Agile Insight Stories

Agile insight stories decide whether time and money invested in extracting insights go to waste.

Insights are catalysts for business decisions

Information superiority for business is aligned with the phases, Observe, Orientate, Decide & Act (OODA) of a cyclic decision process. Insights are associated with these phases and their purpose is to empower stakeholders to Act.

Insights must stand out from noise

However, insights are not automatically actionable. Nowadays, humans are constantly flooded with a mix of relevant and irrelevant information. Insights must stand out from noise, and taking them across the finish line needs extra work.

The last mile determines whether costs per insight are justified.

Sensemaking for stakeholders

In content marketing, it is a proven fact that attracting the attention of humans and providing emotionally focused, persuasive argumentation makes information memorable and understandable. Customers are more likely inspired to take action and purchase.

Making insights memorable and understandable is called data storytelling, and stakeholders faced with engaging insight stories are more likely inspired to take action than from charts on a dashboard.

According to Harvard Business School,

“data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations.”

It’s the way in which we argue with data to convey a message.

Insights stories are the path to value

In many businesses, data storytelling is still viewed as a theoretical peripheral soft skill. But in practice, it is a central business capability that decides whether time and money invested in extracting insights go to waste.

Insight stories combine insights, visualization and narrativity in a single product. Narrativity makes the difference, and as is with any other meaningful narrative, it is based on the elements, character, setting, conflict and resolution.

Business twins are the mentors in the hero's journey

In the context of information superiority for business, digitized enterprises are represented by interconnected digital twins of core business entities. This introduces a fixed character:

The business twin takes the role of the mentor in the story, that answers questions like: What If, What Now and What Next.

The mentor, a digital twin of the customer, passes on his insights to the hero, a marketing or sales person, and acts as a catalyst for the hero to make successful contribution to the economic growth of the enterprise.

Explainability & understandability are key

Due to the complexity of the business problems and the associated data science approaches for solving them, successful insight stories must gravitate around explainability and understandability.

A proven approach for making algorithmic solutions understandable is analogy-based reasoning. The point is to compare complex issues with similar but easier-to-understand situations in order to be able to transfer the solution principle to them.

Large language models boost data storytelling

Data storytelling sounds complex, and it is complex. The good news is, that data storytelling is the realm, where large language models like ChatGPT make the difference.

Getting familiar with the definition of prompts to retrieve inspiring, emotionally-focused and persuasive blueprints for stories about heros and mentors, their conflicts and resolutions, is usually a matter of days.

Combined with modern visualization makes insights stand out from noise and inspire stakeholders to take the right action.

The use of large language models decides whether your business produces zero insight waste.