APPPM Issue Tree

Revision as of 19:35, 16 February 2021

Abstract

Mainly, a Issue-driven problem-solving process consists in three phases: identifying, solving and communicating.

Firstly, the identifying phase consists in the problem definition in which the consultor dentify which problem to solve, stakeholders that influence the solution and key success criteria for the work ahead.

Next, the solving phase consist in three steps:

- Issue identification and prioritisation. Problems are deconstructed into quantifiable and formal problem statements (issues) that can be prioritized

- Identify hypotheses. Hypotheses are identified and formulated for every issue in order to make analysis possible

- Conduct analyses. Collect data and conduct required analyses

Finally, the process proceed with the last phase which is the communicating. This last part of the Issue-driven problem-solving process consists in synthesizing of findings and developing recommendations. The aim of this phase is to develop clear communication of results and recommended solution.

Due to the complexity and length of this process, this article will focus on the first step of the second phase, Issue identification and prioritisation, by using a methodology that will be called: The Issue Tree. [1]

In a general way, it is a question of deconstructing the problem into quantifiable and formal problem statements (issues) that can be prioritized and prioritising what issues to focus on in the analysis based on each issue’s impact on the overall problem-solving.

Big Idea

Application

A problem is the difference between current and desired end state. It can be said that, before solving a case, one is in the current state in which a problem-solving process must be applied in order to reach the desired state. A problem does not necessarily have to be negative, it can simply be an option to improve the efficiency of the company, such as improving the manufacturing process, evaluating better suppliers, implementing new automotive processes in a factory, etc.

The value creation comes from solving difficult problems by mitigating a number of challenges that a company may face:

- Not sufficient time. Deadlines are tight, the organisation waits for critical decisions.

- There are different options. Different people in the organisation see the problem differently and, consecuently, people push for different solutions.

- Too much data. Not known where to start looking or the level of data quality.

- Not sufficient resources. The problem is to be solved on top of daily work.

- The problem is not clearly defined. There is more than one problem.

- Too little insight. Do not have sufficiently granular insights about the market or how it is doing.

The implicit purpose of value creation and of detecting a clear problem leads us to the need to implement a standard methodology that aims to solve in a simple, efficient and concise way any type of business case.

Once the first phase explained above, identification, has been completed, we proceed to the second phase with a definition of the problem. It is assumed that the problem consists of the difference between the expected and the actual state of affairs.

Within the problem, a number of issues will be identified and prioritised. These are a logical component of a problem, potentially made up of several sub issues that can be analysed and often quantified.

From this difference arises the need to use an Issue Tree, which consists of decomposing the main problem into issues. This scheme offers three main advantages:

- Splits complex problems into (quantifiable) elements that can be analysed

- Provides a visual structure of the problem and ensures that nothing is left out

- Is a good tool for communicating how is seen the world

ISSUE TREE IMAGE

In order to build quality into a Logic Issue Tree the MECE principle is used. [2] This theory suggests that all the possible causes or options to be considered in solving these problems can be grouped and categorized in a particular way:

- ME. (Mutually Exclusive) This is a concept related to probability theory which implies that two events cannot occur at the same time. For this reason, when two mutually exclusive ideas are put forward, it implies that they are separate and cannot overlap with each other.

- CE. (Collectively Exhaustive) It implies that the set of ideas includes all possible options. Thus, it means that all entities are considered relevant.

Linking Mutually Exclusive with Collectively Exhaustive allows a large amount of information to be generated and simplified into multiple separate and distinct sets of ideas, the issues and sub-issues. After having verified the quality of the Logic Issue Tree using the MECE principle, it can be said that a structured representation of the problem is available, which was the objective of this second phase step.

MECE ISSUE TREE IMAGE

Then, to conclude this step of the second phase, Issue identification and prioritisation, proceed to prioritise by eliminating issues. The purpose of eliminating issues is:

- To help to prioritise the efforts, identify clearly what is most important.

- To work efficiently and have a better managemnet lifestyle

- To help to ask “so what” ... but also ask yourself what you may have forgotten

IMAGE OF PRIORITISE

Eliminating issues can be difficult because team members will have differing opinions on what is critical to the analysis. In order to standardise the process and to take into account all opinions in order to arrive at a better prioritisation, a methodology is again established to be applied.

The tool used to focus the analysis is called Prioritisation Matrix.

First, each of the issues is numbered in items, and each of them is defined with a corresponding improvement lever that will be a short description of the issues. Subsequently, the matrix is filled in.

The matrix consists of 4 boxes that are evaluated according to two parameters. On the x-axis the financial impact is evaluated, usually a fixed period is set in order to be able to evaluate a more tangible result, e.g. a period of two years. On the other hand, on the coordinate axis, the ease of implementation is evaluated. In both cases the evaluation scale is qualitative, from low to high.

The matrix is then filled in. For this purpose, each item is taken and analysed on the basis of its implementation lever. After deciding among the team which is the level of financial impact and ease of implementation, the items will be implemented in the matrix.

Limitation

Annotated bibliography

https://en.wikipedia.org/wiki/MECE_principle --> Source that explains in depth the MECE principle used for the construction of a quality Logic Issue Tree.