Principles of Analysis Course
Aleph Insights’ Principles of Analysis Course gives experienced analysts a deeper understanding of structured analytical techniques, giving them the tools to decide when and how to apply different methods, and the confidence to explain these decisions to their customers.
The Principles of Analysis Course runs for two days and covers a broad range of analytical concepts and techniques within a staged and coherent curriculum. It focusses on answering practical questions using realistic data, drawing primarily on real problems faced by the course attendees. The techniques covered by the course are appropriate to a wide variety of analytical challenges, ranging from military-political forecasting through to civil contingency planning or risk assessment. The course structure is outlined below.
If you are interested in understanding how the Principles of Analysis Course can help you develop your team’s analytical skills, please get in touch.
aleph@alephinsights.com
Considering what defines an analyst, what skills and functions separate them from other roles within an organisation.
Distilling your customer’s requirement into an explicit question and understanding what kind of analysis this question will need.
Looking at the centrality of hypothesis generation to the analytical process and examining techniques to help you develop focussed hypotheses that are pertinent to your question.
Understanding when and how it is appropriate to make probabilistic judgements, learning about common cognitive biases which affect probability judgements and exploring Bayesian approaches to estimating probability.
Practising the use of hypothesis testing techniques such as Analysis of Competing Hypotheses (ACH), to form defensible judgements about hypotheses, which can be clearly articulated to your customers.
Analysing evidence-based approaches to effective forecasting and knowing how to improve your own ability to make judgements about future events.
Using techniques such as Fermi Estimation to help generate estimates in the absence of reliable data, and backcasting to better identify indicators, warning signs and information gaps.
Producing and utilising base-rates over defined timescales to increase the accuracy of your forecasts.
Practising forecasting techniques with real data that can be gathered about a problem you are currently dealing with.