The Dataco: How Data Companies Are Unlocking the Value of Data

Organisations around the world are starting to recognise that their data holds enormous value beyond its operational applications and basic business intelligence. However, new strategic approaches are needed to maximise the value of data and monetise data assets.

One emerging model is the independent Data Company, or DataCo, a separate corporate entity whose primary purpose is to manage and extract greater value from its parent company's data, both internally and externally.

While these entities have existed for years in industries such as airlines and retail, their prevalence is expected to increase as data becomes a more valuable strategic and financial asset across the global economy.

According to the Data ROI report by the Enterprise Data Management Council (EDM Council), DataCos are proliferating as the importance of data grows across industries. By separating the data business from the wider organisation, companies can foster innovation, mitigate risk and generate new revenue streams through external data sharing, data monetisation and advanced analytics.

The DataCo model has significant potential, but establishing one also presents challenges relating to corporate structure, regulation, technology, data governance and culture. As the data economy evolves, organisations may increasingly consider DataCos as a way to transform data from a cost centre into a revenue-generating asset.

Companies that effectively implement this model can gain a competitive advantage and uncover previously untapped value within their data stores. Reaping these benefits, however, requires foresight, planning and a commitment to treating data as a valuable corporate asset.

What Is a DataCo?

A DataCo is an independent corporate entity created to manage, develop and maximise the value of some or all of a parent company's data assets.

A DataCo typically possesses three characteristics:

1. It administers all or a portion of the data assets of its parent company.
2. It operates as an independent entity from its parent company.
3. Its main goal is to maximise the utility and value of the parent company's data.

DataCos can take various legal forms, including subsidiaries, joint ventures and newly established companies. Separation from the parent organisation can provide strategic benefits, such as the ability to assign a financial value to data, monetise data products, isolate risk and address regulatory requirements.

While independent, a DataCo remains closely aligned with the parent company's goals. The data itself may reside fully within the DataCo or remain partially with the parent company, depending on factors such as risk, regulation and product development.

Why Do Organisations Create DataCos?

Organisations establish DataCos for several key reasons:

• Collateralise data: Data can potentially be pledged as security for financing, as some airlines have done with their loyalty programmes.
• Monetise data: Data products and services can be sold externally to create additional revenue streams.
• Develop new offerings: A DataCo can create products and services that differ significantly from the parent company's core business.
• Assign financial value: Organisations can more clearly quantify the economic value of data rather than treating it solely as an intangible resource.
• Manage regulatory risk: Data relevant to specific regulations can be isolated and managed within the DataCo.
• Limit legal liability: Risks associated with data management and data products can potentially be contained within the separate entity.
• Share and exchange data: DataCos can facilitate data sharing across organisations, partners and consortiums.
• Provide open data access: Public-sector DataCos can make certain datasets more accessible to citizens and other organisations.

What Does the DataCo Landscape Look Like?

The EDM Council identified dozens of organisations operating as DataCos, alongside others that meet some of the criteria associated with the model.

Notable examples identified in the DataCo landscape include:

• AAdvantage (American Airlines), SkyMiles (Delta Air Lines) and MileagePlus (United Airlines)
• Checkr
• 84.51° (Kroger)
• Arity (Allstate)
• Blue Health Intelligence (Blue Cross Blue Shield)
• Bureau of Labor Statistics (US Government)
• Dataworks (FedEx)
• Eurostat (European Union)
• GE Digital (General Electric)
• LexisNexis (RELX Group)
• Pelorus Equity Group
• The Weather Company
• Optum (UnitedHealth Group)

Many DataCos focus on monetising data products and services. For this reason, for-profit organisations have been prominent adopters of the DataCo model, alongside government agencies and other public-sector organisations.

What Organisations Should Consider Before Creating a DataCo

Establishing a DataCo requires organisations to address considerations across data management, corporate structure, regulation, technology and operations:

• Data management maturity: Companies may need foundational data governance and data management capabilities before launching a DataCo.
• Primary objectives: Business motivations shape decisions such as data scope, ownership structure and the level of independence from the parent company.
• Data products: Organisations need to determine how data can be transformed into valuable products or services while accounting for data rights, quality and usage restrictions.
• Corporate structure: Options can range from wholly owned subsidiaries to joint ventures and other independent corporate structures.
• Regulations: Rules around data privacy, data sharing, sovereignty and operational resilience can shape how a DataCo is structured and operated.
• Technology: Data redundancy, cybersecurity, storage costs and infrastructure requirements depend partly on how data is divided between the DataCo and its parent.
• Operating model: Leadership, organisational design, control protocols and governance processes must align with the DataCo's strategic objectives.

While DataCos offer significant advantages, they can also introduce challenges, including additional data and technology costs, privacy risks, competing priorities and data synchronisation complexities.

How Does Data Valuation Support the DataCo Model?

Data valuation is a crucial factor in the formation and operation of DataCos. By assigning a monetary value to data assets, businesses can gain greater insight into the costs and benefits associated with collecting, managing, protecting and using their data.

Measuring the financial value of data can also encourage clearer ownership and accountability for data assets. It can help companies quantify and justify investments in data acquisition, data quality, data governance and analytics.

In some cases, corporate data assets can carry substantial financial value. Airline loyalty programmes, for example, have demonstrated how customer and loyalty data can become strategically important assets in their own right.

Creating a separate DataCo entity can help organisations quantify and express the financial value of data, which is generally treated as an intangible asset under traditional accounting practices. By isolating the data business, companies can establish a more measurable commercial value, strengthen data governance and justify further investment in increasing the value of their data.

The Future of DataCos?

As the strategic importance of data and the regulations surrounding it continue to expand, more companies may explore the DataCo model, particularly in data-intensive industries such as financial services, technology, communications, healthcare, retail and transportation.

Key factors in DataCo success include closely linking the entity to corporate strategy, mitigating regulatory and operational risks, establishing an efficient operating model and developing a culture that supports data commercialisation and monetisation.

With thoughtful planning and alignment to business goals, DataCos can help organisations unlock greater value from their data assets while improving risk management and data governance. The model is likely to attract greater attention as organisations search for new ways to turn growing volumes of enterprise data into measurable business value.