Factory Automation That Transforms Supply Chains

The problem

Turning Challenges into Opportunities

What was slowing revenue, draining cost, or blocking the next stage of growth.

Establish real-time visibility into machine performance and health
Reduce unplanned downtime and bottlenecks
Predict demand more accurately and tie that forecast back into production planning
Align supply chain throughput with marketplace needs

What we built

The work sequence that turned the constraint into an operating advantage.

01
Predictive Maintenance Enablement
Machine data was continuously evaluated to detect early indicators of failure. Planned maintenance schedules replaced reactive responses, resulting in markedly higher reliability and less downtime.
02
Sentiment-Driven Consumption Forecasting
Across some ~12,000 retail doors — including regional and national chains — consumption sentiment analysis was used to generate more accurate, real-world demand predictions. These insights gave leadership a clearer picture of forward demand than traditional transactional forecasting.
03
Demand-Driven Supply Chain Integration
Consumption forecasts were mapped back into production and supply chain models. Instead of scaling production on historical usage alone, the organization could now scale up or scale down across specific SKUs based on predicted demand signals and production capacity.

The results

Numbers the business can take to finance, sales, and the board.

$70M in annual savingsthrough reduced effective cost of goods across the supply chain
$72.5M reduction in IT costsfrom consolidating legacy systems and automating data capture and reporting workflows
Dramatic improvement in uptime and reliability through proactive maintenance scheduling
Faster learning loops to diagnose issues and prevent repeat disruptions

What it unlocked

Follow-on gains after the core system was in place.