The Cost of Chaos: Duplication and Redundancy in the Absence of a Common Glossary

In my earlier articles, I introduced the paradox that most insurers are data-rich but information-poor, explored what truly defines business information, and described how organisations can mature from information to knowledge to wisdom.

Yet one foundational issue underpins nearly every failure in business information management — the absence of a common business glossary.

When Every Department Speaks a Different Language

Walk into any large insurance organisation and ask a simple question:

“Who is the customer?”

You’ll likely get a different answer from underwriting, claims, finance, and distribution — each valid in its own context, but collectively inconsistent.

This semantic confusion has profound consequences:

• Duplicate processes: Each function builds its own interpretation of “Customer” or “Policy,” resulting in parallel workflows.
• Duplicate data: Multiple systems store their own version of the same entity — slightly different, rarely synchronised.
• Duplicate MI: Reports are generated independently, drawing from different sources, each claiming to be “the truth.”

The cost of this chaos is immense — not just in terms of technology spend, but also in lost efficiency, compliance risk, and poor customer experience.

The Anatomy of Duplication

Let’s take a simple example from commercial insurance:

• The Underwriting team defines a customer as a brokered entity.
• The Claims team defines a customer as the claimant or policyholder.
• The Finance team defines a customer as the premium-paying party.

Each definition is legitimate in isolation, but when data, processes, and reporting are built around these different interpretations, the organisation unintentionally multiplies its complexity.

This is why so many insurers invest millions in “data lakes” or “customer 360” projects, yet still struggle to reconcile basic information. The issue isn’t the data — it’s the lack of shared business meaning.

Why Common Glossary Matters

A business glossary provides the shared vocabulary through which the enterprise defines, governs, and interprets its core business concepts.

Without it:

• Process automation initiatives stall because definitions don’t align.
• Data governance becomes an endless exercise in reconciliation.
• MI and analytics teams spend more time debating definitions than generating insights.

With it:

• Business units operate from a single version of truth.
• Reporting architectures simplify.
• Decision-making accelerates.

It becomes the linguistic glue binding capabilities, processes, and systems together.

From Chaos to Clarity: The Role of Business Information Model

Creating a Business Information Model (BIM) is the next logical step. It unifies the organisation’s vocabulary by:

• Collating all the terms used for the same business object.
• Establishing clear relationships between entities (Customer–Policy–Claim–Risk).
• Providing a shared reference for capability design, data integration, and MI architecture.

The BIM doesn’t replace data models — it precedes them. It’s where the enterprise defines what it needs to know before deciding how and where it will store the data.

What's Next in This Series

In the last article in this series, I'll explore how to build and sustain a Business Information Model - not as a documentation exercise, but as a strategic enabler of transformation, connecting business language, data governance and operating model design.

If you agree with my views, here's a hint: Before starting your next data or reporting initiative, as this simple question: "Do we have a common understanding of what our business terms mean?" If the answer is no, that's where your real transformation challenge lies.