People, both consumers and those in business, have had to adapt to the transforming structures and activities as well as changes in our thinking as sudden changes and societal phenomena have molded these elements that concern us all. One good example is the energy sector which, unfortunately or fortunately, has found itself in the public limelight.
This winter, the accessibility and price of energy, not to mention the national security of supply, dominated consumers’ attention in an unprecedented way. The most extensive changes with regard to production structures and various transitions are yet to come. The one essential aspect that underlies all of these developments is that everything is based on phenomena.
The phenomenon-based approach is here to stay – but what does it mean?
Different kinds of phenomena have an impact on the activities of organisations and companies – both externally and internally. These phenomena may include the evolving needs and demands of customers and stakeholders, changes in the production base towards sustainable consumption, and sudden world-changing events.
In the energy sector, the list of phenomena could include the “energy crisis” that was predicted for winter 2023 as well as the transitions concerning fundamental structures, such as production processes and energy sources. Last March, the energy company Helen closed its power plant in Hanasaari in Finland. As is evident, the transitioning towards new energy sources is progressing in a very concrete way. Traditional power plants are more and more being replaced by energy sources that have neither been developed nor are they maintained by humans. For example, solar and wind energy represent a completely different kind of production base in many ways when compared to the energy produced in a traditional power plant. These kinds of developments impose new demands for data, data management, and predictability.
All of these changes raise various questions. How should we plan this new kind of production? What about its storage or resale? How should knowledge-based management be conducted? How do you predict things in the future? The sustainability aspect of the green transition is motivational. If and when the actors and sectors that have been regarded as traditional succeed in their transformation, it is a sign for the rest of us that we, too, can succeed. At the same time, we can support one another both as consumers and actors. A phenomenon-based approach requires co-operation, and it allows us to positively impact and accelerate transitions. In turn, co-operation helps us reach our goals and increases our understanding of various phenomena.
Where should we look for answers then?
Adapting to phenomena requires openness
Throughout time, we have built closed systems and solutions with little regard to future needs for change. This can no longer be the case. The information that we need for decision-making and planning our operations flows freely and is constantly changing. Companies and organisations need to be able to utilise external information and also share their own internal information. This is impossible if the systems are closed and the information is fragmented and subordinate to existing solutions.
Throughout time, we have built closed systems and solutions with little regard to future needs for change. This can no longer be the case.
Data, strategy work, and openness
Data and the information generated from it should in many ways be seen as a strategic element. The way it connects to the business vision, goals, and measures should be taken into consideration already during strategy work – or perhaps it should even function as the starting point for such work.
Respectively, information needs a strategy of its own – a plan on how to reach goals, descriptions of how data supports (or does not support) reaching those goals, and what changes mean for the data. Data strategy is a plan that concerns information, and it both enables and accelerates business strategy.
In a way, data strategy and business strategy mirror one another. Data consists of existing facts but information also includes the views, understanding and ideas of an organisation. We need to consider the people as well.
Data management and its ground rules require rethinking
Previously, the ground rules for data management have been used to define very operative matters. What kind of data do we have, who is authorised to alter the data, what kinds of alterations can they make, and who approves such changes? As the amount of data increases and the information flows more freely, these common ground rules shift to govern culture in particular – curiosity, data literacy, and the understanding of data security. We move away from spelling rules towards thinking, effectiveness, and responsible actions.
As the amount of data increases and the flow of information becomes more free, these common ground rules shift to govern culture in particular – curiosity, data literacy and the understanding of data security. We move away from spelling rules towards thinking, effectiveness, and responsible actions.
The event-driven approach enables the accuracy and timeliness of data
Event-driven activities help us recognise the capabilities that we need in order to address phenomena. The event-driven approach can already be seen in all operations. However, systems and reporting can rarely keep up. Data is constantly changing, converging, and creating new data. Moreover, a great deal of data needs to be enriched throughout their entire lifecycle, and we must ensure that timely updates can be made in all of the necessary directions.
If changes and events are unable to move in different directions, all we can do is analyse the various results of interim stages and even then, the results can often be assessed only in retrospect. It might be impossible to gain information on what actually happened or what took place during the later stages – or at least this information cannot be acquired in a timely manner.
The situational picture can be harnessed in decision-making
In our thinking and actions, it is important to understand and accept that a situation/situational picture is always a reflection of a specific point in time. Understanding is increased with time by frequently forming many situational pictures and systematically analysing them.
By accepting that most of the time our data and its defined scope are not fully complete, we can better utilise timely data and maintain predictability.
Organisations should permanently shift their attention and information needs towards what comes next. This can be achieved by identifying and constantly analysing cause-effect relations. We need to understand and accept that data is like a living organism and so should our thinking be. The more we can utilise the possibilities of, for example, Artificial Intelligence for data processing, analysis, and automation, the more time we have on our hands to study, observe and think. These elements create the foundation for co-operation between humans and AI.
Phenomena can be difficult to grasp
It is indeed difficult. Words can easily remain on an abstract level, and we may fail to connect actions to words and vice versa. In this case, a good solution might be to plan and act from the bottom upwards. By having a better understanding of a phenomenon-based approach in terms of, for example, analytics, we can more easily connect action, reality, and analysis together. A change in thinking brings about a change in action. When new ways of thinking and changes in our actions become established, it gives rise to a new kind of culture and brings us closer to understanding phenomena. How exactly do we achieve this? For example, we can systematise a series of cumulative analyses. To put it briefly.
Data and knowledge-based management create security. Despite everything.
