18 top agile practices

Haitian vodou altar - embodying top practices

Big ideas are dangerous. Something worked somewhere some when but it will not work everywhere and always. Teams and companies are likely to pick some agile practices while they disregard others. Keep reading for a list of the most agile sectors and the most common agile practices.

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4 myths about software development productivity

Greger Wikstrand and Joakim Lindbom talk about software development productivity.

There is no conflict between speed and quality! That was the header for lesson one of your relearning program. You want to improve software development productivity in yourself, your team or your organization? Then follow me along and debunk a few myths.

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Guest appearance on Architecture Corner

I recently had the pleasure of meeting with Casimir Artmann and feature as a guest on his “Architecture Corner”. We talked about agile and why it is necessary. Read more here on the blog or watch the video:
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Sometimes #noestimates can’t help you predict the future

Now that #noestimates has become fairly mainstream, you could wonder how #noestimates can help you predict the future? When I saw that InfoQ included #noestimates as part of their “State of Agile” article for 2014 it was clear to me that #noestimates will continue to be part of our common…

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Should you distrust agile?

Should you distrust people who play with rubber chickens at work?

Why do some people distrust agile software development? Should you distrust agile software development? How can you possible trust people who say that they will “take your money and deliver something” after a month or so? How can you possible trust people who have a rubber bird as part of…

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Software Development Success

A roadpost pointing to success or failure

[bibshow] Software development success is organization dependent. Which organizations are successful in developing and delivering software? Which projects will be successful? That is a crucial question in an industry with an annual turnover of over 400 billion USD and only a 50% success rate. [bibcite key=”citeulike:4540645″] Is it enough to…

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Agile projects requirements breakdown structure

fibonacci series in nature

In Agile projects, when a set of requirements are received from Clients, it may consist of (a mix of) A few needs, objectives, goals and some partial stories (even though it would have come in a structured document). Re-organizing (re-arranging) those into a requirements breakdown structure (RBS) helps ask right questions to…

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Can you trust agile software development?

A CISV educational activity - a trust game

[bibshow] As a consultant [bibcite key=”citeulike:13415391″] and as an agilist [bibcite key=”citeulike:9846510″] I have a vested interest in trust. Trust might be seen as one of the top two factors for success in software development projects [bibcite key=”citeulike:2824986″]. Most of us have a vague idea of what is needed to…

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Agile Community of Practice

A data repository is not a community of practice

I’m a strong believer in learning by doing. I also believe that learning will be better when supported by an agile community of practice (CoP). Communities of practice allow self-selected members to develop their “capabilities, build and exchange knowledge”. In my professional life, I am involved in several communities including…

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Combining Traditional and Agile Estimation

Can you combine traditional and agile estimation? There is nothing magical about “classical” estimation. There are a few basic concepts to keep track of:

  • Bottom up versus top down
  • Expert estimation versus parametric estimation
  • Best – worst – expected case

I think the most common method for traditional estimation is to go top-down using successive estimation which means that when something is to big or uncertain, you break it down into component tasks and estimate them recursively. If you are familiar with Planning Poker you can easily combine it with this approach:

  1. Start with your user stories + other backlog items then FOR EACH
  2. Estimate it with PP, if too big or to wide spread it is an Epic. Break it down into smaller stories (this creates your WBS) and GOTO 2
  3. Now that your item is sufficiently small, think about the worst case and estimate it again
  4. Now think about the best case, estimate again
  5. Calculate the weighted average as (best + 4* “normal” + worst) / 6

Not so different from “pure” Planning Poker, is it? There are a few improvements you can do though — instead of using three estimates for each item, you could use the spread of estimates you already have from PP as a basis for your probability distribution.