As Covid-19 picked up speed and ferocity, digital dashboards were everywhere.
Published by global health organizations, national and local governments, medical centers and media outlets, pandemic dashboards visualized an evolving narrative of life and death — from case numbers and mortality rates to testing capacity and ventilator access.
Very soon, dashboards were deployed to illustrate all manner of non-medical consequences — whether the collapse in air traffic, the rise in unemployment, the sources of response funding or the rules governing restaurants and bars.
In June, NASA co-created the “Earth Observation Dashboard” which allows “user-friendly tracking” of Covid’s planetary impact on “air and water quality, climate change, economic activity, and agriculture.”
Three interconnecting factors catalyzed this Covid dashboard dash:
• the scale, speed and severity of the pandemic, which demanded the urgent assessment of complex streams of interconnected data;
• the widespread availability of dashboard generating software — including Tableau, Domo, Datawrapper and ArcGIS;
• the omnipresence of smartphones, tablets and computers on which dashboards could be (compulsively) viewed, compared and shared.
Before we sail any deeper into the ever-expanding dashboard universe, we need a definition.
At its simplest, a dashboard is any interface that visualizes one or more sources of data. That said, modern digital dashboards will share some or all of these characteristics:
Dashboards visualize
[multiple] [modular] [real time] [critical] [customizable]
data.
Furthermore, to be functional rather than just ornamental, dashboards require an interactive link to the real world, where data informs action, which in turn transforms data — and so on.
The most familiar model is a car, where the speedometer, tachometer and odometer are in a continuous and immediate feedback loop with the accelerator, clutch and brake. Similar loops exist in all mission-critical dashboards — from military drones to scuba gear.
If driving even a Ford Model T required a dashboard of dials, how much more vital are digital dashes to running not only modern corporations and manufacturing plants, but also their critical underpinnings: power grids, water supplies, global logistics, cloud computing, air traffic control and so on.
Of course, dashboards need not be instantaneous to be useful. Both the economic levers of government and one’s personal fitness goals must be assessed over weeks and months, and their visualization is no less valuable for this lag — especially when future scenarios can be explored using historical data and algorithmic analysis.
Although it took a pandemic to make dashboards a topic of daily conversation, “dashboard thinking” has been around for years — having escaped the confines of complex mechanical systems to penetrate corporate management and mainstream consumerism.
For business professionals, dashboards now visualize corporate “key performance indicators” of every conceivable hue.
And for consumers, dashboards track an ever-growing catalog of human endeavor — pregnancy, fitness, finance, medication, mental health, golf, rock climbing, home automation, meditation and prayer, to name but a few.
Apple’s latest iPhone OS transforms the home-screen from a static grid of apps to a dashboard of adaptive widgets — allowing users to gauge at a glance variables such as stock prices, steps walked and sleep patterns.
Indeed, so glued are we to these dashboard devices, we even have dashboards to track and regulate our screen time.
If you doubt the dashboard’s inexorable rise, Google Trends generates dashboards to plot the popularity of specific search terms — like “dashboard.”
And should you need further convincing, consider the dashboard of the Litter-Robot 3 Connect — “the highest rated, WiFi-enabled, automatic, self-cleaning litter box for cats.”
Like all data displays, dashboards are built on the “pillars” of data visualization:
• comparison — how sources stack up
• composition — how parts relate to the whole
• distribution — how data is grouped and located
• interaction — how processes flow
• relationship — how data sources connect
• trend — how data change over time
By adding to these foundations immediacy, interactivity, flexibility and unified focus, dashboards offer a jailbreak from the static grids of Excel; a reprieve from the sequential death-marches of PowerPoint; and the freedom to take command and control of complex and critical systems.
Such tantalizing potential explains why internet-age politicians sporadically discover “dashboard government” — a hi-tech form of “joined up government” that channels the precocious optimism of Thomasina in Tom Stoppard’s “Arcadia”:
“If you could stop every atom in its position and direction, and if your mind could comprehend all the actions thus suspended, then if you were really, really good at algebra you could write the formula for all the future.”
In Britain, this optimism was epitomized by David Cameron’s much hyped “Number 10 Dashboard” — which proved shorter lived than his Angry Birds obsession. It’s unclear if the “NASA-style mission control” just launched by Boris Johnson will fare any better: the British Covid dashboard “missed” 16,000 cases, because of a spreadsheet file-size error.
In reality, the closest most politicians get to genuine “dashboard government” comes in times of crisis — when they decamp from traditional bureaucratic spaces (Oval Offices and Cabinet Rooms) to secure and smart “sit-rooms” where key figures interact with key data in real-time.
Although such locations existed before computerization — witness Churchill’s subterranean Cabinet War Rooms — as politics and technology become ever more entwined, “sit-room government” may become the norm, and running a country (or indeed a corporation) from a coffin-shaped conference table will seem as anachronistic as navigating by the stars.
Our increasing reliance on dashboards is bound to stress-test the assumptions that underlie them. The most significant of these is whether we can truly avoid “Garbage In Garbage Out,” since nothing can lipstick a dashboard pig if its data are incomplete, incomparable, outdated or plain wrong.
During Covid, doubts have been raised both about the accuracy of specific online dashboards, and the neutrality of the numbers coming out of China, Russia, North Korea, Iran and even the United States.
But data does not have to be manipulated (or mishandled) to be misleading.
Donald Trump’s recent Axios interview with Jonathan Swan contained this revealing exchange about America’s Covid deaths:
Trump: Take a look at some of these charts.
Swan: I’d love to.
[ … ]
Trump: Here is one. Well, right here, United States is lowest in numerous categories. We’re lower than the world.
Swan: Lower than the world?
Trump: We’re lower than Europe.
Swan: What does that mean? In what? In what?
Trump: Look. Take a look. Right there. Here is case death.
Swan: Oh, you’re doing death as a proportion of cases. I’m talking about death as a proportion of population. That’s where the US is really bad, much worse than South Korea, Germany, et cetera.
Trump: You can’t do that.
Swan: Why can’t I do that?
Trump: You have to go by where… look. Here is the United States. You have to go by the cases. The cases are there.
Bloomberg
