What if Data Was an Asset?

In part I of this series, Is Data Really an Asset? we explored whether data really is an asset, looking at whether firms are using it to evolve their business models to become stronger. In part II, we take a deeper dive to discover how data should be maintained as an asset. 

When it comes to questioning the assets really driving innovation and profits in business today, Douglas B. Laney may have said it best: “Sure, many senior executives talk about information as one of their most important assets, but few behave as if it is. They spend more money tracking their company’s office furniture and PCs than their information assets.”

It’s a condensed way of describing a limited view of data we see all too frequently, underpinned by only tactical or use case driven use of data, a departmental or business unit focus, weak governance, lack of data metrics and quite frequently, a focus on cost and not usage.

In asset intensive industries such as airlines, asset yield and usage is tracked intensively, requiring a high volume of metrics dedicated to ensuring all assets are optimised at all times. Consider the potential if the same energy and determination was spent on managing data as an asset in a similar way, and the potential new business opportunities data could introduce.

If Data Was An Asset….

Organizations should be looking to change their mind sets when it comes to managing data as an asset, as well as looking at production-level, advanced analytic systems in the cloud in order to support high volume queries. If data is considered an asset, it’s essential to focus on how assets are maintained and what the implications are of doing this properly.
Here are six ways companies can make the data asset mind set and technology transformation to maintain data as a top-value asset.

Make Data an Enterprise Asset: Simply put, data as an asset needs to be easily accessible throughout your organization. Data scientists need to be able to collaborate with product developers and marketing teams, and if data is distributed and not universally available throughout your organization, this type of collaboration is difficult.

Document Your Data: Many business people don’t know what data is available within their organizations because no one has documented it. Companies need a data strategy to complement their business strategy that details what data they have, where it is, and what data they will need in, for example, two to three years to get to where they want to be.

Drive Consumption: Teams need to be dedicated to eliminating barriers for usage of data and focus on the things they can do to make it easier for the business to drive consumption of data. With data as an asset, the more an organization uses it, the more valuable it becomes, so businesses should consume as much data as possible. 

Invest in Data Literacy: Some organizations build small data scientist teams who do everything, and their business people end up not understanding how to model the data. Data democratization is everything. It’s important to establish internal training to get every user using your data. 

Measure Your Data: When data is an asset, organizations must know where it is being used, how often it is being used, and how it is being used. Think about it: if you have an asset, you should be actively measuring how you are making money and ROI on that asset. Organizations invest millions in data, but often fail to understand the cost of using that data. What does it cost to run a query, for example? The great thing about data as an asset is that its cost goes down the better companies get at using it, but it’s impossible to understand this unless you build strategy around measuring it.

Build a Data Organization: To create a data organization, companies must decide what kind of data they want to acquire, how to operationalize the analytics of that data and define a role for data governance – someone who ‘owns’ the data.Companies who dedicate themselves to maintaining data as an asset and measuring the asset in terms of productivity, yield and usage, availability and revenue/profit will be at the forefront of the data analytics and innovation landscape. The good news is that we’re seeing data driven companies valued higher than those companies who have yet to nurture and capitalize on data as an asset, and there’s still a world of untapped data opportunities ready to be recognized and seized. 

To learn more about how to innovate with analytics, click here for information on Teradata Everywhere, a flexible, agile, scalable way to ensure a high return on your analytic investments.