Several months ago, Daan Rijsenbrij approached me (Ronald Damhof) and Martijn Evers to assist him in researching data architecture as it manifests itself in organisations.
Daan: "In the Netherlands an international research is performed about data architecture. The purpose of this research is to investigate the maturity in the thinking about & working with data in modern enterprises. You can download a survey from drop box: https://lnkd.in/ghVCqSx The survey consists of a short intro, a scoring list and a list with 12 open questions. Answer only those items that are relevant according to you in your situation. Please return the filled in survey to Daan as an attachment to an email: [email protected]."
The survey is written by me and Martijn and reviewed by a dozen or so fellow data architects. The intro of the survey is copied 1:1 in the next section. We would like to urge architects - affiliated with data architecture - to do the survey, return it to Daan and help us in advancing data architecture.
Nowadays, one frequently hears senior executives, management consultants or strategists proclaim the phrase: “Data is an asset.” While not necessarily incorrect, it is usually a hollow phrase because it is often misunderstood and seldom operationalized. With data comes the need and responsibility to manage it in a dedicated and professional manner, both from a liability point-of-view as well as to create the necessary conditions to truly leverage its potential to add value.
Data is not an asset like financial capital, which can be spent. Nor is it like human capital, which walks out of the door when it sees a better opportunity. Data asset are different: they are uniquely yours, closely tied to your business language and processes, full of nuance, always defined in a specific context and it provides the ability to generate new data (assets).
Data is also unique in that it depreciates in a nonphysical and often undetectable way, losing its meaning, accuracy and/or relevance as time goes by. Every organization can use its data in its own way to differentiate itself. When data is consumed in your organization, it will not be depleted nor will it expire (like a patent). No other type of asset has these particular characteristics.
Data defines other assets. For example, it reveals your financial state, it holds a reliable record of your employees or customer behavior. Arguably, data is the ultimate proprietary asset. And unlike technology, it cannot be commoditized. Data uniquely defines the state and meaning of an organization and its intrinsic value, which cannot be transferred to another organisation.
While all other assets are managed consciously by entire departments with ample resources to do so, data is often considered a by-product of information systems, something often perceived as technological. Or as Frank Buytendijk of Gartner put it: “Most companies manage their parking-lot better than their data.”
In all the hype and buzz surrounding #BigData #InternetOfThings #Datascience #MachineLearning #Digitization and the like, technology is perceived as a primary differentiator. Well, it's not.
While technology is essential for any business, it is usually of lesser importance in terms of competitive advantage. Technological innovations may give a company a competitive advantage, but the effect is only temporary. Sooner or later, innovations will be copied by competitors. Technology tends to become commoditized over time.
Ignoring the hype that surrounds new data-related technology, the common (success) factor is always data that is relevant, reliable, consistent and timely. Investments that neglect data quality requirements are doomed to fail.
The technological evolution continues to accelerate, yet ultimately it’s not about the technology. “IT does not matter”. What does matter is architecture. We need to understand the data, how it’s used, and to build a supporting data infrastructure. This requires fundamental thinking, not buying. It requires a holistic approach, not a siloed approach. You cannot buy your way out of the data misery you are in - it takes blood, sweat and tears. Or in other words: stamina, discipline, trust and courage, especially by senior management.
How well an organization is able and willing to incorporate this approach ultimately determines how well it can leverage its data assets for the benefit of its customers and operational excellence. It is this approach that we need to focus our energy on, instead of indiscriminately following the latest fad, promise or glossy brochure, with an unfounded belief that this new technology will solve our data issues.
There is no quick fix!
It is imperative to realize that data is a foundational element that drives and leverages innovation, business transformations, acquisitions and other organizational-critical events; data architecture is the guardian of this foundation.
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