Metrics are the beacon, not the destination

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Data-driven expansion of franchises is powerful, but when we become hostages of the scorecard, something very valuable disappears from the radar.

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And therein lies the danger: reducing the market to a Territorial equation gives a sense of precision that, in practice, can produce poor, slow, and sometimes irrational decisions.

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The appeal of calculators is real, you take business results, points, and audience profiles, transform them into clean mathematics, add reach, impact, effort, plot on a spreadsheet and say yes, “the spreadsheet decides”.

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Instead of discussing the expansion thesis, the team spends hours fighting over whether such a square is a “potential” score of 6 or 7, while the business vision leaves the scene.

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It's the False precision: a score 8.2 for a point sounds like science, but it's still a disguised judgment.

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Mathematical models help, of course, make the process more transparent, but they only solve half the problem.

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They rank ideas that are already on the table, they don't say the whether they should be on the table.

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Expansion is, first of all, strategy

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What to do then?

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Here's how to place a strategy filter before the metric:

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• Ask, does this idea of expansion clearly point to one of our strategic objectives?
  
  • If not, file without scoring
  • If yes, then yes, run the scoring model

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In real life, this single filter reduces the universe of possibilities, improves the debate and frees up time to better qualify the few cases that really move the needle.

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Why filter by strategy before scoring?

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Three wins that are multiplied:

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• effectivity You stop measuring what makes sense to measure‍
• Quality with fewer items, you can deepen data, estimates and risks‍
• Alignment The expansion map now contains only regions that climb the strategy ladder, “no” becomes less personal and more logical principle

And there is a cultural bonus: when the filter enters, sales begin to connect Product, Price and Promotion with the Square (Place) and its expansion becomes more strategic, operations suggest improvements linked to business results, finance reads the ROI within the journey, not as a single number.

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The language changes, and when the language changes, the decision changes.

Make the strategy evaluable
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Good strategic objectives for prioritization exclude things.

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They define target customer, trouble and competitive arena.

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Example: “growing along the interior-capital axis with a compact store and a high ticket, reducing the average payback to 20 months”.

Create a simple, binary filter

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For each expansion idea, answer, do you clearly map to a strategic objective?

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• If not, archive in Parking of ideas.
• If Yes, move on to scoring. Mark in the backlog which pillar the idea fits into, nothing gray
  
  

Apply the template to the few filtered items

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The important thing is that you are now discussing what matters, not rounding up numbers to justify preference.

Review with cadence

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It works quarterly, adjust objectives, revisit files, check if the filter is actually reducing noise or if sand has re-entered the machine.

Data-driven or Data-guided?

Ser Data-driven Too much tends to become a number cult, as long as it is Data-guided means using evidence as a trail and maintaining the strategy as a pilot.

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Data illuminates the path chosen by the strategy.

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When metrics start to drive themselves, you outsource intent, and unintentional expansion often confuses speed with direction.

Signs that you're supermetrifying

• Scorecards with 30, 40 variables that nobody updates.
• Debates about “grade” that replace discussions about thesis.
• “Guaranteed” 18-month ROI that ignores operator, brand, and execution.
• Idolized verticalization, flow and Mix ignored.
• Teams spending more time scoring than visiting squares and talking to the real customer.

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Signs that the strategy is alive

• Objectives that Exclude clearly, with no middle ground.
• 5 to 7 criteria that explain 80 percent of the decision.
• Conversations that begin with “what problem are we solving” and only then ask “how much does this yield”.
• Post-opening with Learning agenda that feeds back to the thesis, not just the dashboard.

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An important reminder about cannibalization and “grade engineering”

• Scoring without a thesis tends to “reward” areas with data that are easier to collect, not the drivers of value.
• Cannibalization is underestimated in regions that already perform well, leading to early saturation.
• Strategy avoids this engineering, defines Where to play and How to win, then measure what matters.

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