Category: Writing

There is a common failure pattern we’ve seen in organisations trying to become more sustainable.

It goes like this.

1. The leaders are under pressure

to show they are making their firm more sustainable. They set objectives and targets.

1. Teams are assigned to do work.

They carry out research and identify a series of projects.

1. Leaders are also concerned

with financial impact, and set short payback criteria for project approval as prudent financial practice.

1. None of the identified projects

can meet the hurdle rates required and no projects are approved.

This creates a tension between the stated objective of the organisation and the ability for people to actually initiate projects that will allow the company to meet its goals.

The conflict in this situation cannot be resolved technically – solutions that reduce emissions often have a 5+ year payback while companies have a 2-3 year payback requirement.

Instead, we need to question our assumptions – an approach suggested by Goldratt in the theory of constraints (TOC) literature.

If we don’t – the situation will stay the same as it is now, locked into position by opposing forces, until something else happens to break the deadlock, like a crisis, change in leadership or strategic re-evaluation.

What we need to do is relax this tension – identify the sources of conflict and then think our way out of the situation.

How would you go about doing that?

Where are the learning loops in your career story?

If you’ve read Zen and the art of motorcycle maintenance, you’ll remember a section about a hypothetical student who enters a university where they teach but don’t have exams or grades.

The student turns up. Comes to some lectures. Finds partying more interesting. Skips a few. Finds the later material hard. Doesn’t put in the work to catch up.

As there are no exams or grades, there are no consequences. Eventually the student decides it’s not worth the trouble and drops out.

Now the student has to find something else to do. Perhaps a job to make money. Maybe as a mechanic. Finds that’s interesting. Works at it. Gets better. Wants to make some modifications. Realises that he or she doesn’t know enough. Maybe needs to learn more about mechanics and electrical. Joins a college or university.

This time the mindset is different. The student is driven to learn, because he or she really wants to know more about this subject. It’s intrinsic motivation rather than extrinsic recognition.

That’s a learning loop in action. And the interesting thing is that real learning often starts with practice – with taking action in a situation.

I did an MBA after around eight years of working. The theory I learned in the MBA helped explain the previous eight years. Following that, the continuing work and reflection informed my practice after that, which in turn led to more theory work as I tried to understand the previous experience.

I’m wondering how AI will improve these learning loops – and I think it may be at the level of theory.

It’s easier to work with AI to dissect and understand complex theoretical ideas. It can help us make sense of a large body of knowledge and connect and surface insights that it might take us years to do ourselves.

But the practice and reflection – that’s time we have to spend to apply and internalise the theory.

AI’s main promise, as far as I can see, is that it will help us become better learners.

If you’re finding a job hard to do maybe the problem is a failing system.

Does each step flow seamlessly and inevitably into the next one?

I see this all the time with data flows.

Information is messy and fragmented, and we try to fix it with one-off interventions.

But those on-off tasks become repeated obligations and before you know it we’re working on a complicated monster of a system that’s almost certainly wrong.

That’s why I love the “small programs” idea that you get with Unix systems.

Build small tools that do one job well and connect them together to do complicated things.

It’s a philosophy that you see in organisations that have lean approaches – they focus on flow and better communication as a way to do things better.

And if you get this right, it’s as easy as going down a slide.

Wouldn’t it be nice if work were more like that?

It took me a long to learn that success in systems design is about people, not technology.

Every potential engagement starts with a group of people in a situation.

That situation never has a clearly defined problem. Instead, it’s problematic. Concerning. There are issues. Challenges. Uncertainties.

It’s not a box. It’s a fuzzy boundary that isn’t fully understood.

And this is the work of consultancy. To enter the situation and work alongside the people there to see how we can improve the situation.

Success in consulting doesn’t show up just in engagement metrics and KPIs.

It’s whether the people in that situation are happier than they were before.

Getting a project away these days feels like planning a rocket launch.

You know the problem – the Earth is surrounded by a debris field and you have to wait for the next best time to get your rocket through.

Take an energy saving project, for example. When can you do it?

I remember walking around a production line with air leaks everywhere – a simple source of savings.

But the problem was that the money saved was dwarfed by the money lost if production was stopped.

So no projects could be done unless a planned maintenance window came around or if something failed catastrophically.

Planned maintenance is better. And that idea of working to a window make sense for a lot of projects.

The best time to get in a new energy efficient machine is when the current one comes to end of life and it’s time to replace it.

Retrofits are hard to do and people avoid them unless they have to do them.

Figure out when the windows are for you to make a decision – and work backwards from there to get everything else in place for launch.

What value do consultants add to your organisation?

It depends on the kind of work you do and the resources you have in house.

The rule when adding someone external is that if you need something doing but don’t want to put your best people on it.

In that case, work with someone that’s willing to put their best people to work on that problem.

Which then brings us to the types of problems we face.

Some problems have to do with bits and transactions. Information and its use. So you bring in data services consultants.

It gets more difficult when you introduce interactions. It’s about information but also about how people make choices and operate in networks.

That’s where lobbyists, industry experts, networking groups live.

On the top left you have work that deals with atoms – problems of inventory, factory operations and energy usage.

Consulting work there is all about flow, about getting things moving more effectively and efficiently. Reducing costs. Moving product.

And at the top right you’ve got a mix of all these problems, bits, atoms, transaction and interactions.

That’s where it’s about having clarity of purpose – what you do and more importantly, what you don’t do.

