I’ve written before on the implementation methodology that I tend to follow when managing my integration projects. If you missed it, you can see it here. I’m taking a lean six sigma course from Simplilearn and was pleasantly surprised by how well our methodology aligned to the lean process.

Step 1: Critical to both processes is identify the value. Why is the customer engaging in
the in this activity? what are they trying to accomplish? how is it measured?

Step 2: In six sigma, the next step is to map the value stream. This step is about getting to the goals & requirements. In our integration methodology, this encompasses steps 2 through 8 and is the core of the nitty gritty details. Since most of my projects relate to data integration, I need to know:

• where’s the data coming from?
• what’s the source of record?
• who owns it?
• what’s the data format(s)?
• how is the data accessed?
• how does the data need to be transformed?
• what’s the frequency of exchange?
• what’s the trigger?
• are there software requirements or limitations?
• have yo closed the loop? do you need to?

Step 3: The process of defining and discovering the requirements and goals leads naturally into the development of whatever flow(s) you need. This is true from a data, development and dependencies perspective. This process also helps identify gaps, complexities, inefficiencies and bottlenecks.

Step 4: In lean, like in data integration projects, you must discuss and determine push versus pull. Lean is seeking out the most efficient solution, generating the least amount of waste. While that is the ideal in data integration projects as well, you’re often at the whim of the technology, or other decisions.

Step 5: Seek perfection in all things! In lean, this means developing a system without waste. In my data integration projects, this means developing the process that will deliver the cleanest, simplest, consistent, and reliable system. And for that you need to be vigilant in your measurement, and you can’t forget or forgo testing and validation. This is not a one-time endeavor. With data (and more and more processes (if not all) are driven by data these days), things can change. The importance of closed feedback loops, regular use and validation, the process and data become stale.

As the project manager for data integration projects, I believe that that we should all be looking for ways to simplify and streamline what we are doing to reduce errors and ultimately become more efficient. As we all know, there is a lot we can not control in project management (and in life). We need to be constantly re-evaluating our state and making incremental improvements. This is the core to both lean six sigma and my integration methodology.

For more information and case studies on lean six sigma, check out this “Learn Lean Six Sigma Part 1” article by Mohamed Elgendy.