Have you ever wondered what existed before the ubiquitous dashboards that we see everywhere today?
I have a dashboard that shows how many runs I completed in the last year, but I need an extra paid subscription to access data from earlier. I didn’t realize I required this, but I do right now! In contrast, I had been using Pokemon Go as my run tracker up until this point, and I had logged quite a few kilometers on it. The data is represented so well, and I’m able to grasp my progress (or lack thereof) instantly. Before dashboards, I used to journal just the total distance in a table with dates, times and distances: in short, a lot of numbers.
It gets impossible to wrap your head around them. For example., 1,000,000,000 (a billion) seconds is a lot, but we don’t know what a lot means. We can do a bit better with 1,000,000,000 seconds ~ 11574 days ~ 1,653 weeks ~ 381 months ~ 32 years. The years being the easiest to relate to – I was born a little over 1,250,000,000 (1.25 billion) seconds ago.
Dashboards give life to lifeless numbers and create stories that are easier to understand and remember. Before dashboards, we had beautiful hand-drawn charts/graphs that narrated a story. It’s great to put a perfect plot together, but very tedious and time-consuming – a computer makes this quick and efficient. Dashboards add multiple such graphs into an integrated and simplified view. We get a combination of bars, pies, lines, plots, etc. to represent different types of information. It’s extremely effective to summarise one type of data against one metric. e.g., running distance over time – simple, clean, and elegant. But if I put a few more parameters like running distance over time with a time of day, speed per kilometer, average speed every day, the incline of the landscape, and a map overlay and compare this with my peer group in different parts of the world, we arrive at something like this.
And I haven’t unlocked premium features!
I’m no professional runner, so the combinations are overkill, but you get the point. In today’s age, dashboards become complicated and overwhelming very quickly. Dashboards don’t deal well with information overload – much of the data is summarised, averaged, put in graphs, etc. and users find it impossible to make sense of key data points. To compensate for this, especially for complex systems that power the world, we have Hollywood-esque TV walls with multiple teams managing key parameters 24/7/365. All of this builds up a cognitive overload that increases exponentially with marginal progress in productivity. The result: teams ignore 99% of all data points and make decisions with only 1% of the information.
In this age of hyper-connected people and IoT, we can’t just keep adding more TV screens, people, and dashboards to solve the problem; there has to be a better way. We are entering a world of hyper-specialization with fewer generalists around (hopefully, it will balance out soon), and the specialists will have no idea about various factors outside their area of expertise that impact processes/systems.
The way out is to have 3D dashboards that create digital replicas of all assets, systems, processes, and facilities around the world and show information associated with them in 3D. By converting text/image/video into immersive experiences, we create a tool that is easy to understand and use. We get a view of large complex data and critical information necessary to execute corrective actions rather than post-mortem insights.
3D dashboards of our critical infrastructure bring in not only data, but also written manuals, and historical maintenance information. The icing on the cake is that we now empower multiple experts who can simulate behavioral scenarios on the digital twin to take corrective actions much faster than our current mechanisms.
Examples of 3D dashboards:
1. Integrated Operations Centre for an Oil & Gas facility
2. Integrated Command and Control Centres for Smart Cities
3. FMCG Factory Floors
4. Maitenance, Repair, and Overhaul for aircraft