Using Themes for Enhanced Problem Solving
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 analysis. 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 not only become better predictors of things to come but can also 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:
- Things that are accidental but predictable because of human nature.
- Things that are predictable based on other events and interactions.
- 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, by understanding the recurring themes and triggers you can monitor data and activities proactively. 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 a variety of sources in realtime.
Combine that with Semantic Analysis, which is challenging due to the complexity of taxonomies and ontologies, and now that system more accurately understand what is really happening in order to make accurate predictions. Add in spatial and temporal data such as IoT, metadata from photographs, etc. and you should have the ability 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 to think about.
From a practical perspective, keeping these thoughts in the back of your mind will help you see details that other people have missed. That makes for better analysis, better strategies, and better execution.
Who wouldn’t want that?
New Perspectives on Business Ecosystems
One of the many changes resulting from the COVID-19 pandemic has been a sea change in thoughts and goals around Supply Chain Management (SCM). Existing SCM systems were up-ended in mere months as it has become challenging to procure raw materials to components, manufacturing has shifted to meet new unanticipated needs, and logistics challenges have arisen out of health-related staffing issues, safe working distances, and limited shipping options and availability. In short, things are a mess!
Foundational business changes will require modern approaches to Change Management. Change is not easy – especially at scale, so having ongoing support from the top down and providing incentives to motivate the right behaviors, actions, and outcomes will especially critical to the success of those initiatives. And remember, “What gets measured gets managed,” so focusing on the aspects of business and change that really matter will become a greater focus.
Business Intelligence systems will be especially important for Descriptive Analysis. Machine Learning will likely begin to play a larger role as organizations seek a more comprehensive understanding of patterns and work towards accurate Predictive Analysis. And of course, Artificial Intelligence / Deep Learning / Neural Networks use should accelerate as the need for Prescriptive Analysis grows. Technology will provide many of the insights needed for business leaders to make the best decisions in the shortest amount of time that is both possible and prudent.
This is also the right time to consider upgrading to a modern business ecosystem that is collaborative, agile, and has the ability to quickly and cost-effectively expand and adapt to whatever comes next. Click on this link to see more of the benefits of this type of model.
Whether you like it or not, change is coming. So, why not take a proactive posture to help ensure that this change is good and meets the objectives your company or organization needs.
Changes like this are all-encompassing so it is helpful to begin with the mindset of, “Win together, Lose together.” In general, it helps to have all areas of an organization moving in lockstep towards a common goal but at a critical juncture like this that is no longer an option.