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Data Models

To automate their work, departments use databases, computer systems, and applications, which employ data models and databases to capture and lock in the business language of their users.

While automation can help each department boost efficiency, it can also mean that the company winds up with multiple, disparate, department-level databases that don’t speak to each other very well.

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technical debt is the result of shortcuts — choosing quick fixes over a long-term investment — it causes plenty of problems in the here and now. It adds enormous friction any time people need to coordinate work together across silos.

The seeds of technical debt are sown as businesses grow, change, and innovate, naturally leading teams and departments to develop and adopt new, increasingly specialized business language to help them do their work efficiently.

Over time, departments develop their own languages. While sales, marketing, and finance all talk about “customers,” they likely don’t mean the same thing.

The secret to resolving the conflict lies in recognizing and clarifying the underlying concepts:

People do a lot of work to accommodate the disparate systems: Business departments develop work-arounds and IT crafts custom interfaces to connect these systems. These measures add complexity; though without them, systems simply would not work.

The only proven way to fix this problem is to intervene at step one, via common language. This may seem like a daunting task — after all companies have thousands of terms in their vocabularies.

A senior leader must assemble and manage a diverse team to get the work done, including:

Common language and data models provide an architecture that guides further technological development.

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