Notes on Decision Intelligence

Related: DataScienceJournal DataScienceEthics? MentalModels BehavioralScience? BusinessJournal CareerJournal CourseNotes? Statistics101

CassieKozyrkov has a course on Linked in related to Decision Intelligence. She posted a link that let me take it for free. The course is about 1.5 hours long.

From: https://towardsdatascience.com/the-best-learning-paths-for-ai-and-data-leadership-fabc3d4f8e36

Decision intelligence is the art of giving yourself the skills and tools to turn information into actions (decisions) at any scale and in any setting.

• You do not need to be the smartest data scientist in the room.You have to be able to navigate among different experts in the room and understand the components of decision making.
• Success depends on luck and good decision making. Good decisions compound in their impact ove rtime, and the only thing we have control over (i.e. no control over luck - or is there?:P)
• Map how the components of decision making fit together.
• Individual decisions have a way of affecting others in the connected world today.
• OutcomeBias? : mass irrationality based on results encountered in the past.
• An opportunity should be analysed in terms of the resources it would consume, and the other opportunities it could annihilate.
• An outcome is different from an decision. It is possible to take a good decision and have a bad outcome. It is possible to learn from a wrong outcome and start taking bad decisions.
• Consider SurvivorshipBias and HindsightBias?
• What information was known at the time of making the decision?
• No way to assess the quality of the decision if no documentation was made into the decision process. Diagnosis of decisions can be done only through good documentation.
• Clear objectives make it easier to make good decisions.
• There are different kinds of costs, for example, the cost of execution, the cost of making mistakes, reversibility. These should factor into the time taken to make the decision.
• Cognitive effort : how much is being held in your head while taking the decision.
• Consider Emotional triggers in terms of how it influences how a decision is made, and the ease in taking it.
• Adversarial effects where there are people competing with you as opposed to cooperating with you - makes decisions harder.
• When making a decision is difficult, re-evaluate, take the time and consider getting support from other people, including experts on the topic.
• Don't underspend or overspend resources in making a decision: trait of a good decision maker and built over time (and experience?)
• Trick: consider the value of the ideal outcome and whether it is worth the effort that needs to be put in.
• There is no time or energy to make every decision perfectly.
• Grow your skills as decision maker progressively. Practise makes perfect. It is unreasonable to expect to make great decisions right off the bat and suddenly.
• Intuitive decision making is great when pressed for time, but do not expect or trust your gut when in a situation you are not familiar with.
• We are limited in our cognitive and biological resources. It is not feasible to will power your way through anything.
• People who make the most important decisions in the world tend to make different decisions based on their biological setting.
• Hack your heuristics and biases and human nature to make better decisions. At the very minimum: consider that you are not infinite in your capacity.
• Why are people indecisive: they could be distracted, lack the bandwidth to think about other things. Grief and emotions could be detractors. Have the courage to move ahead if you know no new insight is going to present itself.
• Consider a coin toss and pretend this decision is made: if it makes you extremely unhappy, then that is a sign of a wrong decision.
• the application of the PrincipalAgentProblem is a trick whereby you can pretend the long term you to be the principal and the short term you to be the agent.
• ConfirmationBias can affect decision making. Decision makers lack a key psychological habit : once you have seen the answer you are free to pick the most convenient route to the answer, and stop analysing. They tend to swim around like whale in plankton and a decision is taken when an emotional tipping point is reached.
• A DataAnalyst?'s job is maximising insight per minute. Managing analysts is about balancing the costs and benefits of exploration.
• Decision making in organisations: could be impacted by multiple issues like data illiteracy, lack of skill, lack of advocacy, responsibility spread too thin, lack of skills, misaligned incentives. The most common deficiency in decision makers is that they lack the skill to do something.
• Identify the decision makers, and identify their information sources. This includes human and digital sources. Can these decision makers be inspired to ask more valuable questions?
• Understand what repeated decisions have to be made and optimised. Target these to reduce the burden on decision makers. Work with the decision makers to understand their needs and align with their needs. Data science tends to have a deficiency in leadership skills.
• If decision making skills are not available in the team, then one should look at that as an opportunity, and if that is not possible, then it is not worth spending time in that team.
• Goal Setting influence on decisions:
  • Do I care about something and how much do I care about the topic? Evaluate, understand and optimise for the energy available to make the decision.
  • What are the opportunities available to attain the goal?
  • Extremely rigid or concrete goals can cause a bindness and can harm overall progres. Extremely large goal can cause you to lose focus and/or motivation.
  • Have layers of goals that serve different aspects.i.e. Outcome goals, performance goals and process goals.
  • Outcome goal: may not be fully in your control.
  • Performance goal: mostly under your control. Run without panting for 5 km.
  • Process goal: measurable and fully under your control. Example : run 45 minutes a day. It does not matter what speed or cadence. This is similar to the atomic habits book by James Clear.