|By Nicole Bryan||
|June 25, 2016 01:00 PM EDT||
Consider the following integration scenarios: Moving medical records between EMR systems; financial information between banking systems; HR information between ERP systems; and software development information between SDLC tools.
At first glance the approaches required for these integrations may seem the same. But if you look slightly deeper you will realize that this can't be the case because of impedance mismatch. I'm defining impedance mismatch as the friction that occurs when trying to align two things or concepts that don't naturally/actually match. Because many of the hardest impedance mismatches are domain specific, to overcome them you have to have a layer of domain understanding "baked into" your integration software to address business problems.
That's what too often has been missing, because historically integration has primarily been perceived as being accomplished by overcoming a series of low-level, generic technical problems.
This misconception about addressing integration becomes evident as soon as someone comes into your office to sell you integration software. Invariably, the conversation quickly turns to questions such as: What is your message queue policy? How do you handle conflict management? What value transformations are available?
Those are secondary questions. Of course every application that you use should have those qualities. Shouldn't any integration application have a robust message queue implementation?
If you think of integration as nothing more than a series of low-level technical problems then you're going to default to those questions. No business person knows or cares about message queues, conflict management or value transformations. They care about getting the information they need when they want it. And that requires domain awareness.
Begin to move away from that misguided thinking about integration. There are virtually no troublesome technical hurdles anymore. Integration is a business problem that requires higher level technology solutions that are domain specific. And for different categories of business problems you need very different technical solutions. As a result, the next wave of integration will be all about domain expertise and nuance.
This brings us back to impedance mismatch. When you have something that has "friction" because there are fundamental differences between the two sides, what do you do?
Consider this example: If you are integrating requirements between IBM Doors Next Generation (DNG) and Atlassian JIRA, you need to know that JIRA only allows two levels of hierarchy (three if you include sub-task, but sub-task is used differently in JIRA to other artifact types). However DNG has an infinite number of them.
This business problem can only be solved by having the domain experts (the business analysts and the developers) decide how they will structure DNG such that the right layer in the tree translates to the epic/story in JIRA. JIRA can't handle more than two levels, and no amount of technical magic will help that. The only solution is to add a layer of domain expertise by practitioners, who must make some decisions. And the underlying integration software has to be "domain aware" to know that this situation can occur and what to do about it.
Here is another example. Let's say your organization is implementing the Scaled Agile Framework (SAFe). You need to have the high-level status of either "Ready for Release" or "In Development" at the Feature level. That is all the portfolio manager needs to know - and his tool is configured to handle those statuses.
But your developers have gotten deep into kanban, so the statuses for them are not just "In Development," but rather "Ready for SWAG," "Ready for UX Design," "Ready for Scoping," "Ready for Done Review," etc. What do you do?
Any integration software will know to provide a transformation that allows for multiple statuses in one tool to map to a single status in another tool. But domain aware integration software will provide a much needed level of ease of configuration (i.e. no coding) and should be able to automate the transformation needed. This is only possible if you "layer on" the domain expertise on top of the underlying technical engine.
General integration solutions that are nonspecific to the problem simply can't do this because they have no semantic understanding of the underlying information. Without really understanding the meaning of the data, which requires domain expertise, it is much harder to craft solutions that actually address the business problem you are trying to solve.
Dumb vs. Smart Integration
Consider this next example of integration using what I call dumb (generic) integration and smart (domain aware) integration techniques: Your organization needs to flow defects between itself and all suppliers. Defects are probably the most well understood and clearly defined artifacts that exist in software development. A dumb integration approach would simply list all the attributes that all defects have and then have you map each attribute to an attribute on the other side. If you have no insight into the actual goals of why these defects need to flow between systems, it would be legitimate to use this approach.
Since you are crossing organizational boundaries, you might want to create a "smart" integration to ensure that no proprietary attributes are being flowed outside your organization. And you may wish to limit attributes, for example, only to primary attributes such as priority and status to ensure efficient flow.
Rather than starting from scratch and working through all of the many impedance mismatches (e.g. one tool uses two attributes to represent priority and the other one uses only one attribute to represent priority), it makes sense for the integration tool to tell you what aspects of a defect should be flowed between tools and offer suggestions regarding when and how to best transform information when necessary. Without a layer of domain expertise, this can't be done.
Is the Tool Domain Aware?
All of these impedance mismatch examples require an understanding of the underlying business problem specific to software delivery that is being solved. As such, they are not low-level technology problems. And thus, it is critical that the first question that anyone asks when considering the right tools to help with integration is, "Is this tool domain aware?"
When moving medical records between EMR systems, consider software from a vendor that understands the healthcare industry. The same approach holds true for financial software. Software development is no different. Your approach to integrating SDLC tools should start from a place of domain expertise. Because to do SDLC integration well, you can't just simply throw technology at it. You have to bake in domain knowledge. It's as simple as that.
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