Cafés make decisions every day.
Most of them are informal, intuitive, and undocumented.
Decision modelling exists because intuition alone doesn’t scale — and in high-constraint environments like cafés, it often fails silently.
What Is Decision Modelling?
At its core, decision modelling is the practice of turning judgement into structure.
Instead of asking “What do we feel like launching?”, decision modelling asks:
- What factors matter?
- How do they interact?
- What constraints cannot be ignored?
- What trade-offs are acceptable?
A decision model doesn’t eliminate judgement.
It organises it into a repeatable, explainable process.
This approach is widely used in engineering, finance, and operations — anywhere decisions carry cost, risk, and irreversible consequences.
Cafés, surprisingly, are no different.
Why Café Decisions Are Harder Than They Look
Menu decisions sit at the intersection of multiple systems:
- demand and seasonality,
- supply chains and pricing,
- preparation time and staff skill,
- brand positioning and customer expectation.
Most cafés evaluate these factors sequentially, not together.
- First comes the idea.
- Then taste testing.
- Then sourcing.
- Then operational compromises.
By the time feasibility problems appear, the decision is already half-made.
Decision modelling flips this order.
Intuition vs Structure
Experienced operators often rely on instinct — and for good reason.
They’ve seen patterns repeat and failures recur.
The problem is not intuition itself, but where it lives.
When judgement remains:
- undocumented,
- unshared,
- and untested against constraints,
it becomes fragile.
New staff, new locations, or even a busy week can break it.
Decision modelling captures experience and places it inside a framework that others can understand and use.
What Decision Modelling Looks Like in Practice
In a café context, decision modelling typically involves:
-
Defining decision inputs
Demand signals, seasonality, ingredient availability, cost, preparation complexity. -
Establishing non-negotiable constraints
Supplier limits, storage capacity, service speed, margin thresholds. -
Weighting what matters most
Not every factor is equal. Speed might matter more than novelty. Margin more than aesthetics. -
Evaluating trade-offs explicitly
A drink might score high on demand but low on feasibility — and that tension becomes visible early.
The outcome isn’t a single “correct” answer, but a ranked set of options, each with known risks and reasons.
Why Cafés Rarely Use Decision Models
Not because cafés don’t need them — but because they’ve never been accessible.
Traditionally, decision modelling has required:
- analysts,
- custom spreadsheets,
- or technical expertise far removed from daily operations.
As a result, cafés fall back on:
- copying competitors,
- following trends,
- or relying on whoever has the strongest opinion in the room.
This works occasionally — but it isn’t reliable.
Why Cafés Need Decision Modelling Now
Today’s café environment leaves less room for error:
- ingredient costs fluctuate,
- staff turnover is high,
- customer expectations change quickly,
- and margins are thin.
Every failed launch compounds pressure.
Decision modelling doesn’t promise perfect decisions.
It provides clarity before commitment.
It allows cafés to:
- see risks early,
- compare options fairly,
- and justify decisions internally.
Most importantly, it turns menu planning from a gamble into a process.
Decision Modelling Is Not About Removing Creativity
A common misconception is that structure kills creativity.
In practice, the opposite is true.
When constraints are clear:
- ideas become sharper,
- discussions become focused,
- and energy goes into viable innovation, not damage control.
Decision modelling doesn’t decide what tastes good.
It decides what’s worth testing, launching, and standing behind.
From Decisions to Systems
When cafés treat menu planning as a systems problem rather than a creative one, patterns emerge:
- fewer failed launches,
- more consistent menus,
- clearer accountability.
Decision modelling is simply the language that makes those systems visible.
Reference
IBM-Decision Management & Decision Modelling