The science of problem-solving is that there is logic behind any problem, it’s important to avoid the trap of emotional turbulence or unconscious bias based on personal perception.
On one hand, logic is the very clue to understanding the real problem and solving it effectively. On the other hand, logic could be fuzzy, confused, or linear, all of which cause the pain of undesired effect, lead to unnecessary complication or conventional symptom-fixing.
Streamline the problem-solving logic sequence and consequence by dispassionately taking “cause-effect” analysis and synthesis: The problems today usually have many causes and can be very complex, you can't figure out the exact cause and effect so the solutions are vague. It is important to clarify the logic behind problems, discover patterns, and capture profound insight into complex problems in order to solve them in a creative way.
The more complex the problem is, the more important to break down the large problems into smaller problems, solving them piece by piece; applying a cross-disciplinary approach to discover patterns and put the misplaced puzzle pieces in the right place logically until the premium solutions emerge, without causing other problems or too many side effects.
System Analysis of business logic requires multidimensional thinking: There is always a temptation to use simple linear models to understand highly complex, nonlinear problem-solving scenarios. Large and complex problems have a lot of inter-dependencies and uncertainty, it calls for systems analysis to solve problems with iterative processes and nonlinear logical scenarios. Systems analysis helps to see the interconnectivity between parts and the whole. There are many forms of thinking in systems analysis such as critical thinking, abstract thinking, holistic, system, quantitative, objective, subjective, or temporal analysis, all of which could be applied scientifically to improve problem-solving effectively.
The systematic problem solvers can comprehend nonlinear dynamics through different characteristics such as mixed structures, diversity, volatility, ambiguity, unpredictability, and increased flux. They can use their logic and intuition fluently, leverage sequence-consequence in problem-solving. They are able to apply induction or deduction to understand variables, interfaces, and interactions, weigh in varying decision factors, figure out “why” and “what” about the problem before jumping to the “how,” with the ultimate goal for effective problem-solving.
Business logic is nothing but a business model at a strategic level to solve problems innovatively and make profit: Businesses need to make investments and improve return on investment, either creating a new business model or taking other business initiatives is for solving problems. A run-through of high-level strategic planning can produce a wide range of potential business models, each of them can further be examined in more detail systematically to make it more specific and practical. To improve business model effectiveness, the investment management needs to make an objective assessment. Try not to fixate on single narratives but listen to more feedback and diverse opinions, clarify the logic behind business model design or reinvention in order to solve problems or chains of problems smoothly.
To perceive the value of the business model and make an objective assessment of an investment, you need to have a very clear idea of the new product/service - its life cycle, the overall "value proposition," involving problem-solving and investment mapping. Doing cost/benefits analysis and optimization of cost structure, scrutinize complexity or footprint, improve the visibility of costs measured against the visibility of quantifiable benefit.
The science of problem-solving is that there is logic behind any problem, it’s important to avoid the trap of emotional turbulence or unconscious bias based on personal perception. Business problems are usually difficult, part of the difficulty is that businesses often try to use decision-making processes to define the problem, and in doing so often fail to really define the real problem. Decision logic is an integral part of problem-solving logic. Logic could be perceived from different angles, but more importantly, needs to be proven, abstracted to a certain level; to unify diverse viewpoints, improving problem-solving effectiveness.
Streamline the problem-solving logic sequence and consequence by dispassionately taking “cause-effect” analysis and synthesis: The problems today usually have many causes and can be very complex, you can't figure out the exact cause and effect so the solutions are vague. It is important to clarify the logic behind problems, discover patterns, and capture profound insight into complex problems in order to solve them in a creative way.
The more complex the problem is, the more important to break down the large problems into smaller problems, solving them piece by piece; applying a cross-disciplinary approach to discover patterns and put the misplaced puzzle pieces in the right place logically until the premium solutions emerge, without causing other problems or too many side effects.
System Analysis of business logic requires multidimensional thinking: There is always a temptation to use simple linear models to understand highly complex, nonlinear problem-solving scenarios. Large and complex problems have a lot of inter-dependencies and uncertainty, it calls for systems analysis to solve problems with iterative processes and nonlinear logical scenarios. Systems analysis helps to see the interconnectivity between parts and the whole. There are many forms of thinking in systems analysis such as critical thinking, abstract thinking, holistic, system, quantitative, objective, subjective, or temporal analysis, all of which could be applied scientifically to improve problem-solving effectively.
The systematic problem solvers can comprehend nonlinear dynamics through different characteristics such as mixed structures, diversity, volatility, ambiguity, unpredictability, and increased flux. They can use their logic and intuition fluently, leverage sequence-consequence in problem-solving. They are able to apply induction or deduction to understand variables, interfaces, and interactions, weigh in varying decision factors, figure out “why” and “what” about the problem before jumping to the “how,” with the ultimate goal for effective problem-solving.
To perceive the value of the business model and make an objective assessment of an investment, you need to have a very clear idea of the new product/service - its life cycle, the overall "value proposition," involving problem-solving and investment mapping. Doing cost/benefits analysis and optimization of cost structure, scrutinize complexity or footprint, improve the visibility of costs measured against the visibility of quantifiable benefit.
The science of problem-solving is that there is logic behind any problem, it’s important to avoid the trap of emotional turbulence or unconscious bias based on personal perception. Business problems are usually difficult, part of the difficulty is that businesses often try to use decision-making processes to define the problem, and in doing so often fail to really define the real problem. Decision logic is an integral part of problem-solving logic. Logic could be perceived from different angles, but more importantly, needs to be proven, abstracted to a certain level; to unify diverse viewpoints, improving problem-solving effectiveness.
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