Maximising the value of your organisation’s most overlooked resource
There’s a clear consensus in today’s business world: data is extremely valuable. Report after report validates this claim, with research showing that data-driven companies consistently outperform competitors by as much as 85% in sales growth, gross margin, operating margins, and other key financial performance indicators.
The numbers are indisputable — and so are the equally prevalent statistics demonstrating that most organisations struggle to unlock the value of data in a way that drives materially better business outcomes. Despite hiring data leaders and data specialists and investing vast sums of money in data projects, only 26.5% of company leaders report having achieved their goal to become data-driven.
What’s going on here? If so many business leaders are pursuing the enormous potential of data, why aren’t more of them succeeding?
The answer may surprise you. In our experience, organisations fail to maximise the value of data because, although leaders talk about data as a valuable asset, they don’t actually manage it like an asset.
In this blog post, we’ll discuss what treating data as an asset means in practice, how doing so is different from other approaches to data, and why it leads to better results. We’ll also introduce steps you can take to implement data asset management and extract maximum value from your organisation’s data.
What is a data asset?
In the corporate world, assets are resources included on an organisation’s balance sheet and actively managed to maximise the value they bring to the business.
Traditional business assets include tangible things such as inventory, materials, equipment, real estate, stocks, and contractual claims, and intangible intellectual property such as royalties and patents.
Data is definitely not a traditional corporate asset. In most organisations, it’s much more likely to show up on an IT systems map than on a corporate balance sheet.
So what do we mean by the term ‘data asset’? We’re happy to explain, starting with some quick definitions of a few relevant terms.
- A data element is a defined unit of data such as date, account number, temperature, name, item description, etc. Data elements are stored in your organisation’s databases.
- A data set is a collection of data elements treated as a single unit. For example, the data elements name, address, phone number, and account number may be grouped together to form your customer data set.
- A data asset is a collection of data sets expected to provide specific future economic benefits to the organisation and its stakeholders.
Here’s an example: Your customer data set, sales history data set, and service records are all collections of useful data elements. Together, the three data sets make a data asset that drives better sales and marketing results, provides insight about new revenue opportunities, and delights customers with a seamless, personalised experience.
When data leaders talk about ‘de-duplicating’ or ‘cleaning up’ or ‘restructuring’ data assets, they’re often actually declaring their intention to improve the technical quality and organisation of data elements and data sets.
That matters because you can’t start treating data as an asset if you don’t have a clear understanding of what a data asset is.
Data assets are distinct from data elements and data sets because they are defined by the expected value they bring rather than simply the type of data they contain. They enable, enhance, support, or make possible a specific value driver or business activity that brings tangible or intangible benefits to stakeholders — just like more traditional business assets.
Organisations buy, sell, create, trade, improve, share, and monitor their assets to generate cash flow, lower taxes, create new revenue streams, reduce expenses, boost sales, facilitate partnerships, enter new markets, improve community relations, and achieve other strategic objectives.
If you replace ‘asset’ with ‘data asset’ in the previous sentence, the notion of treating data as an asset makes perfect sense. Data assets have the potential to deliver enormous economic benefits in a variety of ways. You can and should be managing them in the same way and with the same goals as your other business assets.
Mindset matters: how treating data as an asset benefits your business
Now that we’ve established what a data asset is, it’s time to answer the critical question: Why does it matter? Why should you care about the difference between a data set and a data asset — or whether data shows up on your organisation’s balance sheet?
You should care because how you think about your data determines how you approach it, and that determines how successful you’ll be at unlocking the hidden value you know is there. Everything changes when your organisational mindset shifts from ‘data is an IT concern’ to ‘data assets drive results across the business.’
The conversation shifts from ‘How can we solve our data problem?’ to ‘How can we manage our data assets for maximum value to the business?’ It may seem like a subtle difference, but the outcomes are striking.
Suddenly, data investment becomes a value creation activity instead of an IT cost. Data assets are put on par with other valuable business assets, and you have more resources available to devote to maximising the value of your data. You also have the context and value-based justification required to build a quantifiable case for change and get enthusiastic business buy-in.
