🇦🇪UAE

قرارات الشراء الخاطئة بسبب نقص البيانات (Poor Procurement Decisions Due to Data Gaps)

3 verified sources

Definition

Search results emphasize: 'Using historical consumption data, broken down by project phase, to estimate what materials will be needed (and when)' and 'Develop more accurate procurement plans.' Manual spreadsheet forecasting leads to 15–25% forecast errors. Without standardized item codes (search result: 'Using uniform naming conventions and item codes'), procurement staff cannot track consumption by SKU across projects.

Key Findings

  • Financial Impact: 10–20% excess working capital tied up in unnecessary inventory. For AED 20M annual inventory: AED 2,000,000–4,000,000 in excess capital. Carrying cost on this capital: 6–8% annually = AED 120,000–320,000 annual drag.
  • Frequency: Recurring procurement cycles (monthly to quarterly); cumulative annual impact
  • Root Cause: Lack of centralized demand forecasting, no standardized SKU tracking across projects, manual consumption analysis, siloed data (each site maintains own spreadsheets)

Why This Matters

This pain point represents a significant opportunity for B2B solutions targeting Retail Building Materials and Garden Equipment.

Affected Stakeholders

Procurement Manager, Finance Controller, Project Manager, Demand Planner

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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.

Evidence Sources:

Related Business Risks

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