Plutora Blog - Business Intelligence, Digital Transformation, IT Governance, Release Management, Value Stream Management
Single Source of Truth (SSOT): Definition and ExamplesReading time 9 minutes
Your product is creating a buzz in the market. Accordingly, the analytics team is processing your product’s data to evaluate its growth metrics. At the same time, your business team is drilling down the sales data to scale revenue. Your stakeholders and managers are discussing your users’ retention and acquisition data.
You may be inflowing data from multiple sources, but you needn’t create multiple sources to store your data. At the end of the day, you want all your decision-makers in sync with one another, processing the same data from a central source. This central source is also known as a single source of truth (SSOT).
In this post, I’ll walk you through the essentials of SSOT. I’ll also explain why you’re going to love it and provide some relevant examples, implementations, and use cases.
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In order to accurately define SSOT, let’s first understand what SSOT isn’t:
- It’s not a tool or framework you integrate with your system.
- It’s not a master strategy to ramp up your business insights and analytics.
SSOT is merely a practice to keep all your data in a single place. To break down the term, “single source” implies a common reference, and “truth” implies a combination of your data elements.
For instance, if you have a product-centered business, your SSOT could represent a common pool of all the data and information used by a multitude of teams in your organization. These will include
- Resources and assets used by your engineering team
- Business insights used by the analytics team
- User engagement data used by your managers and stakeholders
It’s important to note that the definition of SSOT depends on the context. It doesn’t always have to revolve around data. This becomes clearer in the examples section, but a one-stop platform/solution is a more precise translation of SSOT, where truth varies depending on what you’re trying to achieve.
In information theory and design, SSOT is defined by Wikipedia as “the method of structuring your data models and schema in a single place so that all your data have a common reference.”
There are two technical constraints here. First, all your data resides in a central place. Second, any modifications to the data must be reflected everywhere. To put it differently, you’re only allowed to make a shallow copy, not a deep one. These constraints precisely define what an ideal SSOT should look like.
SSOT Implementations and Architectures
Now that we understand what SSOT is and its technical constraints, let’s see how you implement one. Organizations differ in the way they structure their systems and internally store relevant information. You can architect or implement SSOT in more than one way. These include
- Digital workspaces and project management tools
- Enterprise service buses
- Master data management solutions
- Data warehouses
Let’s take a closer look at each.
Digital Workspaces and Project Management Tools
Digital workspaces and project management tools allow you to organize information for your teams and make it easily accessible. They are your SSOT for ideas, concepts, or suggestions that may have arisen in personal discussions, team meetings, brainstorming sessions, etc. They are incredibly helpful in terms of having all your vital information easily discoverable and organized for future references, especially in a remote work environment. Some common examples include Confluence, Google Keep, and Asana.
Enterprise Service Buses
An enterprise service bus defines the protocol for communication between different applications in your system using a bus-like infrastructure. Imagine a school bus with a number of seats becoming occupied as students board the bus at different stops. This school bus is your ESB, and the seats can be imagined as switches. Accordingly, students boarding the bus represent your ESB’s communication with different applications in your system.
It also notifies your systems when someone modifies anything in your SSOT. Examples of this implementation include Apache Camel and NServiceBus.
Master Data Management Solutions
Master data management (MDM) solutions cater to managing a specific type of data. Called master data, this type of data includes any information pertaining to your product, customers, or assets. MDM solutions let your business users conveniently access and process data independent of the IT team. Some common examples of MDM solutions include Ataccama, Oracle Product Hub, andSAS Master Data Management.
A data warehouse aggregates and manages data from several sources. This includes your own databases, data from your transactions, and other operational sources. It also provides the ability to sort and filter data, which can provide meaningful information that can be further analyzed to deduce business conclusions. Some examples of popular data warehouses include Teradata, Oracle, and AWS.
Diving Deeper Into SSOT: Examples and Use Cases
To understand how and where you can use SSOT, you must define its use case or an end result you expect to achieve from it. Let’s take the use case of enterprise software delivery, which is becoming more complex each day.
Every organization wants to deliver promising software products and services to its customers. An effective approach is to break down the process into objectives or steps and define your SSOT around them.
