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  • Writer's pictureMartin Trevino


Updated: Jul 28, 2023


What exactly will Next Generation Analytics look like? "We don't know, we're figuring it out now, but three things will be true – its foundations will be rooted in science, UX/UI design will incorporate the Neuro and Cognitive Sciences, and its central focus will not be on the data but on how human beings trust and make data-informed decision.

– the Author

Within the fields of Data Science and Business Intelligence, the effectiveness of storytelling through Visual Analytics is almost universally supported by practitioners. And yet when asked precisely how storytelling positively affects data-informed decision-making, few practitioners have little more than a cursory level of understanding. And yet it is true that storytelling possesses a seemingly magical ability to resonate and influence human understanding and decision-making.

Next-Generation Analytics & the Human Brain

As we build the next generation of Analytics, we face several wicked problems. These problems range from the changing nature of data (the technical domain) to our ever-growing understanding of how the human brain makes data-informed decisions (the Human Factors domain). Data brings numerous challenges; among them is the increasingly multi-dimensional nature of data, including multi-spatial and multi-temporal aspects. This presents challenges at both ends of the continuum of data science and human understanding/decision-making. When examining data and developing a mental model/knowledge of presence and relationships (correlation, cause, effect, etc.), the outcome is cognitive overload and data and information exploration termination. Storytelling has the potential to provide a vector by which to present coherently present massive, multi-dimensional data, prevent information overload, and by extension, cognitive errors in understanding and decisions themselves. Next-generation analytics and decision science will be as much about understanding how the human brain processes and makes data-informed decisions at the Cognitive and Neuroscience level as it will about the modeling and mathematics of data science.

Geotemporal storytelling as a component of the next generation of visual analytics, particularly in environments where time and multi-dimensional data are pervasive and wicked elements, holds tremendous potential to influence human understanding and decision-making. From a Neuro and Cognitive science view, Geotemporal storytelling represents a proven approach to multi-modal cognition, a central concept in next-generation analytics. Initial conceptualizations from a UI/UX perspective use 3D technologies (gaming engines) juxtaposed with 2-dimensional maps and traditional interactive visual analytics. It is through the novel blending of the new and old in UI design that we have the potential to fundamentally alter the sensory experience for decision-makers and the paradigm in data-driven decision-making.

A central intent of the next generation of visual analytics is to attempt to alter the sensory experience in ways that "wake up" the brain and create higher degrees of resonance. This includes the on-demand ability to explore data and information vertically and horizontally over time. The hypothesized result will be the improved updating of the brain's Internal /situational model, more accurate situational understanding, improved actionable decision-making, and even more resonance when reporting at the highest levels of the enterprise and government.[1][2]

The answer to this question is as simple as it is profound; storytelling is not only a mode of information transmission but also of Reasoning - AKA Thinking. At the center of storytelling effectiveness are the "why" and "how" aspects that this mode of communication can almost universally resonate in the viewer's minds. This is not true of today's overwhelming number of visual analytics that populate dashboard design.

At the deepest levels, the reasoning process surrounding storytelling encompasses both hemispheres, numerous centers, and human brain systems. The process (as we understand it) is extraordinarily complicated; A prime example is the visual system. This brain's visual system alone is believed to utilize some 30 cortical areas dedicated to visual processing, adding verbal narration, text, etc., which requires even more of the brain to be engaged. Among the intractable equations within the human brain related to data-informed decision-making is the part of the brain that controls decision-making and governs trust and feelings but cannot perform analytic thought. The part of the brain that controls analytical thinking has no capacity for decision-making. Thus, when someone says, "I make data-driven decisions all day long," that's not precisely true and provides a glimpse into why some forms of decisions are highly resistant to data.[3]

Non-Trivial Challenges

Multi-dimensional data has become the norm in complex environments. From a design perspective, this has increased the complexity of coherently presenting data to decision-makers without creating cognitive overload. Next-generation analytics with Decision Science as a foundational element will attempt to address this through understanding the Neuro and Cognitive aspects of decision-making. This brings us to a central tenet of Next Generation Analytics – the intent to alter the sensory experience to benefit the user – think Human Centric through Multi-Modal Cognition. These terms must be introduced into the vocabulary of UI/dashboard designers, data scientists, data architects, and decision-makers.[4]

Next-generation analytics will present multiple views, framings of data, and contextual information, presenting a dramatically altered visualization (designed to 'wake up' the brain) and enabling the user to explore data in ways that uniquely resonate and enable the specific user to interrogate data. For example, think of Operational Technology (OT) being examined by the CISO or Ops team. The exploration would begin with alerts adjacent to a 3-dimensional, interactive view of the facility coupled with motion and juxtaposing of objects. Visual analytics will appear as the user selects tooltips, and dynamic drill-down is available through view selectors. With scientific studies showing an almost equal percentage of users preferring either juxtaposing or motion, the flexibility to select and or rapidly switch views has the potential to produce a more comprehensive and integrated mental model in the mind of decision-makers. The entire environment can be altered with a single click to visualize the PraxiSphere of objects and entities in high dimensional space or space-time cubes to illustrate the geometry of parts and all. From this perspective, we can mathematically determine a geometric threat level or security posture for a group, network segment, building, or plant. Due to its nonlinear and abstract nature, it should be noted that space is a wicked aspect of storytelling.[5] This is because nonlinear does not align with linear event sequences. Thus, as we construct Geotemporal stories, these should be accompanied by visualizations that enable space to be free of linear time – no minor thing to accomplish coherently.

