Towards Financial Valuation in Data-Driven Companies

Despite numerous claims that data is a critical source of competitive advantage for firms, there is little empirical analysis of its link with firm performance. This paper uses a survey of data activity for 500 UK firms which are commercially active online to quantify the contribution that online data use -that is, the collection, analysis and deployment of online customer data -makes to business productivity. We find that a one-standard deviation greater use of online data is associated with a 8% higher level of productivity (TFP): firms in the top quartile of online data use are, other things being equal, 13% more productive than those in the bottom quartile. When we distinguish between the different data-related activities that firms undertake, we find that greater data analysis and reporting of data insights have the strongest link with productivity, whereas amassing data has little or no effect on its own. Consistent with this, we report significant links between online data analysis and reporting and profitability measures. We also study the complementarities between online data activity and other organisational attributes and behaviours. We find that the impact of online data use is stronger for firms with higher levels of employee autonomy, and for firms willing to disrupt their business processes. An implication for managers is that their data investments stand to generate more benefits when they are accompanied by other organisational changes.

Companies that have high growth indicators for liquidity, stock, and return on assets are more desirable to investors and shareholders. Successful managers are thus limited to using financial indicators to convey the value of the firm. Big data can now be the source of innovation and monetary success. Technology, rivals, market and customer data, and these sources of information give businesses hints about emerging competitive attitudes. Therefore, there will be valuable companies that innovate by absorbing new knowledge and data through big data and improving financial performance.

2018

It is well known that Englishmen are in the main opposed to any and every new system with which they are not familiar. Probably to this influence is due the fact, that, with a few exceptions, pay wards are as unknown in this country as the pay hospitals themselves. 1 Sir Henry Burdett, founder of the King's Fund, 1879

IEEE Access

Data is central to modern decision making and value creation. Society creates, consumes and collects data at an increasing pace. Despite advances in processing power, data is expensive to maintain and curate. So, it is imperative to have methods and tools to distinguish between data based on its value. Yet, there is no consensus on what characterises the value of data or how this data value should be assessed. This results in heterogeneous data value models and inconsistent measurement techniques that are siloed in specific application domains. This limits the formalisation and exploitation of these concepts. We present in this paper a methodical literature analysis that discusses data value models, assessment metrics and current applications. We also highlight challenges hindering the development and exploitation of data value as concept. This leads to the identification of a set of research questions to help researchers contribute to this emerging field. The aim of this article is to stimulate further research and deployment of quantitative data value models and value-driven applications. INDEX TERMS Data value, data value characterization, data value quantification, data governance, data value metrics.

2020

Although increases in available data have inspired companies' interest in creating and extracting value from it, many lack the insight and guidance to assess the potential data offer. To address this issue, we conduct a systematic literature review to create a universe of 102 real-world cases from diverse industries with regard to the use of data. Based on an analysis of these cases, this paper provides a set of 12 generic strategies for monetizing data, ranging from sole asset sale to strategically opening data and guaranteeing control. This study supports business practice by aggregating the wide range of established approaches of data monetization from practice for operational purposes. It advances theoretical understanding of value capturing from data and suggests important avenues for future work in this emerging field of research.

International Journal of Engineering Technologies and Management Research, 2022

This research was carried out to design a data strategy focused on the relationship management of a company in the financial sector in Colombia. For this purpose, different knowledge activities were developed; initially, deepened knowledge of it of the organization and its business initiatives. Based on the identified needs, the data that support these initiatives were identified and known, using as a basic instrument the design of a conceptual model. Likewise, the life cycle of the data was documented and its interaction with business processes was analyzed. Also, the state of the general capabilities in data management was known. Based on the knowledge achieved, the work plan was designed to ensure that the highest value of the data is obtained in the area selected as a pilot (relationship management).

Proceedings of Bled eConference, 2024

This study investigates the readiness and challenges European companies face in embracing a data-driven economy. By conducting a comprehensive survey of 1,200 European companies spanning various industries and sizes, we reveal a mixed outlook on the data economy's potential to offer a competitive advantage. We find that 20% have already leveraged data to gain competitive advantage, a majority see potential benefits, while 19% perceive no advantage. Importantly, our findings highlight the need for substantial business model transformations to capitalize on data-driven opportunities. The paper also identifies the obstacles faced by companies in adopting a data-driven approach, including legal complexity, lack of data, competence in data-driven business models and technological competence. Challenges are most pronounced among micro-sized businesses and sectors like arts, entertainment, leisure, and international NGOs. Overall, the research suggests that if the company has the skills, a data economy has the potential to drive innovation and growth. By identifying the disparities in readiness and perception across different sectors and company sizes, this study contributes to a more informed discourse on fostering a conducive environment for all companies to thrive in the data-driven economy.

2011

Abstract: We examine whether firms that emphasize decision making based on data and business analytics (“data driven decision making” or DDD) show higher performance. Using detailed survey data on the business practices and information technology investments of 179 large publicly traded firms, we find that firms that adopt DDD have output and productivity that is 5-6% higher than what would be expected given their other investments and information technology usage.

Communications in Computer and Information Science, 2017

Data is emerging as a key asset of value to organizations. Unlike the traditional concept of a business value chain, or an information value chain, the concept of a data value chain has less currency and is still underresearched. This article reports on the findings of a survey of employees of a financial services company who use a range of data to support their financial analyses, and investment decisions. The purpose of the survey was to test out the idea of the data value chain, as a useful abstract model for organizing the different discrete processes involved in data gathering, data analysis, and decision-making, to further identify issues, and suggest improvements. While data and its analysis is clearly a tool for supporting the delivery of financial services, there are also a number of risks to its value being realized, most prominently data quality, along with some reservations as to the relative advantages of data-driven over intuitive decisionmaking. The findings also raise further data and information governance concerns. If implemented such programs would aid in the realization of value from data within the organization, while also mitigating the risks of this value not being realized.

2013

The growing awareness of information cannot be overemphasized; nevertheless, there is the question of how to evaluate thevalue of information. This paper is a theoretical framework which determines the quality of information content with respectto financial and quantitative valuation. The framework identified information as one of the most important asset of anorganization. The paper also equates the value of information to the damage that envisaged if such information is notapplied. More so, the value information can also be determined by the individual using the information. This research alsoclarified the concept of information as misunderstood and finally the measures of the value of information can be trulydetermined based on the purposes of the information. Keywords : Information, organizational asset, market value, Value of Information (VOI).1. INTRODUCTION