Data compatibility and post-coronavirus rebuilding

Michael R. Czinkota
Data work needs to recognize the emotional component of information.
Michael R. Czinkota
Data compatibility and post-coronavirus rebuilding

A man wearing a protective mask enjoys the weather near Hudson River Park on April 28, 2020, in New York City. 

In an era of lengthy and diverse supply chains, investors need to transparently identify corporate action and its effect on the market place. Clear rules of origin are just like license plates. They identify ownership and assign responsibility. Labels cannot simply state “manufactured in the European Union.”

Information needs to be compatible across domains. For example, to compare medical information across nations, one has to segment patient differences by age, country, health patterns, variations in the access to medical care, prophylactic treatment and pharmaceuticals.

Culture affects personal behavior. For example, research identified the wearing of face masks helpful to viral containment. In Asia, there was ongoing and rapid use of breathing masks. Particularly in wintertime, masks were encouraged both to protect oneself and others from contamination. No negative connotation is associated with the use of a mask.

By contrast, in the United States, a mask reflects for many the existence of a medical problem by the wearer. In consequence, masks are not seen as protective but rather as an announcer of risk, which in turn negates their use.

Social structure matters, particularly as it reflects differences in infrastructure and trust. Not all countries have the capability to fund and collect data within short time spans. The need to save face can then lead to the furnishing of poor data, delivered with elan.

In consequence, “current” information may really be old and may not even begin to alert users to important changes in one’s society or social conditions.

Emotional component

Data work needs to recognize the emotional component of information. How will people feel about their direct exposure to hard and cold numbers alone? How can one systematically but honestly include emotions into one’s analysis? How to cope with self-fulfilling prophecies? What are the short– and long-term effects of optimism with data — particularly when insights can cover the entire range of a scale. For most people, numbers are mere indicators of opportunities for action and change.

Analyses and forecasts need to consider change. An evaluation based on the next quarter may reflect the next 25 years. Insufficient or incorrect reflection of change and innovation may lead to precariously wrong decisions. Imagine the decision-making process for countertrade, where the outcome and conclusion of an agreement may take decades.

Synchronicity is another important dimension. I am reminded of Ludwig Erhard, second chancellor of the Federal Republic of Germany who was credited with Germany’s postwar economic miracle. When Erhard concentrated expenditures on some sectors and called for a “tightening of belts” for others, these steps were rapidly and fully implemented by government, firms and society, leading to a powerful impact. The players actually cared.

In the case of US economy, the coordinated development of a restructured economy accompanied by a synchronous response of all participants with their resources can turn into a wonderful economy that shakes off the problems of post-coronavirus rebuilding like a duck shakes off water.

Apart from human emotions, economic reemergence requires measurement scales benefiting from recalibration and new benchmarks. For example, a scale measuring export controls which ranges from “no controls” to “tight controls” is only in part complete since it omits policy resulting from subsidies and voluntary restraints.

These conditions are not frozen in salt, but they will change and with them their impact. In a dynamic and complex environment, even the efficacy of Aspirin benefits from review.

Michael R. Czinkota teaches international marketing and trade at the McDonough School of Business, Georgetown University. He served as deputy assistant secretary for trade information and analysis in the US Department of Commerce in the Reagan and Bush administrations.

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