Fourth Industrial Revolution

Don't compare data to oil – digitization needs a new mindset

Azerbaijani oil derricks

The old world … the oil industry created a division of labor that is outmoded today. Image: REUTERS/David Mdzinarishvili

Olli-Pekka Heinonen
Director General, Finnish National Board of Education
Hermanni Hyytiälä
Principal consultant, Gofore
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We must be able to make the utilization of knowledge and the processes of collective learning more visible in order to be able to operate better in the future. We must also be aware of the biases, weaknesses and blind spots in our thinking. We must improve our understanding of the way our minds work, both on an individual and communal level. Cognitive and organizational ergonomics are the new black in working life and decision-making.

The word “smart” seems to be in vogue. Talk of smart cities, smart traffic, crowd wisdom and artificial intelligence is on everyone’s lips. Intelligence, knowledge, competence, skills and the ability to learn have crept into the discussion on leadership and organization, now representing the core of the competitiveness of organizations. Data is referred to as the new oil. Both raw materials can be turned into money through skilled utilization, but as oil resources dwindle, the amount of data is increasing exponentially.

We have learned to refine oil into many uses that improve our quality of life, but harm the environment. In the industrial age, high on oil fumes, we honed production and logistics processes to peak efficiency.

Though the information society has been talked about for decades, the problem-solving and decision-making processes based on information still seem homespun. Even the language and terminology we use to talk about data management and data utilization have not been established.

Sensible people make foolish decisions as part of an organization. We allow actions within organizations that we would consider ludicrous in our private lives. Foolishness seems to be systematic within organizations, which means that it should be taken seriously.

Intersubjective narratives

Patterns of thought guide our actions, often unconsciously. These patterns target our observations and energy on certain issues and overshadow other things.

Being guided by their ways of perception, people only see what they want to see, tend to rely on what they have once learned and are reluctant to renounce their preconceived notions. The American theorist Myron Tribus put it well: “What you see depends on what you were thinking about before you started to look.”

These shared patterns of thought and the related stories are tools we create to make society work as expected and ensure the well-being of individuals. These stories are called intersubjective narratives. They become coordinated to tangible reality in terms of truth value.

The Bank of Finnish Terminology in Arts and Sciences defines intersubjectivity as follows: “Intersubjectivity must be separated from both objectivity and subjectivity. The objective exists regardless of subjects, and the subjective only exists for each subject, but the intersubjective exists because everyone believes it exists for everyone, e.g. the value of money and the meaning of words.”

Intersubjective narratives have been a means of survival for Homo sapiens, because they have enabled cooperation between large numbers of people. They have strengthened with time, as people have reinforced each other’s perceptions in a self-sustained circle.

The view of human beings in the context of slavery is an example of a narrative that ruled for thousands of years, which explains why people acted in a certain way in the past. It also shows how difficult it is to reverse a narrative, and, on the other hand, how the reversed narrative will become meaningless to new generations.

According to a popular quote from Einstein, the world as we have created it is a process of our thinking, and it cannot be changed without changing our thinking.

One hundred years ago, there was a shortage of durable packaging materials. The utilization of oil solved the problem, and we created an innovation called plastic. Now, the durability that we once craved has become an issue in the form of rafts of floating plastic stretching for kilometres, and we cannot solve this new problem with the same type of thinking that brought us plastic.

It is obvious that the narratives created by our thinking become problematic once they no longer correspond to the needs of people or society at large or prevent us from finding functional and sustainable solutions to the problems at hand.

Killing perception bias

The world is faster-paced than before. Diversity together with a fast pace is challenging the way in which we are used to perceiving things. Problems perceived earlier, and the appropriate solutions, are very different to problems we face today.

The phenomenon is emphasised by the decreasing significance of universal validity and predictability. This phenomenon is clearly discernible in working life, as many organizations continue doing things that used to be successful for far too long and wither away. The nature and context of the work of an increasing number of people is changing from day to day on an individual level as well, creating a need to constantly update skills and expertise.

The faster diversity increases, the greater the risk of biases in perception. Comparing data to oil is an example of a perception bias. If we do that, we are essentially looking at the utilization of data through the perception of industry.

Conceptions from the industrial age provide us with tools that are used in a world with considerably less diversity. This means that we are continuing to use mental models from the industrial age even when they start to act against their original purpose.

We are often caught up in our patterns of thought and end up “medicating” the problem with more of the disease. Perception biases can occur in both individuals and entire communities.

Patterns of thought, the solutions based on them and the end results created are intertwined, for better or worse.

If we, for example, organize knowledge work in the same way we used to organise industrial work by hierarchies and separating thinking and doing, we are obviously at risk of failure. Hierarchy and the division of labour generate localized operational efficiency, but at the same time they create silos for and form obstacles to a more comprehensive co-creation invaluable to communal utilization of knowledge, learning and creativity.

