OTIF Optimization Solutions

Smart analytics solutions to optimize business processes, cultivate a data-driven decision-making practice and build a flexible supply chain

Tackle the order fulfillment challenge head-on through on time in full deliveries

On time in full (OTIF) is a key supply chain performance indicator that measures a company’s ability to deliver on its promises in the order-to-delivery process. Quantzig’s offers cutting edge OTIF optimization solutions that help businesses to identify and prioritize potential risks and root causes, while proactively improving OTIF scores through supply chain optimization. We leverage machine learning algorithms that iteratively query data through constraint-based modeling to find the core set of factors with the greatest predictive accuracy. Our customizable solutions also help find new patterns in supply chain data on a regular basis, thereby eliminating human intervention.





Improved Order-to-
Deliver Process



Reduced Freight



Better Probability

Focus on what matters the most by using your OTIF score as a KPI

The OTIF standard puts a lot of pressure on enterprises up and down the supply network. The key driver of on time in full deliveries is supply chain visibility, but the benefit of gaining such insights rely on the ability to build confidence in ETAs and avoid making commitments that have a low chance of being met.

Quantzig’s OTIF Optimization Capabilities

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    Inventory Cost Optimization

    We work with clients to offer solutions to their most pressing cost optimization issues and help them in identifying and implementing significant reductions in material and service costs while enhancing service levels and revenue.

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    Audit and Gap Analysis

    Assess current procurement cost optimization practices, identify gaps, determine relevant sourcing strategies, processes, and resources.

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    Procurement Risk Mitigation

    Identify potential uncertainties and develop a strategy to manage the risk exposure and minimize critical supply chain risks.

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