Connectivity breeds agility
By Dan MitchellAutomation
Sponsored by SAS
How the right data delivers visibility in the CPG supply chain
No one in any industry or the culture at large would deny that the world is highly connected. Everything from smartphone apps and social media algorithms to artificial intelligence and machine learning is simply part of our everyday reality. In addition to connectivity, the past couple of years have threaded in another element of business (and life) we can count on: disruption.
For consumer packaged goods companies (CPGs), this duality requires a perspective – and process – shift so businesses can be ready to react when (not if) disruption happens. Better yet, they can proactively plan for potential disruption internally and throughout their supply chain, able to predict responses and recover quickly. This can be achieved through digital connectivity.
But it’s not just potential disruption that should be a catalyst for CPG digital connectivity. General manufacturing processes can be assessed, enhanced and corrected, whether a company is looking at scaling production, changing suppliers or implementing robotics. What are the impacts of one change – or multiple changes? How quickly will a particular change be visible to the consumer? What’s the effect on your supply chain – and the supply chain on you?
Shifting from demand generation to production data
For CPGs today, creating demand for their products is the least of their concerns. Instead, efforts are focused on accurately understanding their capacity to create, as well as the effect of ingredient/material availability, staff issues and equipment on production levels. The right data allows for scenario analysis of possible outcomes and efficiencies, both internally and through those last “thousand miles” to the consumer – and how all those possibilities affect margins.
Advanced analytics and AI solutions, including machine learning, IoT and computer vision, allow manufacturers to optimize processes and find even small efficiencies that translate to significant cost savings (and maximum profitability). Modeling across production can help businesses react well – and be ready – when problems arise.
Simulating efficiency with digital twinning
How do companies get the right data – and enough of it – to analyze ideal processes and predict disruption response? Digital twin simulations make it possible to have computerized replicas of your production and supply chain, simulating disruption to quantify impact and assess recovery.
What are some of the challenges digital twin technology can address?
- Maintaining production quality and reducing waste.
- Predicting product shortages.
- Meeting demand shifts while minimizing lost sales.
- Identifying bottlenecks that cause the supply chain to experience low fill rates.
- Controlling costs and margins.
- Anticipating risks and managing supply chain disruptions.
- Determining corrective actions to reduce the risk of future shortages.
- Minimizing environmental impact.
At the supply chain level, CPGs can use digital twins to elevate connectivity well beyond their own infrastructure, including their entire operations network flow from suppliers and factories to warehouses and customers. As within manufacturing, this supply-chain level of virtual representation allows for visibility that would otherwise not be possible. You can test responses and decisions against various potential scenarios to determine and create optimal plans for the next disruption – because it’s just a matter of time.
Digital connectivity through today’s sophisticated AI and analytics solutions enables agile production and proactive planning, allowing you to predict the best possible outcome and muster a swift response.
Do you have the right connections?
Get the e-book from SAS and Intel to learn more.
Dan Mitchell is Global Director, Retail and Consumer Goods Practice, SAS
Print this page
- Oatbox raises $7.1M to build an oat base manufacturing facility
- Mondelez sells gum business to Perfetti Van Melle