Solutions that are successful in one operational environment can be the root cause of failure in another.

Equality in service provision

As there is less diversity and it is more permanent in nature, only focusing on the supply side of things serves its purpose. This method of perception worked well in the organizations and structures of the industrial age and improved the ability to deliver.

However, the perception methods of traditional industry and the growing service industry should be significantly different, because traditional industry aims at improved ability to deliver, whereas the objective of the service structure is to develop the ability to interact.

In traditional industry, the delivery of piece goods is successful when the production system is linear, whereas the service structure requires that several experts are able to perform a unique service to satisfy the need created by the customer.

The ability to interact can be assessed by how quickly the need is satisfied at any time – the shorter the time spent by the need within the system, the better the ability of the service structure and the more cost-efficient it is.

This leads to people not being able to only focus on examining the supply side of things in the service-structurally multiform world, but having the need to primarily understand demand and needs in the context of unique circumstances. This thought is challenging the traditional way of perceiving the development of services.

Many public sector reforms deal with the question of increasing the ability to interact with diversity: The diversity of needs has increased significantly, and the service structure is at present able to “absorb” diversity to a degree.

We are often inclined to think that uniform and equal solutions generate equality. If the service structure offers a homogenous interface in a multiform operational environment, it is very likely to diminish equality in its fulfilment of different needs. Most often the discussion around the public sector reforms has thus far only focused on examining the supply side.

In order for the service structure to operate more smoothly in a diverse world, its front line needs much more diversity. Increasing the amount of diversity in the front line of a multiform operational environment increases equality – this is a paradox that conflicts the current intersubjective narrative.

The elastic mind

Even though we find it hard to fathom now, combining the concepts of ”sustainable” and ”development” was originally thought impossible. Corporate executives and environmentalists were hard-pressed to find anything good about each other, let alone a common language. Through extended discussions, sustainable development became the new shared intersubjective narrative that we now rely on to solve large, global problems.

People learn in different ways: some by reacting to direct observations by changing their behavior or by combining different things to make creative solutions.

The most challenging aspect of learning is rethinking and reshaping your own patterns of thought. It requires strong metacognitive skills and the ability to identify and challenge your own basic assumptions.

A self-regulating elastic mind provides opportunities to adapt to changes in the environment and maintain the ability to experience significance. Complex and wicked problems won’t be solved by increasing the amount of information, but by learning to utilize the constant analysis and transformation of your own thought patterns.

Similarly, we must be aware of the numerous natural cognitive biases in our thinking and actions. A good story will sweep an individual or an entire community along with it, whether it be true or not. We have such trust in our senses that the things we cannot see don’t even exist to us. We cling on to arguments and information that support our opinion and ignore other information. And we jump to conclusions even when the leap is far too dangerous to succeed.

We value loss more than a corresponding acquisition. We believe that we control the end result even if we don’t. We downplay the importance of chance. We want to continue on our path, even if it has been proven wrong, and we are very aware of our wrong choices. We make choices based on how the information is given to us.

We make decisions based on information we have found first. We overreact in the event of crises in the short term, but we underestimate their impact in the long term, which is why financial crises and bubbles always take us by surprise.

Aristotle's dimensions of thought

How should we learn to act in this time and age to fully utilize our collective wisdom?

The entity of data, information, knowledge, vision, conclusions and actions cannot be examined as an industrial-age oil-refining process. We have been doing that for a long time. We have acquired a raw material called data and stored it in warehouses called archives or statistics. Silos, data administration, archive institutions and the statistical centres that store data have been established in the spirit of the traditional way of perceiving things and the following organization and division of labour.

We store data, but what do we remember? Or do we forget that information in silos, and act only guided by our working memory that is able to remember a few facts at the deciding moment?

Data and artificial intelligence are seen as solutions to a lot of issues. We have talked less about how to combine open data and experience-based, tacit knowledge, intelligence and wisdom. The journey from data to wisdom is also a journey from quantity to quality, from the general to the context-bound and from easy routines to energy-consuming efforts.

Aristotle differentiated between three dimensions of thought. Episteme is logical thought based on rules, which is represented by scientific reasoning and research. Techne refers to testing things in practice to see whether they work or not. And lastly, phronesis is defined by its context; it is wisdom based on ethical choices presented at any moment.

All these dimensions of knowledge will be needed in the future as well. However, combining data and experience-based knowledge to form sustainable solutions in unique circumstances is emphasized in solving the global challenges of today.

Data management and information-based decision-making are treated as refinement processes, as processes of receiving and transferring information. The insufficient amount of incoming data, or the fact that information does not reach all of those that it should reach, are seen as the problems.

Data transfer is an important viewpoint, but in discussions the complex mechanisms of the mind seem to be covered by an invisibility cloak. In our experience, the problems associated with data management or data-based decision-making are not connected to a lack of information, but an unwillingness to utilize data that differs from the user’s own pattern of thought.

