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.

Even in the structured, staid, sometimes same-as-it-ever-was field of infrastructure engineering, there seems to be regular occurrences of project start-up frenzy. There is never enough time at the beginning of a project to start it up ‘right’.

Project kick-off is always time-poor; the pressure and rush at project start-up will never change. Therefore, processes and procedures must be versatile and flexible in order to allow quick ramp up. It’s like they say: if you keep doing the same thing, you’ll get the same result each time.

That works in the positive as well. So, utilise repeatable, robust and reliable procedures.

A university or college degree, or any certification, gives a certain level of “confirmed competence” or “assumed abilities”. The qualification is third-party validation around that person’s capabilities.

Someone else – some other institution – has judged the credential-holder to be competent. The other party has determined that the holder is able to do the credentialed kind of thinking or problem-solving. That third-party validation is part of the value of the degree or credential. In some roles or industries, specific credentials are less important. But in the built environment, the opposite is true: a level of competence is assumed and should be expected.

In Susan Cain’s book “Quiet”, the astute observation was made, that the culture of character (serious, disciplined, honourable) has lost out to the culture of personality (bold, entertaining, dominant). The book also addressed the yin/yang of introverts and extroverts, noting that personality is like a rubber band — elastic and changeable, but only to a point.

There was a time, not long ago, that attributes such as citizenship, honour and reputation were recognised and appreciated. Now it is all about being fascinating, stunning, and magnetic.

So, manoeuvring through the expectations and preferences of colleagues, friends and family requires awareness of self.

Back in March, during Australia’s initial lockdown, we were confined to our suburbs and would only leave the house for a few reasons: exercise, work, school, groceries and maybe caretaking. Brisbane has not re-entered lockdown, but our Melbourne friends have.

It was an eerie time, back then. But I also realised today, while out walking, that during that time, we as a neighbourhood went out of our way to say hello to each other. And, ironically, we saw our neighbours more often then, than we do now.

It was an odd positive out of a negative, which we’ve lost again.

To describe yourself or who you are, there are two things that prevail. Picture them as 'facing in', or 'facing out'.

The 'facing out' part is what others see: your title(s), labels, category, discipline or specialty, expert or generalist. These are the answers to "what do you do?” and would also be indicated by what you're "known for".

The other aspect, 'facing in', is what you see in yourself: what characteristics, interests, passions, innate skills, personality, aptitudes and attitudes that make you, you. These are your "known self".

So, together, the 'known for' and 'known self' define who we are.

The need for a business — and / or a person — to manage risk and quality is ever-present. Just about every task, every decision, every activity, has outcomes that are tied to risk, and to quality. A financial or costing decision has risk attached to it; a design calculation or drawing has both risk and quality associated with it.

If we are removed from the consequences of our decisions or actions, the connection to risk and quality are lost as well. To stay connected to risk, quality, and consequences, retain direct and obvious ownership of responsibility for the documents and records.

Uncertainty avoidance is a phenomenon originated by G. Hofstede, describing the level of stress experienced when faced with uncertainty or ambiguity. It was originally developed to apply to cultures or organisations.

In the knowledge workplace, particularly a technical or hazardous one, uncertainty and ambiguity are generally not welcome.

The alternative is to look for the predictable. Being predictable is the antidote to uncertainty. In the hazardous work environment, having standard work processes, which are executed in a disciplined manner, delivers predictable results.

Consistent use of proven best practises delivers good results. And being predictable like that, reduces or eliminates uncertainty.

By the time a new graduate is a year into their first job, particularly in a knowledge industry like engineering, it’s quite likely they have been asked to review several documents, specifications, or design drawings, that were written by or prepared by others.

As that worker advances, there is no slowing down of those requests. The requirement or request to review other people’s writings only increase with experience.

And yet, there is rarely a clear understanding given by the requester, or communicated by the reviewer, about what the expected specific outputs are in this ever-so-common exchange in the knowledge workplace.

"Need more training" seems to be a default answer when a worker finds themselves with a perceived lack of knowledge, or having made a mistake, or not knowing what to do 'next'. While not wrong, a follow up question should then be, “what does it look like when you’re trained?”

Training is isolation does not guarantee change. Training to individuals is a temporary fix but is not always permanent. For training to stick, the trainee should also be obligated to either tell someone else what they’ve learned, or, should prove that they’ve used the knowledge soon after the training session.

As observed by Cal Newport in his book “Deep Work”, three groups will have a particular advantage in the future: those with access to capital; those who can work well and creatively with intelligent machines; and, those who are best at what they do.

So: if you are born into or come into money, or, if you are comfortable with the influx of machines and AI, you will be okay.

Alternatively, and perhaps more satisfying, is to be very good at what you do, and, able to communicate it. Additionally, be able to learn new and complex things very quickly.