The 80/20 rule: Achieving more with less

It is astonishing: we tend to use just 20% of our possessions 80% of the time. We habitually wear 20% of our clothes 80% of the time. And 80% of our phone and text communications typically are with just 20% of the contacts saved on our phones.

Since this is a blog about minimalism, I feel an article about the 80/20 rule has long been overdue. The 80/20 rule is widely used by minimalists in their decluttering approaches. Many minimalists choose to give away the things that don’t matter (about 80% of what we own), while making space for those that are important (roughly 20%).

The 80/20 rule, or Pareto principle, is named after Italian economist and sociologist Vilfredo Pareto (1848-1923), who discovered that 20% of the pea plants in his garden produced 80% of the healthy peas. Following on from this, he noted that 80% of the land in Italy was owned by just 20% of the population.

The 80/20 rule can be extended to many areas of life and in business. While, of course, those percentages do not always apply exactly, it is true that most things in life and business are not evenly distributed. And a minority often generates a majority!

The 80/20 rule can help us adjust our priorities, declutter our everyday schedules, and stay sane

In what ways might the 80/20 rule be helpful to translators and freelancers in how they go about their work lives and manage their businesses? How could we leverage this principle to our advantage? Here’s some food for thought:


Easy prioritisation of tasks

- If indeed 20% of the tasks we carry out account for 80% of the results, can we pin down what these tasks are? PRIORITISING those tasks accordingly would most likely benefit us in most surprising ways.

- If 80% of results come from just 20% of actions, should we not then expend more energy on, dedicate more attention to, and aim to OPTIMISE these actions?

- If 80% of the value of a work project is achieved with the first 20% of the effort put in, should we not then plan our workdays in such a way that this happens at a time when we know we WORK BEST?


Better customer relationships

- Who are the 20% of customers that, according to the Pareto principle, provide 80% of our revenue? In what ways can we STRENGTHEN RELATIONSHIPS with them? But note also: is it safe to rely on such a ratio of our income, or should we better collaborate more with other customers as well?

- How much time do we spend on HANDLING CRITICISM? If 80% of complaints (especially unjustified complaints) tend to be raised by 20% of our customers, is it actually worth continuing to work for those customers?

- According to the Pareto principle, 80% of a business’s TURNOVER typically is achieved by 20% of its products or activities. I am aware that we sometimes feel we occasionally need a break from the areas we usually translate in. But against this background, perhaps translating too many texts outside our subject areas isn’t advisable.

- Marketing is time-consuming, and thinking about where to start in a campaign is daunting. Here’s an interesting thought, though: 20% of the marketing messages you come up with can produce 80% of the results. What’s more, 20% of the overall marketing effort often brings about 80% of the SUCCESS OF A MARKETING CAMPAIGN.


Eliminate, automate or delegate?

- Which activities can we ELIMINATE or AUTOMATE? Are there activities that don’t move us towards our goals? For instance, it might not be worth spending so much time on updating online profiles if perhaps in our current circumstances we don’t actually need them to be successful in business.

- And are there any tasks that we can DELEGATE? For example, wouldn’t it be better to entrust accounting tasks with an accountant and focus on translations instead? Find a cleaner? Pay for a meal occasionally (or regularly), rather than waste time in the kitchen, when work is piling up on the desk?

- 80% of software users apparently use just 20% of their software’s features. So could we undertake further training to also learn about other features of our software? Learning to use more than the usual 20% of features could make us more EFFICIENT.

Is it really necessary that all business tasks are completed to perfection?

A word on perfection

- No doubt we should strive for PERFECTION in producing our translations, but is it really necessary that other business tasks are also completed to perfection? Should we seek perfection in writing blog posts? Maintain a regular Twitter posting pattern? Zealously reply to every single message that reaches us?

- And lastly, how about deciding for yourself that your order book is full once it’s filled with orders up to 80%? A buffer or some EXTRA TIME that can be handled flexibly can feel like pure luxury.

