MODsight

Advanced Analytics and Prediction

MODsight

Advanced Analytics and Prediction

MODsight

Gaining Insights with Advanced Analytics

 

With MODsight, Modum offers your organization solutions that provide deeper insight into your supply chain. Our team uses advanced analytical models and machine learning techniques based on trusted data from MODsense data loggers, your company enterprise data, and other relevant data sources.

We help you find answers: improving supply chain operations, reducing related costs, and addressing customer needs with applications such as adaptive packaging optimization or autonomous identification of shipment process anomalies.

Analytics Built for You

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Aggregated Analytics

MODsight harnesses leading technology to provide aggregated analytics, offering your team a basis for increasing business intelligence, process improvement, and new opportunities.

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Better Forecasting

Better forecasting comes from using your unique enterprise data. The same data that you collect to fulfil quality requirements and meet regulatory obligations can be leveraged for predictions.

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A Global View

By aggregating your organization's data with trusted data from your industry sector, MODsight can offer unprecedented perspective.

The MODsight Packaging Selector

Active or passive temperature management systems are commonly used when shipping sensitive goods. However, such temperature management systems come with drawbacks in terms of operative handling and cost compared to standard packing materials.

What if using standard packaging would be sufficient based on favorable external temperature during shipment?

In collaboration with a client, we sampled more than 800 shipment routes across all regions of Switzerland during winter to assess the potential for a risk-based approach to use conventional packaging for the shipment of medicinal products. We wanted to know how many shipments would not require full thermal insulation, but only reduced insulation or even none at all (standard packaging).

The Results

The result was astonishing: taking a cold-chain shipment with a temperature band of 2 to 8 °C, we found that approximately 40% of these shipments had the potential for optimization.

To offer our client an operative optimization tool, we created a model to predict the package temperature during transit using machine learning and created a first demonstrator: the MODsight Packaging Selector.

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Temperature Prediction

A machine learning predictive model for temperature allows you to optimize your delivery schedule to lower risk and costs.

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Packaging Risk Selector

Simple and intuitive module helps you choose packaging based on monetary risk indicator, backed by quantitative and historical data.

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Integrates with ERP Systems

Integrate seamlessly with your company's ERP system and automate optimized shipping processes.

Ready to Get Started?

Connect with us to talk about your needs.