Decision Intelligence: From FACTS to ACTION

From FACTS to ACTION: A Starting Point for Discussions

Ever since I have been teaching “Decision Intelligence” to students and executives I integrate an exercise where I let them think about a few key terms that strongly affect the way we see and talk about the world today. These terms include Data, Information, Knowledge, Insight, Decision, Action as well as Facts, Experience, Expertise, Wisdom, Opinions among others. As much as we normally disagree in class about the exact definitions and the interdependencies between these terms, we also agree on the importance to create an advanced understanding in order to navigate in a Knowledge Society & Data-driven Economy.
In the following, I summarize the results of multiple discussions with students & executives with NO CLAIM to have the best possible framework (i.e. understanding) already. 
Following really smart people like Cassie Kozyrkov, Chief Decision Scientist at Google, one of the most promising but also challenging tasks in today’s world is to turn DATA into ACTION. In order to do that, I have created a FRAMEWORK that summarizes the logic we have developed. 
Let me explain its elements:
We have three levels: 

• MINDSET
• ACTIVITIES
• RESULTS

Source: Roger Moser, 2018

RESULTS
Let me first introduce the RESULTS Level including:

• DATA: Facts collected for a purpose
• INFORMATION: Data arranged in a structure
• KNOWLEDGE: Information in a specific context
• INSIGHTS: Knowledge relevant to make a specific decision
• DECISIONS: A conclusion/resolution reached after considering all insights
• ACTIONS: Process of doing something, typically to achieve an aim

 
 ACTIVITIES
While the RESULTS are rather easy to define and understand (although multiple variations exist in the academic and real-life world for each term), the ACTIVITIES that actually transform DATA into ACTION are much more difficult to agree upon or even define. In the following I try to provide an framework that might add to your understanding and your own interpretation of how to turn DATA into ACTION. The key ACTIVITIES are:

• CREATING FACTS -> DATA: When human beings create facts and collect & store them in one way or the other, they actually create data.
• STRUCTURING DATA -> INFORMATION: Data that is stored in a structure way in order to further process it can be called information.
• PUTTING INFORMATION into CONTEXT -> KNOWLEDGE: Information that is interpreted and put to use in a specific context might be labelled as knowledge.

So far, most people would probably agree. However, in today’s Knowledge Society & Data-driven Economy much knowledge has actually become a commodity-like product as it is basically freely available through the internet or the costs of accessing it via a data bases are marginal. Thus, in today’s world that is also often characterized by an information overflow any decision maker’s major challenge is to apply filters to sort out the ‘noise’ and focus on the essential parts of knowledge in order to make a specific decision. In our framework, we label knowledge that is relevant for a specific decision as insights. While many of my students and executives agree on this understanding, we have never found, so far, a common understanding of HOW we should describe the FILTER that is separating relevant from non-relevant knowledge for a specific decision-making challenge. After numerous discussions I have not been able to come up with something that everybody could agree upon. However, a framework that most students & executives could somewhat agree upon looks as follows:

• APPLYING WISDOM to KNOWLEDGE -> INSIGHTS

To many executives and students, it is very uncommon to use the term wisdom in a business context and specially to label it as the filter to sort out the ‘noise’ from a constant knowledge and information flow. However, let’s have a closer look how wisdom is aggregated.

• AGGREGATING PROFESSIONAL EXPERIENCE & EXPERTISE -> WISDOM

Simply put, wisdom is a combination of professional expertise in the form of rich knowledge and professional experience that has been accumulated over time. Based on the insights that a decision-maker has selected through his/her wisdom he/she has to make a decision.

• APPLYING OPINIONS to INSIGHTS -> DECISIONS

The question then arises how a single or a group of decision-makers filters again the available insights to make the final decision. This kind of filtering is mostly happening in the form of personal and semi-professional opinions (as the professional experience & expertise in the form of wisdom has already been applied to select the relevant knowledge; i.e. insights). Opinions about what matters almost automatically give a weight to each single insight when considering them in the actual decision-making.

• AGGREGATING PERSONAL EXPERIENCE & EXPERTISE -> OPINION

Similar to our understanding of wisdom, opinions are formed based on a combination of personal experiences and expertise. They form what we might call the opinions of a person which again influences how each single insight is put into consideration when making a specific decision.

• IMPLEMENTING DECISIONS according to your OBJECTIVES -> ACTIONS

Finally, decisions need to be implemented. This requires the allocation of time, money and other resources which are normally prioritized according to the major objectives that the decision-maker(s) have.

MINDSET
I want to emphasize again that the proposed framework is nothing else than a suggestion based on the numerous discussions with the students and executives in my “Decision Intelligence” courses at the University of St.Gallen, Switzerland. The framework consists of three levels:

• Results that start with DATA and end with ACTIONS.
• Activities that primarily take the form of FILTERS
• Mindsets that shape the configuration of these FILTERS

These mindsets might primarily consist of a private and a professional mindset that are partially built upon the private and professional experiences & expertise as well as the personalities of the decision makers.

Your suggestions to improve the framework are highly appreciated at: [email protected]

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