2021. We chased it hoping to leave the year that preceded it very quickly behind us.
And if change has become the watchword for all businesses, we find ourselves dealing with "unknown worlds"in which venturing is as necessary as it is risky.
Yes, because there is no world more unknown than the one towards which we must direct the digital transformation of our companies. Risk management is inherent in change management.
On the one hand, today, to cope with crises and navigate unknown worlds, the business strategy of digital transformation makes use of automation tools such as artificial intelligence applied to decision-making processes.
On the other hand, it remains true that in order to make the right decisions it is essential to ask ourselves the right questions, even and above all, when they undermine our belief systems.
For this purpose, there is a model that you can apply to assess risks and anticipate possible future scenarios, in relation to a given theme.
Read on to find out.
Article by Daniela De Giorgi (CommunicationsStrategist) and Paolo Quattrocolo (Service and UX Designer).
Given that the unknown is that part of change that is inevitable and difficult to govern, we want to share with you a strategic tool - a compass that we use at Bixuit to guide us in managing business in times of crisis.
It is the Known / Unknown matrix, which from now on, for convenience, we will identify with the acronym KKUU [Editor’s note].
This model serves to place you in the scenario between the known and the unknown to help you understand what kind of tools you need to guide your future strategies.
“Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don't know we don't know. And if one looks throughout the history of our country and other free countries, it is the latter category that tends to be the difficult ones”
Although the KKUU matrix appears to have ancient origins, its popularity is due to DonaldRumsfeld, former Defense Secretary of the United States who served in the administrations of President Gerald Ford and George W. Bush.
“There are known knowns” is the sentence uttered by Rumsfeld in 2002 during a press conference at the Pentagon, in response to a question from a reporter who insinuated the lack of objective evidence of weapons of mass destruction in Iraq.
It is no coincidence that the KKUU matrix is used in the political-strategic context where the strategic theme of crisis management and the unknown is, as we can see, the main theme.
Rumsfeld's response to the reporter at that event went down in history for highlighting the limits of human knowledge.
For Rumsfeld there are some things we are completely unaware of; so much in the dark, that we don't even know we don't know them.
While instead, the "known facts" are precisely facts, rules, laws that we know with certainty. We know, for example, that the force of gravity is what causes an object to fall to the ground.
Meanwhile, those we might call "known unknowns" are gaps in our knowledge, but are gaps that we know exist. This is the case with the response thatRumsfeld gave to the journalist, highlighting a degree of complexity that cannot be reduced to a simple line of decision-making.
The idea of the known and the unknown reveals that the information of those in positions of responsibility - whatever they may be - is almost always incomplete. This concept emphasizes the importance of intellectual humility, a fundamental attribute in the decision-making process and in the formulation of a strategy.
Obviously, it is difficult to accept that there are things unknown to us, which, nevertheless can be important. The best strategists, Rumsfeld says in his book Known and Unknown: A memoir, try to imagine and consider what is possible, even when it seems unlikely.
In his speech, Rumsfeld defines three spaces that represent "known knowledge". These are areas of knowledge that fall into what we could define as a zone of comfort, controlled and understandable.
In this known space, the risk has a relative dimension, because it is proportional to a clear and accessible environment.
Not just that. Even when we know we don't know, the boundary can still be measured. This means that by asking the right questions, we can fill that void of knowledge.
And it is precisely in this way thatRumsfeld, in answering that uncomfortable question at the press conference, traces absolute perception to relative perception.
This is exactly what happens with Data Thinking, the approach we use atBixuit to transform data into information and manage precise and measurable data sets, with a relative risk margin.
With the inquiry and acquisition processes (Ask + Acquire) we mentioned in the post on How to design the data mindset for digital transformation, we can push the boundaries of a certain area of knowledge. These are essential steps if we want to know what questions to ask in order to better understand what is partly beyond our area of knowledge.
Now let's do an exercise.
Try to bring the three spaces of known knowledge back to the reality in which we live and to the theme of information, which is the subject of this post.
What is the space in which we feel -technologically speaking - most at ease? What are the places on the web where we are both victims and creators of false, unverified or incomplete information? How much does this same information feed our prejudices?
Exactly. Social Networks are the virtual spaces where our cognitive biases proliferate. What do we mean by cognitive biases? We mean all those systematic errors we make when we rely on structures without critical judgment. They are preconceived.
There are many types of bias. In the context of social networks, for example, we are often victims of confirmation bias, that tendency to seek information that confirms our beliefs. In some cases like Facebook, the algorithm also plays its part by showing us news and information based on our behaviour and our interests on and off the platform, reinforcing our belief system.
This and other biases multiplied by the number of users of the various social networks, gives us a clear picture of just how much the amount of information that hits us does not actually contribute to increasing our level of knowledge, but instead to reinforce our initial ideas and to identify with a select group that represents them.
