Why goals and control are not enough for business and society


We have been conditioned for a long time to think that setting goals is the way to achieve success.

This may partly be due to the work of Herbert A. Simon, a Nobel prize winning economist who pioneered work in goal-seeking, which spawned fields such as artificial intelligence, decision science and complex systems.

This kind of thinking leads to the unquestioned assumption that the way to make something better is to throw technology at it – a very common theme at present in the energy world.

We think energy markets aren’t working, so the way to make them work is to implement blockchain, AI, machine learning, comparison engines and other types of solutions – which will magically transform it into a clean, lean machine.

Except it doesn’t work that way.

A countering approach comes from the work of Geoffrey Vickers who came up with the notion of appreciative systems.

He argued that ways in which we often thought about the world were inadequate.

The goal-seeking method leads to a narrow reductionist view.

An alternative – the cybernetic view, where there are controllers and actors and one controls the other doesn’t really exist in reality.

Take for example a prison guard and a prisoner. While one is behind bars – both are in prison – and we know how the environment can quickly turn good people bad.

Vicker’s approach is one where life is experienced as a flux of events and ideas – brought out in the picture above from Checkland.

Imagine a loud, raucous party. You arrive, having been invited. You meet a few people, get to know more. Over time, you make friends, have conversations, even throw your own mini-parties in a corner of the room. Then you leave – but the party carries on.

That’s pretty much how life works.

Appreciating the world, or life, then means perceiving it in the first place and making judgements about the things we see.

Those judgements are usually about fact – what we believe is – and value – or what is good.

Given our perceptions and judgement, we can envision what might be and take action.

And we do all this not to meet goals, as a rationalist approach might assume, but to maintain relationships – our place and friendships at the party, if you will.

All this activity results in standards – our expectations of fact and value.

What needs to be seen is that our previous experience results in standards which are then modified in the light of future experience.

At a very basic level, this is what happens when companies become more diverse – the introduction of new thoughts and approaches from a greater range of individuals can change our standards.

A few years ago, no one would have questioned mostly male panels. Now it would be a brave organiser that didn’t have any women up at all.

Why does thinking about any of this matter?

It’s easy to be cowed by what seems like the unstoppable march of technological progress – the bots are going to take our jobs and there will be nothing left for humans to do.

Except to be human – appreciate life as it is and aim for better standards and relationships in business and society.

What does it mean when an organisation has a social purpose?


Organisations are changing and the boundaries between them are getting blurry.

Once upon a time it was simple. The government did some things. Profit driven companies did other things. And non-profits picked up the pieces.

The regulatory structures in many countries grew up to support organisations that fell into one of these three categories.

But, that’s not enough for people any more – they want to work with organisations that do more than just make money – that have a social purpose.

But what does that mean exactly?

In this BCG article, Cathy Carlisi and Dolly Meese from Brighthouse define purpose as the why of an organisation, resulting from the intersection of two questions:

  • Who are we?
  • What need do we meet in society?

Does this become a social purpose if we just add the word social to it?

Not according to the Advertising Standards Agency, which ruled that A4E, now known as People Plus, could not describe itself as a social purpose company because its activities made a profit but people could mistake it for a non-profit.

So, while leaders in organisations are trying to make their businesses about more than just money, the system of regulation and oversight is trying to understand what this means and how it should respond.

In the U.S, the concept of a for-benefit organisation is being mooted, one that makes a profit and acts like a normal business, but whose primary purpose is provide social benefits.

The normal way to get this message across is through marketing – by structuring branding and messaging around concepts like “social enterprise” and “sustainable business” according to this article in the Harvard Business Review.

But, the article argues, it can also be achieved through organisational architecture – by creating a set of rules and operating principles that go beyond profit and involve suppliers and customers in decision making and even profit sharing.

A report by the Mission Alignment Working Group of the G8 looked at a new form of organisation called profit-with-purpose businesses – a type of organisation that has the freedom to distribute profits like a traditional business but also commits to prioritise, deliver and report on their social impact.

They also propose a way for these organisations to become formally recognised in law – with a definition, legal framework and operating model.

So… it’s not that easy to understand social purpose – the words make sense, but what does it really mean when an organisation starts to focus on the impact it is making rather than the profit it is taking?

The starting point is getting the internal and external narrative right – the story we tell ourselves and others.

And we can start by answering a few fundamental questions.

Who are we, what need do we meet and why do we exist?

