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LeSS is clearly in the Scrum and Agile tradition. It is the simplest of the three approaches and makes only a few changes to vanilla Scrum. When I look at Spotify, an organization that has scaled from 6 to 1200 staff members, I see a company architecture that is very close to LeSS. It will be a very natural approach for small organizations that are scaling up as they grow.

FDA and other regulatory agencies fundamentally want to see that your product has safety in mind. To do so, they require complete traceability through the hardware and software. There is even a fairly new standard, IEC 62304, adopted worldwide that is wholly focused on software traceability from requirements through architecture to tests.

Medical devices companies are going primarily agile to respond to change and effectively manage technical complexity by collaboratively building solutions with their partners and customers to ultimately deliver what the customer wants before the competition does.

demo the new functionality created after each iteration to your customers, using web-based meets. Using these tools enables you to get immediate feedback from your customers throughout the project. Continuous customer feedback reduces the risk of building the wrong solution. The fact is in most cases you can’t make the release cycle more frequent since it includes giving tests to regulatory agencies. This is a tedious process that makes sure the device is safe. Doing the whole release cycle more frequently can be way too time consuming.

In its common usage, evolutionary design is a disaster. The design ends up being the aggregation of a bunch of ad-hoc tactical decisions, each of which makes the code harder to alter. In many ways you might argue this is no design, certainly it usually leads to a poor design. As Kent puts it, design is there to enable you to keep changing the software easily in the long term. As design deteriorates, so does your ability to make changes effectively. You have the state of software entropy, over time the design gets worse and worse. Not only does this make the software harder to change, it also makes bugs both easier to breed and harder to find and safely kill. This is the "code and fix" nightmare, where the bugs become exponentially more expensive to fix as the project goes on

the planned design approach has been around since the 70s, and lots of people have used it. It is better in many ways than code and fix evolutionary design. But it has some faults. The first fault is that it's impossible to think through all the issues that you need to deal with when you are programming. So it's inevitable that when programming you will find things that question the design. However if the designers are done, moved onto another project, what happens? The programmers start coding around the design and entropy sets in. Even if the designer isn't gone, it takes time to sort out the design issues, change the drawings, and then alter the code. There's usually a quicker fix and time pressure. Hence entropy (again).

One way to deal with changing requirements is to build flexibility into the design so that you can easily change it as the requirements change. However this requires insight into what kind of changes you expect. A design can be planned to deal with areas of volatility, but while that will help for foreseen requirements changes, it won't help (and can hurt) for unforeseen changes. So you have to understand the requirements well enough to separate the volatile areas, and my observation is that this is very hard. Now some of these requirements problems are due to not understanding requirements clearly enough. So a lot of people focus on requirements engineering processes to get better requirements in the hope that this will prevent the need to change the design later on. But even this direction is one that may not lead to a cure. Many unforeseen requirements changes occur due to changes in the business. Those can't be prevented, however careful your requirements engineering process.