Software, Cloud, Agile, other….
In a recent talk I gave on Scrum I highlighted the power of inspect and adapt cycles. Or as the the Agile Principle puts it: Our highest priority is to satisfy the customer through early and continuous delivery of valuable software. First I talked about a non-agile project that did NOT inspect and adapt. On […]
We should trust data. We certainly should trust data more than we trust the HiPPO. But when we dive head-first into the data looking for answers when we ourselves do not know the questions, that can be risky. After all, Goal, Question, Metric (GQM) was promoted (in that order) over 20 years ago. (here is […]
Photo credit: http://www.filmchronicles.com/star-trek-nemesis/
You can’t sort of A/B test your way before the product launches, because you don’t have it in users’ hands yet. You need to use your product intuition to make the right choices. You make these choices and people are paying you to make them. Steven Sinofsky, former Microsoft President Windows D11 Conference, May 2013 […]
It is funny that whenever I teach (or lecture, or cajole) software engineering teams about the necessity for customer centricity, I almost inevitably get challenged with the example of Steve Jobs’ Apple. Jobs did not care about focus groups, Jobs did not task his teams to deeply mine customer data… he just told them what […]
I spent a long time talking to folks about the merits of a conscientious Testing in Production (TiP) strategy. But I knew TiP had a bad rap. I even shared the story of how some would mischaracterize it as a common and costly technical malpractice While evangelizing TiP, I and my Microsoft colleagues would happily […]
HiPPO stands for Highest Paid Person’s Opinion HiPPO driven decision making is the opposite of data-driven decision making. The highest paid” person may be your boss, or the VP with his eye on the project, or even the CEO. But no matter how many of those big bucks they are pulling down, it turns out […]
The scientific method is the time-proven way we have learned about the very principles that govern the universe. It can be summarized by the following sequential steps Ask a question Construct a hypothesis Test the hypothesis with an experiment Analyze results of the experiment Determine whether hypothesis was correct Answer the question Testability A hypothesis […]
The "dictionary" definition of Data-Driven Quality (DDQ) is: Application of data science techniques to a variety of data sources to assess and drive software quality. But it is really about questions and answers, specifically using data to find those answers. Trying to derive insights from data without knowing what you are looking for can be […]