Using Themes for Enhanced Problem Solving

Posted on December 23, 2020 Updated on November 28, 2023

Thematic Analysis is a powerful qualitative approach used by many consultants. It involves identifying patterns and themes to better understand how and why something happened, which provides the context for other quantitative analyses. It can also be utilized when developing strategies and tactics due to its “cause and effect” nature.

Typical analysis tends to be event-based. Something happened that was unexpected. Some type of triggering or compelling event is sought to either stop something from happening or to make something happen. With enough of the right data, you may be able to identify patterns, which can help predict what will happen next based on past events. This data-based understanding may be simplistic or incomplete, but often it is sufficient.

But people are creatures of habit. If you can identify and understand those habits and place them within the context of a specific environment that includes interactions with others, you may be able to identify patterns within the patterns. Those themes can be much better indicators of what may or may not happen than the data itself. They become better predictors of things to come and can help identify more effective strategies and tactics to achieve your goals.

This approach requires that a person view an event (desired or historical) from various perspectives to help understand:

1. Things that are accidental but predictable because of human nature.
2. Things that are predictable based on other events and interactions.
3. Things that are the logical consequence of a series of events and outcomes.

Aside from the practical implications of this approach, I find it fascinating relative to AI and Predictive Analysis.

For example, you can monitor data and activities proactively by understanding the recurring themes and triggers. That is actionable intelligence that can be automated and incorporated into a larger system. Machine Learning and Deep Learning can analyze tremendous volumes of data from various sources in real-time.

Combine that with Semantic Analysis, which is challenging due to the complexity of taxonomies and ontologies. Now, that system more accurately understands what is happening to make accurate predictions. Add in spatial and temporal data such as IoT, metadata from photographs, etc., and you should be able to view something as though you were very high up – providing the ability to “see” what is on the path ahead. It is obviously not that simple, but it is exciting.

From a practical perspective, keeping these thoughts in mind will help you see details others have missed. That makes for better analysis, better strategies, and better execution.

Who wouldn’t want that?