the product where we have no competitors – but if there is competition we need to look at the growth in our market share.

Then there are the people we need to work with. This includes individuals we need to deliver the product and those that will buy it and that we will continue to work with in the future.

Who are they, where are they and how can we start the process of talking to them?

Finally there are the resources we need – the things and stuff that is required to deliver the product, whether its a factory somewhere or a laptop and mobile phone to get going.

These days we can’t be sure of things.

But we can try and test our beliefs.

How to use Lean Data to get better feedback


We need feedback to improve how we do things – but what is a good way to get it?

At one extreme in the feedback spectrum is Big Data – if we collect as much information as possible and feed it into clever machines that can learn and have artificial intelligence (AI), we’ll get deep insights into customers, organisations and systems.

At the other extreme is the collection and processing of information that seems important to people that matter – bosses, shareholders and government.

These focus on output metrics that are important.

In local government, for example, the number of jobs created is the main question asked of any project and so, unsurprisingly, most proposals will bump up the number of jobs projected to numbers that may never be realised.

The Big Data approach has a barrier to entry made up of knowledge and systems.

The output based approach makes the numbers look good but may not reflect reality.

So, is there a middle way that is simpler and cheaper to do?

Sacha Dichter and Tom Adams at Acumen, a non-profit that looks at innovative ways to reduce poverty, and Alnoor Ebrahim at Harvard Business School have used a new approach to measurement that combines lean design principles with quick and inexpensive data collection methods that they call Lean Data.

Lean data has two goals:

  1. Make measurement cheaper.
  2. Increase the value to enterprises of collecting data.

In the non-profit sectors that Acumen studies things change quickly, there is little money, there isn’t anyone in the organisation with deep data experience and the systems to collect and keep data aren’t there.

These problems aren’t limited to non-profits, however. Virtually all organisations will face the same issues.

Acumen have come up with an acronym – BUILD – that we can use to create a measurement system that works.

Such a system will be:

  • Bottom Up: created after listening to customers so that it addresses what they need.
  • Useful: What comes out of it helps us to make decisions.
  • Iterative: We won’t get it right first time – we need to iterate and continuously improve it.
  • Light touch: We need to be able to use cheap tech that needs little time or money to get going.
  • Dynamic: Things will change – and we need to be able to change as they do.

A problem with many management systems is that although they are designed around principles of test and learn and continuous improvement, they quickly degenerate into compliance activity with box ticking and paper processes that don’t match the real world.

A truly lean approach may help us cut through that and look at the underlying reality with fresh eyes.

We are certain to improve performance if we improve the quality of feedback.

Why we find it hard to make decisions about the future


One of the oldest and best known proverbs is a bird in the hand is worth two in the bush.

This way of thinking is so ingrained in us that we accept it unquestioningly.

We give more importance to what is happening now than what may happen in the future when making decisions.

The simple instance of this is that many people will take a small reward now, say £10, in preference to a larger reward in a year’s time – say £20.

Given a choice between waiting a year for £10 and two years for £20, they will often choose to wait the two years – what’s the difference between a year or two?

It’s a struggle to pass up chocolate now to avoid the weight gain that may accumulate in a year’s time.

This way of thinking is endemic in business.

Managers spend a lot of time focused on the short term – cutting costs and deferring spending now to protect short term results.

In the long term the costs are almost always higher as we take action then only when compelled to by a failure or catastrophe – at which point we are forced to pay whatever it costs.

The economics of this approach is summed up in a term called discounting.

We discount the future – on a linear basis for accounting, on an exponential basis for investing and on a hyperbolic basis (possibly) for impulse purchases.

Let’s spend that money on a new telly now because putting that money in a retirement pot is so much less appealing.

Our future self, sat in a retirement home, will appreciate that telly so much more when sat waiting for the weekly visits from our family.

But that’s simply over-dramatic. We could die tomorrow – we should enjoy things while we are still around.

But we probably won’t die tomorrow.

In many parts of the world the chances are that we will live longer than previous generations and, for the first time, we may be poorer than our parents when we grow old.

Future generations will think up new ways and come up with the technological solutions they need, so we should put ourselves first and the earth could be destroyed by a comet at any time.

Except we can be pretty confident that a future will arrive – and if it’s accompanied by climate change on a vast scale – the amount of investment and technology required to deal with it may be beyond the capabilities of those future generations.

Think about it this way – a discount rate of 5% over 500 years results in a number that looks like this: 39,323,261,827.21.

That’s 39 billion, give or take a few 100 million.

A pound we spend now on ourselves, at that rate, would be worth £39 billion to someone 500 years from now.

That perhaps still doesn’t compute…

The point is that the decisions each of us makes now impact the lives of billions of people some time from now.

We need to try and make wise ones.

How to really make change happen


It shouldn’t surprise anyone that what we say and what we do often don’t match up.

For example, this paper exploring the green consciousness of Egyptian customers says that more and more people say they are concerned about the environment and want to contribute to protecting it by buying green products.

In reality, they don’t do this consistently.

Many companies in Europe are going to start doing energy audits over the next couple of years to try and find opportunities to save energy.

A lot of these will result in recommendations that go into a report, which then sits on a shelf because going from what we should do, to doing it is not easy.

When trying to change behaviour we can easily think of all the things we can do to change things.

At home, we could turn lights off to save energy, control the amount of chocolate we eat to lose weight or set the alarm a half hour earlier to get up and go running.

If we rely on willpower, however, then the amount of willpower we have left determines whether we do something or not.

After a tiring day at work and a late night with the kids it takes superhuman effort to get out and go for a run when there is sleet and rain falling out of a dark sky.

So, how can we make a change?

The research talks about the market as the intermediating factor

When we’re trying to do something new, say a new gadget, the worst question we can ask people is whether they would like a gadget like the one we have.

That’s called an ice cream question – because no one says no when you ask them would you like some ice cream?.

A better question to ask is what gadgets have you bought recently?. Maybe they’d love to have the latest things but can’t justify buying them.

Or they’d love to save energy, but consistently leave lights on in at least five rooms in their house in the evening despite spending all their time in just one.

To find a change pathway that people and organisations will adopt, we need to understand how they change now – and that change is best seen in the way they have been spending money so far.

The case for change needs to be made in the same way previous cases were made and approved to have a chance of succeeding.

We have to make it easier for people to get their money to where their mouth is.