Structured analytical techniques

Module title:

Structured analytical techniques

Module overview:

Students learn to apply structured analytical techniques to overcome cognitive limitations and instinctive mental traits in decision-making and business decision making. Students will learn the role risk assessments, data gathering and data dissemination, pointing out overall importance of analytical techniques to policymaking and uses critical exercises and case studies for student development.

The objectives of the course are to enable students to:

• Overcome cognitive limitations by taking them through a process that generates more imaginative thought

• Identify assumptions regarding a particular problem set and apply assumptions challenging methods

• Apply a variety of analytic techniques that can be used throughout the analysis framework (analysis, synthesis, and estimation).


Introduction to analytical management and structured analytic techniques

Structured analysis:

- cause and effect techniques

- decomposition and visualization techniques

- hypotheses generation and testing techniques

- scenarios and futures analysis techniques

- indicators – descriptive and predictive

- indicators validator

Case analysis.

Literature:

Required readings:
1. Pherson, R. H. and Heuer, R. J. (2020) Structured Analytic Techniques For Intelligence Analysis, Third edition, Washington D.C.: CQ Press
2. Kopal, R. and Korkut, D. (2020), Analitički menadžment, Zagreb: Algebra University College

Supplementary readings:
1. Richards, J.H., Pherson, R.H. (2010) Structured Analytical Techniques For Intelligence Analysis, Washington D.C.: CQ Press
2. Miller Beebe, S., Pherson R.H. (2011) Cases in Intelligence Analysis: Structured Analytical Techniques in Action, Washington D.C.: CQ Press