Map IT knowledge via skills

IT knowledge is not only very short-lived ( See article), but also both broad and deep. This is due to the nature and content of the IT industry, which we will briefly discuss in this article. Nevertheless, there should be a way to make this knowledge tangible and precise.

Do skills give this possibility? And how well do they reflect the knowledge? More on that now!

IT knowledge is broad and deep

At start, we would like to show why the knowledge from the IT industry can extend massively in both dimensions.

Broad IT knowledge

The breadth of knowledge comes from the fact that there are always competing solutions for different methods and tools. The developer must know these, or at least know that they exist.

For example, there is not just one programming language, but an almost unmanageable number of worlds. The JVM universe with Java and Kotlin, the JavaScript ecosystem with vanilla JS and TypeScript, the C world with C++ in its different standards, plain old C and Rust, PHP, C# and many more singular languages like Python, PHP, Go, Haskell and much more.

A system architecture can be built on different database types: relational SQL databases, NoSQL databases, object or graph databases, data warehouses or no database at all.

It is no different with the frameworks. There are at least five popular JavaScript-based web frontends: React, Angular, Vue, Svelte and Ember. All of these are are based on different development philosophies. The same applies to methods or design patterns and and and.

There are always different approaches at a certain level. There is no “one” right solution, architects and developers must choose from a multitude of options.

IT knowledge in depth

The depth of knowledge ranges in almost all subject areas from the theoretical basics of computer science (such as runtime complexity O(n)) to highly specific requirements (such as the structure of SQL queries for the best possible high-performance answers).

The more one can speak of an expert status, the deeper the knowledge usually goes. An expert for instance in PostgreSQL not only knows basic SQL functions, but also, through experience, various specific features and procedures that others do not know. Why is this distinction important?


In practice, most teams are built on a broad IT knowledge base.

Possible solutions are already predetermined by the technology stack of a company. Nevertheless, every employee has different depths of knowledge about the individual solutions.


In order to make this knowledge visible, certain areas of knowledge can be provided with "labels" so that they are meaningful to the outside world. That’s what we at 8Buddy call skills. What do these skills look like? As a rule, they consist of one or more words that are intended to specify the knowledge of the team member:

  • Cloud Computing
  • Data management
  • Information security
  • Java
  • SAP
  • Scrum
  • Identity & Access Management
  • SQL

Skills act as placeholders for an employee's knowledge. In practice, this is much more complex and extensive, because weeks, months or even years were often invested in acquiring and enriching this knowledge.

However, there are no "standardized skills" from which employees can choose. Depending on the company or even the person, these terms differ. Another problem: Skills cannot always be clearly distinguished from one another, as the following examples show:

  • TypeScript and Javascript
  • TensorFlow and Python
  • Observer Pattern and Futures

Despite these challenges, skills are useful to cluster and categorize knowledge.

Skills in practice

In practice, teams can benefit from the skill labels. On the one hand, teams can use this to make transparent which skills, i.e., which knowledge, lies in a team. If the team is to enter new technological area, it can quickly be seen whether the team already has the relevant skills. If the knowledge needs to be developed or bought into the company, the team can specify which skills a new team member should bring with them. Even when looking for experts, teams can specify requirements for technological support.

In 8Buddy, each skill can also be assigned a level. The range is from skill level 1 to 8, the higher the value, the more experience the employee has in this area. The levels express the depth of knowledge. A PostgreSQL novice gets a 1 out of 8, while an expert gets an 8 out of 8.

Of course, this system is not perfect either, but it makes it easier to find your way through the jungle of knowledge and helps you to get to the buddy who can help you more quickly. In the case of a complex problem, you can search directly for a buddy with a higher level. For simple basic questions, a contact person with a lower skill level is sufficient or even more appropriate. this relieves the experts. In addition, the inhibition threshold to speak up to a colleague with similar experiences is often lower.

Skills are also helpful when looking for a job: Developers can state briefly and precisely which skills distinguish them, and companies can use skill information for job advertisements. This enables developers to find exactly the jobs that match their skillset more quickly.


Skills help to present complex knowledge in a simplified way in order to quickly find the right contact person who has the relevant knowledge. Like any system, this mapping method has its limitations.

Companies benefit from making skills in the company transparent and promoting the exchange of knowledge. We can support this with 8Buddy, because our platform makes it possible to disclose skills in the company. Not only teams, but also recruiting benefit from this solution.

Do you have any questions? Write to us.