The balancing and optimization or analysis versus action is a critical aspect of how to make the most effective change in the world. Often, more analysis can lead to a better understanding of a given system, which means that a given action is more influential. However, analysis is not free and takes energy and time. The energy and time used for analysis, means that energy and time is not used for action. So, there is a delicate balance for agents to create meaningful change. Change agents can’t just analyze forever without action because nothing will be accomplished. On the other hand, doing action with no analysis can lead to unforeseen consequences and not focusing on the right topic. While there is not precise formula for balancing analysis and action, finding the right balance of these factors is a critical component of becoming an effective change agent.
One of the key tools in system’s theory is the processes of a system analysis. A system analysis works to identify the most relevant factors in a system and how these factors interrelate. For example, the graph below shows an example of a system analysis of a conventional agricultural system. This graph uses a causal loop diagram where direct relations (more leads to more, and less leads to less) is written as a plus symbol and an inverse relation (more leads to less, and less leads to more) is written as a negative symbol. For example, more forage biomass increases environmental quality (+), but more tillage practices decrease environmental quality (-). This kind of systems analysis can be useful for stakeholders to map their understanding of a system together, understand the key relationship (which can also be represented with mathematical formulas), and use this information to decide on the best action to take to create the desired change.
Now, it should be mentioned that models are never a perfect representation of reality and there can always be more and more factors included. So, there is a question of when a system analysis to is good enough to make the decision for how to act. A key factor here is for stakeholders to include the most relevant factors, while not including less relevant factors as this takes more time and energy with less relevance to the decision at hand. How decisions are made is not a strict science, but rather an art. Complex systems of business, politics, and social systems are often impossible to predict and at some point the analysis needs to be good enough to take some action.
In a very fundamental way, doing an analysis always takes energy. For example, following the notion that a system analysis is accomplished by processing, manipulating, and organizing information, there are strict energy requirements. Landauer’s principle states that there is a minimum energy needed to erase one bit of information that is proportional to the temperature at which the system is operating. More specifically, the energy needed for this computational task of erasing or creating one bit of information in an irreversible process is given by E ≥ kbT ln(2). This means that computation and manipulations of data for a system analysis must always use energy, and can’t be done for free.
On the other side of the spectrum, action takes energy. In order to change a system in a way that doesn’t occur naturally following the principle of least action (which reduces potential energy and tends to increase entropy over time), energy must be used. This means that energy is required to do something that wouldn’t already naturally occur. Most of the actions for changing systems, like introducing or removing a new type of factor, or changing a factor, re-organizing the relationships between factors, and so on, are highly ordered actions that require energy and don’t naturally occur. This can also be understood from a business sense. It always takes time, money, resources, and energy to accomplish a significant action in the world.
System change is a broad field that studies how systemic solutions can be implemented in complex systems. A systems change view prioritizes leverage points, working to avoid unforeseen consequences, and fixing root causes of problems rather than symptoms. A systems change view takes both analysis, to understand complex system, and action, to implemented changes to these systems. To create the most effect system change, analysis and action need to be balanced and optimized.
While there is no formula to apply to all cases for how much analysis versus action is needed to create the most effective change, there are some common patterns that apply to many cases. One commonality is that after a certain point, there is diminishing returns for an analysis. For example, it may take 100 units of energy to get to a 80% analysis, but 200 units of energy to get to a 90% analysis, and 300 units of energy to create to a 95% analysis. More and more energy is required to get to higher any higher forms of analysis, that include more factors. At some point, the decision needs to be made that the analysis is good enough to take action and to go forward, and revisit the analysis and circle back as needed. It is impossible to get to a 100% correct analysis of nature, so the decision needs to be made at some point to go forward.
Optimizing analysis and action is both a science and an art that business leaders, political agents, and people enacting system change need to consider on a day-to-day basis. More and more energy can be used to consider more factors in an analysis, but this leaves less and less energy to perform the action itself. On the other side, using all the available resources and energy for immediate action may not produce the best results and the identification of the best levers and interventions to create systemic solution. Balancing and optimizing analysis and action is critical to be an effective change agent. Change agents can create their own methods and procedures to identify how to balance analysis and action for the decision at hand.
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