Your people can have super powers

You select employees for their skills, competencies and attitude. You train them to function at maximum efficiency. What if they had super powers that enabled them to do even more?

That’s the promise of well-engineered, well-designed automation working in partnership with humans.

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Help them make better decisions and instantly improve processes through better data.

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Improve employee job satisfaction by offloading boring and repetitive tasks.

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Give them increased bandwidth so they can accomplish more.

This automation can be likened to giving everyone a ‘mini assistant’, constantly available at all times across web, mobile, desktop, messaging – in fact, any platform you can think of. We call this mini assistant Nibo. People in a range of organizations are already benefitting from working with Nibo. And the journey’s just beginning.

an opportunity, not a threat

Some make the mistake of thinking new automation technology does away with the need for people.

Buzz Aldrin used a slide rule to make last-minute calculations before Apollo 11 landed on the moon. Within a few short years such old ways of working had been replaced. Yet the pocket calculator never caused mass unemployment among engineers, architects and mathematicians.


Automation improves working conditions and creates employment

Automation just replaces a set of tasks. And that doesn’t mean replacing a job. Today we have layers of automation on top of each other and yet, even with a growing population, more people are employed now than any time in history.

Ever since the Luddites attempted to smash early machines, many people – and the media – have been nervous about automation decreasing employment. This worry was stoked with each successive wave of innovation.

 Yet over the long term, statistics show working conditions and employment rates improving in line with increased automation. Despite a near five-fold increase in global population rates since 1900:

We’ve reduced the hours people work.

We’ve reduced the hours people work.

We allow people to retire earlier, younger.

We allow people to retire earlier, younger.

And we don’t use children in the workforce.

And we don’t use children in the workforce.

We are at a near-historic low in unemployment.

We are at a near-historic low in unemployment.

Automation makes us more
productive and better off

Since 1973, technological advances have made workers more productive and better compensated for their efforts. One study by the US Dept of Labor’s Bureau of Labor Statistics suggests productivity increased by over 100% over the years to 2014, while pay increased by over 80 percent in the same period – even after adjusting for inflation.

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Short history of automation and computing

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Automation is about enabling us to do more.

  1. We built human-operated machines to multiply our strength (such as cranes, tractors, or factory robots), and we designed ways for them to work in a specific order, creating mass production lines that produce more goods, faster and cheaper.

  2. Producing a lot, quickly, means that small errors become very wasteful.

  3. So we invented processes like Lean to carefully monitor quality, putting more emphasis on human judgement in the assembly line.

  4. We built computers to stop us making calculation mistakes (we still have logic mistakes today, but we like to call these ‘bugs’). And then we equipped billions of individual humans all over the planet with one or more computers, generating data that reveals complex patterns that we’re not capable of deriving via intuition.

  5. We’re now using data even more to solve problems, attempting to reduce our human biases, and to become even more efficient and more inclusive. Compare this situation with how our day-to-day activities would have been carried out 100 years ago.


Insights from some Nibo colleagues

How can we make automation easier to use and more helpful for the user?

How can we make sure users don’t fear automation?

As a software development company, we believe we’re on the safer side of ‘automation hysteria’, but we truly believe there’s a lot of misunderstanding about how automation and computers are changing the workplace and the jobs. If there are areas of concern, there is better literature available on the topic of automation, AI and progress in general than you’ll find in much of the press. Here’s what some of our own colleagues think about the topic.


It's like being in a team where you can offload the boring part.

An interaction designer perspective

People spend a lot of time doing repetitive tasks like setting up meetings, managing emails, filling in reports, sorting files — tedious things that don’t require too much thought but that take up a lot of time. We’re on a path where AI will be able to complete a lot of these routine tasks.

But while AI can complete tasks with no mistake at a great speed, it scores low on creative thinking, ethics, emotional intelligence and understanding the bigger picture. AI is specialized, but humans live in the real world and are aware there are different kinds of information.

This makes it a team effort, where computers do things super-fast and without errors, and where humans orchestrate and interpret. This human-AI joint force is enhanced by a large network of available information. The greatest results will be achieved by a better understanding of both human and AI possibilities and limitations. Just like managing a team, it is about assigning the right tasks to those best equipped to do them.

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Would you go back?

A software developer’s perspective

Just ask yourself this: Would you be happy if all washing machines disappeared tomorrow? Would you be grateful to do all your washing by hand again? Or would you prefer your washing machine, instead of vanishing suddenly, to discover how to order detergent, separate clothes and even fold them nicely? Would you complain that you have too much spare time and get bored or find new interesting things to focus on? We, at Nibo, know for sure which we'd choose. Because, just as industrial automation has reduced the hours we have to work, domestic automation – like washing machines – has dramatically reduced the amount of housework we have to do.

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Artificial Intelligence doesn’t mean Hollywood-style sentient software.

Software architect’s perspective

Remember how you used to search for information in your school textbooks? Page by page, paragraph by paragraph? It could take hours to find that equation. Now, we have search engines that can answer almost any question in milliseconds.

