Systematic, algorithms-based, or intuitive problem-framing, etc are all great methodologies and practices and "on balance" scenarios for problem-framing.
Problem-solving is about seeing a problem and actually finding a solution to that problem, not just the band-aid approach to fixing the symptom.
Framing the right problem is halfway to solving it. Running a business is fundamentally an iterative problem-solving continuum. It’s critical to take multiple scenarios for framing the right problems in order to improve problem-solving effectiveness and build unique business competencies.
Systematic problem-framing: It should be beneficial to apply Systems Thinking to both frame the right problems and provide a framework for problem-solving. Systems thinking defines how we perceive the "problem” because it allows people to understand the interconnectivity and interdependence of the parts and the whole. It provides a useful framework for a better and more accurate understanding of the overall situation and problems, and hence, better defining the problems and subsequently how we should go about solving them and in what sequence!
Systems thinking helps you actually understand the problem, the current situation, and then, if an intervention is needed, to guide the resolution and improvement of the situation, and understanding a problem is the most critical step in solving it. Systems Thinking provides an insight into the emergent inherent properties, both the positive emergent issues required and the negative emergent issues (both known and previously unrecognized problems) that come about. It is a great technique to leverage Systems Thinking for problem definition with problem boundaries smaller or larger (single or multiple goals), depending on what you consider relevant and endogenous as your hypothesis regarding why these things have evolved in a certain way.
Algorithm-based problem framing: An algorithm is a model of the real world and it is a procedure or formula for framing and solving a problem. A good algorithm needs to be developed through integrating knowledge-based data into analytic models simulation testing implemented for problem-solving or design nonlinear models for “predictive" cause and effect in system dynamics. Every single prediction depends on some kind of model. It’s important to do data investigation or any attempt at understanding the business context. The point is that humans should all have some humility and recognize the limitations of their expertise and partner them with the other experts to apply the analytical algorithms for problem-solving. A well-developed algorithm could be a scientific tool to:
(1) Identify the problem: What is exactly wrong, out of balance, unjust, etc, the exact description of the problem.
(2) Find the factors involved in the"incorrect" outcome. See if you can measure or weigh each factor's contribution to the result, or the description of the unit of measure.
(3) Build a hypothetical equation that describes your "incorrect" outcome: See how changing any of getting better or worsens that outcome.
Intuitive problem-framing: Intuition or being intuitive is when you have a gut feeling about something. Intuition is like the inner compass that gives direction to people in making good decisions. Intuition, therefore, is a "reflex expression of wisdom” that is the first step in the right direction to provide acceptable answers to questions regarding social and natural sciences. It is the quality or ability to have such direct perception or quick insight for either framing the right problem or solving it effectively. It’s a subconscious mode of evaluation that can help to better understand the so-called "reality," in which we operate or maximize our engagement with the broader and deeper aspects of our mind and our experience.
Intuition involved in the development of a scientific theory is abstract and often working together with “thinking.” Intuition works fine for problem-framing when there isn’t an exact answer to the puzzle because you don’t have all the pieces. For this inner compass to work correctly, you need intuition (the wisdom of past experience and pattern-recognition at both conscious and subconscious levels). You should have the right balance of the depth and breadth of the technical and business knowledge. This knowledge comes from a combination of several things such as educational training, experience from past successes/failures, observation, cognizance, etc.
Systematic, algorithms-based, or intuitive problem-framing, etc are all great methodologies and practices and "on balance" scenarios for problem-framing. It needs to be supported by but going beyond the data you can master for improving problem-solving maturity and developing high-level professional competency.
Systematic problem-framing: It should be beneficial to apply Systems Thinking to both frame the right problems and provide a framework for problem-solving. Systems thinking defines how we perceive the "problem” because it allows people to understand the interconnectivity and interdependence of the parts and the whole. It provides a useful framework for a better and more accurate understanding of the overall situation and problems, and hence, better defining the problems and subsequently how we should go about solving them and in what sequence!
Systems thinking helps you actually understand the problem, the current situation, and then, if an intervention is needed, to guide the resolution and improvement of the situation, and understanding a problem is the most critical step in solving it. Systems Thinking provides an insight into the emergent inherent properties, both the positive emergent issues required and the negative emergent issues (both known and previously unrecognized problems) that come about. It is a great technique to leverage Systems Thinking for problem definition with problem boundaries smaller or larger (single or multiple goals), depending on what you consider relevant and endogenous as your hypothesis regarding why these things have evolved in a certain way.
Algorithm-based problem framing: An algorithm is a model of the real world and it is a procedure or formula for framing and solving a problem. A good algorithm needs to be developed through integrating knowledge-based data into analytic models simulation testing implemented for problem-solving or design nonlinear models for “predictive" cause and effect in system dynamics. Every single prediction depends on some kind of model. It’s important to do data investigation or any attempt at understanding the business context. The point is that humans should all have some humility and recognize the limitations of their expertise and partner them with the other experts to apply the analytical algorithms for problem-solving. A well-developed algorithm could be a scientific tool to:
(1) Identify the problem: What is exactly wrong, out of balance, unjust, etc, the exact description of the problem.
(2) Find the factors involved in the"incorrect" outcome. See if you can measure or weigh each factor's contribution to the result, or the description of the unit of measure.
(3) Build a hypothetical equation that describes your "incorrect" outcome: See how changing any of getting better or worsens that outcome.
Intuitive problem-framing: Intuition or being intuitive is when you have a gut feeling about something. Intuition is like the inner compass that gives direction to people in making good decisions. Intuition, therefore, is a "reflex expression of wisdom” that is the first step in the right direction to provide acceptable answers to questions regarding social and natural sciences. It is the quality or ability to have such direct perception or quick insight for either framing the right problem or solving it effectively. It’s a subconscious mode of evaluation that can help to better understand the so-called "reality," in which we operate or maximize our engagement with the broader and deeper aspects of our mind and our experience.
Intuition involved in the development of a scientific theory is abstract and often working together with “thinking.” Intuition works fine for problem-framing when there isn’t an exact answer to the puzzle because you don’t have all the pieces. For this inner compass to work correctly, you need intuition (the wisdom of past experience and pattern-recognition at both conscious and subconscious levels). You should have the right balance of the depth and breadth of the technical and business knowledge. This knowledge comes from a combination of several things such as educational training, experience from past successes/failures, observation, cognizance, etc.
Systematic, algorithms-based, or intuitive problem-framing, etc are all great methodologies and practices and "on balance" scenarios for problem-framing. It needs to be supported by but going beyond the data you can master for improving problem-solving maturity and developing high-level professional competency.
1 comments:
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