International Data Need to Add Up

A useful analysis requires the understanding of data and a belief both in the data and their issuer. Companies, organizations, and scholars wary widely in their interpretation and use. International comparisons often differ substantially in data collection and quality control. This commentary eases comparisons of research across national borders. Here is an international perspective on research numbers, going beyond quantitative data aspects and embedding human warmth and insights. 

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. 

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, the second chancellor of the Federal Republic of Germany who was credited with Germany’s postwar “Wirtschaftswunder” or 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.

On this dimension, President Trump will find his largest risk and opportunity. 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 re-emergence 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. Numbers are only snapshots of a current condition. 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. 

Professor Michael Czinkota teaches International Marketing and Trade at the McDonough School of Business of Georgetown University. He served as Deputy Assistant Secretary for Trade Information and Analysis in the U.S. Department of Commerce in the Reagan and Bush Administrations. 

Urgent need for data deletion in big data era

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18 years ago, I wrote fervently about the imperative of more data deletion in the Journal of International Business Studies: “The growing risk of information overload is likely to lead to the emergence of a new industry concentrated on the reduction of knowledge… Due to rising concerns in the information dissemination area, the role of privacy experts and mechanisms designed to withhold information will also be on the increase”

After six years of testing, Google finally announced the option of “undo send” in its Gmail service. However, rumors of deletion capability are vastly exaggerated.  Instead of actually “deleting” the email after sending it, the new “undo send” function just provides a time delay ranging from 5 to 30 seconds before sending out the email. Once the send button has been clicked, nothing can be “undone” after that time delay . Even now, if you accidentally send sensitive bank information to a total stranger, you still have to get a court order before Google can unsend an email full of sensitive data that  mistakenly arrived in the inbox of a wrong person.

We don’t have the slightest doubt that big data technology has played an irreplaceable role in letting economies boom. Google, for example, has collected data from Gmap in mobile phones to report accurate instant traffic information. IBM’s Watson Supercomputer collects all medical journals and clinical cases and makes them available to doctors.

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After Hillary Clinton’s email scandal, many people prefer a delay to a delete function in order to maintain accurate records. But for privacy’s sake, deletion may be essential. It  can take  a long time for laws to catch up with modern crimes.

Too many data can also disable people’s decision making capacity. Dr. Ron Friedman, a social psychologist on the science of workplace excellence conducted  research on how more information influences people’s decision making. We used to think that more information leads to smarter decisions. However, when data are missing, we tend to overestimate their value.

Increasingly, we can build our understanding based on data derived from applications. We will be able to compare the use of air-conditioning in Shanghai to that in Berlin. A Smart Factory can offer solutions and services to consumers in different  and changing conditions. Key obstacles are the reality of  messy information and the problem of getting rid of useless data.

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The Future is Small Data CLICK TO READ

Just yesterday, Facebook acquired a small Israeli startup called “Onavo” for a cool $150 million. Onavo specializes not in big data analysis – which seems to be today’s hot commodity – but rather data compression and optimization (“small data”). Onavo is of significant value-add to Facebook because its optimization algorithms effectively make the product lighter on data consumption – a major boon to consumers in developing countries that pay a relatively large amount for cellular data – and effective analysis methodologies. In order for Facebook to keep growing, they need to keep growing their network while simultaneously making big data “smaller.”

Social networks like Facebook and Twitter are some of the most useful, updated, and heavily utilized consumer preference databases available – and marketers are constantly looking for ways to monetize on the action. For instance, Facebook has recently been wooing network broadcasters with consumer data reports to help broadcasters understand consumer opinion on their content.

For companies trying to understand foreign consumer preferences, especially in countries in which official data may be fudged or incomplete, it can be quite difficult to ascertain consumer preferences from a hands-off approach. Traditional information agencies such as the Economist Intelligence Unit (EIU) may not have the same reach that social networks do. Social networks, unfiltered by bureaucratic corruption, can bridge the knowledge gap for foreign companies without the risk of government book-cooking. That’s why Facebook needs to grow its presence in developing markets, to make it easier for people to online: to bolster its ad revenues and to deepen its potential as a treasure trove of consumer information.

Acquiring small data pioneer Onavo will certainly make it easier for citizens of developing countries to get online. The more people that are online, the more valuable Facebook becomes. I believe that Facebook, Twitter, et al certainly have the potential to surpass information-collection resources like the EIU, McGraw-Hill, and others at the consumer level – provided that they focus not only on getting more people online, but also making big data smaller. The Onavo acquisition is a step in the right direction.

This text was written and presented by Mr. Ryan Cunningham, Student at the McDonough School of Business of Georgetown University in the course on International Business (STRT-261-01) on October 17th, 2013.

In addition to the written work, the author also offered a very interesting presentation on the issue: Business Intelligence, Facebook, and Small Data.  You can contact Ryan here.