Overview Chapter I (Problem-solving)
- The seven-step problem-solving process:
1. Define the problem (Agree upon a problem definition)
2. Disaggregate the issue (Problem needs to be broken down)
3. Prioritize the issues (which ‘problems’ have the biggest impact)
4. Build a work plan and a timetable
5. Conduct a critical analysis (what will take the most work to fix?)
6. Synthesize findings from the analysis (get others on board with the findings)
7. Prepare a powerful communication (develop a storyline)
- Several types of trees:
1. Factor/lever/component --> used early on when not much is known about the
structure of the problem
2. Inductive logic tree --> early on when you know something about the
endpoints, but still don’t understand the structure of relationships between the
parts
3. Deductive logic tree --> when you have a very clear idea of the problem
structure, especially when it is coherent
4. Hypothesis tree --> when you know enough about the structure to make clear
hypotheses to begin to test with your data gathering
5. Decision tree --> When you know a fair amount about the problem structure
and the nature of the decision is a series of cascading junctures
- The trees are essential to good problem solving due to
1. provide a clear visual representation
2. Everything that is relevant is being captured within the tree
3. lead to a clear hypothesis
- Within the trees, it is key to look for what is the key determinant within the problem to
solve?
- The core of a good tree is asking the right questions and disaggregating the problem
into straightforward chunks
Chapter I, key takeaways:
- Good problem solving is an incremental process
- The most important step in the problem-solving process is to disaggregate the problem
in a logical way into components
- Prioritizing analyses is essential so that you avoid working on parts of the problem that
contribute less to solving the problem
- A well-defined work plan is needed to allocate tasks to team members
- Problem-solving is not over until others can synthesize your results
Overview Chapter II (Define the problem)
- Getting the problem definition right, including boundaries is essential to good problem
solving and can be an essential competitive advantage
- Good problem statements have the following characteristics (OSCDSS):
o Outcome focused
, o Specific and measurable
o Clearly time-bound
o Designed to specifically address decision-maker values and boundaries
o Structured to allow sufficient scope for creativity and unexpected results
o Solved to the highest possible level
- SMART = specific, measurable, action-oriented, relevant, timely
o Smart workplan guarantees: 1) clear transparent actions 2) priorities that are
set 3) responsibilities that are shared 4) traceability is secured 5) realistic
timing 6) communicating based on facts/figures
- Portfolio effect = the grants it makes are invested into new projects that can build off
and support each other
- Problem statement evolution models help to see how teams start to understand
problems better and better
- A fresh perspective and a new pair of eyes with new analytical approaches can bring
new light to old problems
- Solve the problem at the highest level possible, the insight here is that the most local
solutions are often not optimal for the larger organization
- Design thinking allows teams to use a creative problem-solving process to find
innovative solutions, it consists of:
o Empathize (understand)
o Define
o Ideate (brainstorm/think outside the box)
o Build
o Test (experiment)
o Deliver
- The idea behind design thinking is that you don’t have to make decisions based on
historical data and instinct. Rather than decisions can evolve, based on evidence from
users’ reactions to failed prototypes
- Dealing with biases can be done:
o Through diversity in teams
o Excellent team leadership and coordination
o Multiple trees
o Questioning your hypothesis
o Use brainstorming
Obligation to dissent (team rules & regulations)
Roleplay (the client wishes/expectations)
Dialectic standard (thesis & anti-thesis)
Perspective-taking (modeling another assertion)
Constructive confrontation (spelling out all assumptions)
Team distributed voting (brainstorm ruling via votes)
Solicit outside views (asses the outside)
o Explicit downside scenario modeling
o Good analytical techniques
o Broad data sources
Chapter II, key takeaways:
- The seven-step problem-solving process:
1. Define the problem (Agree upon a problem definition)
2. Disaggregate the issue (Problem needs to be broken down)
3. Prioritize the issues (which ‘problems’ have the biggest impact)
4. Build a work plan and a timetable
5. Conduct a critical analysis (what will take the most work to fix?)
6. Synthesize findings from the analysis (get others on board with the findings)
7. Prepare a powerful communication (develop a storyline)
- Several types of trees:
1. Factor/lever/component --> used early on when not much is known about the
structure of the problem
2. Inductive logic tree --> early on when you know something about the
endpoints, but still don’t understand the structure of relationships between the
parts
3. Deductive logic tree --> when you have a very clear idea of the problem
structure, especially when it is coherent
4. Hypothesis tree --> when you know enough about the structure to make clear
hypotheses to begin to test with your data gathering
5. Decision tree --> When you know a fair amount about the problem structure
and the nature of the decision is a series of cascading junctures
- The trees are essential to good problem solving due to
1. provide a clear visual representation
2. Everything that is relevant is being captured within the tree
3. lead to a clear hypothesis
- Within the trees, it is key to look for what is the key determinant within the problem to
solve?
- The core of a good tree is asking the right questions and disaggregating the problem
into straightforward chunks
Chapter I, key takeaways:
- Good problem solving is an incremental process
- The most important step in the problem-solving process is to disaggregate the problem
in a logical way into components
- Prioritizing analyses is essential so that you avoid working on parts of the problem that
contribute less to solving the problem
- A well-defined work plan is needed to allocate tasks to team members
- Problem-solving is not over until others can synthesize your results
Overview Chapter II (Define the problem)
- Getting the problem definition right, including boundaries is essential to good problem
solving and can be an essential competitive advantage
- Good problem statements have the following characteristics (OSCDSS):
o Outcome focused
, o Specific and measurable
o Clearly time-bound
o Designed to specifically address decision-maker values and boundaries
o Structured to allow sufficient scope for creativity and unexpected results
o Solved to the highest possible level
- SMART = specific, measurable, action-oriented, relevant, timely
o Smart workplan guarantees: 1) clear transparent actions 2) priorities that are
set 3) responsibilities that are shared 4) traceability is secured 5) realistic
timing 6) communicating based on facts/figures
- Portfolio effect = the grants it makes are invested into new projects that can build off
and support each other
- Problem statement evolution models help to see how teams start to understand
problems better and better
- A fresh perspective and a new pair of eyes with new analytical approaches can bring
new light to old problems
- Solve the problem at the highest level possible, the insight here is that the most local
solutions are often not optimal for the larger organization
- Design thinking allows teams to use a creative problem-solving process to find
innovative solutions, it consists of:
o Empathize (understand)
o Define
o Ideate (brainstorm/think outside the box)
o Build
o Test (experiment)
o Deliver
- The idea behind design thinking is that you don’t have to make decisions based on
historical data and instinct. Rather than decisions can evolve, based on evidence from
users’ reactions to failed prototypes
- Dealing with biases can be done:
o Through diversity in teams
o Excellent team leadership and coordination
o Multiple trees
o Questioning your hypothesis
o Use brainstorming
Obligation to dissent (team rules & regulations)
Roleplay (the client wishes/expectations)
Dialectic standard (thesis & anti-thesis)
Perspective-taking (modeling another assertion)
Constructive confrontation (spelling out all assumptions)
Team distributed voting (brainstorm ruling via votes)
Solicit outside views (asses the outside)
o Explicit downside scenario modeling
o Good analytical techniques
o Broad data sources
Chapter II, key takeaways:
