The decision this guide supports: what are the few financial and behavioral metrics that distinguish valuable growth from activity? A useful scorecard does not reproduce every dashboard. It enables a recurring decision about revenue quality, profitability and constraints.

Build a metric tree with three levels. Outcome metrics describe what the business ultimately values. Driver metrics explain the major commercial mechanisms. Diagnostic metrics help investigate a specific suspected bottleneck. Put definitions and source ownership beside the numbers, not in a forgotten appendix.

Start with a contribution model

For a product business, order revenue is not contribution. A practical first view subtracts relevant discounts, refunds and variable expenses such as cost of goods, payment fees, fulfillment and attributable acquisition cost, with clear handling of tax and shipping charges. For a subscription business, separate recurring revenue from cancellations, service costs and acquisition economics. For services, utilization and delivery labor often matter more than inventory turns.

Be consistent about which costs enter a measure. Gross margin, contribution margin, operating profit and cash flow are not synonyms. Profitability may look healthy in an accrual report while a rapidly expanding inventory purchase creates a near-term cash constraint.

Organize the one-page scorecard

The top row contains one to three outcomes, such as contribution, revenue from retained customers and cash runway. The middle layer contains drivers including qualified demand, conversion, average order contribution and repeat purchase. The bottom layer contains only the diagnostic signals required to understand a material variance this period.

For each metric, write its formula, source, timeframe, refresh expectation and owner. Show the last reliable value and flag stale or incomplete data. A simple spreadsheet is better than an expensive dashboard that quietly fills unavailable numbers with zero. If channel attribution is incomplete, present platform-reported media cost and measured order outcomes separately rather than pretending to calculate exact causality.

Illustration: why order count can mislead

Suppose a hypothetical store sells 1,000 orders at an average net selling price of ¥10,000. Net order revenue is ¥10 million. If variable product and fulfillment costs average ¥6,000 per order and acquisition cost averages ¥2,500 for each incremental order, the remaining amount before fixed costs is ¥1,500 per order in this simplified case. If a new campaign doubles orders but raises acquisition cost beyond that amount, order volume improves while incremental contribution may turn negative.

These illustrative figures exclude other real-world complexities, including tax, cancellations, cross-order retention and inventory timing. Their purpose is to show why the cost boundary and unit of analysis matter. Your real scorecard needs your own verified definitions and cost inputs.

Build it in a spreadsheet

• Choose the economic outcome that defines healthy growth

• Define revenue, margin and cash measures separately

• Add a small set of commercial drivers with numerator and denominator

• Mark source, refresh date, owner, data-quality issues and comparison period

• Set a recurring variance review that ends with a decision

Quality test: if a channel spends more, can you tell whether its incremental demand is likely to cover its marginal cost? If conversion falls, can you identify the segment and data source to investigate? If the scorecard triggers only reporting commentary and no decisions, remove redundant metrics and sharpen ownership.

Next: G03 uses this scorecard to identify the most consequential constraint and prioritize a realistic 90-day roadmap.

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