The Data-Centric Revolution: Integration Debt

Integration Debt is a Form of Technical Debt

As with so many things, we owe the coining of the metaphor “Technical Debt” to Ward Cunningham and the agile community. It is thetechnical debt confluence of several interesting conclusions the community has come to. The first was that being agile means being able to make a simple change to a system in a limited amount of time, and being able to test it easily. That sounds like a goal anyone could get behind, and yet, this is nearly impossible in a legacy environment. Agile proponents know that any well-intentioned agile system is only six months’ worth of entropy away from devolving into that same sad state where small changes take big effort.

One of the tenants of agile is that patterns of code architecture exist that are conducive to making changes. While these patterns are known in general (there is a whole pattern languages movement to keep refining the knowledge and use of these patterns), how they will play out on any given project is emergent. Once you have a starting structure for a system, a given change often perturbs that structure. Usually not a lot. But changes add up, and over time, can greatly impede progress.

One school of thought is to be continually refactoring your code, such that, at all times, it is in its optimal structure to receive new changes. The more pragmatic approach favored by many is that for any given sprint or set of sprints, it is preferable to just accept the fact that the changes are making things architecturally worse; as a result, you set aside a specific sprint every 2-5 sprints to address the accumulated “technical debt” that these un-refactored changes have added to the system. Like financial debt, technical debt accrues compounding interest, and if you let it grow, it gets worse—eventually, exponentially worse, as debt accrues upon debt.

Integration Debt

I’d like to coin a new term: “integration debt.” In some ways it is a type of technical debt, but as we will see here, it is broader, more pervasive, and probably more costly.

Integration debt occurs when we take on a new project that, by its existence, is likely to lead someone at some later point to incur additional work to integrate it with the rest of the enterprise. While technical debt tends to occur within a project or application, integration debt takes place across projects or applications. While technical debt creeps in one change at a time, integration debt tends to come in large leaps.

Here’s how it works: let’s say you’ve been tasked with creating a system to track the effectiveness of direct mail campaigns. It’s pretty simple – you implement these campaigns as some form of project and their results as some form of outcomes. As the system becomes more successful, you add in more information on the total cost of the campaign, perhaps more granular success criteria. Maybe you want to know which prospects and clients were touched by each campaign.

Gradually, it dawns that in order to get this additional information (and especially in order to get it without incurring more research time and re-entry of data), it will require integration with other systems within the firm: the accounting system to get the true costs, the customer service systems to get customer contact information, the marketing systems to get the overlapping target groups, etc. At this point, you recognize that the firm is going to consume a great deal of resources to get a complete data picture. Yet, this could have been known and dealt with at project launch time. It even could have been prevented.

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