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Analytics & Optimization for Consumer Packaged Goods

Analytics & Optimization for Consumer Packaged Goods

Driving faster analytic insights from the IoT and other big data.

Solution Details

Put the right product, in the right place, at the right time.

The product a consumer selects from a store shelf or from the online store is the culmination of a series of smart decisions by the manufacturer. To win the sale in today’s consumer-centric, demand-driven, ever-changing markets, you have to manage the tremendous complexity involved in producing more products, brands, packaging and sizes.

By putting the power of advanced analytics and optimization in the hands of your business users, FICO decision management solutions help you handle the complexity while controlling costs and maintaining quality. As essential elements of Industry 4.0, predictive and prescriptive analytics identify the SKUs most important to your revenue, margin and market share goals. They reveal ways to increase value across the cycle from planning through order fulfillment.

Use Cases

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Planning, Forecasting and Scheduling

Increase demand-driven agility while shrinking production costs and order fulfillment cycles.

As a CPG innovator, you’re making more frequent adjustments to your SKU portfolios based on market feedback and strategies for addressing unmet consumer needs, assortment gaps and growth pocket opportunities. Essential technologies include predictive analytics to understand changing demand patterns and produce more accurate forecasts, intelligent automation to keep master data in sync across your enterprise, and optimization and simulation to identify the most advantageous production schedules under various demand scenarios and business constraints.

  • Streaming data analytic platform
  • Business rules management system
  • Predictive analytics
  • Machine learning and other explainable AI
  • Production scheduling optimization
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Pricing Incentives

Optimize pricing and discounts for changing consumer behavior and channel relationships.

Consumer sensitivities to price and other values, like convenience, vary by channel, retail format and delivery options. Optimization lets you to take all of these factors into consideration while balancing multiple business goals and constraints, as well as those of your cooperative marketing partners, to pinpoint the best pricing and promotional strategies.

  • Predictive models (propensity to buy, time-to-event, uplift)
  • Pricing optimization
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Logistics and Supply Chain Optimization

Put inventory, capacity and supplies where current demand requires them.

Optimization recommends the best inventory levels for any number of demand scenarios. Use it with simulation to develop tactical sourcing strategies for handling spikes in demand or coping with supply chain disruptions. Analyze digital twins of supply chain processes to simulate more advantageous product flow paths. Optimization can also bring decision clarity to other complexities of supply chain management, including logistics concerns such as warehouse dock door scheduling, transportation network design and production facility location.

  • Inventory forecasting, placement and right-sizing
  • Spend and supplier mix analyses
  • Vendor contract management and performance analysis
  • Product flow path optimization
  • Supply network optimization
  • Rapid design/deploy of analytics-driven digital applications
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Production Management

Reduce changeover time for product and packaging variations.

Fully leverage all the data being captured from IoT sensors, machines, cobots and work teams to understand what’s happening in production lines and how to accelerate processes. Optimization and simulation can be used to analyze digital twins, revealing opportunities for improvement in many areas, such as production scheduling and process flows, beverage and blend mixing, workforce scheduling and production facility location strategies.

  • Business rules management system
  • Streaming data analytic platform
  • Machine learning and explainable AI
  • Predictive maintenance
  • Production scheduling optimization
  • Rapid design/deploy of analytics-driven digital applications
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Equipment Diagnostic

Reduce downtime through predictive asset maintenance.

Decision rules add intelligence to diagnostics systems, reducing time-to-identification of the root causes of production problems. Predictive analytics identify machines that are outliers in terms of expected ranges of production, speed or energy consumption — triggering maintenance intervention before failures occur. Machine learning can analyze a wide variety of factory data for insights — like relationships between humidity and machine energy consumption — that point to improvement opportunities.

  • Streaming data analytic platform
  • Business rules management system
  • Machine learning and explainable AI
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Distribution

Move products in more ways to more places with more speed and ease.

Optimization can identify the best choices among several million routing options in seconds. One company used it to cut planning time from 80 minutes to 2 minutes while increasing the number of distribution sites from 7 to 20. Another is using the technology to make hundreds of millions of SKU-level warehouse inventory decisions every day. And optimization, along with rules-driven automation and “What if?” scenario simulation, can help you make better decisions about all of the interrelated complexities of product fulfillment: packaging options, container types, dock door scheduling, load building, carrier and truck load allocation, route assignment and more.

  • Business rules management system
  • Streaming data analytic platform
  • Machine learning and explainable AI
  • Load, trip and route planning optimization
  • Rapid design/deploy of analytics-driven digital applications