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These manifestos are basics to agile project development or we can say estimation and planning of project is carried out in accordance with agile manifesto and 12 principles. Agile estimation and planning includes a famous approach called Poker planning which will be discussed later. Project Planning includes answers of what will one get? When will one get the project done, what will be the cost of project. Major techniques used for estimation are expert opinion, analogy, divide and conquer. Good estimates reduce risk, uncertainty, establishes trust. Agile methods are characterized by incremental delivery and frequent course correction.
Involving everyone (developers, designers, testers, deplorers. . . everyone) on the team is key. Each team member brings a different perspective on the product and the work required to deliver a user story. For example, if product management wants to do something that seems simple, like support a new web browser, development and QA need to weigh in because their experience has taught them what dragons may be lurking beneath the surface. Likewise, design changes require not only the design team’s input, but that of development and QA as well. Leaving part of the broader product team out of the estimation process creates lower quality estimates, lowers morale because key contributors don’t feel included, and compromises the quality of the software. So don’t let your team fall victim to estimates made in a vacuum. It’s a fast track to failure! Agile Estimation and planning together gave rise to poker planning which is popular platform to start thinking in agile way and is discussed later in here.
No individual task should be more than 16 hours of work. (If you’re using story points, you may decide that, say, 20 points is the upper limit. ) It’s simply too hard to estimate individual work items larger than that with a high degree of confidence. And that confidence is especially important for items at the top of the backlog. When something is estimated above your team’s 16-hour (or 20-point) threshold, that’s a signal to break it down into more granular pieces and re-estimate.
For items deeper in the backlog, give a rough estimate. By the time the team actually begins to work on those items, the requirements may change, and your application certainly will have changed. So prior estimates won’t be as accurate. Don’t waste time estimating work that is likely to shift. Just give the product manager a ballpark figure she can use to prioritize the product roadmap appropriately. C. Learn from past estimatesRetrospectives are a time for the team to incorporate insights from past iterations–including the accuracy of their estimates. Many agile tools (like Jira Software) track story points, which makes reflecting on and re-calibrating estimates a lot easier. Try, for example, pulling up the last 5 user stories the team delivered with the story point value 8. Discuss whether each of those work items had a similar level of effort. If not, discuss why. Use that insight in future estimation discussions. Like everything else in agile, estimation is a practice. You’ll get better and better with time.
Estimates are not created by a single individual on the team. Agile teams do not rely on a single expert to estimate. Despite well-known evidence that estimates prepared by those who will do the work are better than estimates prepared by anyone else, estimates are best derived collaboratively by the team, which includes those who will do the work. There are two reasons for this.
First, on an agile project we tend not to know specifically who will perform a given task. Yes, we may all suspect that the team’s database guru will be the one to do the complex stored procedure task that has been identified. However, there’s no guarantee that this will be the case. She may be busy when the time comes and someone else will work on it. So, since anyone may work on anything, it is important that everyone have input into the estimate.
Second, even though we may expect the database guru to do the work, others may have something to say about her estimate. Suppose, for example, that the team’s database guru, Kristy, estimates a particular user story as three ideal days. Someone else on the project may not know enough to program the feature himself but he may know enough to say, “Kristy, you’re nuts; the last time you worked on a feature like that it took a lot longer. I think you’re forgetting how hard it was last time. ” At that point Kristy may offer a good explanation of why it’s different this time. However, more often than not in my experience, she will acknowledge that she was indeed underestimating the feature.
If you want to know how long something is likely to take, ask an expert. At least, that’s one approach. In an expert opinion-based approach to estimating, an expert is asked how long something will take or how big it will be. The expert relies on her intuition or gut feel and provides an estimate. This approach is less useful on agile projects than on traditional projects. On an agile project, estimates are assigned to user stories or other user-valued functionality.
Developing this functionality is likely to require a variety of skills normally performed by more than one person. This makes it difficult to find suitable experts who can assess the effort across all disciplines.
An alternative to expert opinion comes in the form of estimating by analogy, which is what we’re doing when we say “this story is a little bigger than that story. ” When estimating by analogy, the estimator compares the story being estimated to one or more other stories. If the story is twice the size, it is given an estimate twice as large. There is evidence that we are better at estimating relativesize than we are at estimating absolute size.
When estimating this way you do not compare all stories against a single baseline or universal referece. Instead, you want to estimate each new story against an assortment of those that have already been estimated. This is referred to as triangulation.
Disaggregation refers to splitting a story or feature into smaller, easier-to-estimate pieces. If most of the user stories to be included in a project are in therange of 2-5 days to develop, it will be very difficult to estimate a single story that may be 100 days. Not only are large things notoriously more difficult to estimate, but in this case there will be very few similarly sized stories to compare to.
“Is this story fifty times as hard as that story” is a very different question than “Is this story about one-and-a-half times that one?” The solution to this, of course, is to break the large story or feature into multiple smaller items and estimate those. However, you need to be careful not to go too far with this approach. The easiest way to illustrate the problem is with a non-software example. Let’s use disaggregation to estimate my golf score this weekend. Assume the course I am playing has 18 holes each with a par of 4. (If you’re unfamiliar with golf scoring, the par score is the number of shots it should take a decent player to shoot his ball into the cup at the end of the hole. )
Estimating and planning are critical, yet are difficult and error prone. We cannot excuse ourselves from these activities just because they are hard. Estimates given early in a project are far less accurate than those given later. This progressive refinement is shown in the cone of uncertainty.
The purpose of planning is to find an optimal answer to the overall product development question of what to build. The answer incorporates features, resources, and schedule. Answering this question is supported by a planning processthat reduces risk, reduces uncertainty, supports reliable decision making, establishes trust, and conveys information.
A good plan is one that is sufficiently reliable that it can be used as the basis for making decisions about the product and the project. Agile planning is focused more on the planning than on the creation of a plan, encourages change, results in plans that are easily changed, and is spread throughout the project.
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