Erro de Decisão de Compra por Falta de Visibilidade de Dados (Poor Purchasing Decisions Due to Data Gaps)
Definition
Managers without data-driven tools cannot accurately identify which products are fast-moving, seasonal, or stalled. Source [2] states that 'Previsão de demanda com base em dados históricos' and local demand patterns optimize reordering. Manual intuition results in bloated inventory (excess carrying costs, storage risk) and missed sales opportunities.
Key Findings
- Financial Impact: Estimated: 10–20% of annual inventory value tied up in excess slow-moving stock. Average pharmacy inventory: R$ 100,000–500,000. Excess working capital tied up: R$ 10,000–100,000+. Carrying cost (rent, shrinkage, deterioration): 15–25% annually = R$ 1,500–25,000 per pharmacy annually.
- Frequency: Continuous (monthly purchasing decisions with poor visibility)
- Root Cause: Absence of sales analytics dashboard; no historical data aggregation; no forecasting model; purchasing decisions based on supplier push rather than demand pull
Why This Matters
The Pitch: Brazilian pharmacies tie up 10–20% excess working capital in slow-moving inventory due to poor demand visibility. Automated analytics reduce over-purchasing and free up R$ 50,000–500,000+ in cash per multi-location chain.
Affected Stakeholders
Purchasing Manager, Pharmacy Owner, Regional Manager (chains)
Deep Analysis (Premium)
Financial Impact
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Current Workarounds
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Methodology & Sources
Data collected via OSINT from regulatory filings, industry audits, and verified case studies.
Related Business Risks
Perda por Vencimento de Medicamentos (Product Expiration Waste)
Custo de Gestão Manual de Estoque (Manual Inventory Management Labor Cost)
Ruptura de Estoque e Perda de Vendas (Stock-Out-Induced Revenue Loss)
Multas ANVISA por Falha no Controle de Estoque (ANVISA Fines for Inventory Control Violations)
Multa por Violação de LGPD e Privacidade do Consumidor
Risco de Recusa de Cobertura de Plano de Saúde por Violação de Dados Sensíveis
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