With the right strategy and governance, your company's data can become a valuable asset.
Dec. 20, 2023 | By Marc Smith
Data is a byproduct of many digital business systems, but it shouldn't just be a concern for your IT department. When your enterprise views data from a strategic business perspective, you can use it to optimize existing revenue streams, as well as create new product offerings and new revenue streams.
But where do you begin with valuing data? And how can you generate the most economic value from your data assets?
Understanding the Principle of Data as an Asset
First, you need to start treating your data as an asset, like you do with all other assets on your books. An asset is any resource owned by an enterprise that can be used to generate economic value. It doesn't have to be tangible, like buildings and equipment, which are physical assets most businesses hold. Assets can be intangible, such as a company's brand or intellectual property, generating additional revenue for the organization. Data is an intangible asset that should be valued in the same way you do with other intangible assets.
To truly understand and take advantage of data as an asset requires a shift in how your business values data. Some of the largest digital companies in the world, like Google and Meta, stand on a foundation of data, but your company doesn't have to traffic in online advertising to view data as an asset. For example, reducing your cash cost per barrel means getting to the next level of production optimization. This takes event-driven surveillance, predictive insights and real-time intelligent automation, which is all enabled by your data.
You've heard the saying, "knowledge is power," and that's true for the information derived from data, which can be transformed into valuable business and marketing intelligence.
Looking at Data as a Strategic Asset
Before you begin using your data as a strategic asset, it's important to build a strong foundation for how your company handles data. Start with developing a comprehensive data strategy, creating a detailed plan for how your enterprise captures and stores raw data, as well as how you plan to monetize and create value from it.
With a clear strategy in place, you can then shift your focus to modernizing your data for strategic use. Your data strategy should define exactly what data assets your business has and how you can derive key intelligence to monetize that data for use within your organization to achieve business outcomes. This resulting data intelligence is the final and most valuable step in the data value chain, where your business can clearly drive economic value from this intangible asset—putting your data to work.
Benefits of Viewing Data as an Asset
The knowledge companies can derive from data isn't limited to the digital space. Data intelligence touches every area of business, from marketing to finance to research and development. Enterprises can use data intelligence for big-picture thinking, such as forecasting industry trends and making data-driven decisions and smaller-scale business improvements, like streamlining processes and reducing inefficiencies.
For example, as utilities modernize their transmission and distribution grids for reliability and resilience, they need to forecast the impact of distributed energy resources, such as solar and battery energy storage systems, along with the impact of transportation electrification. Data is required to support these forecasts and ultimately support the decisions needed to prioritize the investments required for grid modernization.
Data intelligence also plays a key role in AI and machine learning, providing critical knowledge to these algorithms. By strategically using data, your company can automate decision-making, optimize spending and generate new opportunities across the organization. Data as an asset can enable your business to drive innovation and reduce risk, staying ahead of the digital curve.
Managing and Valuing Data
Just as with any other kind of asset, governance is critical to realizing your data's full economic value and using it to further your company's success. While there currently are no consistent guidelines around the valuation of intangible assets like data, regulation is coming. For that reason, any business can benefit from having a comprehensive data governance strategy that includes data value sooner rather than later.
But how do you value data as an asset? There are currently three common approaches to data valuation for businesses.
The cost approach of identifying data value focuses on the expenses incurred to build up a company's data assets. These investments can include the cost to acquire data, as well as the cost to implement and operate systems for storing and monetizing data.
The market approach to data valuation takes a look at other companies and how they value their data. Public benchmarks and transaction information from other organizations can help your business establish a standard for valuing data as an asset.
The income approach is perhaps the most straightforward and focuses on the current and future cash flow derived from data monetization. In short, you can value data by how much revenue you currently generate from it and what you expect to generate from its use in the future. Here, the data value is directly related to its potential to generate income.
What's Next? Looking to the Future of Data as an Asset
As more corporations have continued to invest in data intelligence and policymakers have turned their attention to standardizing data governance and valuation, viewing data as a strategic asset has become a defining aspect of the digital age. Investing in data and developing a strong data strategy is quickly becoming essential for companies to stay innovative and competitive.
If an enterprise generates data through normal operations, why not turn that resource into a strategic asset increasing business value? Viewing data as an asset opens the door to a wide range of potential benefits, including the opportunity to explore and use emerging technologies. One of the biggest challenges we see in artificial intelligence and generative AI (Gen AI) adoption is the availability, accessibility, quality and usability of the right data. The data strategy is a guide to help customers navigate the steps necessary to create the data foundations needed for their AI efforts. With a strong data strategy that is aligned to business and corporate strategies, a company can get in on the ground floor of the latest tech innovations and move toward greater productivity and profitability while staying ahead of regulations and managing risks related to confidentiality, privacy and ethical bias.
Uncovering the Value of Your Company's Data
With the right data analytics capabilities, data can become the foundation to your business growth and success—and the key to taking advantage of the latest technologies, like Gen AI. Understanding the data's value is crucial in this process. Just like tangible assets, data can be a valuable asset to an organization, which is why it's critical to develop a plan for managing data ahead of any future regulatory guidance. By shifting company perception to viewing data as an asset, an enterprise can productize data, generate new revenue streams and enhance the value of the business as a whole. Recognizing data value can be a game changer in this digital age.
Marc Smith
Transformation Client Executive, Energy
Marc is a recognized leader in digital analytics in the energy and resource sector. As a transformation client executive, Marc leads clients through journeys in their digital, cloud and data transformations to enable their organization strategy. Marc has over 30 years of experience architecting and implementing data, analytics and artificial intelligence solutions in areas of risk, energy transition, asset management and operational excellence.
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Managing data as a strategic asset isn’t as simple as flipping a switch. Your organization needs a comprehensive plan to transform your goals into measurable results. Our full-stack expertise can help you navigate the expanding world of data and avoid pitfalls so your company can derive the most value from your data.
Marc Smith
Transformation Client Executive, Energy
Marc is a recognized leader in digital analytics in the energy and resource sector. As a transformation client executive, Marc leads clients through journeys in their digital, cloud and data transformations to enable their organization strategy. Marc has over 30 years of experience architecting and implementing data, analytics and artificial intelligence solutions in areas of risk, energy transition, asset management and operational excellence.