In the British drama "Sherlock," Holmes exhibits remarkable deduction skills in solving crimes. However, his reasoning process largely relies on deduction and induction. When compared to the real world, Sherlock's approach, while dramatic, may not work as effectively in reality.

This is because the reasoning Sherlock employs is dependent on hypotheses designed for dramatic outcomes.

Let's take a robbery case as an example.

A window is broken, and a woman who has had documents stolen is in a financially vulnerable situation. A common hypothesis that might arise at the scene is "someone broke into her house and stole the documents."

However, Sherlock, based on the immediate observation that pieces of glass are outside the window, focuses on the hypothesis that the woman is the culprit, turning his suspicion on her, leading to her confession and confirmation of the truth.

In reality, however, this kind of leap in reasoning can be risky, as it requires direct verification of complex factors to be quickly proven true.

In the world of business consulting, this deductive and inductive reasoning is found in the field of management science.

It's mainly suitable for improvement and scalability within known areas. The logical progression of McKinsey and BCG can be said to fit this. The defining characteristic of deduction and induction is the presence of a hypothesis at the outset. Statistical assumptions emerge that this approach is efficient in similar structures, and this leads to results that are well suited to the goal of optimizing within a completed structure.

And in business growth, growth and crises occur repeatedly. There are times when we manage for stable growth, and there are times when we need to try to create something new from nothing at the end of growth.

This challenge to new areas and markets is synonymous with investment in high uncertainty. When hypotheses used in deductive and inductive reasoning are absent or have low reliability, an abductive approach is appropriate.

Abductive approach begins by questioning familiar hypotheses.

When attempts based on previously accepted hypotheses prove ineffective, when facing the challenge of entering new areas or markets, and when there is a lack of benchmark information to rely on, we begin by taking the actual step into the world. And from within that, we create new hypotheses based on observed patterns and insights discovered, challenging existing rules and creating a unique starting point.

This approach is suitable for exploring unknown areas and focusing on originality. The logical progression of ReD and Gemic, based on theories in the social sciences, can be said to align with this.

It seems that it is necessary to consider and apply different types of reasoning such as deduction, induction, and abduction according to the level of uncertainty that a company faces.

This diagnostic framework helps identify big unknowns in business, a term that refers to unfamiliar and complex business problems where sensemaking can be especially useful. Here's an overview of the levels that categorize business problems and how sensemaking applies:

Level 1: Knowns

Characteristics: Familiar with the customers and market; clear problem definition; future outcomes can be predicted; conventional data and analytics can be used to address it.

Example: A sales issue during the holiday season can be traced to weather-related factors; increasing advertising and discounts can help resolve the problem.

Level 2: Hypotheticals

Characteristics: Moderate familiarity with the customers and market; a range of possible outcomes; similar problems seen before; hypotheses can be framed and tested; conventional data and analytical models may apply.

Example: Per-store sales are down despite increased investment in salespeople. A range of hypotheses can be tested to find the root cause.

Level 3: Big Unknowns

Characteristics: Highly unfamiliar with the customers and market; no clear sense of likely outcomes; problem not encountered before; no hypotheses to test; conventional data and analytics are unlikely to provide clear solutions.

Example: An innovation pipeline full of ideas, but product launches are not driving growth. In this case, sensemaking can help understand unfamiliar social or cultural contexts and guide new strategies.

Source: An Anthropologist Walks into a Bar…

https://hbr.org/2014/03/an-anthropologist-walks-into-a-bar⁠⁠⁠⁠⁠⁠⁠