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Why IT is Failing Compliance

In the IT industry where I spent much of my early career, a significant amount of resources are dedicated to integrating components together. This is needed to build enterprise solutions made from capabilities across a variety of existing and new technologies.


Why IT is Failing Compliance
Why IT is Failing Compliance

A common architectural principle used for this kind of integration is to minimize coupling, how tightly they are connected, between the solution and its components. That way you can, in theory, replace the components with something else downstream. You can also avoid unintended side effects when code changes.


Along with the design goal to achieve loose coupling it is also standard practices to achieve a high-level of encapsulation – hiding the internals of the components from the solution that uses it.


Both of these design principles are intended to minimize disruption arising from future changes to either the solution or its components.


While these design principles makes sense for IT solutions, they are not what's needed for compliance. Instead, compliance needs to achieve a tighter coupling and greater transparency with the value chain.


You could say in technical terms, there is an impedance mismatch between IT and compliance objectives.


What Compliance Needs from IT


Compliance needs an integrative approach with the value chain not just integrate with it. This also applies to the tools an technologies that are used to support compliance.


However, IT solutions struggle to realize these principles particularly SAAS and cloud applications. While they may integrate with your business they seldom provide the means for compliance to be an integral part of the value chain so that the business always knows if it is operating between the lines.


Negotiating the cultural and architectural differences between compliance and IT is critical for compliance to achieve higher levels of performance and effectiveness.


This is more important now with the advent of artificial or rather machine intelligence where we need greater levels of transparency, explain-ability, and trust.

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