The 80/20 rule can help us adjust our priorities, declutter our everyday schedules, and stay sane. By taking stock of the time percentages that our work activities take up, we can implement steps to free up space in our schedules and move ever closer to business success!

The 5-step guide to switching into minimalist work mode

This is my easy-to-implement guide to switching into minimalist office work mode for increased productivity, efficiency and job satisfaction:

1) Remove physical clutter.

Physical clutter invariably leads to mental clutter. Studies demonstrate that physical clutter around you tends to pull at your attention and hence impacts your ability to concentrate in a negative way. Therefore, creating a distraction-free environment by removing all physical clutter from your office will greatly boost your concentration.

2) Create a 3-item to-do list every morning.

I’ve already blogged here on the benefits of a minimal to-do list. I recommend it wholeheartedly! Having a 3-item to-do list in place will create amazing momentum that’ll keep you going until you’ve finished the 3 tasks that you’ve made your primary focus of the day.

3) Keep to your own natural rhythm of the day.

Whether it’s the early morning hours or late in the evening, it is vital to understand when your most productive part of the day is. Then make the most of that time! For example, I function best in the mornings, so I set aside mornings for essential work tasks.

It is vital to understand when your most productive part of the day is

4) Gear up for concentration.

I find that in my work as a translator – especially ahead of preparing the very important final version of a translation – I can best tap into the power of concentration if I “gear up” for it. For me, this usually involves taking in some fresh air on the morning school run, sitting down at the kitchen table to enjoy a cup of espresso mindfully, or having a power nap during the day.

5) Block out all distractions.

I love shutting out the outside world completely to create a hushed, tranquil and productive work atmosphere. I then most relish being a “minimalist translator” in that there’s just me and my translation for a while – with Twitter notifications, personal email and everything else far away.

Switching into minimalist work mode will remove many motivational barriers and help you become proactive and productive. Try it out!

Machine translation in human translation workflows

With the cognitive computing age approaching at mind-boggling speed (before humans and technology likely will merge from about 2040), there seems to be a certain urgency in the need to familiarise ourselves with Artificial Intelligence. For translators this involves thinking about how (and whether!) to integrate machine translation into their workflows.

Post-editing a translation is not the same as revising it!

On 24 January 2018 an event on the use of machine translation in professional contexts was held at Clifton Hill House in Bristol. It had been organised by the University of Bristol in partnership with Universidad Pablo de Olavide in Seville and the ITI Western Regional Group (WRG), attracting academics, professional translators, translation companies and technology providers.

My main takeaways from the event:

The job of post-editor is a relatively new profession. Post-editing nowadays is either offered as a service in its own right or just used as a tool that is incorporated into the translation process.

Post-editing has been defined in the ISO 18587 standard. Yet, although it’s been defined and hence should be clear-cut, in practice it’s more complicated since clients tend to have different requirements.

Final questions, from @lnunesvieira:
1) Are more MT-friendly pricing mechanisms needed?
2) Do we need to train translators differently for post-editing?
3) What about the 'human side' of quality?
4) How to ensure positive use of activity tracking?#MTBristol

— Bristol MA Trans (@BristolMATrans) 24. Januar 2018

Machine translations often are over-edited, rather than under-edited. It is therefore important to note that post-editing a translation is not the same as revising it! They are two different skills.

Ideally, MT should be regarded as an additional tool, or translation memory, or source of reference, which for certain projects (!) can help improve efficiency and productivity.

A useful reminder from Rosario of @tatutrad: you can have good work that's cheap; cheap work that's fast; fast work that's good; but you can't have fast, cheap and good. You have to pick two!#MTBristol pic.twitter.com/BvifeHQI03

— Carol O'Sullivan (@carol_osullivan) January 24, 2018

There will inevitably need to be a move from word count-based pricing to time-based pricing for projects involving the post-editing of machine translations.

There has been a notable shift in the perception towards MT among translators because it’s becoming more capable of producing results that are usable. However, feelings of uneasiness, or strong dislike, towards MT continue to persist.


