The case for more digitization at Covid time

  • -
  • J.Bughin

The case for more digitization at covid time

May 8. The Covid-19 pandemic has officially taken the life of hundred thousands people worldwide. It has put the economies in standstill, with about a 5% decline in GDP for this year, as a result of the lockdown imposed to crush the diffusion of the disease.

While we are at progressive exit now, the challenge remains large to prevent a “L-scenario” of economic recovery. We make the case here for including a digital toolbox to government stimulus plans, so as to maximize a more promising recovery emerging out of the Covid-19 outbreak.

A more pessimistic scenario

Covid-19 impact on economies is estimated to be gloomy. Yet, most estimates are however based on the assumption that the society will go soon “back to normal”, with a gradual and smooth reopening of economies, even if possibly some localized and less prolonged shutdowns are to be implemented to avoid a second wave of outbreak. Those estimates all are leading to a recovery in about one year, and a pandemic that is mastered without any large second or third wave.

Those two assumption may be optimistic. On the health side, there is still a possibility of a second and worst outbreak than the first, like the world had witnessed in major infleuneza pandemics, e.g. during the 1918-19 Spanish flu. On the economic side, there is also a risk of what is called a « L » economic recovery, where the disruptions may lead to a permanent output gap. This is not an “extra doom scenario” – after all, ten years after the sub-prime 2008 crisis and the Lehman Brothers bankruptcy, about 60% of countries in the world, still have an output trajectory below precrisis according to robust research by the IMF.1

A major cause of this gap is a large cut in intangible capital by firms or reduced education due to school close that may impact long-term productivity.2 Other factors are citizens behavior, among which, fear that may not easily go away. For example, more than 40% of US workers do not feel at ease to go back to work,3 while 65% of Chinese citizens might resist to consume as much as before the disease.4

A cost of another outbreak, versus the gradual case assumed, is likely to weight another 2-3 percent drop in GDP, should the risk materialize. The long-term impact, may be of the same magnitude, cumulatively after 10 years. That is, if we use the comparison with the 2008 crisis from the IMF that led to a mode of sustained drop of yearly output of minus 15 basis points a year, for countries affected by the sub-prime crisis.

Digitization as a way to limit covid-19 risk and boost our future

Given those major risks, Covid-19 is also making transparent how digital may be a formidable enabler to fight the disease in the short-term, while building a more productive, and safer society than currently in the long-term. Consider a few examples.

  1. Tracing and testing for the disease. A challenge is that the Covid-19 is very contagious, and one needs to spot infected very quickly and timely, while also act upon the social chains of contacts. Digital technology tools, leveraging location services, big data and analytics, are critical for making this happen, and there is evidence that countries with such tools at hand, mostly in Asia, have been able to better curb the disease.5 This is not exclusive to Covid-19, as nowcasting was successfully used during the 2015 Zika virus, or even for the flu.6

  2. Supply chain boost. A major issue during, and of, the pandemics has been supply chain disruption. Dun & Bradstreet had once reported that million of companies around the world have a first and second tier supplier in the Hubei region, the center of outbreak of the covid 19.7 Digital technologies here may help better anticipate those effects and react accordingly for much better resilience.8 Examples include digital twins as more pervasive simulation tools or effects, and better synchronize responses.9 A large set of companies are also using 3D print of health supplies (eg swabs) to circumvent shortage.

  3. Effective R&D. As early as in February of this year, digital machine learning tools have identified multiple rheumatoid arthritis treatments as being powerfully repurposed for treating the virus. Such type of drugs have been recently confirmed as effective in random health trials by end of April, or two months later.10

  4. Working with, rather, than against the machine. Many companies are now adopting tele-working, and digital automation interfacing tools for work, replacing physically-exposed contacts. Without appropriate technology, the alternative would be not to work for 40% of non essential jobs time. For essential jobs, - those that allow the economy still to work, eg retail logistics, etc - the risk is to expose individuals to the risk of infection. Digitization of the full chain of retail, including e-commerce, has proven to be a very effective solution to the Covid-19 challenge.

