The Problem
Why do we need a multi-dimensional platform? It's a boring discussion for most. However, for many years we have collected and processed visual information for work and education from flat surfaces — on paper with books, news clippings, reports — and more recently from a computer or mobile screen that allows us to quickly access a higher quantity of information.
What's the problem? Most of the information we examine should be represented in a true three-dimensional environment. You might immediately think of a video game, yet how 3-D is it if you are navigating through it on a flat screen? It's not and the advent of immersive Virtual Reality (VR) and Mixed Reality (MR) will change this in a major way. Consider two facts:
Data visualization tools have made it easier to glean intelligence from a mass of information. Today’s tools are still inefficient, as they fail to incorporate the full science of human visual perception into data visualization, which can lead to an increased probability of human error.
Corporate strategy pioneers including Harvard Business School's Michael Porter, Clayton Christensen, and BCG founder Bruce Henderson have long discussed how companies operate in a three-dimensional environment. It has been applied and easy to understand, but difficult to properly visualize.
What's the problem? Most of the information we examine should be represented in a true three-dimensional environment. You might immediately think of a video game, yet how 3-D is it if you are navigating through it on a flat screen? It's not and the advent of immersive Virtual Reality (VR) and Mixed Reality (MR) will change this in a major way. Consider two facts:
- 90% of information transmitted to the brain is visual
- Visuals are processed 60,000X faster in the brain than text
Data visualization tools have made it easier to glean intelligence from a mass of information. Today’s tools are still inefficient, as they fail to incorporate the full science of human visual perception into data visualization, which can lead to an increased probability of human error.
Corporate strategy pioneers including Harvard Business School's Michael Porter, Clayton Christensen, and BCG founder Bruce Henderson have long discussed how companies operate in a three-dimensional environment. It has been applied and easy to understand, but difficult to properly visualize.
Our Goal
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Big data only continues to get bigger. The challenge for businesses of the future is to draw valuable insights from this ever-growing pile of information. Unsurprisingly, data visualization tools (such as Tableau) have enjoyed strong growth because they enable executives to use the human mind’s ability to detect visual patterns (fine-tuned over millennia) in datasets.
Yet, as data grows in volume and complexity, these tools will reach a limit as to the insights they can provide. This is because they are limited to presenting data in two dimensions: either on a screen or on paper. We are working to develop an enterprise-grade, data-visualization software platform that interfaces with commercial off-the-shelf VR and MR hardware. For the first time, executives and managers will be able immerse themselves in the “big picture” – and, in so doing, fully understand the relationships that drive the success (or failure) of their firms. |
Our Solution
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With software built for use on a Virtual Reality headsets such as the Oculus Rift or HTC Vive, VRtices delivers a new type of data visualization. A firm’s performance is impacted directly by its contributive ecosystem: customers, suppliers, and competitors.
VRtices generates insight into where firms themselves can move for short and long term growth by capturing advanced warnings of ripples effects in the contributive ecosystem. With more information on demand, users will be able to make faster and more accurate decisions. Visualizing the competitive ecosystem of a company allows them to see where there is value and create a virtual war room that simulates the big picture. It is very difficult to do with a two-dimensional space and users are more likely to lose engagement or have a higher error rate while interpreting data points. Consider a network visualization that represents "non-linear" data that goes in multiple directions. If you want to fully grasp the entirety of it, can you do it from a flat screen without flattening the data? To truly understand and assess it, you need to be immersed in a visual environment where you are surrounded by the data. |