Knowledge workers at the edge of the cliff. The importance of algorithms at work to stay relevant.
I met with an organisation the other day that employs many educated professionals whose jobs are based on handling information, interacting with customers and using their knowledge to produce a result. If they must define the role those educated professionals do, they would probably call them knowledge workers, to differentiate them from the rest of their labour. They acknowledged they do not know much about new technologies and ways of working. I will not mention what industry they are in.
Not being an expert on new technologies is one thing, not being aware of their power and implications is a different matter. It is terrifying finding knowledge workers who know little about algorithms, self-learning algorithms, connected products, pattern recognition, or anomaly detection.
For a start, using the name knowledge worker is an oxymoron, since you cannot consider yourself to be in the know if you do not use or are not even aware of how those algorithms help to make decisions or make decisions themselves. These so-called knowledge workers are doing a job that could be done faster and better by making use of what´s available out there — the very definition of an irrelevant job, or an irrelevant job in the making.
What´s more disturbing is that their management or HR leaders did not seem to understand the implications of this and were not doing or planning to do anything about it. Their people have limited information available to support their decisions, or accelerate what they do. They are in the dark or spending too much time on things that should happen automatically. But there is not a perception this may impact negatively what they do for the organisation.
Many companies are optimising order or delivery routes, maximising the number of operations they do, classifying things to do the right thing the first time, clustering things to be more effective, recommending relevant things to their customers, reacting faster to deviations and errors, or increasing their accuracy when making decisions. The list goes on and it applies to many industries.
Do your people know and use algorithms to do their jobs? Or is what they experience at work, once again, way behind what they experience in their personal lives?
Algorithms are like electricity. You cannot be competitive without using them, the same way we cannot live or work without electricity. They help us to use computing power to accelerate or simplify what we do, same as appliances -powered by electricity- do at home, or at work. Doing more with less, knowing more to help us take action.
If employees do not use and understand the fundamentals of algorithms, they are washing clothes by hand, living with no heating system, and cooking with no fire. And if your neighbours are doing all these things, you are simply going to fall behind.
I often talk about role augmentation. The need to constantly plan how a role must evolve for this person and the organisation to stay relevant. It is about defining what tasks must be automated to make room for more value adding ones. It is important to be proactive about it. Roles are becoming obsolete without people noticing it, simply because their leaders are as oblivious to this obsolescence as they are.
If we want people to grow, we need to help them grow. If we want to be competitive, we need to explore what is already available and take advantage of it. The people I met with the other day felt perfectly fine. They are successful in what they do, to some extent. They were unconscious incompetents in using computing power and algorithms to do more and faster. They did not know they were missing out in something big.
Someone had to wake them up to the fact that many organisations out there are using these things for production, customer interaction, people development, procurement and replenishment, product design, business development, or technical support. And so should they, and all of us.
Once we are conscious, we can define what Digital competencies we need to have and work to be competent. All workers, at least the wrongly called knowledge workers, should know what an algorithm is and why it helps, be familiar with how they are used today in plenty of business situations and know what works well and not so well in the world of data and calculations.
Algorithms are here to stay and to help us. We need to understand how we use them, (or how we could), contribute to make them better and make sure they help us to stay relevant.
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