Can we think of a search engine as artificial intelligence? Is it more intelligent than us? It can definitely store more data than our brain can and 'remember' things much faster. But can it use the data to prove any scientific theory? No. It just saves us time, so we, humans, can focus on making use of that information, sticking pieces together and inventing new things.

Some of us get scared when we hear about machine learning, artificial intelligence or robots, but we forget that, not long ago, we considered a calculator a very smart machine; a toy that said 'hello' when you pushed a button was also a 'smart robot'.


Layers upon layers

Product owner’s perspective

Even though we’re at a historic low in unemployment, people seem always anxious about automation. This is most often caused by a fear of change.

People often confuse the day-to-day tasks of their job with their value. Historically we’ve used computers to automate and replace some of these steps, so a person is not actually doing the same set of tasks over and over again. If we actually replace a broader set of actions this usually takes many years and requires integrating multiple layers of innovations. The advantage is that we can now achieve new things at such scale that everyone can benefit from them.

Imagine you were in an unfamiliar city and trying to reach a specific destination just a few years ago. You'd need a map and preferably a co-pilot to guide you, or you’d just stop and ask someone for directions. It may not have been mandatory to know the language; someone would probably have pointed you in the general direction if you stated the destination. Street signs could help you (if you could read their alphabet), and after a few stops you'd eventually get there. If you were looking for a good restaurant you’d have also needed a guidebook and you'd have had to be content with the 10-20 preselected restaurants.

How do we do this today? We just pull out the smartphone, type the name of the place, and get turn- by-turn directions. If there is heavy traffic the app will know and redirect you via another route. Oh, and for the restaurant you just type ‘restaurant’ and get a list of almost all restaurants nearby with reviews, ratings, images, menus, pricing etc.

How much did we have to do to get to this point? We had to build satellites, and rockets, computers, the internet, we had to map the world, shrink everything to a smartphone and convince almost everyone to get one, develop the maps app, record navigation instructions in almost all languages, make it easy enough for people to use it for directions as well as to add places and leave reviews…

Was all this done exclusively for our maps use case? No. The point is that we build each layer on top of what we had before, and this creates new services and new capabilities. To take the example even further: what have we done since everyone’s had a smartphone and Google Maps is a thing? Services like Uber have been created on top of all that. And on top of services like Uber? Food delivery services like Postmates and Doordash.

Routine tasks done in seconds, intelligent search, adaptive processes, huge bodies of data to support your decisions, consistent and error-free execution… these are all skills that are not humanly possible but nor are they useful without a person using them. Using these principles Nibo aims to give each employee super powers.


Unifying islands of automation
for true digital transformation

The automation landscape is fragmented because it’s built around tasks, not around users.

Today’s AI, machine learning and digital transformation initiatives have their roots in – and their futures determined by – emergent processes. In fact, they are merely the latest manifestations of a continuous process whereby we are moving toward new ways of doing things that haven’t even occurred to us yet.

So the reality of trying to integrate and automate all that we want is today still very hit-and-miss. Teams typically build islands of tasks and processes at department level. ERP software tries to pull everything in as more features. CRM software does the same, and ticketing solutions try to do a similar thing. All these solutions are focused first on their core competency, finance, sales, marketing support. But human competencies are not the same as a set of tasks you can do inside an app that you can just record and automate. And if you ‘zoom out’ in any organization it’s clear that there is less integration, automation and communication happening in practice than might be expected.

That’s why we build Nibo focusing on the end user, irrespective of the department in which they work. That’s why we obsess about how the user feels about Nibo. You cannot do digital transformation if your end users are not onboard with it.

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Workflows are simple,
but how about processes?

The more work people have to do to prepare information for other departments, the less bandwidth they have for the job in hand. This problem recurs in all organisations, from startups to large corporations. Small teams have a high level of communication and information exchange. They function at a very efficient level, but this becomes degraded when scaled up across the whole organization.

Why does this happen? It’s simply because other departments have different priorities. To make things happen you have to wait on people and wade through different hierarchies. You discover processes are not understood at every level, and that parts of the information needed are missing. It follows that attempting to automate at departmental level can only bring about limited success and disgruntled employees.

At Nibo we understand the lessons of history and accept that we can’t be sure what we’re going to end up with when we start out. Instead of endlessly consulting and preparing, let’s begin by inferring what should be automated.

Nibo aims to identify and prioritize procedures that will cut out boring and repetitive work, accelerate hand-offs between teams / departments, and identify bottlenecks so they can be eliminated. In this way, completely new processes will emerge in due course and will keep improving.


A brain, but not a mind

Together, Nibo and people create so much more.

For convenience, we depict Nibo with a brain, much like a human’s. People empathize with anthropomorphic characters, and this ‘brain’ emphasizes the similarity to our own adaptive logic circuits. Nibo’s brain may be faster and freer of errors than ours, but only humans can apply the judgement that creates something useful.

With Nibo as everyone’s mini assistant, super powers can literally be achieved – powers that go beyond what humans can achieve alone. Or, indeed, what Nibo could achieve alone. Nibo’s always there, always ready, but most importantly always part of your team.