Overview
This lecture covers essential decision making and problem solving skills for laboratory management, including the decision-making process steps, human factors, and both qualitative and quantitative analytic tools.
Learning Objectives
- Recognize features of a good decision.
- Identify the influence of human behavior in decision making.
- Explain the steps to making a sound decision.
- Select appropriate qualitative and quantitative techniques for problem solving in laboratory management.
Characteristics of a Good Decision
- Involves thorough investigation of root causes, potential problems, and symptoms.
- Identifies and evaluates alternative solutions.
- Selects the best solution through in-depth analysis of available information.
- Develops an effective strategy for implementing the solution.
Human Factors in Decision Making
- Emotions, prejudices, peer pressures, and personal interests influence choices.
- These factors cannot be eliminated but can be controlled.
- Objective analytical tools should be used, while also considering human perspective and context.
Eight Steps in Decision Making
- Recognition: Become aware of a problem that requires attention.
- Investigation: Gather data and information, including interviews and issue identification.
- Definition: Clearly define the problem, considering symptoms, one-time errors, and root causes.
- Identify Alternatives: Generate multiple solutions or options to address the problem.
- Evaluate Solutions: Analyze pros and cons of each alternative.
- Select Best Alternative: Choose the most suitable solution based on evaluation.
- Implement: Put the chosen solution into action.
- Follow-up: Monitor compliance and assess if the problem is resolved.
Qualitative Tools for Decision Making
- Personal judgment develops with experience and training.
- Soliciting advice includes brainstorming, synectics, nominal grouping, and the Delphi method.
- Systematic option review prioritizes options; a T-chart can clarify advantages and disadvantages.
Quantitative Tools for Decision Making
- Operations Research provides structured, numeric analysis for decision making.
- Probability Analysis: Assesses chances of events (a priori, empirical, subjective).
- Queuing Theory: Determines staffing needs for varying workloads.
- Linear Programming: Allocates limited resources among competing needs.
- Simulation: Uses models to predict outcomes of different scenarios.
Key Terms & Definitions
- Decision Making — The process of choosing among alternatives to resolve a problem.
- Root Cause — The underlying origin of a problem.
- Qualitative Tools — Non-numeric methods like judgment and group advice.
- Quantitative Tools — Numeric, data-driven methods for systematic analysis.
- T-chart — A visual tool listing pros and cons of options.
- Probability Analysis — Estimating likelihood of outcomes.
- Queuing Theory — Study of waiting lines to optimize service.
- Linear Programming — Mathematical approach to resource allocation.
- Simulation — Modeling real scenarios to predict outcomes.
Action Items / Next Steps
- Review the eight steps of decision making.
- Practice creating a T-chart for a laboratory problem.
- Read more about operations research methods used in laboratory management.