Single Source of Truth: What Is It and Why Does Your Project Need It?

Friday, May 21, 2021

Adopting a data-driven Single Source of Truth (SSOT) framework can offer a range of organization-wide benefits for corporations and enterprises.

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Single Source of Truth: What Is It and Why Does Your Project Need It?
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We all strive to make the best decisions whenever we can. Whether it be something as simple as buying more natural groceries or planning to purchase a new home, we rely on our experience, and more importantly, the information we’ve gathered through various means.

Just like you would ask your friend who’s working in the IT sector what’s the best laptop for the buck or your mother for some financial advice, employees of every company rely on similar dialogues, albeit on a bigger scale. Now, today’s topic is the Single Source of Truth, aka SSOT. Let’s dive in, shall we?

What is the SSOT concept?

The SSOT is essentially synonymous with centralized data, which is accurately compiled and readily available to the entirety of staff in an organization (be it a company, a one-off or a pending project).

The idea behind it was born with simplicity in mind. As technology progressed, the speed of communication sky-rocketed, which made data acquisition more rapid but also slightly less reliable.

Save from entrepreneurs and a handful of small businesses that rely on a centralized organization plan, most companies and projects have at least several intellectual inputs. Some of these sectors require more time to gather required information, others update their servers too fast; both extremes lack the reliability to make proper data-driven decisions on time.

The necessity of SSOT in modern-day enterprises and companies

Before we get to the discussion of the potential benefits of this concept, let’s touch on the topic of its necessity in modern times.

Companies that have existed for multiple decades have seen all kinds of trends and schemes come and go, so it’s safe to say that a fair amount of resistance to innovations in terms of (proven) business plans would be present.

Traditionally, the hierarchy of an enterprise mirrors the availability of data simply due to the fact that decision-making isn’t privy to everyone in the same quantity.

It’s not hard to imagine that a truck driver who’s supposed to deliver cargo from point A to point B doesn’t need to know the exact list of his company’s business partners, but they do need to know what they're transporting, to whom and by which time.

The advent of digital technologies has simplified modes of communication; it vastly improved navigation via apps such as Google maps and various GPS devices, but it also paved the way for conflicting data.

Connected platforms sometimes don’t yield the same results

Several applications may be made by the same company, just like several sectors may belong to the same enterprise; they often don’t use the exact same ways of acquiring data, let alone of processing it.

Consumers are ultimately the people who contribute data to apps, systems and companies, whether they do it automatically by using any sort of device or by answering questionnaires and such.

Obviously, different people have different experiences. It’s not hard to imagine that the same person can like a product/service while at the same time giving it different ratings on different platforms.

For instance, a GPS system is deemed as dependable and accurate throughout the year; the consumers label it as affordable, and just around the time when a global update is scheduled to happen, negative reviews start popping up.

People who weren’t using the aforementioned system wouldn’t feel too inclined to update their rating while those stuck abroad would be deeply affected by it and may completely abandon it.

One sector of the company would analyze the statistics of people who are using the app, the second sector would observe the feedback on social media and app-based platforms, the third sector would check out polls and questionnaires.

This is arguably one of the simplest scenarios of a business with decentralized data processing system with a single product on the table, and still, we can see that the data will conflict even in the most typical day-to-day events.

Implementing SSOT in your enterprise

There are multiple ways to go about integrating SSOT into a company, and the best way to do it is to adapt it to your particular business plan. The smaller the project is, the easier it gets, as you’ll need to filter the information through fewer outlets. Still, there are a few models that have proved to be effective, so let’s take a quick look:

Enterprise service bus (ESB)

In simplest terms, the ESB model enables all systems to send or receive updates across the whole board regarding data transitioning.

Data acquisition, storage and analysis are three separate tasks; normally, the systems can be granted access to stored data while they would regularly receive analyzed information pieces required for their normal operation.

Master-data management (MDM)

The MDM model substitutes as an SSOT for systems that don’t have an actual SSOT. Prior to distributing relevant info, its availability is limited according to the section’s hierarchy.

In such cases, the MDM model can serve as a valid alternative, offering readily available unprocessed data to any team that may depend on it without compromising the aforementioned hierarchy.

Data warehouse (DW)

The data warehouse concept is essentially one of the simplest forms of SSOT. All systems (centralized or decentralized) gather data and provide copies to DW, allowing sectors and teams that have processed it in any different way to easily compare their results.

Andy Schmidt

Andy has been in the online content world for over 10 years as a freelance copywriter, technical writer and translator, covering different topics - finance, energy and also sustainability. What is he doing when not writing? Andy learned how to enjoy long walks, play chess, and finally - how to sleep at night. 


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