Here are just a few of the benefits made possible by these fundamental changes to your organisation’s approach to data:
- Meaningful changes to data governance, data management, and other critical elements of your data landscape
- Stronger connections between data strategy and business strategy, with smart data investments powering business growth and success
- Reliable data that can be used to make better decisions and support organisational strategy execution
- Tangible business results such as increased operational efficiency, better sales results, and new opportunities and revenue streams — including data monetisation
- Intangible business value in the form of happier customers and stronger relationships with vendors, suppliers, and partners
Making the switch: a holistic approach to extracting maximum value from your data
We’ve done our best to help you understand what a data asset is and why treating data as an asset is a smart strategy for your business. Now we’d like to discuss how you can start extracting maximum value from your data by taking a closer look at what data asset management looks like in practice.
Data asset management is a holistic approach to managing your data assets. Data transformation is a marathon, not a sprint. Some approaches to data transformation focus primarily on technology, systems, and analytics, but that’s like jumping into a marathon at mile 24 and sprinting the last 2 miles to the finish. You’ll look impressive to the crowd at the finish line, but you won’t actually have accomplished much.
There are no shortcuts to completing a marathon, and there are no technology shortcuts to unlocking the value of your data. Dashboards and analytics won’t help you if the underlying data is in poor condition or you don’t know how your data assets drive business value. You’ll just end up with pretty dashboards of dubious reliability — and no meaningful increase in the value you derive from your data.
Just as you must run all 26.2 miles to complete a marathon, you must employ a holistic, value-centered approach to data to transform your business results.
We’ve identified six key components of holistic data asset management:
1. Realistically assess the current state of your data landscape
Before you can take steps to improve how you manage your data assets, you must understand what is preventing you from realising the value of your data right now.
You need to take a detailed look at all aspects of data in your organisation to determine your level of data maturity and identify gaps and opportunities for improvement.
2. Determine the business value of your data.
Next on the list is quantitative data valuation. You need to understand the current and potential value of your data assets in the same way that you understand the value of your organisation’s other assets, such as real estate, equipment, contract claims, and stocks.
Data valuation is a lot of work, but it’s well worth the effort. The resulting map of how your organisation uses (or could be using) data to create value gives you the language you need to think about your data as a strategic asset and compare ROI from data investments with ROI from projects involving other business assets.
3. Evaluate the condition of your data.
Once you know how your data assets can drive value in your organisation, it’s time to figure out how well your data is (or isn’t) fulfilling its intended purpose.
We call this evaluating data condition. It’s the best way to measure two things: how fit for purpose your data assets are and what state they need to be in to deliver optimal business results.
4. Develop an action plan to unlock value from your data.
The first three components of data asset management involve understanding and identifying opportunities to increase your data’s value to the business.
Now it’s time to act on what you’ve learned by developing a detailed, costed data remediation plan. Each proposed project or investment should have a clear connection to improving specific business outcomes or achieving defined strategic objectives.
5. Prioritise projects based on expected value.
Even in organisations where data asset management is standard practice, it’s impossible to execute all your data projects at once. Budgets and personnel are limited, making prioritisation necessary.
You should prioritise the actions in your remediation plan based on the expected impact on business value. Focus on projects with the highest ROI first, and then work your way down the list at whatever pace your organisation can sustain.
6. Demonstrate progress & communicate results.
Leading your organisation to adopt data asset management is a huge accomplishment. If you want to make the switch permanent and avoid reverting to the old way of doing things, you must be able to prove that your data investments are producing tangible business results. It’s the same standard to which investments in traditional business assets are held.
Each of the six aspects of data asset management we’ve covered is important and valuable on its own. When adopted and practiced together as part of an organisational mindset shift to holistic data asset management, they have the potential to finally break the bad data cycle and unlock the transformative power of your data.
Ready to give data asset management a try? Let’s talk.
We hope you’ve found this article helpful in understanding why treating data as an asset is critical to successfully unlocking the enormous potential value of your organisation’s data.
Anmut offers a suite of solutions designed to help data leaders maximise data value by implementing data asset management. Get in touch to learn more. We’ll be happy to answer your questions and hear about your business goals and challenges.