Making decisions – especially large or important ones - requires a balance between deliberate and instinctive thinking.

Using an algorithm, or model, or bias can help, and often does; sometimes in the negative. These mental models prevent us from being swamped with too much information.

But expertise contributes as well. The ability to act intelligently and instinctively is possible only after time and experience have honed the skills needed to make decisions. Children who are introduced to making decisions early in life, even as simple as what colour to wear, respond better as decisions get more complex and have more consequences.

Competence, for knowledge work in the built environment, is assessed through pictures and words (outputs), behaviour (interactions with others), and references (stories people tell).

Competency framework assessments typically require a user to declare whether they are ‘competent’, by ranking themselves at some level or some categorisation. This one-liner, “identify your competence level”, is loaded with a lot of unsaid behind-the-scenes work. The ability to define – and defend – a competence level is not something that is normally taught to us.

It's useful to have a reliable, intrinsic and painless way to record your daily growing applicable knowledge, skills and experience.

Does a habit develop into sustainable workflows, or, do we fall into workflow patterns that then become a habit?

Habits can protect us from decision fatigue. Habits help by just being a given, so there’s no decision – like deciding whether to have coffee or tea in the morning.

Habits are also known for providing “freedom in routine”. Performing the same actions in the same context or location or decision point means that there really isn’t a decision, there’s no emotion, it’s automatic and situational.

The brain functions more smoothly when it spots patterns and can respond without too much effort.

The quality management standard ISO 9001, over the years and over revisions, has provided a guidance for businesses to address quality in a systematic way. Originally requiring several specific documents and procedures to be prepared, the 2015 revision takes a step back, requiring that the business determine its important processes, and then determine which of those need documented procedures.

In effect, a successful quality management system is recognisable (authentic), predictable, and repeatable. This is what auditors look for. To demonstrate quality, a business recognises its priorities, and has predictable and repeatable processes.

To be effective, people should do the same.

There is no shortage of quotes and mantras that invoke the phrase ‘work hard’, or ‘hard work will get you there’.

However there doesn’t seem to be a clear definition of what that means, to ‘work hard’. And getting to that state probably varies with people. Someone can produce something and say, “I worked hard on this”, and we tend to take their word for it. Sometimes it shows, sometimes it doesn’t. But still, it’s an amorphous and vague thing to aim for, or plan for. “Try harder” or “Do better” are generalisations, and therefore allow for lack of accountability.

When we claim to be “too busy to fit that in”, it actually means we have higher priorities already scheduled in.

Rather than thinking or saying, “I’m too busy”, it’s more accurate to say or think, “I have other priorities taking precedence”.

It may not feel like it, but we choose how we spend our time. Choices have consequences, meaning other opportunities are missed. Sometimes it means not going out with friends, not meeting a deadline, or not writing that novel. It’s a choice to spend time on “X” instead of “Y”.

And that is okay. Just own that choice.

“Some skills and knowledge can be learned from university courses and other specialised training, but much of what people know (or think they know) about their work comes from experience. Experience provides an important way in which people link actions to likely outcomes, based on past feedback.”

These are not my words; they are from a research report on the impact on public safety of formal and informal design processes. It can also be observed that poor documentation is an underlying issue with many, if not all, built environment project failures. Experience, and effective documentation, are connected in many ways.

Most work can be viewed as a process.

With most work, there are people problems, and there are process problems.

Process problems always cause people problems. On the other hand, people will often set out to defeat processes, especially if those processes have problems.

As work becomes more complex, especially in the knowledge work field, simplifying the process so that it has no problems is a lofty goal. Once that is done, bring in the artificial intelligence. But there will always be problems for people to solve. In these early days, even AI will likely have problems to be solved.

Originally described by Paul Graham many years ago, there are two ways of working: being a maker or a manager.

A manager is dominated by meetings and fitting in short bursts of work in between ad hoc drop-in conversations and email responses.

A maker is dominated by deep work, creative and innovative thinking, and spending long chunks of time on one thing.

The real work – the work that should be valued – is done when making. It’s probably preferable to oscillate between the two approaches. Many won’t have a choice but to be in manager mode almost all of the time.

Accumulated knowledge leads to assumed outcomes, and these assumed outcomes guide our thinking. When using knowledge resulting in the same outcomes, over and over, it’s logical to expect that outcome each time we use that knowledge. However, conversely, assuming an outcome based on little or no accumulated knowledge will possibly be wrong.

Wisdom — or deep knowledge which has the luxury of being able to assume outcomes — is based on a lifetime of learning. It takes time. Trying to leap to wisdom after only a few years of accumulating knowledge may be like skydiving without knowing how to pack a parachute.

Data-driven decision-making is big news, since big data is so ubiquitous and available now. Collecting the right – and useful - data, leads to being able to analyse it for assistance in making decisions.

