Decision Intelligence Navigator

DMI Version 4.0

This 11th issue of the Decision Model Innovation newsletter is dedicated to a brief introduction to our latest version of the Decision Intelligence Navigator (Version 4.0). An brief description of the evolution of the Decision Intelligence concept including the Decision Intelligence Navigators V 1.0 to 3.0 can be found HERE .

The Decision Intelligence Navigator has been the centrepiece of Dr. Moser’s work on Decision Intelligence since 2014. Over the years, Dr. Moser’s efforts to create a holistic yet simple guide to improve decision-making at the personal, organizational or societal level have led to different versions of a general Decision Intelligence Navigator.

Starting Point: Decision Intelligence Navigator 3.0 & Decision Intelligence Cube

End of 2023, Dr. Moser combined his Decision Intelligence Navigator (Version 3.0), his Data-to-Action framework (2018) with the Decision Intelligence Cube logic (2021) and created the Decision Intelligence Navigator (Version 4.0).

The major challenges with the Decision Intelligence Navigator 3.0 were the following:

• The DIN 3.0 had an implicit process model involved but did not account for the iterative nature of decision-making processes.
• The DIN 3.0 integrated the challenge of avoiding cognitive biases along the decision-making process only after the creation of insights (labelled as “Decision Proficiency”) but didn’t account for the problem of cognitive biases that occur when defining the decision context, selecting questions or framework or collecting and analyzing data.
• The DIN 3.0 didn’t account for the challenge of identifying dissent or creating consensus among the stakeholders along a decision-making process.?

Exhibit 1: Decision Intelligence Navigator (Version 3.0)

Similarly, although the Decision Intelligence Cube had already integrated three major dimensions of the ‘updated’ Decision Intelligence Navigator (Version 4.0), it tried to create a continuum along each dimension. In the last couple of months, my colleagues and I realized that these continuums weren’t applicable in practice as they were defined as opposite poles, which they weren’t in the reality of various decision contexts.

Exhibit 2: Decision Intelligence Cube

Decision Intelligence Navigator (Version 4.0): The Silicon, Oxygen & Carbon dimensions of better decision-making

Combining the Decision Intelligence Cube with the Decision Intelligence Navigator 3.0 along with other inputs I have received during the last 18 months, we have created a refined Decision Intelligence Navigator 4.0 that consists of six major elements. Three dimensions represent the situation that a decision-maker is in, while another three dimensions contain the key aspects that any decision-maker needs to constantly consider throughout a decision-making challenge.

Decision Situation Dimensions:

• The Decision CONTEXT focusing on understanding the key paramaters of the decision challenge at hand and, finally, the questions that need to be answered to make an optimal decision.
• The Decision PROCESS focusing on the specific process from understanding the decision context to finally make the decision and learn from the outcome.
• The Decision STAKEHOLDERS focusing on understanding who finally makes the decision, who can contribute crucial input throughout the process and who needs to be informed about the decision and outcomes.

Exhibit 3: Decision Intelligence Navigator (Version 4.0) Visualization

Decision-making Dimensions:

• The SILICON Dimension including the challenges to move from data to insights and actions & to choose the most suitable models and frameworks depending on the Decision Context.
• The OXYGEN Dimension including the challenges to identify dissent among the Decision Stakeholders & to foster consensus among them where appropriate.
• The Carbon Dimension including the challenges to preventing cognitive biases & to foster cognitive diversity throughout the Decision Process.

In the following, let me explain the labels of the three decision-making elements 'silicon', 'carbon' and 'oxygen' while I will explore each dimension in more detail in future articles.

The SILICON Dimension of the Decision Intelligence Navigator

One of the recently most discussed aspects of any good (or improved) decision-making is represented by the growing potential and power of digitized data, information, knowledge or insights (i.e. intelligence) and their application in algorithms, models and frameworks throughout the decision-making process.

Why do we label this aspect of the Decision Intelligence Navigator (Version 4.0) as the SILICON dimension?

• Silicon is a semiconductor, meaning it can conduct electricity under some conditions but not others. This property is fundamental in the digital world for processing and storing data. The ability to switch between conducting and insulating states mirrors how data can be manipulated and controlled, symbolizing the transformation of raw data into meaningful information and knowledge.
• Silicon is the primary material used in manufacturing microchips and transistors, the building blocks of modern digital technology. This makes it a physical representation of the vast amounts of data and information processed and stored in contemporary computing systems.
• Silicon's semiconductor nature, whose conductivity can be altered by external factors like temperature and impurities, can represent the concepts of uncertainty and risk. Just as silicon's behaviour can be influenced by external conditions, data and information are subject to uncertainties and risks that can affect their accuracy, reliability, and security.

The CARBON Dimension of the Decision Intelligence Navigator

The Carbon dimension of the Decision Intelligence Navigator is another omnipresent aspect of good decision-making: Avoiding cognitive biases and leveraging the cognitive diversity of individuals and entire teams is essential. This aspect doesn’t only matter when finally interpreting insights to make decisions, but it starts with the first steps of defining the decision context, which questions matter and what kind of models or frameworks to use to structure the answers.

Why do we label this aspect of the Decision Intelligence Navigator as the CARBON dimension?

• The human brain, like all organic life, is carbon-based. Carbon's role in organic chemistry is fundamental; it is a key component of amino acids, proteins, nucleic acids, and carbohydrates, all of which are vital to brain function and structure. This elemental presence underscores the importance of carbon in the biological processes that govern thought, emotion, and consciousness.
• Carbon is also renowned for its ability to form a vast array of complex molecules, including long chains and rings. This property, known as catenation, is analogous to the intricate and multifaceted nature of human relationships. Carbon's versatility in bonding reflects the diverse and complex connections that define human interactions and societal structures.

