In today’s competitive world of complex information and technology, it has become necessary for organizations to use a data-driven approach in order to achieve success. The advantages of data and information can be seen everywhere such as a company looking for a competitive advantage or a government body seeking to boost its development agenda through valuable data. In fact, a lot of useful information and data are available in the environment we live in. But the absence of a proper framework that facilitates combining all the useful data and information at a single and appropriate place; may lead to the dead-end street.
One such framework is the MECE Framework of McKinsey which is considered an excellent tool for explaining ways to organize information properly and systematically. “Me-see” is the pronunciation of the MECE concept which is made of two main elements i.e. ME (Mutually Exclusive) and CE (Collectively Exhaustive). This framework was initiated by Barbara Minto of McKinsey & Co. in the late 1960s and acts as a basis of Principle given by her i.e. Minto Pyramid.
MECE framework is considered as an analytical framework through which information can be grouped into elements or categories i.e. ME and CE. In this process, different ideas, solutions, problems are arranged in the MECE framework. In simple words, MECE Framework breaks down a business issue or problem into various key components related to it. It suggests that to examine and resolve any complex problem, businesses need to determine various possible options by arranging them into Mutually Exclusive and Collectively Exhaustive categories.
For example, while looking for solutions or making strategies for business problems such as finding out various available options for the growth of a company, ways to reduce costs, increase sales, etc., the principle of MECE proposes that various possible solutions or options that can be considered to sort out these problems are supposed to be categorized and grouped in a certain manner.
– Mutually Exclusive
This means all the listed options on the MECE framework have to be mutually exclusive with no scope of overlapping and there is no dependency of options on each other. So, all the options can be adjusted in a single category at a specific period. In other words, there should be categories to group all information, and overlapping is not there between these categories. This is the first step to reduce complex issues with no overlaps and requires careful analysis of possible solutions for avoiding the situation of considering them twice.
– Collectively Exhaustive
The next query that arises while using the MECE framework is to see whether the list of options is collectively exhaustive. In other words, to check if the proposed analytical options cover all the relevant aspects of the issue. This element is aimed at ensuring a thorough list without skipping any alternative. Exhaustive is related to considering all possible options. So, collectively exhaustive includes all the categories of a group along with all possible options.
Frameworks of MECE Framework McKinsey
MECE framework includes three main frameworks that management or strategy consultants utilize to separate the problems of their clients into logical categories of data that can be assessed in a systematic and micro way by their project team. These frameworks of the MECE framework include:
A) Issue tree
These are the powerful elements that are used by McKinsey & Co. and other management consulting companies to sort out business-related problems. An issue tree is defined as a method to arrange all the relevant information or complex problems and split these problems into components and sub-components. By doing so, complex issues or problems can be resolved in a better and systematic way.
This element is termed as a tree because of its structure as on the top, it’s narrow and starts with a statement consists of an issue or problem. At the bottom, it becomes wider as the issue is divided into further levels of issues and sub-issues.
A typical structure of the Issue tree is as under:
Uses of an Issue tree
Issue trees are preferred to solve problems because of the following benefits:
1. Segregate issue into sub-issues that are manageable
Businesses face problems that are complex and tough to handle. With the help of the issue tree, these problems can be sub-categorized into issues and sub-issues. This brings out smaller problems that can be easily resolved.
2. Sorting out the right components leads to solving a big problem
As a problem statement is made of issues and sub-issues in the issue tree, so, it is feasible to solve the whole problem by chasing the right or correct issues.
The MECE issue trees are most commonly used for profitability analysis. The profitability issue is sorted by defining various sub-categories related to the problem and all possible solutions.
The working mechanism of an issue tree
- The process of creating an issue tree starts with defining a problem statement. For example, a problem statement of a wholesale clothing firm can be “it’s business is not profitable” or “occurring losses rather than profits”. This problem statement acts as the starting point of the issue tree as a component on top of the tree.
- Further, different sub-levels would be created in the issue tree to solve problems related to making the wholesale garment firm’s business profitable. In a broader and strategic aspect, sub-levels will answer how to increase revenue and reduce costs in order to increase profitability which is the main problematic area.
- The next level which is part of the first level’s sub-issues would suggest ways to increase revenue and reduce cost. Enhance the total number of orders and increase the cost of different cloth items; these can be the two solutions under the “increase revenue” level. The solutions under the level “reduce cost” can be related to reducing rentals, reduce transportation costs, or reduce salary expenses.
- The third level consists of solutions or answers related to the issue of determining the ways to enhance the total number of orders. Solutions can be to shift in the area where more retail customers are available, or to add more verities of cloth items, or to target more number of retail customers.
- Also, one solution under reducing rentals maybe “to shift in less costly building”, “look for cheaper and fast transport” under reducing transport costs, and “to reduce less productive manpower” under reducing salary expenses.
- Once this MECE issue tree is prepared, each solution or sub-level can be analyzed properly to check feasibility. Accordingly, a firm may choose an optimum solution.
