The hidden cost of designing system around Tools

This is a topic that deserves far more attention than it currently receives.I have seen multiple organisations become trapped by tools — not because the tools were bad, but because the systems were designed around the tools. Once this happens, exiting the tool becomes extremely difficult, expensive, and risky. Over time, the tool starts driving decisions instead of the business.Ironically, this often happens in the name of being “tool agnostic”.As a transformation architect, when I engage with large transformation programs — especially in the Intelligent Process Automation (IPA) space — I often see an excessive number of tools introduced across the end-to-end solution. BPM, RPA, ECM, analytics platforms, GenAI layers — each added with good intent, but rarely with a cohesive architectural philosophy.The result is usually the same: highly coupled applications, fragile integrations, and a solution that struggles to scale.Eventually, the program fails — not because of technology limitations, but because the design introduces bottlenecks that slow down decision-making, change, and growth.I recently worked on such a transformation. The solution had already been delivered to business users, but when I started interacting with them, several anti-patterns became immediately visible:

• Critical decisions lived in individual agents’ minds

• Heavy reliance on SMEs for knowledge transfer

• Business rules embedded in processes instead of being explicit

• Low confidence in scaling or changing the solution

These are not isolated issues — they are systemic problems across the industry.The question is: can this be avoided? In my experience, yes — but only through strict, principle-driven design.Below are the core principles I believe every modern transformation should follow.

1. Loosely Coupled Architecture

Each technology layer must be designed as an independent capability.For example, the BPM layer should focus purely on business orchestration, not business logic, data storage, or reporting. A loosely coupled architecture allows each layer to scale independently and evolve without impacting others.Tight coupling may feel faster initially, but it becomes the biggest barrier to scale later.

2. Orchestration Driven by Business Events

Not every event deserves orchestration.Starting a business process simply because a claim is submitted is an anti-pattern. Instead:

• Validate the input

• Extract and enrich the data

• Apply rules

• Only then initiate orchestration

This reduces unnecessary process overhead and improves system efficiency.

3. Configurable Business Rules

Business rules that influence outcomes must be configurable, not hard-coded.Changes in business policy — such as introducing discount coupons or eligibility criteria — should not require process redesigns. If a small business change triggers a large technical change, the design has already failed.

4. GenAI as a Probabilistic Layer

GenAI should be treated as a probabilistic decision-support layer, not a deterministic system.Every GenAI interaction must:

• Return a confidence score

• Support human-in-the-loop for low confidence outcomes

• Be justified by clear return on investment

Using GenAI without economic or operational clarity has already caused multiple initiatives to fail.

5. Content Management as a Document Store

Content Management systems should act as document stores, with attributes captured as metadata.When designed correctly, ECM becomes the foundation for paperless transformation rather than a passive storage system.

6. Data Store and Data Lifecycle Design

Data is the backbone of transformation.If data lifecycle management — retention, archival, partitioning, analytics decoupling — is not designed upfront, the solution will not scale. Performance degradation is not a question of “if”, but “when”.

7. Secure and Compliant Data by Design

Data is an organisation’s most valuable asset.Security must answer:

• Who accessed the data

• When it was accessed

• Why it was accessed

Strict access control, auditability, and compliance are not optional — they are foundational.

8. Asynchronous, Resilient Design

Multi-technology solutions must be asynchronous by default.Each layer should be able to operate independently. Failure or change in one system should not cascade into others. This is critical for sustainability and long-term governance.

9. Explicit Error and Exception Handling

Errors should never be “handled later”.In complex ecosystems:

• Errors must be logged clearly

• Retry responsibility must be defined

• Ownership of failure must be explicit

A system that cannot be governed easily will eventually collapse under its own complexity.

Closing Thought

Tools will continue to evolve. Technologies will change. But principles endure.Successful transformations are not tool-led or vendor-led — they are principle-led, with technology serving the business, not defining it.