Sense Making Under Crisis
As tradition dictates, each year during the anniversary of Red & White’s founding, I write an article summarising some of my thoughts and learnings from the year gone by …
It was late Jan’20 in Singapore. I stood in front of a Data & Analytics (D&A) class that I was teaching and made an extraordinary claim: that Covid-19 did not originate in China. But that China was the only country capable of detecting it, and that many in the present class had already contracted the virus! You can imagine the uproar. The purpose of the claim was to get the class to consider how our sense-making abilities were poor, and often hijacked during a crisis.
I proceeded to explain to the class that because Covid-19 had flu-like symptoms and low mortality rate, it would require both time and a large population to detect the signals (from regular flu); it would take at least 3 consecutive months of statistically significant variation in flu-related deaths to trigger an investigation. China checked all the boxes: large population to derive statistical significance, centralised and coordinated data collection, and deep bio-medical expertise. No other country satisfied all these necessary conditions.
Further, given that Singapore was a travel hub, it would only be reasonable to assume the local population came into contact with the Covid-19 virus between Q3 to Q4'19. I asked who had a bout of unusually bad flu in Nov-Dec’19 and many raised their hands. I rest my case.
The initial strong disbelieve in the class started to dissolve as people realise the possibilities …
The ability for sense-making goes well beyond the requisite data collection and analysis. It is about understanding the (bias) assumptions we make and how we interpret (and fit) the data. Sadly, it is a skill we don’t teach. Perhaps because we simply don’t understand or don’t appreciate the principles of the craft. And during periods of crisis, our ability for sense-making is probably the critical difference between survival and demise.
The pandemic was a necessary wake-up call for many — on the personal, business and government fronts. While much of the digital gap was self-imposed and easily overcome as seen in how quickly work switched to remote, the D&A divide was palpable. The more digitalisation we pursue, the more we lose embedded human cognition (i.e. capacity for agile intervention), and the more we require D&A expertise to supplement this loss. Many of our digital work processes were simply not instrumented for D&A and thus, sense-making became increasingly diluted.
Crises are low validity situations; and during such situations, what’s needed is deep expertise in Descriptive and Diagnostic Analytics. I laughed at the attempts by many established institutions to predict the ‘flattening of the curve’ during this pandemic as it was inappropriate and a complete waste of time. With a focus on high quality and diverse data, human input is what’s needed to arrive at decision-making during low validity situations; predictive analytics will not provide any better accuracy.
With the rise in digitalisation due to this crisis, companies are now scrambling to either build out their D&A capabilities or re-wiring it to address this sense-making gap. In a post Covid-19 world of remote working, the ability to interpret and present data will be a critical differentiator in getting work done effectively, and we need to be equipping all our employees with these skills. This is not a competency that should be reserved for data scientists and business analysts. We need to take a more holistic approach to D&A, embracing it as a sense-making and decision-making discipline. That’s much more than what data science is set up to do. But it’s a good wake-up call.