Strategic consultants, the ones who’ve been there and done that and have the experience to help you avoid pitfalls operate in that segment.

Now it’s not really a simple 2×2 matrix. it’s more about how the four components: bits; atoms; transactions; and interactions, come together in a business.

Consultancy, at its core, is a helping profession.

The idea is to help clients get things done that they need doing but shouldn’t be doing themselves.

We don’t need to make it any more complicated than that.

If I had to boil my view of the world down to one thing – it’s this quote from Warren Buffett.

“If something’s not worth doing at all, it’s not worth doing well.”

Too many products are optimised to do something that doesn’t need doing at all.

A classic example in our business is extracting data from pdf invoices.

Here’s what happens. A computer somewhere creates a dataset. That dataset is used to produce an invoice. The invoice gets sent to your business. You scan it and put it into a financial system. Along the way, the scan loses quality, the image includes that stamp someone put on it to show when it was received. And you’ve got a few thousand of these to process.

So, you go out and buy a best in class image processor that can use AI to extract numbers from these messy scans.

But why?

Why not just dissolve the problem. Go to your supplier and get the data directly from them in a machine readable format – a csv?

This cuts out all the messy middle data wrangling. The closer you get to the source the easier it is to get what you want.

Now this can be more or less difficult depending on where you are.

But this is where thinking in systems comes in.

The more complex you make something the more expensive it gets and the more likely it is that something will go wrong.

Complexity creates value for a while but after a certain point you start diverting resources from doing your task to managing complexity.

At which point value drops.

The trick, then, when building something is knowing when to stop.

A friend of mine says you should take every call because you never know what you might learn.

As a heads-down engineer this is hard advice to take. Other engineers will know this – we’d much rather build something ourselves than look to anyone else for a solution.

This is not always a good thing.

Taking a leaf out of the asset management industry the thing to figure out is what matters in the short term vs the long term.

For example, it’s well known that the long term operational costs of an asset like a boiler or vehicle are much more than the initial cost of acquiring the asset.

It’s the same with software systems – it’s just instead of buring fuel we burn people’s time.

So as an engineer, there’s a hierarchy – a way to do things to save time, just like you would if you wanted to save fuel.

1. Start with the tools you already have

We build sustainability tools using SharePoint, PowerBI and Python because organisations already have these tools. With AI’s help you can now do pretty impressive things very quickly.

It’s frictionless. No procurement. No legal. Just service.

2. Use tools that have a proven track record

If you need something specialist then it’s time to look at tools that have a proven track record of use.

All too often people buy tools for other people that are never used. There should be a rule that a manager shouldn’t be allowed to buy a new package unless they’re willing to personally spend three months working on it.

See how people have used it before. How it’s saved them time. You need proof.

3. Buy new tools when they add new value

Look at a new product when it genuinely adds value – something new that you couldn’t do before.

Many tools simply reinvent something that’s already available. And research shows that we’re easily overwhelmed – seeing a thousand options makes us less likely to buy any single one.

So, the takeaway is that we should listen to what’s out there – because there is some amazing stuff being built.

But before you buy – ask how this will actually work in the long term and what impact it will have on the fixed amount of time you have to spend.

Thing go wrong when our actions outpace first the numbers, and then the story.

I was reading Morgan Housel’s “Same As Ever” where he explained why we have cycles.

Say an economy is doing well. We have growth and optimism and investment.

Because it’s doing well more and more people pile in, wanting a return on their money.

After a while, there’s more money than the economy can absorb – so you go past the point where the numbers make sense.

A 10x PE becomes a 40X PE, because people believe it’s going to transform itself with some new technology and make huge amounts of money.

The story keeps the market rising.

And then, when you punch past the story horizon all that’s keeping you going is momentum.

And when that flames out, you experience what Icarus did, flying too close to the sun.

Markets. Companies. Political figures. They all go through this cycle. A slow start. Then pushing through horizons. Until they fall back and a new cycle begins.

The winners in a cycle aren’t the one’s that make it big.

They’re the ones that are resilient through the cycles – the ones that are still around when the noisemakers are out.

Warren Buffett stepped down this year from Berkshire Hathaway leaving a legacy that included a collection of curated businesses and some of the finest business writing education you could want.

That’s the kind of journey more of us should aim to take.

How do we keep adding value as we progress in our careers.

In the early days we learn and create value by doing.

I learned more about software development in three months of a student placement at Arm than all the lectures I had sat in previously.

Later, we might step away from the doing and start developing others.

We start thinking about systems that help get things done.

And that’s where the problems start.

If we get lost in the doing, our days turn into firefighting.

If we get lost in the thinking, it looks a lot like navel-gazing.

It’s the combination of thinking and doing that leads to growth and produces value.

It turns out there’s a term for that – Action Research – and it’s been around for 70 years.

This is about taking action and doing research at the same time – together with critical reflection.

Whether you’re trying to work out how to integrate AI into your business, decarbonize your estate, or work out your supply chain issues, Action Research is a way to engage with the problem in a pragmatic way.

Action Research has changed my own practice. Over the last 13 years, every service that I’ve developed has come from conversations with clients and prospects where we’ve co-created a value proposition and figured out how to make it real using Action Research.

Rather than trying to guess what customers wanted it was easier to simply talk to them, understand their situations, and co-create solutions to improve those situations.

It can seem like there’s an increasingly complex world out there – with AI, regulations, politics – all vying for attention and threatening rapid change.

But real change comes from both thinking and doing.

And Action Research is a way to make that happen.