This is the comfort zone that nourishes our preconceptions. Looking at the quadrant, we are in the space of the Unknown / Knowns, that space of knowledge in which the things we do not know that we know reside.
Now, if we keep this parallel between information and technology, using the model, you’re probably wondering what we find within the Known / Unknowns quadrant.
What do you see there?
As with the first two quadrants, this third quadrant also has to do with a dimension of information whose boundaries can be defined through investigation.
In this case, however, we are dealing with an area in which we have neither certainties nor prejudices; it is precisely that dimension in which “we know we don't know”.
Think about it for a moment. What are those tools - and there is one in particular that we all use - that we rely on when we need an answer? Who do we question?
Yup! Right again. From a B2C perspective, our reference points are search engines, and the top of the list is Google.
The same type of reasoning can be done from a B2B / B2E perspective when, for example, our company adopts Business Intelligence systems for the collection of structured and unstructured data, useful in decision-making processes.
Isn't this what the likes of Oracle, Tableau, QlikSense do?
But beware of blindly believing in self-diagnosis on Google or in the ready-to-use data of a dynamic analytics dashboard. To govern the complexity of certain information, critical thinking must never be lacking.
There is one last quadrant that deserves our attention as individuals and as business makers: the space of the Unknown / Unknowns.
If we move further away from the realm of objectivity and observability and head to where risk is the greatest, we enter the X zone. It is the zone of the unknown. That area of knowledge that is totally out of our reach.
But human beings have developed a technology capable of approaching this world - artificial intelligence.
It is a technology that goes beyond the human limits of knowledge and that finds its comfort zone in the unknown space because there is no complexity of information that can overwhelm it.
We can think of artificial intelligence, with its related branches such as machine learning amongst others, as an autonomous entity capable not only of reasoning like a human being but of also learning automatically.
And there is more. In addition to the interpretation of the data and the prediction of the results, now promised by various AI platforms, there is a further even deeper interpretation.
Deep learning uses artificial neural networks - algorithms that mimic the structures and functioning of the brain - to process and break down a task into different phases. Just like a human being would.
What are the challenges we are involved in as people, technologists, designers of an experience in a field of knowledge controlled by an autonomous artificial entity?
Here, new worlds open up for you to explore. If you find this question interesting and would like to go deeper into it, write to us or comment on our social networks and we will cover topics such as ethical design in a separate article. If you don't follow us on social media yet, you can find us on LinkedIn and Instagram.
Last year we started working on redesigning the user experience of a decision support system.
This system uses decision science, which is a set of quantitative techniques -including decision analysis, risk and cost-benefit and cost-effectiveness - to support complex decision-making processes.
As designers and data thinkers, we faced the challenge of designing the way in which information will be represented in this system, intended as an operation of visualising the fragment of a piece of data to be traced back to information.
Ublique, that’s the name of the decision support system, is made up of a suite of vertical solutions or modules. The suite can have a wide range of applications for users in various markets and sectors, from supply chain to transport planning, from revenue management to demand intelligence.
Arranging the data shown in the tables and graphs and prioritising them was necessary for the simplification that led us to an ideal data visualization.
To do this, the Bixuit team ran a series of workshops with Ublique's decision scientists. The ad hoc data visualization tools (histograms, Gantt, data tables, etc.) have been redesigned for all the input and output sections of the Ublique modules. For the dashboards, it was instead preferred to create a standardised layout, capable of representing the mainKPIs present in the various modules in a hierarchical manner.
On some data visualization elements, guidelines have been devised to be applied every time the data visualization element of interest is used. The application of these guidelines across all modules allowed us to make the Ublique product coherent and consistent. An example of these guidelines is the depth of detail that each row of the data tables can achieve.
The goal we set ourselves was to have common data sets, transversal to the different modules of the suite that would elevate this customisable system to a product. This step, the last one, is intertwined with the rebranding process of the platform recently acquired by Spindox.
Bixuit also carried out the rebranding of ACTOR, but maybe we’ll talk about that in another dedicated article.
In this article, we have shared how much the issue of risk management is inherent in change and how important it is to ask the right questions to face and overcome the challenges imposed by an accelerated digital transformation.
As we have seen, the KKUU model is useful for orienting oneself and asking about one's own level of knowledge with respect to given themes. It is not a tool, but a model that requires a deep understanding of the needs and objectives we pursue, in specific areas of knowledge. A model that becomes even more useful in defining the boundaries of what we do not know.
We were also able to observe what technologies and methods can be used for each of the quadrants of the matrix, to increase our level of knowledge on certain topics and simultaneously manage the risks deriving from everything that falls into the unknown.
Did you know about this model? Was this article helpful to you? Let us know by commenting on the posts on our social networks.