Information Economics and the Value of Business Data Visualisation

A key area of economics today has to do with how people use different kinds of information to make decisions. In theory, a company should be making rational choices based on the best available information; however, the modern enterprise has so many different types of data being generated that this is becoming increasingly difficult for business leaders. For companies, data may be generated every minute of every day (in terms of customer and financial data, operational data, etc.). Simply because more raw data is created does not equate to better decisions.

The disparity experienced by businesses stems from the notion of incomplete and imperfect information. For example, most managers do not have complete and/or organised information available when trying to make a decision. Rather, they are often forced to evaluate incomplete data under a significant level of pressure to complete the evaluation in time to make a decision. Increasingly defined by a digital operating model, businesses now have a significant volume of data available to them (Globally estimated at a few hundred zettabytes of data being created each year) with the amount of data generated by and about business activities continuously increasing.

That said, when raw data is produced but cannot be effectively processed into usable decision-making information, little (or perhaps no) economic value arises from it over the long term. For modern businesses, information overload is a significant issue. The more complex the data, the more constrained the manager becomes when evaluating information processing options, therefore leading to poor management decisions.

Data visualisation systems were designed with the intention of addressing the information overload issues experienced by the modern enterprise. These solutions convert raw data into visual (graph) representations that allow managers and other decision-makers to find patterns in data, thus allowing them to enhance their agreement on emerging trends or absences of trends (bottlenecks), which enhances both the organisations' responsiveness to change and their effective resource allocation processes.

Overall, data visualisation systems improve the quality of decision-making by decreasing the cost/risk associated with the processing of information. For example, a manager reviewing thousands of rows of data in a spreadsheet may be unable to identify newly emerging risks or opportunities. In comparison, through the use of data visualisation, a manager can effectively identify trends, bottlenecks, or risks within a matter of seconds. Consequently, this practice improves the overall responsiveness of the organisation and thus the effectiveness of resource allocation decisions.

The trend of shifting towards data-driven decision-making is illustrated by platforms like Ideals. Increasingly, businesses are turning to centralised, digital software systems that integrate complex flows of information and allow managers to view this information visually to assist with improving efficiency, collaboration and strategic planning. Economic value related to these software systems is created not just from the ability to store data but also from being able to create actionable insights from it.

One significant area where this trend is exhibited is supply chain management. Large retailers and logistics providers utilise real-time visual dashboards to measure inventory levels, shipping delays, and buying activity. During periods of disruption, companies that are able to quickly identify bottlenecks may avoid stock shortages as well as minimise operational losses. This became an essential characteristic after the COVID-19 pandemic led to disruptions in the global supply chain. Companies that have a stronger degree of data visibility have generally demonstrated success in adapting to changing conditions through their data-based decisions.

The trend of data-driven decision-making is evident in the area of financial and operational forecasting. Many companies are taking advantage of data visualisation to conduct revenue trend, labour-cost, customer-acquisition-cost, and cash-flow analyses simultaneously. Executives have the ability to monitor the company's performance continuously through live dashboards, as opposed to only utilising static monthly reports. This empowers businesses to respond quickly to declining margins or changing customer demand.

Improving the processing of information provides broad economic value beyond individual organisations. Enhanced information processing improves managerial efficiency and is a primary factor driving productivity gains. Economists have long known that productivity differences between companies are not only a function of labour and capital investments; management and information coordination are two of the greatest contributors to business success.

The importance of reducing the information asymmetry that exists in organisations is further demonstrated through the principles of information economics. There are instances when employees in different departments have partial information, and this partial information often is not effectively shared throughout the company. Visualisation systems consolidate data and improve the ability of the finance, operations, marketing, and logistics teams to communicate with one another to create a more integrated environment for decision-making. Visualisation systems can also assist organisations in reducing coordination failures.

A company's information system can also provide a significant competitive advantage over its competitors' information systems; a company with a superior information system will have the ability to respond more quickly to changes in market conditions and to identify profitable opportunities earlier than its competitors. In cases where industry margins are thin or demand is volatile, the ability to quickly analyse and interpret the information contained within the data can also have a significant impact on profitability.

The development of artificial intelligence and the use of predictive analytics continue to intensify these dynamics and behaviours of organisations, as most modern visualisation systems include automated forecasting, anomaly detection and scenario modelling capabilities. Companies are no longer utilising dashboards solely for the purpose of measuring their performance; they are using dashboards to anticipate and assess risks and opportunities.

As businesses become more digitally oriented and interconnected, organisations that are able to effectively process data will have a strategic competitive advantage over their competitors. As more organisations learn how to more effectively translate large amounts of raw data into actionable economic insight, the organisations that do the best job of allocating resources, managing their uncertainty, and adapting to a rapidly changing marketplace should be the best positioned for success.