Operational Intelligence Platform

OI Platform Overview

Current stock management practices expose significant variances between  stock on the financial records and actual physical balances.

The following operational dynamics are the root cause of the discrepancies that limits access to accurate inventory insights.

  • Manual recording of internal movement transactions exposing manipulation risk, human error risk, and data processing delays
  • Archaic inventory survey methods exposing measurement errors
  • Hard-coded enterprise inventory systems unable to cater for all operational transactions which limits capacity to make end-to-end operational improvements.

The limited access to timely and accurate inventory insights compromises supply chain decision making thus negatively impacting the bottom-line.

With the OI Platform variances are systematically eliminated using the following levers:

  • Digitization of 360ᵒ inventory data to drive end-to-end visibility
  • Use of digital survey technology for on-demand and accurate physical stock verification
  • Dynamic machine learning algorithms and inventory models that adapt and evolve over time within the operation to improve the accuracy of the stock levels and optimize the supply chain to drive greater efficiencies and save further costs.

The Qnum Analytics OI Solution not only saves time spent on reconciliation, reduces errors, and end of quarter stock write-offs,  but it also provides real-time access to accurate inventory level to help improve decision making around supply chain management which increases profit.


Digital Inventory Records

Unlocking real-time access to verified inventory levels

The OI Platform is underpinned by a dynamic inventory model that adapts and evolves with an operation. This breakthrough technology ensures that all inventory touchpoints, often fragmented in existing operations, are consolidated on a single platform. This opens the opportunity to digitize the inventory management practices end-to-end (paperless).

  • Dynamic inventory model catering to operation specific internal material handling transactions without hard coding
  • All transaction paperwork digitized
  • Bulk stock survey devices providing real-time physical inventory levels
  • All weighing systems outputs and data pulled into the solution

Real-Time Business Intelligence

On demand custom dashboards & reports to support
data-driven decision making


The OI Platform is fully configurable and utilizes the digital data to deliver custom dashboards and reports that empower management and operators with real-time insights and optimize end-to-end operations to maximize profitability.

  • Key decision-making dashboards available on-demand via mobile, computer, or mounted screens
  • Custom dashboards and reports easily configured to meet operational and managerial needs
  • Dashboards available at plant-level, head office level, and on the move to empower decision makers

Smart Inventory Reconciliation

Integrated financial & audit controls allow continuous variance
management and credible financial reporting

The OI Platform incorporates multiple internal audit controls (system-to-system, paperwork, and devices) that unlock the capacity to confidently detect and control discrepancies at source to enable credibility and ease in inventory reporting

  • Continuous stock reconciliation function allows the isolation and resolution of discrepancies
  • Comprehensive audit trail enables increased accountability
  • Cross-system verification prevents data manipulation
  • Digitized transaction paperwork increases the credibility of reported inventory levels and reduces time spent on month-end reconciliation

AI-Driven Operational Optimization

Data science and AI capabilities deliver
end-to-end optimization


The OI Platform has the capacity to deliver sustained bottom-line benefits through a Machine Learning Inventory Model that learns each client’s environment to drive continuous process optimization end-to-end.

  • Real-time tracking of production performance against sales requirements
  • Low inventory level flags preventing costly stock-outs
  • Determine optimal replenishment patterns to improve working capital/cash flow
  • Monitor productivity and waste levels to dynamically detect sources of inefficiency

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