How to take your company digital


Amazon is ruining things for many businesses – teaching customers that they can expect to get products and services quickly, have a great user experience, no errors, 24-7 availability and personalised interfaces – and save money and time.

What about everyone else? How should they think about transforming their organisations to stay competitive?

Tunde Olanrewaju and Kate Smaje from McKinsey set out seven traits in this article that they have discovered effective digital enterprises share – and that we can use as a blueprint for our own programmes.

Going digital is less evolution and more reinvention.

We need to set unreasonable goals, make choices about targets and strategies that make people around us nervous about the scope and extent to which things will change.

Someone, somewhere is working on an idea that will make our existing business obsolete, our products expensive or redundant and that will satisfy our customers more.

We need to work on destroying and rebuilding our business before they do.

And the skills we have in the organisation now are not the ones that will take us there.

We need to recruit for skills, not experience.

The capability that built our organisation is unlikely to be the same capability needed to build a new digitized one.

The kinds of people needed – developers, user experience designers, system architects – are likely to be in other fields and need to be recruited.

Most organisations will be better off in the long term with in-house capability because a digital transformation is a core strategic initiative.

Then, talent needs to be protected, perhaps in a Skunk Works.

Lockheed Martin’s Advanced Development Programs are referred to as the Skunk Works, a group given a high degree of autonomy and freed from bureaucracy, and told to get on with new projects.

It’s very hard to stick talent in the middle of an existing organisational structure and expect them to innovate.

The resistance from people used to business as usual is too much, and can slow everything down.

Nothing is sacred – challenge everything

When going through a transformation, every aspect of the business and how it works needs to be questioned.

Do certain processes have to be carried out? Are there things we can stop doing?

A formal way to this is a method called Final Cause Analysis (FCA).

We ask what is this for? over and over again – and focus on the essential elements we discover as a result.

We haven’t got a year – we need to move fast.

These days no one has 12-24 months to put a new system in place.

We’re talking weeks and months to getting working systems that we can test and refine based on customer feedback.

Lean and agile ways of working are taken for granted now.

There are more projects than we can do, so we need to prioritise based on value – follow the money

Our projects will help us increase revenue.

At the same time, and as importantly, they can help us cut costs.

We need to rank our projects based on contribution to the bottom line and then commit to a programme – putting money, resources and management in to get things done.

All of this effort and reinvention is focused on one thing – the customer.

Customers leave because they are unhappy – so successful digital organisations are obsessed with the customer and their experience (in a healthy way).

Digitization is not a choice – it’s just what we now have to do to stay in business.

Can a bot help us predict financial performance?


We are bombarded with information every day and don’t have enough capacity to process and analyse it all.

One way we try and simplify is to look at the numbers.

For example, we look at figures and statistics over time – the performance of markets, the change in interest rates, the purchasing managers index and year-on-year comparisons.

Numbers are easier to process, chart and analyse, so we focus on them – but are they telling us the full story?

Are we missing out on what the associated text is saying?

Numbers rarely exist in isolation. They are often accompanied by analysis and commentary in the form of text.

Take annual reports, for example.

New investors look at company annual reports as an accurate and faithful rendering of a company’s performance.

Seasoned investors know that an annual report is the starting point.

It says what the company officers want to say.

The real messages are buried in the text and the numbers have been “managed” to meet expectations.

Is it possible to automate text processing?

This paper by BangRae Lee, Jun-Hwan Park, Leenam Kwon, Young-Ho Moon, YoungHo Shin, GyuSeok Kim, and Han-joon Kim analyses the relationship between business text patterns and financial performance in corporate data.

Specifically, they use annual reports of US listed companies in 10-K format that report on financial performance, the state of the business, competitiveness and the risks the companies face in their industry.

These reports talk about the past. What can text analysis tell us about the future?

Text mining is a way to process and extract insights from text

Text mining techniques process text and analyse it using descriptive statistics, clustering and sentiment analysis.

For example, the length of text in company annual reports can be expressed in terms of the number of sentences, the number of words and the number of words per sentence.

Clustering involves grouping companies that have similar statistics and then comparing their performance.

For example, we could use their average compound annual growth rate (CAGR) and compare that with another set of companies.

Finally, sentiment analysis looks at how positive, negative or neutral the text is – a way of measuring the subjective content and tone of text.

Does it work?

It’s still early days for this kind of technology but some interesting things are pointed out in the paper.

Companies with good performance talk about products, services, users and business, while those with poor performance talk about the government, contracts, results and the future.

It’s possible that companies that do well write more – longer sentences and more words about how they are doing.