News headlines about advances in machine translation have led to inflated expectations by clients of what such tools can do. It’s worth bearing in mind we’re still very far from the point where machines can take over from us!

The upside of such news headlines, on the other hand, is they’ve drawn attention to professional translation and interpreting, an industry which had previously often been overlooked.

DeepL: Tool or threat for translators?

The end of August saw the launch of DeepL, a new machine translation tool developed by Cologne-based start-up DeepL GmbH (formerly Linguee GmbH). It was born from Linguee, a translation tool that has been around for some years and is a popular resource amongst us translators.

DeepL apparently performs better than any of its rivals’ products because it’s based on the relatively new Neural Machine Translation (NMT) approach, in which the processing of data is modelled on thought processes as they occur in the human brain. Its makers also claim to have created one of the world’s most powerful supercomputers, conveniently located in Iceland (where electricity costs are lower than elsewhere).

Neural Machine Translation (NMT) is modelled on thought processes in the human brain

Curious about these latest developments in machine translation (MT), I incorporated DeepL into my own work last week so I could familiarise myself with it. Since I’d heard it supposedly is excellent at what it does, I started off my experiment with a bit of a feeling of dread in my stomach. I was soon relieved, though, when I realised it’s basically yet just another tool. However, unlike many of its predecessors, it produces some output that is actually usable!

Having said that, I also encountered severe (in some text types potentially even dangerous!) issues in the DeepL MT output. They may seem minor or insignificant if you don’t work with language professionally; yet in translation for the commercial world they do matter. They do, in fact, matter very much!

I’m going to list a handful of these issues from the patent I was translating assisted by DeepL. (Note that for this article I’ve deliberately picked just shorter sentences or terms from shorter sentences, as DeepL couldn’t cope with longer sentences or shorter sentences with more convoluted syntax.)

“In one embodiment, the guide tube 106 includes an opening 105 on a first end which receives the medications.”
Although I was supplied with a sentence in perfect German grammar, so at first sight there seemed nothing wrong with it, DeepL had incorrectly assumed that the relative pronoun refers back to “a first end”, whereas its actual antecedent is “an opening”.

“treatment of the surface of the guide tube 106 that comes in contact with the pill”
Here we have the same issue as above: The antecedent of the relative pronoun “that” in this particular context is “surface”, i.e. not “guide tube”, because the surface comes into contact with the pill. How can a computer decide what the antecedent of a relative pronoun is? It can’t.

“The shape of the guide tube 106, the orientation of the guide tube 106 to the force of gravity or other source of force, and the coefficients of friction and drag can be specifically designed to orient the axis of each pill in the direction of travel or with the axis of the tube 106.”
“direction of travel” was nonsensically translated by DeepL as “Fahrtrichtung”, which would, of course, be the correct term in automotive contexts, whereas here it simply means the pill is moving in a particular direction.

“ridges”
Translated by DeepL as “Rillen”. Further down in the text, though, and especially when I looked at the technical drawings, it became clear that “Erhöhungen” or a synonymous term is more appropriate because the ridges on the internal (i.e. not the external) surface are described.

“low-distortion transparent material”
Translated by DeepL as “verzerrungsarmes transparentes Material”, which does not make sense here since “low-distortion” in this particular context simply means the material in question isn’t prone to becoming deformed. (Also, DeepL omitted the important comma between the two adjectives in German.)

“cameras with fast shutters”
Translated by DeepL as “Kameras mit schnellen Shuttern”; however, people working in this field tend to call them “Ultrakurzzeitkameras”.

“System 700 includes an image analyzer 704 and includes or has access to an image database 706.”
Translated by DeepL as “Das System 700 verfügt über einen Bildanalysator 704 und eine Bilddatenbank 706”. Although the sentence is correct grammatically and sort of conveys the meaning, leaving out parts of a sentence is a no-go, especially in patent translation.

