Economic Data Discussion Reply

Question

Discussion Reply on the below thread: 275 words and 3 peer reviewed articles from (2017-2021) please use APA 7 and include the DOI in reference area:

In the article by Hughes-Cromwick and Coronado (2019), the authors describe the number of organizations in the private sector utilizing government-provided open data for internal economic decisions. Hughes-Cromwick and Coronado note that government data usually complement organizations' internal data, as theirs is insufficient to drive optimal business decisions. Industry sectors that rely on government data to support business decisions are called government-intensive-data-sectors by the Economics and Statistics Organization. These sectors include the automobile industry, the housing market, or retailers. Information is used to make production and inventory decisions or even market expansion plans.

Hughes-Cromwick and Coronado (2019) speak of the value of this information to these organizations and note that these organizations' use of government data has significantly increased revenues by including government economic data in their business decision-making process. According to the World Bank, the valuations of some companies have grown to more than $1 billion by using open government data. Hughes-Cromwick and Coronado write that government data is a strategic asset for US businesses, but the value is difficult to measure.

They speak of value as a noun in that it is important or provides worth to businesses. Others studying open and internal organizational data speak of value as the verb describing an asset with monetary value (Oxford English Dictionary, 2021). The balance of this discussion will focus on the distinction of the two values, the challenges of open data, and future research opportunities.

Current Trends in Data Valuation

Any organization can recognize the two valuations of data. The value of data gleaned from other sources may be of great importance and significance in driving business decisions. On the other hand, the value of data, such as customer information, can have a monetary value when used as a marketable asset. Companies such as Google or Facebook have a significant amount of consumer information that can be sold to advertisers. In his book, Laney (2020) developed the concept of Infonomics, which is “the theory, study, and discipline of asserting economic significance to information. It provides the framework for businesses to monetize, manage, and measure information as an actual asset”.

Using Infonomics allows asset managers to utilize standard practices to value, handle, and market information assets. Utilization of Infonomics involves a shift in mindset for the Chief Information Officer to consider information as a business asset and not as just information that needs to be stored. In their discussion paper, HM Treasury (2018) estimated that globally there exist 8 trillion gigabytes of information, with expectations for that to increase by 40 times by 2020. But, they write that volume is not an indicator of economic value because of the form and composition of the data. Specifically, in the United Kingdom, less than 10% of businesses collect customer data from customer relations management software, and of those who do, only 6% use that to market to customers.

The biggest challenge for organizations is realizing the value, both in worth and monetized, to utilize data effectively to drive business decisions. HM Treasury (2018) suggests that organizations fail to recognize this value because proven cases or evidence does not abundantly exist. The recognition of this value and the accumulation of data also creates the issue of security for that information. Bajwa (2021) writes that data does not just support business, but increasingly, data is the business. Because data is the business, Bajwa argues that organizations will have to leverage proven data protection solutions and modern data protection technology, offering options to customers for security.

Adequate valuation and security are just two of the issues related to data. A third issue is that of information governance and data storage. Information governance is the process for managing data, including data management, security, storage, and classification (Allen & Allison, 2018). An ineffective information governance policy can make accessing information difficult for customers, employees, or even investigators. For the government, the issue lies with open data and how to manage the open records database. Ahmadi Zeleti et al. (2016) write that governments must develop the capacity to sustain the availability of high-quality open government data to take advantage of the high value of open data assets.

Conclusion and Future Research

The realization of value in information is relatively new to many organizations. As shown from the articles cited, there are sufficient opportunities for future research and development. Ahmadi Zeleti et al. (2016) suggest that future research focus on developing open data business models to help organizations better manage data accumulation, storage, and accessibility. HM Treasury (2018) writes that future studies should determine methods for ensuring fair competition in the digital economy, especially as the value of data increases for businesses. Laney (2020) wants to develop processes to guide CEOs and CIOs to not just store data but to weaponize it and to understand better, gauge, and financially leverage the economic benefits of data.

Allen and Allison (2018) write that as the government expands its volume of data, it must embrace a policy for information governance. Especially for guarding the security of that information as the federal agencies are entrusted with the personal data of individuals. There are many opportunities to continue these studies as information accumulation grows. The suggestions by these researchers are essential but critical to evolving industry of open data, both in the government sector and the private sector.

References

Ahmadi Zeleti, F., Ojo, A., & Curry, E. (2016). Exploring the economic value of open government data. Government Information Quarterly, 33(3), 535–551. https://doi.org/10.1016/j.giq.2016.01.008

Allen, L., & Allison, K. (2018). IG in U.S. Federal Agencies: Balancing Information Value and Risk. Information Management; Overland Park, 52(5), 38–40.

Bajwa, R. (2021, March 7). Unlocking the Value of Data. BW Businessworld. http://www.businessworld.in/article/Unlocking-the-Value-of-Data/07-03-2020-185430/

HM Treasury. (2018, August). The economic value of data: discussion paper. https://assets.publishing.service.gov.uk/

Hughes-Cromwick, E., & Coronado, J. (2019). The Value of US Government Data to US Business Decisions. Journal of Economic Perspectives, 33(1), 131–146. https://doi.org/10.1257/jep.33.1.131

Laney, D. (2020, December 9). Infonomics – An excerpt from Doug Laney’s new INFONOMICS book. Chief Data Officer Magazine. https://www.cdomagazine.tech/

Oxford English Dictionary. (2021). Oxford English Dictionary. https://www.oed.com/