In conclusion, next-generation analytics will enable multi-modal cognition through geo-temporal, multi-spatial, novel interfaces with the ability to dynamically explore data in vertical and horizontal manners while addressing time and simultaneously offering an option to be free of its constraints. This, coupled with an entirely new generation of metrics/KPIs developed from geometric relationships, is hypothesized to enable the building of cognitive colleges in impossible ways in today's "flat" interfaces and dashboards. [6][7]

From a technical/developmental perspective, the not-trivial decision of pathing and framing must be addressed. This includes but is not limited to displaying the information through predefined paths such as personas, time-based sequences from predefined viewpoints, or open data segments to be freely explored by the user must be undertaken. Using other methods, such as transitional techniques and visualizations, juxtaposing, animation, slideshows, layer superimposition, and even space-time cubes, are now being addressed to create dynamic environments for high levels of understanding while minimizing information overload. Geotemporal scaffolds are among the techniques borrowed from other scientific disciplines for use in Enterprise Risk and Cyber Security in OT environments.

Today we can use technological advances to create complex multi-dimensional, dynamically linked views with time as a natural element. This mimics how the human brain processes and perceives information, even though time as a component can be an issue for various reasons. These reasons range from the quality and quantity of multi-dimensional data/information to how the memory is created and functions in the brain. It's important to note that scientifically we have proven that mental models generated from maps and stories differ from those of the analytics we now utilize in dashboards.[8]

Trust in data also becomes a factor when dealing when time is a central element, and the framing of the data differs from the decision-maker's mental model. Here, Geotemporal storytelling has the unique potential to avert the outright dismissal of information that disagrees with the internal model of the decision-maker. Storytelling offers higher degrees of resonance and the ability to influence individuals to levels that discrete numbers or even charts/graphs have difficulty doing. Next-generation analytics incorporates multi-scaffolding data techniques to enable Geotemporal and Multi-spatial views simultaneously. These techniques hold the potential to form a unique analytic backbone that can significantly improve the formation of unified situational models in highly complex and high-risk environments.

Conclusion & UI/UX Design

From a design perspective, it is here that next-generation analytics begins to take shape. A prime example is the developed spatiotemporal scaffolds and their potential to augment traditional metrics, measures, and indicators in framing and informing of timeline occurrences. Additional context and drill-down capability are added through hierarchical tree maps, force-directed network graphs, double helix, and other relevant visual analytics to fundamentally alter the user's sensory experience and data exploration processes. The intended outcome is to enable the human brain to do what it does best – derive understanding and make decisions in complex, unstructured environments.

References [1] Among the most effective ways to convey the Cyber threat landscape or Enterprise Risk and actions being taken by the firm to the Board of Directors is through Geotemporal Storytelling. [2] The term “situational model”: Dijk, T.V.; Kintsch, W. Strategies of Discourse Comprehension, Academic Press: Cambridge, CA, USA, 1983 [3] Decisions that require high degrees of complex reasoning – termed ‘Higher Order’- are highly resistant to data. Think of strategy formulation, mergers, acquisitions, or design work that requires a high degree of creativity and reasoning. You will also find high resistance or outright dispensation with data when it contradicts the mental model of the decision-maker. [4] Terms first, then we discuss the foundational elements such as ‘intelligent data,’ visualizing geometric relationships, and use of high dimensional space, space-time cubes, and 3D interactive environments – currently being explored by the OT Space. [5]Kriglstein, S; Pohl, M,P; Smuc, M. Pep your time machine: Recommendations for the design of information visualizations of time-dependent data. In Handbook of Human Centric visualization; Springer: Belin/Heidelberg, Germany, 20124; pp. 203-205 [6]KPI’s- Key Performance Indicators. [7] PraxiSphere is my term intended to convey all things in a technical environment – IoT, CPS, Routers, Computers, MES systems, - all things a cyber security team would have to deal with in an OT or IT environment. [8] Tversky, B. Cognitive maps, Cognitive Collages and Spatial Mental Models; Frank, A.U., Campari, I., Edcs.: Springer: Berlin/Heidelberg, Germany, 1993; Volume 716, pp. 14-24

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