When enterprise software delivery is your “truth,” your SSOT should effectively optimize these steps discussed in the next section to bring the best customer value possible. This is also known as value stream management, which outlines how an organization can deliver high-quality software on time.
SSOT for Enterprise Software Delivery
Let’s look at how you can define your objectives or steps in your software delivery life cycle to deliver a high-quality software product. Once that’s out of the way, it’s easier to understand what purpose your SSOT is going to serve and help you decide which SSOT to go for.
Your software releases should be well planned. Release management will help you streamline your development and operations. Intelligently tracking and scheduling releases will lower the chances of release failures, something that every organization is deeply concerned about.
Throughout the process, your entire team must adhere to the common governance requirements laid out by your leaders and managers. You also need business intelligence to create a single pool of data from where all your teams can derive valuable business insights. Ultimately, these insights will fuel improvisations in the process to refine customer value at each step.
You should also be able to visually evaluate certain metrics to analyze business-related aspects. It helps you understand how well you’re adding customer value to your software at each step. You can then use these metrics to evaluate your progress and detect bottlenecks if any. For instance, have a look at Plutora’s value stream flow dashboard:
It provides a graphical presentation of parameters such as features, tech debt, and defects that are important from a business standpoint. You can then use this information to gather insightful data such as which items need priority, how to mitigate defects, how to ship features faster, etc.
Plutora also caters to other use cases for SSOT, including business intelligence, IT governance, and release management. Being a complete value stream management platform, it’s a great choice of SSOT for enterprise software delivery.
Benefits of SSOT
There are several advantages you can leverage by implementing SSOT in your organization.
- Data is easily discoverable: With SSOT, all data and information are aggregated in a single place. This makes it easily discoverable. In turn, this ensures that your team doesn’t lose time when collecting relevant information because they have to go to multiple sources. It thus empowers the decision-makers in your company because they have only the right information in their hands.
- Reduced errors and duplicates: SSOT mitigates the chances of running into any errors and creating duplicate or redundant data. The data could also refer to resources in your organization that are used simultaneously by other teams on different projects. For instance, your design and development team could be using the same placeholders and assets in their projects.
- Unification of thoughts: Another great advantage is how SSOT defines a standard for all your teams to agree upon. It imposes a natural constraint on individuals where they feel more convicted toward the information. It essentially brings all your teams on the same page, reducing room for ambiguity and conflicts. This promotes teamwork and effective collaboration.
- Increased efficiency: Finally, SSOT’s most compelling advantage is fueling your teams’ productivity. A one-stop destination for all your resources and information makes it easier for all your teams, managers, and stakeholders to process and analyze it anytime. Consequently, the weekly or monthly reports will come in well before the deadline. As a result, there will be more room for targeting future goals.
Challenges in SSOT
Implementing SSOT could bring in some obstacles, and it’s important to understand how to deal with them.
IT leaders and managers must establish what the central store should be built around. This means formulating the most reliable, accurate, and authentic information as SSOT’s key ingredients. This will most likely get rid of implementing SSOT for poorly defined use cases. It also will prevent its broken implementation.
The next step is to collect high-quality data. It’s natural that data funneling into your system contains duplicates and irrelevant data elements and that it’s highly unorganized. An easy way to combat this problem is to periodically clean your data. You can have your SSOT regularly filtered and sorted to help your teams work with what’s most relevant for them. It’s one cumbersome job once in a while versus an unnecessary daily effort.
Finally, your decision-makers need to read between the lines when drawing conclusions from SSOT. When all your data is in a single place, it becomes difficult to resolve ambiguities and conflicts with respect to what the data is actually conveying. After all, what’s the point of having SSOT if the truth itself is ambiguous and misleading?
How to Implement SSOT in Your Organization
In this post, you learned what SSOT means and why it’s important. You’ve also seen some of its common implementations, examples, and use cases.
Remember that the first step to using SSOT is defining what it means to you. It could be bundling key activities together in order to efficiently deliver an end result or putting together fragmented, unorganized data to obtain more value from it.
Once you’ve defined your use case, explore the best methods, architecture, or implementations around it. Next, keep in mind the challenges so you can use your SSOT to its full potential. Finally, refactor your SSOT periodically so it dynamically scales with your infrastructure.