“In one embodiment, the light sources are continuous.”
Translated by DeepL as “In einer Ausführungsform sind die Lichtquellen durchgehend”. The grammar is impeccable, yet the sentence sounds odd. A human translator would likely opt for a more technically sounding translation such as “In einer Ausführungsform sind die Lichtquellen Dauerlichtquellen.”

“optics”
Translated by DeepL by “Optiken” in the plural. Difficult for a computer to get right, but Germans tend to use the term in the singular here to refer to an assembly of optical elements.

“electrophoresis (e.g., capillary)”
Translated by DeepL as “Elektrophorese (z. B. Kapillare)”. A human translator would likely elaborate a bit and render the whole phrase as “Elektrophorese (z. B. Kapillarelektrophorese)” as otherwise it all somehow doesn’t fit together.

“limit the invention to the precise forms disclosed”
“forms” was translated by DeepL literally as “Formen”. In this particular sentence, however, its meaning in the patent is “embodiments” or “forms of embodiment”, so it really should have been output as “Ausführungsformen” (or “Ausführungen”, which is even more common in patents originally drafted in German).

Following my experiment, I can confirm DeepL is indeed more precise and nuanced than any of the other machine translations that I’ve previously seen floating around the internet. So should we translators see DeepL as a threat? Will it disrupt the translation industry? I don’t believe it will. Machine translation is becoming more and more widespread, but: I am convinced human input will always be required for many text types.

For any change that looks potentially disruptive, there is both threat and opportunity. It’s ultimately all about how we respond to such changes! It’s also worth remembering there is a shortage of translators (read: good translators) across the board, while translation volumes are increasing year by year. So there is no other way than additionally employing machine translation for all the easier-to-handle-texts that require to be translated.

Machine translation or MT (also often referred to as instant, automated or automatic translation) was pioneered in the 1950s, and although this has taken a very long time, machines are gradually becoming better at translating. We have to acknowledge they are now no longer producing the hopeless gibberish of the early days of MT.

I have until recently been sceptical about the viability of post-editing machine translations as a new field of work in professional translation, simply because the MT output has typically been poor. But following these latest developments, I wonder if it is now worth exploring a bit more? Although DeepL hasn’t set out its vision yet, I wouldn’t mind if DeepL was made available for professionals at some stage – perhaps as a plug-in in the CAT software that we use?


If computers are indeed becoming more and more capable of taking over the boring bits of our work, then this can only be a welcome move forward. For it’ll mean we will at last be able to concentrate and spend more time on the bits in our texts that are actually interesting, that are blissfully complex and therefore worth getting our teeth into!

The minimal to-do list

Does your daily to-do list sometimes become overly long? Do you rely on your to-do list, but want to focus more on what matters most? Do you wonder how best to combat procrastination? Then it might be time to adopt this bafflingly simple tool which I’ve come across on Joshua Becker’s blog: the 3-Item To-Do List!

Every morning Joshua Becker identifies the 3 most important tasks of the day and makes these his primary focus. The 3-Item To-Do List has increased his productivity and job satisfaction significantly. What’s more, it provides him with a sense of accomplishment at the end of each and every day.

A minimal to-do list helps increase productivity and job satisfaction

I love the idea of incorporating minimalism in to-do lists and have implemented it into my everyday life, too. My minimal to-do list, for example, may consist of these 3 items: 1) put the finishing touches on a translation project and deliver it; 2) bring my accounts up to date; and 3) sit down for a German grammar lesson with my children after school.

I will probably get quite a few additional things done that day, too, such as starting a new work project, doing some housework, drafting a new blog post, and more. But if I don’t, it doesn’t really matter as these additional things weren’t among my 3 priorities for the day anyway.

The logic behind the 3-Item To-Do List concept is simple: If I have completed my 3 tasks, my day has been productive. It’s a concept that can be applied by anybody, in whatever circumstances. Focusing on 3 priorities per day, and optionally fitting in other things as well, means you no longer feel overwhelmed by interminable to-do lists.

Why not give it a shot, too?



(I've translated this blog article into German and published the German translation here.)