Data, Information, and Knowledge

In daily conversation, the words data, information, and knowledge are commonly used interchangeably. However, in the context of information systems, the three words have a separate meanings. Bourgeois, (2019) defined data as raw unprocessed facts, that may be devoid of context or purpose, while information is processed data that has context, relevance, and special intent. Knowledge in a certain field is perceived relationships between facts or concepts relevant to that field.

For instance, let’s say, a jewellery company got an order from their website and the system recorded the address of the customer making the order. The address is data. When the managers of the company made a recap of the orders for a year and where their customers are coming from for the purpose of targeting, they found out that 90% of the orders came from the wealthiest city in the country. That is information. The managers are not surprised by the information, as they already knew that the country had a very unequal distribution of wealthy people. The wealthy people of the country who can afford to buy jewellery are concentrated in that one city. The perceived relationship of the information is knowledge.

Knowing this, the managers can take a better decisions. For example, they can focus their marketing effort on that particular city. That way, the company can target their customers better, improving the marketing cost-to-income ratio, and enhancing overall marketing performance. Utilizing information-based knowledge can ultimately become the company’s competitive advantage over its competitor.

While it may not be as simple, the case above can depict how recording and processing data enables organizational competitive advantage. Data is processed to become information that can add value to the enterprise, and information becomes knowledge when insight, abstraction and a better understanding are added to it. Thus, knowledge can also be defined as the capacity for effective action (Grangel et al., 2007).

The limitation of the case above is it’s fairly easy for competitors to do just the same thing. Insights that come from data processing are powerful, but the knowledge doesn’t guarantee a defensible competitive advantage. Hagiu and Wright (2020) listed the characteristics of information that can give firms a solid competitive advantage. Those are the information that offers high and lasting value, is proprietary, drives improvements that can’t be imitated easily, or produces insights that can be incorporated quickly.

In the jewellery company case, let’s say, the data, information, and knowledge enable the company to create a sophisticated customer relationship management system that none of the competitors can imitate. Moreover, the system enables them to scoop the majority of the market share. Then the company can safely say that they have a solid competitive advantage due to its data management.

Also read about Moore’s Law and a Company’s Sustainable Advantage

Role of data and Data management solutions in organizational decision-making

Experts almost collectively agree that data-driven decision-making is more reliable than intuition-based decision-making (Swain, 2020). While it is not possible to say that we are approaching a state where data takes leadership and human intuition is not needed anymore, data is becoming an essential part of the decision-making process (Potančok, 2019).

The goal of information systems is to transform data into information in order to produce knowledge that can be used for decision-making (Bourgeois, 2019). The transformation should be managed so that it can focus to serve the main purpose, which is enhancing decision-making. Many companies turned to data management solutions to perform this task.

We can learn one of the most powerful examples of how data management solutions leverage decision-making from the fast-moving consumer goods giant, Procter and Gamble (P&G), which even renamed its IT function as “Information and Decision Solutions” (Soat, 2007). The company developed an in-house business intelligence system named Business Sphere, which was based on its power of access to real-time data. The system enables the company to make fast and informed decisions by combining expert analysis of real-time information and data visualization within an immersive environment (Watson, 2012).

This system is not only improving the quality of decision-making but also its speed and relevance of it. Business Sphere utilizes a group of business intelligence capabilities that consolidate real-time global data, analytic models, advanced visualization and IT analyst facilitation (Watson, 2012). In this case, we can learn how the role of data and data management solutions is crucial in organizational decision-making.

References

Bourgois, D.T., Smith, J.L., Wang, S., & Mortati, J. (2019, August 1). Information systems for business and beyond. Saylor Foundation. https://digitalcommons.biola.edu/cgi/viewcontent.cgi?article=1000&context=open-textbooks.

Hagiu, A., & Wright, J. (2020, January). When Data Creates Competitive Advantage. Harvard Business Review. https://hbr.org/2020/01/when-data-creates-competitive-advantage

Information Systems: A Manager’s Guide to Harnessing Technology. (2015). University of Minnesota Libraries Publishing. https://open.umn.edu/opentextbooks/textbooks/16

Potančok, M. (2019). Role of Data and Intuition in Decision Making Processes. Journal of Systems Integration. https://doi.org/10.20470/jsi.v10i3.377

Soat, J. (2007). P&G’s CIO Puts IT at Users’ Service. InformationWeek.

Swain, G. (2020, August 11). Intuition vs. data-driven decision. https://www.insightly.com/blog/intuition-vs-data-in-business/

Watson, B. P. (2012, January 30). Data Wrangling: How Procter and Gamble Maximizes Business Analytics. CIO Insight. https://www.cioinsight.com/big-data/data-wrangling-how-procter-and-gamble-maximizes-business-analytics/

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