The OXYGEN Dimension of the Decision Intelligence Navigator

Another dimension of good decision-making is much less discussed in academia and practice. It deals with the problem of identifying dissent and fostering consensus (where useful) throughout the decision-making process. It’s the interaction between different (decision) stakeholders of a decision-making process that matters often much more for good decision-making than an (over)emphasis on data gathering and processing.

Why do we label this aspect of the Decision Intelligence Navigator as the OXYGEN dimension?

• Oxygen forms strong bonds with a variety of elements, including itself (O2), reflecting the strength and ubiquity of human relationships. The bonding of oxygen atoms to form O2 is analogous to the formation of strong, stable partnerships or friendships.
• Oxygen's role in water (H2O) can symbolize the essential nature of relationships in human life, much like water is essential for life. Water's properties, such as its ability to dissolve many substances, represent the way relationships dissolve barriers and bring people together, fostering communication and understanding.
• Oxygen is highly reactive and supports combustion, which could symbolize the energizing effect of relationships in human activities and endeavours. Just as oxygen supports life and energy release, good relationships provide support, energy, and motivation.

Exhibit 4: The Visual Representation of the Silicon, Oxygen & Carbon Dimension of the Decision Intelligence Navigator (Version 4.0)

The DECISION CONTEXT is the essential starting point to improve your decision-making (process).

While there is currently much written about the power of big data and AI/ML, the problems we have with polarized opinions preventing any sort of consensus or the challenge of avoiding cognitive biases,? there is no point in trying to optimize any decision-making process without taking into account the specific decision context.

What are the critical elements of defining the DECISION CONTEXT? ??

• Who is/are the decision-maker(s)?
• Who are relevant stakeholders along the decision-making process?
• What is the actual decision that needs to be made?
• How fast does the decision need to be made? How irreversible is the decision?
• How can the intelligence context be characterized? (clear, complicated, complex)?
• How often does this decision need to be made? And how much do the circumstances change?
• …
• And finally, what are the questions that you need to get answered to make a specific decision (better)

The DECISION PROCESS is sometimes like a project or an assembly line.

The decision context determines the basic type of the decision process. Like Roger Martin wrote in his seminal piece on "Rethinking the Decision Factory ", many executives make decisions that aren't made regularly and sometimes of a pretty unique nature. The decision process in such a context might have been instead managed like a project. Other decisions have to be made regularly under very similar circumstances. In such decision contexts, the logic of an assembly line to structure the sequence of the decision process is probably more suitable.

In the recent past, new advancements in the area of cognitive automation have enabled complete reconfigurations of how #humans and '#technology' are splitting up the work of making good decisions.

Exhibit 5: The Separation of Decision-making between Humans & Technology

The new possibilities of AI/ML (including #GenAI and other cognitive automation technologies) to re-distribute the chores of decision-making and/or decision-making preparations between humans and technology are opening up a new race when it comes to what BCG Henderson Institute called already in 2018 "Competing on the Rate of Learning ".

A completely new breed of technology providers such as Celonis , Aera Technology , UiPath , Palantir Technologies or SatSure present different forms of #DecisionIntelligence providers helping other companies to improve their decision-making processes (i.e. Decision Model Innovation as a value proposition).

DECISION STAKEHOLDERS aren't a new concept, but they highlight the importance of clearly defining the roles and responsibilities of all people involved.

Thinking of stakeholders is a well-established concept, but applying the concept of decision stakeholders is still helpful as it explicitly includes everyone contributing to a specific decision, not only those affected by it. Decision-makers need to think broader today and even extend their thinking of decision stakeholders to new technologies such as software agents and other forms of 'decision/analysis #avatars'.

The Decision Stakeholder concept helps decision-maker(s) to think along issues like:

• Who inside / outside of my organization can contribute throughout the decision process?
• What kind of expertise or experience can they contribute?
• Who is how affected by our decision, and is it legally required and/or valuable to understand their perspectives on the decision-making challenge or selected questions to be answered?
• What kind of technologies can we leverage to learn about the views and intelligence (i.e. data, information, knowledge, insights) that different stakeholders have to offer?
• ...
• How can we report and communicate our decision-making (processes) in case we have to justify our activities to authorities or other interested parties?

The Decision Model Navigator (Version 4.0) visualization - inspired by the Business Model Navigator

In sum, the Decision Intelligence Navigator (Version 4.0) is less process-oriented than the DIN 3.0 and is more flexible in terms of aspects to consider at each step of a decision-making process than the Decision Intelligence Cube concept. Inspired by the logic of the #BusinessModelNavigator and the concept of #BusinessModelPatterns, the Decision Intelligence Navigator (Version 4.0) also has a starting point consisting of the Decision Context, the Decision Process and finally, the involved Decision Stakeholders - just like the Business Model Navigator focuses on the customer (Who) as a starting point. The Decision Intelligence Navigator then integrates all kinds of mechanisms, concepts and especially behaviour patterns along the three core dimensions (silicon, carbon, oxygen). These dimensions are interrelated and continuously influence each other throughout the decision process. Similarly, the core elements of the Business Model Navigator (value proposition (value creation), revenue model (value capture) and value chain (value delivery) are affected by underlying business model patterns. At the moment, each core dimension of the Decision Model Navigator (silicon, carbon, oxygen) has two major elements in terms of mechanisms, concepts and behaviour patterns that decision-makers need to consider when moving from data-to-action but this might change over time when additional crucial aspects are identified.

I want to thank SatSure for its continued support of this newsletter. SatSure is a great example of how Decision Model Innovation can lead to competitive solutions!