Simplicity

Analyzing business or IT problems is an inherently complex task, and it should not be made even more complicated by introducing meaningless processes and producing outputs that are not needed or which nobody can understand. Effective analysts keep things organized and consistent but must also strive to make things as simple as possible. Simplifying itself is not hard. What is challenging, though, is to find the balance between making things simple but not too simple. In other words, the goal is to find the simplest solution which still delivers value.

Simplification Tips

1. Create Simple Outputs

When creating an output, be it a document or model, it should have the simplest form possible, which is still able to clearly communicate the message. Also, the author should always keep in mind the artifact could be used or read by somebody who has limited knowledge of the area and limited time for understanding the output. Therefore, the consumer must be able to understand it instantly without needing to search for additional information or asking somebody for an explanation.

2. Don’t Polish Details

A famous idiom states: “The devil is in the detail”. However, the details are not usually needed right in the beginning and it is basically not possible to capture all of them. The more details are documented during analysis, the more effort is then required to maintain them. The detailed analysis, therefore, costs time twice - the time required for creating it and the time for keeping it up to date. Analysis and documentation outputs must be kept as simple as possible, and details should be added only when the current level of detail has shown to be insufficient. The necessary level of detail must be continuously evaluated, and the balance between having all the details documented and spending time wisely must be found.

3. Formal Is Not Always the Best

Every output produced can be just an informal description, or its format can be prescribed by a set of formal rules. The formal outputs have the benefit of being readable to everybody who knows the rules and the outputs look all very similar. However, as always, reality is not just black and white.

Let’s illustrate it on modeling standards, which define how to graphically describe some aspect of the reality; in other words, they describe the semantics of the symbols used in the model. Modeling standards such as UML and BPMN are certainly beneficial, as they enable different people to speak the same language. But using them comes at a price. First, creating such models takes time as it will always be more time-consuming to create a formal model than to sketch a free-hand diagram. Second, to be readable, all recipients need to understand the notation, which might be limiting.

So, all in all, before delivering some artifact, it must be carefully considered who the target audience is and whether the model is going to be a one-time artifact or a permanent. According to the purpose, the final format must be then selected accordingly.