Finally – and an interesting result – the tone of the text has no relationship with sales performance.

The takeaway is – don’t get sucked in if the company officers predict good times ahead, or if they are pessimistic about things.

That says more about them than the company.

It’s possible that text mining techniques will help us make better forecasts as we continue to use and refine them.

Key principles for smart appliance standards


The appliances in our houses – washing machines, fridges and air conditioners – have a key role to play in the transition to a low-carbon economy.

Electric vehicles and electrification of heat could increase peak demand from 60-70 GW now by 18 GW by 2020.

That will need around 6 new nuclear reactors the size of Hinkley Point C and a huge investment in additional network reinforcement.

Smart appliances that can change when they use electricity could reduce that additional demand from 18 GW to only 6 GW, according to a government consultation on smart appliances that runs from March to June 2018.

The consultation is looking at defining standards – the principles and associated functionalities required for smart appliances – to give industry something to aim for.

A smart appliance is, according to the policy, a product which:

  1. Has communications: It can connect to a network and communicate
  2. Is flexible: It can change how it uses electricity based on a signal like price (automatic, responsive modulation)

The standards will not apply to all products – only the ones with the most potential for flexibility. In particular, lighting and cooking are not included.

The kinds of products that could be smart are:

  • Cold appliances: fridges, freezers
  • Wet appliances: Washing machines, dryers, dishwashers
  • Heating: Electric heaters, controls, heat pumps, air conditioners
  • Battery storage: Standalone or combined storage like PV-Solar systems

The standards for smart appliances look at five key areas.

It’s important that people can choose brands of product without having issues with how their machines talk to each other.

Open standards that promote interoperability help with this – and using a common data model that has a standard instruction set is a preferred approach in the policy for communications between machines and between machines and their controllers.

The point about smart appliances is that they help with grid stability, for example by shifting when they are on away from times when there is lots of stress on the grid.

Clearly, they can also do the opposite: add load to the grid if misused and put more stress on the grid – potentially leading to faults and blackouts.

So, cyber security is an essential part of all internet connected devices these days to make sure this doesn’t happen.

A secure by design approach is a recommended one.

The appliances will create and store data so data privacy requirements will be in the standards.

Finally, when it comes to consumer protection, the standards will cover product safety and end-of-life process – and these will cover how the physical product is recycled and how the data on the system is handled.

Products that comply with the standard will have a label, and the standards will also be aligned with what is happening internationally.

A smart energy system could save taxpayers £17-40 billion to 2050, so many people will be watching this space with interest over the coming years.

Why I sold my crypto holdings


Like many other people, crypto currencies weren’t really something I looked at seriously until the staggering rise in their valuations in 2017.

In December and January, the price of Ethereum went from under $500 to over $1,250, more than doubling in two months.

The entire world got very excited.

Everyone seemed to be looking at these currencies and talking about buying it.

Was crypto something I should get into as well?

Buying a crypto currency is not like buying a stock or an index fund.

With a stock, we are taking an ownership stake in a company, with underlying cash flows and the possibility of growth and more income over time.

As an owner, we share in the growth (or not) of the business – and it makes sense to buy good businesses and hold them over time.

An index fund that covers a market is taking a position that an entire economy will grow and we will share in that.

For example, a S&P tracker will simply follow the performance of the largest companies, and they will probably be worth more in 20 years than now.

Cryptos are a pure trading play

Currencies don’t work like that – they have no intrinsic value.

They are worth what someone else is willing to pay for them in another currency.

That means we need to understand how buyers and sellers in that market work.

I needed a trading method

In many situations, we only need to be good at the buy side.

We’re going to buy and hold for the long term – and as an investment method that works quite well for things like buying stocks or making decisions on commodities like electricity and gas that we actually need for our homes and businesses.

In trading, however, we need to be good at the sell side as well.

More than good actually.

Lets say that we are 70% right at picking when to buy. That seems good, right?

If we are also 70% right at picking when to sell, then for any trade that involves a buy and sell, our probability of success is 0.7 x 0.7 = 49%.

That means we have a less than 50% chance of being right over time on both elements.

That’s where a system comes in, so my first step was to code one up to use for crypto currencies and I decided to apply point and figure charting (P&F).

A P&F system is designed for long term traders that want to understand how buyers and sellers are operating and make decisions on taking positions in that market.

The picture above is a snapshot of my P&F chart for Ethereum.

A position with actual money makes it more real

It’s easy to talk about what we would do, but to really get a feel for how we will act in a trading situation, it’s necessary to put down real money.

