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Qnum Analytics We Minimize Inventory Shrinkage in Dry Bulk Industries

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We are fixing defragmented supply chains between last mile inventory and theoretical inventory recorded in ERP supply chain systems. The actual levels of inventory at source are dynamic and difficult to track and measure as material moves around the plant or floor. As the process of recording inventory levels is manual and relies on spreadsheets where an additional layer of human errors is introduced thus making the process of inventory reconciliation difficult. The outcome of this is an inventory variance between actual stock levels and recorded stock levels (theoretical). The magnitude of the resultant variance most commonly results in financial losses due to write-offs as significant stocks are now unaccounted for and there is knock on effect of disrupted production planning. Our solution solves this problem by digitising inventory management and extending the ERP directly to the last mile thus minimising losses and providing realtime insights and control.

SectorsCloud solutions, Machine learning, Software as a Service
LocationRandburg, South Africa
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