An analyst must frequently contend with structure-less environments and relentless rejection, and the character of Alice highlights many desirable characteristics that constitute the makeup of a good business analyst. Having identified the value of the Mad Tea Party as a learning ground in the previous episode of this series, we will now examine some of the key lessons learned and how they are applicable to the work of the business analyst.

A list of business analysis techniques is pretty extensive and from year to year new techniques appear, or become more formalised, and are adopted by business analysts all over the world. Some techniques become more popular and are widely used and some are used rare or only when a specific need arises. But definitely there are techniques that became very popular and are used on a daily basis and even become buzz words for some people. These techniques are mainly used to create solution design and they are business process maps, use cases, user stories, wireframes and business rules. Sometimes even business analysts are confused how they should create solution design and what techniques they should use.

By signing up to go through this process, you will be doing yourself a huge favor – a favor that you will never regret especially when people will look at you as the ‘wow’ person who completely transformed his or her life, achieving something that was not even vaguely possible otherwise.

A Feature Tree is an RML Objectives model that shows the full scope of features for a project or product on a single page in a tree format. A feature is just a short form description of functionality provided by the project or product that brings value to the end user. The Feature Tree is great for bringing new people on a project up to speed and showing executives, business stakeholders, or customers all the features that are in scope for a project or release.

Operational business decisions happen every minute of every day in your organization. You’d like to think that business managers can truly manage them. You’d also like to think that the results of those decisions are comprehensively correct, consistent, traceable, and repeatable (high quality). But are they? Based on real-life evidence I strongly suspect they often are not.... When IT professionals talk about “decisions” they often mean branch points within the deep systemic logic executed by machines – classic decision points in data processing. I don’t mean that either.