After the fall in value in February 2018, I entered the market with a very small position on the first reversal – marked as BUY on the chart.

I bought at around $725, and set a stop-loss at $650 – the red line.

The price went up a bit, down a bit, up a bit and then started to come off consistently during late February and into March.

When it crashed through my stop – I sold.

There isn’t much point having a trading system if you don’t stick to it

The point is that my sell wasn’t due to market conditions or timing or emotional decision making.

At the time I bought, I had a sell in mind, both for the upside and the downside.

This was a trading play, not an investment one – so when it went against me, the only rational thing to do was cut my losses and stop playing.

The next thing to answer is – when should I enter the market again and have another go?

How to create an online marketplace


Markets connect buyers and sellers, bringing them together to carry out mutually beneficial transactions.

Village and town markets are still popular because they give people a chance to come and browse the goods on offer, compare between different sellers and choose something they like.

Usually, there is enough business for everyone – but the markets themselves are operated and regulated by something like the town council.

Online marketplaces take the same idea and create a platform to do this instead – and there is a rush to create new platforms at the moment.

We see marketplace systems to make transactions easier in everything from selling houses to paintings, from comparing energy suppliers to recruiting freelancers in a gig economy.

An article in the Harvard Business Review by Andrei Hagiu and Simon Rothman sets out some of the key things to look out for when creating an online marketplace.

The point out that the network effect – where reaching a critical mass of users that then results in exponential growth – is not enough.

What is more important in getting a market working is that it gets the buyer-seller fit right.

The platform will only work when both sides are happy.

This means that transactions need to be mutually beneficial. Both sides need to be happy with what they get.

But, the parties don’t know each other – it’s the marketplace that brings them together.

So, the market needs to create a safe, trusted environment – by providing contracts, guarantees and insurance.

The point of a market is to help people easily compare goods and services – reducing the search costs of finding information, reducing the friction involved in negotiating a transaction and lowering the total cost of doing a deal.

This is the equivalent of a well-lit showroom, where we can walk around and compare things and see the good and bad points.

Doing these basics correctly will mean that it is more likely that buyers and sellers will enter into deals and come back to do more of them.

Having lots of buyers and sellers then creates a liquid market, one that becomes self sustaining and is used repeatedly.

That’s the point where the marketplace has staying power and is likely to be around for a while, and the marketplace operator earns a good commission on providing it as a service.

The final point raised in the article is that marketplaces need to contribute to society.

They are centres of commerce online, and so the tax collectors and regulators are interested in them.

They want to get their share of the profits and make sure people’s rights are protected.

Marketplaces are the future of business – when we walk down high streets in towns now they are often a dismal collection of charity shops, pound stores and cash advance places.

Business is moving online to new marketplaces.

And, some of us will create some of them.

How could microgrid and peer-to-peer energy networks work?


Why is the energy business so heavily controlled and regulated?

Mostly, its history.

When you have a few large generators and millions of consumers, its big business – and that leads to operators trying to control markets which triggers political oversight, which inevitably leads to questions of control.

So what we have across the world is a system of generation, transmission and distribution over a grid system that connects where energy is made and where it is used, and a parallel system of metering and accounting to bill users.

Microgrids and peer-to-peer systems want to change that

Imagine a new housing development where the developers have decided to create a private network of electricity wires that connect the homes instead of using the cables and equipment provided by the grid.

There may be a few connections to the main grid, but the rest of the properties are effectively off-grid.

At the same time, each house has solar panels for electricity and hot water, excellent insulation, low running requirements and perhaps a micro-chp unit and battery storage.

The independent network forms a microgrid.

The existence of housing units with the ability to generate electricity and heat from a variety of sources and a population that uses energy creates a network of peers – equal participants.

The concept of peer is sometimes forgotten – the households of the future will be both producers and users of energy – so called prosumers.

What they need to work are markets

In a microgrid peer-to-peer system, there will need to be some way of keeping everybody happy – and that is done by a price system and a market.

If people are free to set prices (or the trading is automated and the machines trade among themselves) then the market will result in a price that matches supply and demand.

It avoids the cost of routing energy through the grid, so it should be cheaper.

Experiments like the Brooklyn microgrid set up by LO3 Energy are showing how this could be done.

A peer-to-peer network does not have to be part of a microgrid

We could have renewable generators, like a solar farm, connected to the grid that want to directly sell all their output to a user connected somewhere else on the grid.

They can currently enter into a bilateral contract that is settled and billed by a supplier.

