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  • Achint Sanghi

A Simple Framework for Complex Decision-Making

Tasked with making a critical decision for the umpteenth time, Gramhal recently utilised an important principle of MECE, which stands for Mutually Exclusive and Collectively Exhaustive.


The premise is straightforward - to understand and solve for a problem, you need to understand your options by dividing them into categories that are:

a) Mutually Exclusive - each item can fit into only one category

b) Collectively Exhaustive - all items fit into atleast one of the categories


Simply put, MECE means no overlap and no gap!





Why is this important? The MECE framework helps one identify all possible decision options in relation to solving a problem. It provides a clean framework, reduces overlap in data points and covers all bases. The resulting decision is arrived at in an efficient and effective manner.

At Gramhal, we were ready to give it a go!


Gramhal’s MECE experience


In November, Gramhal had to make an important decision with respect to our Whatsapp-based chatbot, Bolbhav. Specifically, whether to use a third-party platform or build it in-house. As one would understand, this critical decision involved a complex set of factors that had to be taken into account.


The MECE framework was called into action here. The aim was to use it to effectively decide between different technology options to build the chatbot. Following was the process followed.

First, a list of factors in a technology solution were drawn using the MECE principle:

  1. Cost to build a platform

  2. Performance (quality of code/scope of the software)

  3. Speed to market (time taken to develop it)

Next, I further broke down each list into more MECE lists. For instance,

  • Cost was broken down into short-term and long-term costs

  • Scope (requirements) was divided into functional requirements (sending broadcasts as subscriptions, collecting user analytics) and non-functional requirements (maintainability, scalability, security)

Additionally, to ensure I took all objective and subjective criteria into consideration, I devised a method to further organise the factors by ranking them according to importance:

  • First, relevant weightage was assigned to each category. For instance, short-term costs were valued at contributing 20% to the final decision whereas long-term costs made up 5%

  • These options were further scored on a scale of 1 to 5. For example- the third-party platform scored a 5 within short-term costs owing to its low price. On the other hand, a custom bot would have been an expensive undertaking and thus scored a 2

  • For each factor - by the magic of basic addition, multiplication, and a simple spreadsheet - I arrived at a net score per option

  • Finally, to get the final picture these factors were ranked in order. If there are several factors, only the top few can be considered to make a management decision

Thus, a MECE list of all factors that went into making a crucial technology decision was ready. Not only was the conclusion an optimal one, using the MECE framework helped save time and resources as I arrived at the decision! The above framework can be generally applied to any technology decision, such as choosing between different frameworks, platforms, build vs buy, etc. One can start with the “Big 3” list of Cost, Performance, and Speed and further proceed to make lists of those lists.


A fair disclaimer: I am mindful that not all of the points mentioned above may strictly qualify under the MECE criteria. However, the framework still remains relevant in categorising almost all available options and enabling key stakeholders in making crucial decisions.

 

MECE for processes


Apart from effective decision-making, we can also apply the MECE framework for processes.


The fundamental importance of human-centered design has become increasingly prominent in the social sector. It starts by deepening an organisation’s understanding of the needs of the community that they intend to serve.


At Gramhal, we have attempted to make human-centered design an integral part of our product by offering a space in the chatbot for farmer users to share their feedback and concerns. We can use the MECE framework to ensure that their feedback is acknowledged and adopted into the product. Here, steps in the process can be divided into the following categories: Collate feedback; Analyse feedback; Prioritise feedback and draw insights; Communicate to the team to act on the feedback. We can confirm that each step is distinct and that we have covered all the steps in the process. Each step will further hold detailed steps which are also Mutually Exclusive and Collectively Exhaustive.


MECE - No overlaps, no gaps. Better decisions, all claps! We aspire to utilise the MECE framework going forth not only for all decisions that require analysing a complex set of information, but also for ensuring we have all the necessary processes in place.

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