AI: The robo management consultant experiment

I stumbled across a Tweet describing McKinsey's 'Rule of Three' for crafting persuasive arguments

The rule states: You need to provide the client with 3 reasons to adopt your recommendation. Not 2, Not 4. Just 3

... and this piqued my interest

McKinsey's consulting model generates in excess of $1 Million per employee

Just how hard would it be to create a Robo Management Consultant that replicates McKinsey's advisory model?

Textural analysis of the HBR suggests the question can be resolved if we can reduce the activity of the management consultant into a value equation

For example...

The objective of the consulting assignment is to...

Increase [w] by Reducing [x] and/or Improving [y] by Changing and/or Creating a new [z]

Having developed the value equation we can then randomise the outputs based on the assignment objective

For example...

We can increase

(Choose an Option)

Profit Revenue Growth Market Share Retention ROA ROI Efficiency Cash Flow Visibility

Answer:

Of course this isn't AI. But with a user questionaire (ie Please rate the quality of this solution out of 10) creating the feedback loop it becomes the basis for generating an AI training set

Add a chatbot engine, once it has been trained and hard wired into Google Trends and there you have it... A veritible McKinsey for the masses

However the deeper observation I want to make is this simple random solution generator illustrates how, what passes for strategic thinking in the management consulting world, is in reality, just combinatorial word play targeting the collective pareidolia (The psychological phenomenon of discovering patterns in randomness) of the C-Suite

Originally Published Spring 2020. What are we talking about today? Follow us on Twitter