A true peer-to-peer system could eliminate the need for a supplier, and simply have a separate contract – based for example on a contract for differences model – although these are still complex to create and agree on a one-to-one basis.

A start in this direction is Open Utility’s Piclo platform that matches users with local generators.

We are still in the early stages of a transition

We’re a long way away from having solar PV on every roof and local networks of users have yet to spring up.

Will there be a revolutionary peer-to-peer change, or is it likely that the majority of the system will still be controlled by a few producers.

If history is anything to go by – network effects and scale matter.

We may have lots of committed, small players, but Google style companies for energy will still probably emerge – a few highly connected hub players that aggregate and influence how everything else works.

We still operate in a winner-takes-all ecosystem, and peer-to-peer is a small part of it.

Will it be different this time?

What is emergence and how can we make it happen?


We’ve all seen a flock of birds wheeling and swooping as if it were a single, giant organism.

The same thing happens with shoals of fish, or even people trying to leave a train station at rush hour.

Why and how does this happen, and what does it mean for us?

The term emergence is used to describe complex phenomena or behaviour that emerges from the interaction of simpler elements – often in a way that can’t be predicted from the features of the simpler element.

We can simulate flocking behaviour by setting up a system that follows three rules:

  1. Don’t crowd neighbours
  2. Move in the average direction of where neighbours are moving
  3. Move in the average direction of where neighbours are

These three rules result in a swarm – see here for example.

In organisations, emergence can happen in two ways.

In a hierarchy, the rules are set by those in charge.

People are given jobs, roles and responsibilities. In most organisations now, they have latitude and discretion in how they do their roles but have rules to follow.

Take the flocking rules, for example, and recast them for a job role. This might say:

  1. Avoid doing the same work as someone else – create your own niche.
  2. Try and make sure what you do is aligned with the vision and mission of the organisation.
  3. Do work that feeds into and works with what others in the organisation are doing.

If company had a number of people who organised their work in line with these rules it’s very likely that they will do some very interesting things.

It’s that balance between individuals and the collective that creates the conditions for innovation and creativity to emerge.

It’s also why micromanagement doesn’t work.

We need freedom and control – too much of either results in very simple or chaotic behaviour, neither of which are useful.

The second way in which emergence happens is through markets

Take Ebay, for example.

By creating a platform where people can exchange things, they created a thriving ecosystem of buyers and sellers.

Products from bicycles to floor mats flow through the system, in bursts of transactions that spill out into the real world – triggering a flow of packages in white vans that then creates emergent behaviour in the flow of traffic.

On a macro-level, the most successful economies are those that let markets form – allowing people to freely exchange goods and services.

We are surrounded by emergence – and what it reminds us is that we cannot control everything.

The best stuff happens when find the space between simplicity and chaos.

Do you have the skills needed for modern work?


Hedge funds could look very different in a few years.

The Financial Times published an article about the rise of DIY algorithmic traders – people who develop automated investment strategies.

These people don’t work for hedge funds or banks on Wall Street.

Instead, they are mathematicians, progammers, physicists and data experts who are using their skills and cheap, powerful computers to tackel investing.

And this is happening everywhere we look.

Online sales are hyper-competitive, and the companies with an algorithmic edge can squeeze out more profits from their platforms.

Recommendation engines are key to keeping users interested, as algorithms work out personalised offers.

The energy business is fuelled by data – from meters recording generation output to those working out who has consumed it and what their bill should be.

In a world of abundant, cheap money, projects have to work on razor thin margins.

Getting the numbers wrong, over time, will mean that the project makes negative returns.

So, who is going to succeed in this new world?

Drew Conway came up with the Data Science Venn Diagram to explore the key skills needed in the world of Data Science – the field that will most likely underpin modern work.

In adapted form, the key is having three sets of skills.

Hacking skills are an entry requirement – being able to deal with and clean text and numeric data is part of every project.

Excel won’t hack it anymore – we’re going to have to use better tools to deal with more and messier data.

Then we need some maths and stats knowledge.

Knowing how to draw and interpret charts and understand the relationships between sets of numbers makes the difference between guessing and having a theory.

And a scientific approach is based on having hypotheses and running experiments.

Finally – many people think they can simply waltz into a new field and take it over.

Domain knowledge often makes the difference between success and failure in a field – it’s very hard for someone to build a tool to solve a problem that they have never experienced themselves.

That’s why we get lots of tools that look pretty, but end up doing little.

Curious people with good tools are what we need for modern work.