Future Data Assets

Smart data balancing to determine corporate data assets

Application industry: Sector-independent
Technology area: Machine learning; data and service management

Future Data Assets is developing a system for evaluating the data inventory of companies and providing it via a digital platform. With the help of machine learning methods the data capital of a company can be evaluated.

The baseline
The digital transformation requires companies to invest heavily in physical capital and software as well as in training and further education of staff. To date, no standardized, reliable key performance indicators are available to evaluate the economic success of investments in the digital transformation: Existing and potentially available data stocks created by investing in digital transformation are not systematically evaluated from a business management perspective and hence cannot be compared to the required input. Whilst tangible assets of a company are reported as monetary values in company balance sheets, this is not yet the case for data.

The project goal
The goal of Future Data Assets is to develop a framework for setting up so-called data balance sheets. The data balance sheet is designed to visualize the commercial value and potential of a company’s data stocks, thereby closing a gap in traditional reporting to various stakeholders. The data balance sheet as a reporting tool should contain two central components:

• The data balance management report shows the data stock of a company and its balance sheet value for a certain period in the past. It is also possible for external stakeholders, such as auditors, to understand this part of the balance sheet.

• The data balance forecast report provides information on a company’s future data management. Machine learning methods can be used both to predict future developments and to estimate planned investments.

The long-term goal of the project will be to include the data assets as an asset in the consolidated balance sheet in addition to the management reports and the forecast report. This will require rules for the qualification and certification of data management concepts that allow an objective measurement of data quality.

Companies can obtain a so-called data balance toolset from a digital platform that is being developed in the project. This toolset can be customized and allows the creation of structured, systematic, and uniform data balance sheets.

Application and practical benefit
Small and medium-sized enterprises and the manufacturing industry will especially benefit from evaluating their data as corporate assets. By analyzing their data capital, companies can question previous investment strategies and evaluate future expenditure on digital technologies more reliably. Transparent quantification of digital values offers greater certainty to stakeholders, such as banks and credit institutions.

Term: 1 August 2019 to 31 July 2022

Future Data Assets is a joint German-Austrian project.

Consortium: atlan-tec Systems GmbH (lead member), Deloitte GmbH, DMG MORI Services GmbH, FIR at RWTH Aachen University, Saarland University

Contact:
Thomas Froese
atlan-tec Systems GmbH

E-Mail: T.Froese@atlan-tec.com

Website: www.future-data-assets.de