In need of faster digital diffusion

The digital technologies above are part of frontier of digitization - as it includes big data, AI, 3D, IOT, digital twins, or still AR/VR. Those technologies, and related applications are however still far from being used extensively both by consumers and enterprises.

For examples, testing and tracking tools based on digital technology have demonstrated very good specificity, eg they may spot 70-80% of infected cases, despite a large set of non-symptomatic cases. The key challenge for the case of digital tracking is that it must have sufficient reach - eg more than 50% of citizens must it to spot infected and warn their social ties. While this means a penetration à la Facebook in the US, this rate is in practice not easy to achieve. Even in countries promoting digitla tracking, the adoption rate is not at this level - it is reported to be at 40% in Iceland, and about 20% in Singapore and Israel.11

Another example is the use of teleworking technology to put to work the workforce, with non essential interaction tasks, while automation may be the solution for virus-prone interactions. About 50% of people never worked from home before Covid-19.12 Yet, again, here, teleworking is usually used by less than 30% of employees in countries such as US or Japan, to date, and half of them only do it for one day a work week.13 Similarly advanced automation is also relatively low, eg about 10-15% in entreprises are implementing, as it is badly perceived as a way of machines against employment.14

Regarding digital supply-chain tools, the effects may be in the range of boosting productivity by 10-30%.15 There as well, the challenge is adoption — only about 40% of companies worlwide have been digitizing their supply chain.

We conclude that digitization holds the promises of both fighting Covid-19 in the short-term as well as offering a solution for faster and stronger recovery of our economies, against the worst case of « L-scenario ». The current economic stimulus plans advocated by many governements must include a digitization tool box - a message to relay in the face of limited awareness of the digital lever in the current discussion of those plans.

References

© Jacques Bughin, all errors remain mine

  1.  Chen W., Mrkaic M., and M. Nabar; “The global economic recovery 10 years after the 2008 financial crisis”, IMF, April 2019. ↩

  2. Baker S., Bloom N., Davis S. J., Kost K., Sammon M., and Viratyosin T. (2020). “The Unprecedented Stock Market Reaction to COVID-19”,Covid Economics: Vetted and Real-Time Papers1, 3 April. ↩

  3.  How employees feel about coronavirus now: A pandemicex survey update ↩

  4. Covid-19 economic impact ↩

  5.  See The western world should urgently play the asian smart route to control the covid-19 ↩

  6.  Akhtar M., Kramer M., and Gardner L. (2019). “A dynamic neural network model for predicting risk of zika in real time”, BMC Medecine, 17. ↩

  7. Ivanov D. (2020). “Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case”. Transportation Research Part E: Logistics and Transportation Review, 136, 101922. ↩

  8. Ivanov D., Dolgui A., Sokolov B.; “The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics”. Int. J. Prod. Res. 2019;57(3):829–846 ↩

  9. Ivanov D., Dolgui A., Sokolov B.; “The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics”. Int. J. Prod. Res. 2019;57(3):829–846 ↩

  10.  Beck B., Shun B., Choi Y., Park S., and Kang K. (2020). ”Predicting commercially available antiviral drugs that may act on the novel coronavirus”, BioRxiv, 2, Feb. ↩

  11. Thorneloe R., Epton T., Fynn W., Daly M., Stanulewicz N., Kassianos A., Shorter G. W. et al. “Scoping review of mobile phone app uptake and engagement to inform digital contact tracing tools for Covid-19”, (2020). ↩

  12.  Covid-19 is a before and after moment in the digital transformation ↩

  13.  Higa K., Wijayanayake J. I. “Adoption of Telework by Japanese Organizations: A Survey Study” ↩

  14. EIBIS 2019 Report on Digitalisation ↩

  15.  Bughin J., and van Zeebroeck N. (2019). “The right response to digital disruption”, Sloan Management Review, The right response to digital disruption ↩

Learning from the curve

An open source research project on COVID19 and economics. A collaboration between academics to reach out to policy makers and the general public.

Website design by Alessandro Gallina