However, that data usually ends up in documents. Those documents are then used to help make the decisions. So, obviously, those documents should be prepared and presented with a decision, or strategy, in mind. Documents are prepared using the analysed data, in order to present a decision, or to assist in making the decision. Too often, documents present the information without reference to the required outcome. Collecting the right – and useful - data, leads to being able to analyse it for assistance in making decisions.

Currently popular is Marie Kondo and the question ‘does it spark joy’ when clearing out the materialistic items in your home. Similarly, Tim Ferris has a ‘minimal effective dose’, which applies to exercise or supplements. The philosophy is to take, or do, only the minimum amount that produces results, and no more.

There’s another application for a minimalism approach: documents.

Minimal. Effective. Documents.

Start with why, and consider who uses it, and more importantly, what is its lifecycle. Consider the consequences if the document is not used or read thoroughly or seen or adopted. Consider that maybe it isn’t needed.

There is no shortage of information about how language has developed, and how humans have refined and changed it over time. It is undoubtedly a complex and fascinating subject. Considering the complexity of language, it’s a marvel that society gets on as well as it does. With ongoing foibles of course – particularly in the current age of (un)social media.

Definition and interpretation of words is an ongoing challenge, particularly in knowledge work. Having a common understanding goes a long way to making progress, perhaps without realising why. On the other hand, differing interpretations of a word can cause undefined difficulties.

To manage risk, quality, or knowledge, the tendency is to default to nominating a ‘level’.

We talk about the risk level being low or high; the quality is low or high; or knowledge level is low or high.

A better approach may be to describe them as controlled or not: “that risk is controlled with these measures:…” “The quality is maintained through these controls:…”. The knowledge or competency for that person or this business “is managed by these methods:…”.

Measures, controls, methods. Tangible things that are either in place or are not. More meaningful than “the risk level is intermediate”.

Something not often equated, is that risk is an inevitable partner with trust. When perceiving a risk, such as flying in a plane or hiring an expert, the only way to get past it is to trust in something or someone. Therefore, to overcome risk, having trust as part of the equation is fundamental.

Conversely, where there is no risk, we don’t need trust. But almost every transaction involves risk, and therefore almost every transaction requires trust.

Managing risk is sometimes outsourced by having insurance. This model is incomplete – and unsatisfying - because it overlooks that the equation includes trust.

Two approaches to consider:

Intelligent behaviour is behaving, or reacting, or working, in a way that takes responsibility. It is knowing enough to do it well — sometimes following a rule book or recipe — and to the best of your knowledge. It also means knowing when you need to get advice.

Intelligent thought is needed to thoroughly understand something. It’s thinking deeply, applying critical views and going beyond what’s on the page. Using intelligent thought requires more than just following a rule book or recipe.

Apply the known with intelligent behaviour, and, sometimes, explore the unknown, using intelligent and deep thought.

Along with having the right skills and knowledge, being experienced is an important ingredient to competency.

Being experienced is different to having an experience. We can have an experience skydiving, but that doesn’t mean we are experienced at it. Getting experience takes time.

What is important is recognition of everyday experiences, and how they fit with other knowledge and skills, and therefore can be adopted and adapted. Experience isn’t necessarily doing the same thing over and over – although that is an important way to improve skills. Rather, practise acknowledging everyday experiences, which relate to the bigger picture of overall competency.

For knowledge workers in the built environment, documentation is impossible to get away from. In whatever form, be it online or on paper, the need for documentation never goes away. When things go wrong, documentation is one of the first things gathered together.

There’s another view that says there are too many documents.

Too much paperwork, too many checklists and signoffs and, dare we say, too many approval responsibilities out there.

In the built environment, the requirements to comply with so many codes and standards and specifications and contracts, … there’s no doubt about it - it can be overwhelming.

Skills, like playing the piano, develop through practise. Doing something once, even done well that one time, does not mean you are skilled at it.

Demonstrating skill needs some proof or facts, some data or tangible outcomes, and, evidence of more than one example.

It’s hard to measure the value of knowledge worker efforts, especially when “thinking” is the precursor to the “value”. Using the black box analogy: successful business and individuals capture, and more importantly, value what goes on in that black box between input and output.

If thinking is a skill, it requires practise. And it requires time.

In the early 1900s we had scientific management, originated by Taylor and Ford, which analysed workflows for economic efficiency. Then we had Drucker come along in the 1950s, promoting management by objectives, which defines the results that employees are expected to achieve. Those management theories generally assume a ‘black box’ for the worker. There’s an input, and an output, and not much happens in between.

But knowledge workers process information into something more valuable. Knowledge work requires, as Cal Newport puts it, recognition of the internal processes within the black box that performs that messy work of producing the output.