The reasons for this vary: an unwillingness to question the beliefs of one’s own professional identity, the prevailing point of view or that of tradition, beliefs that maintain group cohesion, or a more comprehensive intersubjective perspective. Being busy, suffering from pressure at work or fear for one’s own position and the themes of power increase obstacles to utilizing data.

Feelings won’t make a dent in the surface of an oil pipe, but in the realm of data management they may stop the flow altogether. Organizations that outsource feelings won’t learn or increase awareness. Feelings are crucial to our attitudes towards our surroundings and to how we create meaning in and interpret the world. Understanding feelings is at the core of data management.

Flawed leadership models

Digitalization new ways of organising interaction-intensive work, either on top of previous patterns of thought or by building something new. Digitalization can be used to make past truths the most effective, to streamline digital Taylorism.

We are very good at doing the wrong things better or faster. Primarily, we still perceive organzation as if we were on the battlefield: the commander monitors the battle from a nearby hill, for example, in order to gain an overall picture of how the situation is developing, enabling them to instruct the soldiers if need be.

Digitalization employs the same principle, foregoing any independent thought of the organizational soldiers, bordering on the view of human beings associated with slavery. Some might call this model smart, but it is not very wise or adaptable.

Hierarchy might still be necessary for making executive decisions, but on the other hand, we need significant amounts of self-direction and common direction. If the first thing we think of when we hear the word “organization” is a stack of boxes depicting the structure of power, we are looking at the organization of cooperation between people from a very limited perspective.

To put it simply, we can say that leadership is only one way of implementing organized cooperation. This is a challenging thought to anyone looking at the world from the point of view of leadership. If the operating environment, the purpose of cooperation between people and commitment allow, leadership may be left with a very small role in the organization.

In a world of diversity, the situation picture should be made collective, which opens up new opportunities for organization – and leadership. The possibility of thoughts, feelings, viewpoints and arguments to flow freely is key, and not just within organizations, but throughout the systemic entity that is producing added value.

Leaders that emphasize hierarchy and their own status make their subordinates dumber. Power structures, egos, authorities and pockets of psychological insecurity preventing dialogue, creativity and the free flow of information are the cancer of expert organizations.

The silo-like organization makes it difficult to solve complex issues, because the fragmentation always decreases collective intelligence.

The collective, shared meaning of organization prevents the silo effect in terms of information and enables focusing on what really matters. In our fast-paced reality, organizations must be able to examine their own operations from the point of view of an outsider; in addition to observations, we must learn how to challenge our own thought patterns and be subjected to criticism.

The dissonances in information, contradictions between prevailing assumptions and beliefs and reality, are the sheet music for data management. The task of leaders as conductors is to expose the dissonance, because it is a prerequisite for learning.

Alongside learning new things, it is often more challenging, but key, to unlearn. Those that succeed in the future will have learned to let go of things they have learned before.

The roots of change

Going forward, selecting a perception tied to context and circumstances will be one of the core skills in decision-making and leadership, because your perception determines the set of methods to use in solving a problem. It is easier to solve identified problems than to learn to identify unknown issues.

We spend a lot of time, energy and resources to develop work atmosphere, agile and lean management, data system projects, organizational reforms and leadership training. These all have one starting point: how can, collectively, we act more wisely?

The solution won’t be a ready-made recipe or the streamlining of what we do now. We need radical changes in our way of thinking, in the original sense of the word. Radical is derived from the Latin radix, root. By focusing on what seems important on the surface, we are presented with an image of appearing to do something in the face of issues. But it is not enough.

Amid all this ado about change, we must take the time to focus on the root causes that change slowly, run deep and intersect. We must reach the grassroots level. We must be able to highlight the basic assumptions underlying our thinking in order to enable development and learning.

This is the only way we can create an information society that reflects our values, and where everyone has the opportunity to grow to meet their full potential, belong to a community and realise their talent in a meaningful way.

We need a new intersubjective narrative to perceive the operation of organizations and work in a reality that consists of interaction, data and knowledge. Artificial intelligence brings with it new important tools to find solutions, but only if it is applied wisely, by employing phronesis in problem-solving. We need a general view of data management and data utilization.

The success of each organization comes down to how well it is able to learn and utilize what it has learned to solve certain problems in its own ecosystem.

What would happen if the skills that created the willingness to share on Facebook, to search while playing Pokemon GO, to recommend on Amazon and to crowdsource on Wikipedia were used to eradicate inequality or meet the goals of Agenda2030?

The individual and communal development of the understanding of data management and the mind are worth the investment. In proportion to how many companies constantly use the word “smart”, there is still plenty of uncharted blue ocean left.

You can start by determining how the operations method and decision-making process based on data and learning works in the organization, and how it could work better. This applies to all organizations that want to reinvent themselves from the perceptions of the industrial age and move towards learning communities and networks.

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