The Problem Solving and Decision-Making Process
by Juan C. Hernandez, Ph.D., Professor of Management
and Director of Corporate Training and Development
IMPAC University

Problem Solving and Decision-Making are tasks practiced in a wide range of organizations. Management and occupational employees engage in solving problems and selecting appropriate courses of action regularly, regardless of the products or services their organizations provide. The activities depicted below are carried out throughout all phases of the typical process improvement cycle.

A brief description of the key concepts and steps associated with a systematic approach for problem solving and decision-making is given below.

A problem can be defined as a “deviation form a standard”. This definition implies that performance standards have been established to help identify deviations and determine the extent to which they affect achievement of economic, customer and productivity targets. If standards do not exist, they must be established to be able to economic, customer and people “value-added”, monitor performance and proactively control behavior of key "variables" over time.

Examples of these performance metrics include:

• Economic Value Added (EVA) - an estimated annually recurring or one-time cost savings.
   

• Customer Value Added (CVA) - a process and/or procedure improvement (e.g., reduction in cycle time and/or defects) that results in a higher quality output delivered to internal or external customers.

• People Value Added (PVA) - a process and or procedure improvement (e.g., reduction in cycle time and/or defects) that results in increased satisfaction of process associates involved in producing the output.

Decision-making is the process of selecting a course of action among "feasible" alternatives. An alternative is considered feasible when it is both "effective" and "efficient", i.e., the selected option will help the organization reach its goals at a reasonable cost.

To be effective in problem solving and decision-making we need to "transform" raw data (qualitative and quantitative) into "meaningful information". This transformation process consists of the following steps:

• Defining the problem
   

• Listing the possible alternatives

• Listing the payoff or profit of each combination of alternatives and outcomes

• Selecting one of the decision theory models

• Acquiring data

• Developing a solution

• Testing the solution

To arrive at a “feasible” solution, we must consider both quantitative and qualitative factors, such as:

• Quantitative Analysis Qualitative Analysis
   

• Logic Weather

• Historic Data State and federal legislation

• Historic Data New technological breakthroughs

• Marketing Research Election outcome

• Scientific Analysis

• Modeling

Following such a systematic process helps management:

• Drive a consistent approach to resolving issues and achieving business improvements.
   

• Simplify communications and issue management across processes/organizations.

• Create consistent time frames to assure timely issue resolution.

• Use quality gates to assure effective issue resolution management (i.e., review/approval of business needs/gaps, action plan implementation evidence and corrective action plans).

• Easily summarize and report key metrics including financial, customer and people benefits.

Finally, implementing and maintaining an effective problem solving and decision-making environment requires continuous development of rational skills, interpersonal skills and sound managerial judgment across all organizational levels.

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