- Organizations or strategy consultants who develop such issue trees are required to cut branches of the tree or in other words, they need to eliminate those options or solutions that are not worthy once detailed analysis at the initial stage is done. In the above example of the issue tree to sort out the problem area of enhancing the profitability of the wholesale cloth firm, increasing cost may not be a suitable solution and this solution of the issue tree may be considered eliminated. In large organizations, there are more complex problems exist. So, the solutions are required to be based on extensive data for a logical and proven approach.
Other examples of an Issue tree
A few other examples of issue tree for common types of issues related to business situations are as under:
1. Issue related to entering a new market
Major sub-issues that are highlighted and sorted out through the issue tree include the attractiveness of the new market, position of competitors (strong or weak), a firm’s capabilities or potential to enter, the profitability of the firm by entering the market.
2. Issue related to Merger & Acquisition
The issue tree is beneficial to determine whether a firm should look for a strategy of acquiring another firm or not. Different main issues that are explored include the attractiveness of the target market and the target company, acquisition synergies, and expected high returns through acquisition.
3. Issue tree example for a new product or service launch in the market
Another example of a common type of business situation is when a firm is looking to launch a new product or service. The major concerns related to this consist of the attractiveness of the market, the reaction of customers whether they will like the product or not, capabilities of the firm to launch the product in a successful manner, and the probability of the firm to earn profits after the launch.
B) Decision tree
A graphical representation that is tree-shaped and represents various decisions and possible results of those decisions; is considered as a decision tree. It is used to determine a series of actions to be taken to resolve an issue. The tree supports a company to determine different merits and demerits of each decision being taken and it’s possible end-results.
The working mechanism of decision tree
Generally, the direction of drawing a decision tree is from left to right. A small square represents a specific decision that is the starting point of the tree. Different branches that are on the right side of the square represent each potential alternative. For each new decision, the square is formed and further branches for new alternatives. A circle is made in case there is no clarity on the result. The branch is kept as blank if an alternative is inclined towards a decision that facilitates reaching a solution. A potential solution path can also be represented by a triangle which is placed at the end portion of a branch.
The common thing in issue tree and decision tree is that both include different elements of an issue such as decision, alternatives, results, and circumstances. The decision tree user considers each of these and decides to choose the best possible alternative.
The difference between the two trees is that unlike a decision tree, an issue tree goes beyond determining possible solutions as it also determines the required analysis and sources of data. So, a decision tree doesn’t provide a road map to follow and organize the process of problem-solving.
Example of a decision tree
- A simple example of a decision tree would be to make an investment decision for investing Rs. 20 lac with a higher return in the future. If a specific decision is required to invest Rs. 20.0 lac for the maximum return potential then different suitable alternatives/ options may be determined and represented by drawing a decision tree to look for the best appropriate option. One option, in this case, is to invest in a bank in the form of two FDs (Fixed deposit) of 1 year with an annual return of 6% and 7% respectively that will generate total annual interest income of Rs. 60,000/- and Rs. 65000 respectively. So, the total return would be Rs. 1,30,000/-. Another option is to invest in a post office saving scheme of a minimum of 5 years with an annual return of 7.0%. This will generate an annual return of Rs. 1,40,000/-. The above decision and suitable options can be represented through below decision tree:
C) Hypothesis tree
A hypothesis tree is also developed to structure an issue. This explains the problem in the form of graphical representation for all MECE hypothesis. Unlike the issue tree, it arranges a problem in different hypotheses and provides a more straightforward approach.
The working mechanism of the Hypothesis tree (Making MECE Hypotheses)
The following steps are involved in building MECE Hypotheses suing Hypothesis tree:
- Thorough understanding of the problem that needs to be resolved.
- To mention the clear problem statement in written form in order to avoid any ambiguity later on.
- List hypotheses or alternatives to sort out the problem through the MECE tree. Also, ensure that no overlapping of options should be there (mutually exclusive) and all alternatives are involved (collectively exhaustive).
- Each alternative is required to be considered individually by focusing on the merits and demerits. Illogical ones need to be dropped and any new idea should be incorporated as an alternative after understanding the problem in a better way.
- The last step includes choosing the best alternative for execution.
Example of Hypothesis tree
For instance, a problem area is that a company wants to enhance its sales. For this, different hypotheses and sub-hypotheses can be:
Hypothesis 1: The organization can expand into new markets
Hypothesis 2: The organization can choose a strategy to increase sales volume in the current market only
Sub-hypotheses under Hypothesis 1:
Sub-Hypothesis 1: Company can invest in highly effective promotional activities
Sub-Hypothesis 2: Company can hire more trained sales staff
Sub-hypotheses under Hypothesis 2:
Sub-Hypothesis 1: Company can provide attractive sales offers on products or services
Sub-Hypothesis 2: Company can generate more sales leads from current customers
HYPOTHESIS TREE EXAMPLE DIAGRAM: