In today’s world, data is omnipresent. We are surrounded by it, and it has become a crucial element in decision-making processes. The rise of Artificial Intelligence (AI) has enabled us to analyze and interpret vast amounts of data, uncovering patterns and trends that were previously unknown. This has given birth to a new field: AI-driven foresight. Yet, with the growing amount of data, challenges arise when it comes to communicating the results of data-based approaches. Here, we need to be aware of a view rules to translate rich data into targeted and added-value information. Data narratives and the Narrative Activation Space are key to turn data into action.
Many projects today – including foresight projects, which aim to predict and prepare for future events – involve a vast amount of data. The challenge lies not only in collecting and analyzing this data, but in drawing reasonable and communicative conclusions from it. The question is: how can we extract meaningful insights from the data and communicate them effectively to stakeholders? AI-driven foresight uses horizon scanning approaches with a huge amount of data. It can be used as a “research partner” for finding, structuring and discussing future-related data. But finding data is not the end of the road. Raw data or uncoupled information cannot unfold impact until they are utilized in an organizational context. This is where future-oriented communication comes into place.
Finding data is not the end of the road. Raw data or uncoupled information cannot unfold impact until they are utilized in an organizational context.
There are a couple of emerging trends in digital communication that we need to keep in mind when it comes to (future-oriented) data communication: the growth of social media, the proliferation of mobile devices, the convergence of media and an increasing importance of data privacy and security. At the same time, we need to take into account ethical considerations in digital communication like misinformation, privacy violations, or social manipulation. The richness of data becomes a threat if not properly and transparently used for communicative purposes. This is even more the case when it comes to future-oriented communication where strategic messages are linked to assumptions about future developments.
The Narrative Activation Space: the next step towards explaining and utilizing complex data
One of the most famous concepts in knowledge management from data to competency comes from Klaus North (2002): The “Knowledge Ladder” (German: Wissenstreppe”). North describes several steps how signals develop into knowledge, capabilities and competence. Data is here seen as one step that gives meaning to signals/facts, whereas information creates meaning in a certain context. As a next step knowledge is built for a particular application that creates action and motivation (see post picture). Thus, the ladder follows the logic of consciously bringing data to a informational and organizational context.
Yet, it is worth adding one important peace here: the Narrative Activation Space. Narratives, engaging stories and storytelling can be seen as a powerful bridge between often abstract information and data. Knowledge becomes vital in an organization when you match it with stories how information, data and signals relate, how they develop and are connected to each other. For future literacy, such stories could be imaginations about future development paths based on data linked to trends. Knowledge is only valuable if it is shared with stakeholders inside and outside and organization. Therefore, the way how knowledge is expressed matters. If you use storytelling and narratives, you can increase motivation and action even more.
Knowledge becomes vital in an organization when you match it with stories how information, data and signals relate, how they develop and are connected to each other.
From data to engaging content
The key to successful communication lies in telling future-oriented transformational stories from data. This requires more than just presenting numbers and statistics; it demands a narrative that is both informative and engaging. Effective communication of data-driven foresight requires a multi-faceted approach.
„When data is shared transparently and in a comprehensible format, it becomes more persuasive and impactful, and creates a common language that encourages cross-functional collaboration. But how do we weave the data in a way that can make it easier for audiences to grasp the key messages?“ Ross Jenkings (Decision Foundry)
This includes:
Transparency
First, you need to ensure that the data and methods used are transparent and understandable, allowing stakeholders to trust the insights gained. No one will trust you core messages about any data if it is not clear and transparent. Data can come of a variety of sources like surveys, social media or databases. It can even come from advanced in-house data labs covering vast amounts of data. It can combine multiple sources of internal and external data. Keep in mind to tell your audience why a particular data set matters and where it comes from. Transparency is key.
Information Structure and Link to Overall Communication Strategy
The majority of data comes unstructured. This is where you need a structure in your data. You should know your audience and define communication objectives. What do you want to tell to whom? In my experience, most data can be structured in a way to create a story. For instance, if you want to show how future markets or technologies will evolve you could focus on data points like market volume, market and technology trends, competitors or related branches to structure information.
Related data could be patents, publication trends, start-up investments or CEO statements. The list is extensive here. The point is: define you goal of analysis, analyze your target group and structure information specifically for this group. Please make also sure that the information structure is in line with all you communication, e.g. corporate designs, core strategic messages and the way you usually approach your general audience. Do not underestimate the value of strategic communication in data-based communication.
Narratives
Once you structured your information you can continue scripting a story about your data structure. Craft a compelling narrative around the data, using a clear structure and visualizations to convey complex information in an intuitive way. It provides context, explains why this data matters and gives key insights. You can use the basic narrative structure where there is a beginning, transformation and end. This helps you in underlining why the data matters. Following the example above, you could show that a market was initially saturated but at one day a new technology was introduced that changed the market tremendously. The data behind it can be used to proof the story well. As this simple example shows, a narrative structure brings data to life. Narratives are strong elements for telling even complex things.
„The cornerstone of DataStory is gaining an intimate understanding of your stakeholders before designing your narrative.“ Kevin Hanegan (Turning Data into Wisdom)
Pictures and Visuals
Visuals, pictures, diagrams and infographs are a very good tool for showing the background behind you data-based communication efforts. It is the perfect addition to a data narrative approach that simplifies complexity, enables a smooth way of highlighting core facts and helps in supporting transparency and comprehensibility. Be creative here and use the defined structure and storyline as an orientation of what visuals to be included.
Flexibility and Adaptability, Monitoring and Updating
Perhaps, one of the things that are often forgotten is monitoring your data-based communication. Data changes and data sources may change fast. The same goes for the stories you tell. Make sure to have all your communication up to date and change it if necessary. As we talk about stories here, it can be even beneficial to update your narrative once there are changes. Keep you communication lively. Think of it like a stock exchange of data, where the foundations of stories change naturally.
Data Literacy
Not to forget, one the greatest misunderstandings is the assumption that all people have an understanding how to interpret data. This underlines the importance of involving the human behind the data, ensuring that insights are not only data-driven but also contextualized and nuanced. By promoting data literacy, we empower stakeholders to make informed decisions. For your communication you may think of a glossary or simple explanation of what’s your data about. Again, transparency and clarity are key.
By telling future stories that are well-grounded in reliable and comprehensible data, you can ultimately combine the power of big data and AI as well as narrative imagination
The value for foresight and future-oriented communication
You may finally ask yourself: what has AI-driven foresight or future-oriented communication to do with it. Well, the answer is simple: In my point of view there is no better type of communication than telling stories how trends, technologies, markets or societies may develop. It sparks imagination and creativity. By telling future stories that are well-grounded in reliable and comprehensible data, you can ultimately combine the power of big data and AI as well as narrative imagination. By combining a well-designed data strategy with strategic communication, foresight and future-oriented missions can achieve more accountability and meaning.