Industry 4.0 for Consumer Packaged Goods (CPG)
Technologies like automation, IoT, and advanced analytics will permanently change the way packaged goods are produced, distributed, and sold. Industry 4.0 presents a remarkable opportunity for AI and data analytics to reduce costs by accurately estimating demand and inventory levels. While machine learning can help businesses anticipate and predict their consumer needs and gain a competitive advantage.
Given the scope for process improvement within the distribution sector, organizations need robust strategies to effectively estimate their business transformation needs, analyze their operations, and focus on cost management. A mindful overhaul of the company culture also has the potential to make value-chains more productive for all involved and boost efficiency. Well-informed strategic decisions can significantly elevate the productivity and profitability of any CPG company.
CPG Use Case
Industrial Use Case – Operational Efficiency
A mid-market automotive supplier recognized its lack of supply chain resilience was generating additional challenges
The company was seeking a robust supply chain control tower model that could accurately predict future supplier relationships and event driven-inventory movements. Incorrect inventory positioning had resulted in 5 of the company’s 17 tier 2 suppliers being blacklisted. They also looked to incorporate live feeds from Wall Street into a dashboard.
Supplier relationship challenges were resulting in an untenable accounts payable dilemma.
The company’s supply chain was dysfunctional. It severely lacked both backward and forward visibility
Modularized Solution from Amplo Global Inc.
Utilizing the AmploFly4.0™ cloud-based platform, quick identification of the cash flows, inventory positioning and capability needed to enable the establishment of the desired control tower was achieved. Also, the live dashboard they sought was able to be established, resulting in greater marketplace awareness and accelerated responsiveness.
The organization make more mature with data and hence started predictive analysis as a new normal..