Issue tree and MECE: what it is and what to do instead

The idea worth keeping

Not as boxes to fill, but as questions that fall out of the maths of the goal:

• What number is the client trying to move, and what multiplies or adds up to it?
• Could one cause sit in two of my branches? If so, they overlap.
• Is there anything that could move the number that falls outside every branch?
• Which branch would I check first, and what do I know about this business that says so?

Why reaching for it fails in an interview

• It is generic. A tree split into internal and external factors fits a bank, a mine and a hospital equally well, so it shows nothing about this case.
• It misses the driver that matters. A tidy tree with no maths behind it cannot tell you which branch moved, so you end up asking for every number.
• It sounds rehearsed. Drawing the same top split for every case shows you learned a shape, not how this business works.

What to do instead: a worked case

1. 1

   Pin the question

   Find why weekly orders in this one city fell 10% in six months, and the fix that wins them back fastest.

2. 2

   Write the maths of the goal

   • Weekly orders = active customers x orders per active customer per week
   • Active customers = last period's customers + new customers minus customers who stopped ordering
3. 3

   Use what you know about the business

   • Delivery apps win on choice, speed and fees. A customer who waits too long, or sees fewer restaurants, orders less and may leave.
   • Supply drives demand: fewer riders at peak hours means slower deliveries, which lowers orders per customer.
   • Only one city fell, so the cause is probably local: a rival's launch discounts, a rider shortage, or restaurants leaving the app.

   The structure that falls out of it

   • Active customers
     • New customers joining each week
     • Customers who stopped ordering, by reason
   • Orders per active customer
     • Delivery time and late orders
     • Restaurant choice in the app
     • Fees and discounts compared with rivals

   Hypothesis: Because only this city fell, I expect a local supply problem: slower deliveries cutting both how often people order and how many stay.

4. 4

   Find the facts that decide it

   • Active customers fell from 200,000 to 190,000 (down 5%) and orders per customer from 1.5 to about 1.42 a week (down about 5%). 190,000 x 1.42 is about 270,000 orders a week, against 200,000 x 1.5 = 300,000 before: a fall of 10%.
   • Average delivery time rose from 30 to 41 minutes after a change to rider pay in this city, and customers who had a late order stopped ordering at twice the usual rate.
5. 5

   Say so what

   Orders fell because deliveries got slower after the rider pay change, which cut both order frequency and the number of customers who stay. Restore rider supply at peak hours first, then win back customers who had a late order. The risk is cost: the extra rider pay must be covered by the orders it brings back, so test it in the busiest areas first.

Build the acumen behind it

The worked case used two things a list cannot give you: the five moves, and knowing how this kind of business makes money. These pages teach both.