This is Part 1 in a series about actionable ways to start treating your data like an asset.
“We are a data-centric organization and we make data-driven decisions. After our people, data is our greatest asset!”
You probably hear jargon like this at every company town hall. And I’m guessing you can tell pretty quickly whether the statement is genuine, a true reflection of what your organization is currently doing. Decades of human resource management has taught us what good looks like for managing people. You know when people are treated as a company’s greatest asset. You know what it looks and feels like when a manager values employees, checks in on them to make sure they’re healthy and ready for work, and invests in their improvement and development.
With data, if you haven’t developed that sense yet, ask around. Your data team will know immediately whether those statements are aspirational based on how data is actually treated. Maybe it’s more of a proclamation: “We will treat our data like an asset!”
But what does it even mean to treat our assets like assets? And what makes an asset an asset in the first place?
Assets are most often tangible things (and sometimes, intellectual property) that are owned by the organization. They either have immediate value or a probable future value to the company. That’s pretty broad, and deliberately so. Does this accurately describe data? Or should data be treated more like a product? A product is a type of asset, so the two concepts aren’t necessarily exclusive.
Some data are indeed like products. They are finished goods that are produced and can be traded (or sold), like a piece of software. This may be a helpful analogy for people with software or product management experience on your team. But most of the time data behaves more like a fixed asset: it serves the same purpose as equipment that is operated and used internally within the organization, and doesn’t have a clear customer.
Data is more often used to make a decision, provide a service to a client, or create some other product that is sold. For example, think of a report with recommendations that a consultant prepares using data, or an airline that creates an optimized schedule for a new route. This data is created and used for internal purposes only. Treating it as a product would mean that you need to distinguish your internal customers from your external customers. Similarly, you would need to distinguish your internal products from your external, and true products.
That may not be a difficult leap to take, but there’s an easier analogy to make. One that already comes with a set of processes for managing it and where a definition of an asset is broad and consistent - fixed assets. Not many people argue that equipment is too dissimilar to a building to treat it like an asset. Indeed, a common set of standards can be applied to both. And it can be applied to data as well with a few small adjustments.
Before going too formal into a standard like ISO 55001, let’s start with some basics. A previous post in this blog (Radziwill, 2022) showed some ways to start working with fixed assets. Let’s revisit that example. Figuring out what assets you have is usually the first step.
Take a look at your laptop right now. If it’s company issued, chances are it has some sort of identifier on it - a number, barcode, or QR code. That identifier is stored in an asset management system that specifies what the asset is, where it is, who’s assigned to use it, and what person or group is responsible for patching it or fixing it. It’s also probably linked to a purchase order that shows when it was acquired, from whom, and how much it’s worth. Generally, organizations know 100% more about the laptops, hard drives, and servers it owns than the data that lives on them (or is processed on them).
Now look around your office. You’ll see things like chairs, desks, and storage cabinets also tagged as assets. Why is data on a laptop treated more like pens in a cabinet than the laptop or cabinet itself? Is this bad?
Find out in Part 2 of this series, coming soon.
Ultranauts helps companies establish and continually improve data quality through efficient, effective data governance frameworks and other aspects of data quality management systems (DQMS), especially high impact data value audits. If you need quality management systems for your data pipelines, Ultranauts can quickly help you identify opportunities for improvement that will drive value, mitigate risks, reduce costs, and increase impact.
Additional Reading:
Radziwill, N. (2022, July 1). Is Your Data an Asset? Then Treat it Like One. Ultranauts Blog. Available from https://info.ultranauts.co/blog/is-your-data-an-asset
Author: Peter Dobson is a data quality professional with a M.Sc. in Mechanical Engineering and background in industrial inspection and maintenance.