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From Disorder to Insight: The Road to a Digitally Transformed CPG Industry

Consumer Packaged Goods - Success in Simulation and Scheduling

Imagine a manufacturing enterprise churning out billions in revenue from selling approximately 5,000 different consumer packaged products relying on pen and paper analysis to make complex decisions? Sounds alarming right? This scenario highlights, to an extent, the current situation in the consumer packaged goods industry. According to a survey, although 25% of enterprises in the CPG industry have purchased digital transformation solutions, just 2% apply digital transformation tools to optimize operational processes.

Today, enterprises in the CPG industry struggle with challenges such as optimizing supply chain routes, improving inventory management processes, managing available resources, and more importantly, meeting the consumer’s needs. Applying informal processes to analyzing these challenges is one of the reasons why many CPG products end up getting recalled which makes it difficult to meet increasing customer demands for accountability. To eliminate the chaotic process of managing unstructured data, integrating a structured process for capturing data across the production cycle and applying analytical tools can help. This is where a comprehensive digital transformation plan is required.

Charting a Course to Utilizing Structured Data

The first step to dealing with the large data sets enterprises in the CPG industry produce is developing a structured process for capturing data. In a scenario where diverse departments are tasked with recording sales order data, inventory data, and machine utilization data using traditional processes, analyzing the multitude of data coming from each department becomes a nightmare. Thus, demand and throughput data become the most important KPIs while other data sets such as machine downtime, available inventory, and supply chain data are relegated to the background.

Relegating data sets that are perceived to be inconsequential comes at a price. The example of Peanut Corp and its failure to monitor its food production processes and constantly evaluate its standard operating procedures led to the largest food poisoning case and over a billion-dollar settlement. Although the example of Peanut Corp may be at the extreme end, the average cost of recalls in the CPG industry is approximately $10million.

The first step to utilizing data is accurately capturing data and digital transformation technologies provide diverse solutions to capture data from every phase of the production cycle. The process of capturing data begins by implementing a data readiness program. The readiness program must consider the best solutions for capturing unstructured data and the business value they provide.  Today, multiple IT service providers offer cloud platforms that serve as a single source of truth for capturing both structured and unstructured data.

These cloud platforms are, in turn, fed data through IoT devices, inventory management, and edge computing devices that can track real-time data. The accurately captured data, which is the most important ingredient in every digital transformation process, can then be used for data-driven business purposes aimed at meeting the challenges within the CPG industry.

Applying Analytics Tools to Solve the Most Complex Industry-specific Challenges

The capture of unstructured data is the first phase of the digital transformation process while gaining insight from captured data begins the second phase. To gain insight analytical tools, which are also digital transformation tools, are required. It is important to note that one of the reason only 2% of CPG enterprises apply digital transformation as an operations optimization tool is because many stop their digital transformation journey at the first phase.

Captured data must be analyzed and put to work to solve problems. One example is that of a CPG manufacturer who struggled with meeting customer demands due to capacity planning and workforce management challenges in its distribution centers. Although the manufacturer was able to capture operational data such as demand, available products, and its available capacity, it required an analytical tool to analyze its captured data to optimize its planning.

In this case, the manufacturer utilized risk-based scheduling and simulation modeling software to analyze its challenges. The simulation model which was designed using captured data helped the manufacturer determine how to optimize its warehouse load preparation time, workforce staffing requirements, and increase its maximum storage capacity. On implementing the results from the simulation model, the manufacturer reduced its load preparation time by approximately 15% which also improved its service levels.

Digital twins which are virtual representations of physical processes and facilities, is another extensive analytical tool that can be applied to improve operational processes within CPG facilities. The cyber-physical environment a digital twin creates ensures real-time occurrences within a manufacturing facility can be analyzed and challenges evaluated in real-time to provide speedy solutions to production teams.

Conclusion

Although digital transformation tools can reduce recall rates, material waste, and improve operations within the CPG industry, proper implementation of digital innovations is required to reap these benefits. This is where having an expert innovative partner to implement digital transformation solutions comes into the picture. With the right partner, you can evaluate multiple scenarios and optimize multiple processes to go-to-market, reduce the total production cost, and stay ahead of the competition by implementing digital solutions. If the right partner to take your digital transformation initiatives to the next level is what you’re in search of, then speak to a Simio expert to learn how Simio scheduling, simulation modeling, and digital twin solutions can help.

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