Supply Chain Design Tools: Optimizing Total Landed Cost in Uncertain Times
Hear from Coupa partner Grant Thornton about the changing role of the finance function in the face of disruption.
Even without the global disruption that COVID-19 introduced, business disruption has become more frequent. Battered by political changes, trade agreements, dangerous weather events, and supply chain breakdowns, occasional disruptions have become a series of disruptions that organizations must address with a strong foundational strategy.
Finance teams have become critical to this strategic shift. This is because companies need to maintain tight control on costs as there is a huge amount of change going on in the market.
A good remedy is to utilize artificial intelligence (AI) enabled digital supply chain design tools to support an evidence-based decision-making approach. Also, companies with multiple products may decide to cut down on their supply chain costs while increasing sales through product rationalization.
By optimizing total landed cost, companies can unlock demand, increase efficiency, and remain profitable in these uncertain times. However, it is not just about keeping the lowest cost. Supply chain operations also need to be optimized, so as to maximize supply chain resiliency in the face of rapid changes in the market.
Listen to the recorded fireside chat with Head of Operational Consulting, Oliver Bridge, from Grant Thornton UK, and supply chain expert, Mat Woodcock, from Coupa who discuss and use examples, to demonstrate how companies manage disruption and break down silos to make the best decisions in the face of supply chain disruption.
Here are some highlights from the conversation:
How to Address Supply Chain Changes in Uncertain Times
Businesses leading through disruption are adopting advanced AI supply chain management technologies to minimize costs and attain profitability. Implementing AI technologies can help organizations speed up and improve the quality of decision-making, reduce cycle time, streamline operations, and enhance continuous improvement.
In the event of a major disruption such as COVID-19, businesses can leverage the capabilities of AI to analyze their supply chains and develop contingency plans to optimize total landed cost, increase sales, and improve profitability.
Restructuring the Role of the Finance Function
In the past decade, businesses have been experiencing a myriad of challenges due to supply chain impacts triggered by unforeseen events. To cope, the structure of the finance function has been modified significantly.
The emergence of new supply chain software tools has allowed finance professionals to take a more strategic role. Data and insights derived from mathematical modeling and simulation have become increasingly important in decision-making.
Responding Quickly to a Changing Supply Chain Environment
To react quickly to a changing supply chain environment, businesses are embracing resilience and flexibility. This affords companies more control over the total landed cost of their products. However, to achieve this, it’s imperative that companies can assess all options and choose the best course of action.
In the webinar, the speakers highlighted several companies that demonstrated great resilience during the peak of COVID-19. For example, automotive companies in the UK faced a huge challenge with the supply of new car wheels. This occurred due to delays in the delivery of shipments from overseas manufacturers due to COVID-19-related restrictions. The best solution was to work with local manufacturers to make their supply chains more resilient. For retailers, the solution involved rethinking costs of warehousing and transport to stores before sourcing products.
Balancing Between Service Cost, Quality, and Resilience
Striking a balance between quality, service cost, and resilience is a strategic approach toward maintaining a successful business in difficult times. However, balancing these aspects correctly can be difficult. The trick is to start by understanding how these critical aspects interact with each other.
To increase profitability, the tipping point is making a choice about service levels. Implementation of “U-shaped solutions,” in which the lowest cost is taken as the governing criteria, was the norm for years. This technique includes “hammering the supply chains to make them as efficient as possible.”
However, flexibility is lost at such optimum efficiency levels. A balance is, therefore, needed to minimize cost while maintaining flexibility. As Oliver Bridge pointed out in the webinar, “It’s a mindset change from how do I minimize cost to how do I find the position where I could have a U-shaped cost.”
AI Supply Chain Design Tools: Modeling and Optimization
Traditional supply chain design modeling methods, such as using Excel sheets, is not only time-consuming, and siloed but also very ineffective. A more effective approach is to apply programming languages, such as Python or C++, to develop customized machine learning algorithms, perform calculations, and optimize results. However, this requires advanced programming skills and ample implementation time. The ideal solution is to use available software tools to model the processes and generate optimized solutions without coding.
According to Mat Woodcock, “business expertise will never be replaced. The trick is giving the tools to the people who are making those decisions to be able to test them and see the implications. You don’t have to know python or be a statistician. AI-powered supply chain design tools provide an easy front end that allows you to build these models by answering questions.”
These tools allow the users to implement scenario planning, which uses a question-based “what-if scenario modeling” approach to investigate and solve supply chain planning problems. The user can define important process constraints, develop and simulate models, adjust and test the behavior of different process parameters for different scenarios, and finally generate optimized results.
With the optimized results, the supply chain analyst can prepare an evidence-based proposal and share it with the management to aid the decision-making process.
Benefits of AI Supply Chain Tools
Supply chain design tools can effectively handle huge and complex data sets, allowing businesses to accurately manage logistics and inventory variables, such as order processing, packaging, transportation, and delivery, and overall improve supply chain analytics and inventory management optimization.
- Strategic decision-making: Supply chain design and optimization tools allow users to develop, compare, and test hundreds of unique scenarios. This is important for strategic decision-making in response to unexpected supply chain interruptions. By performing a sensitivity analysis, the user can identify the most suitable strategy to adopt and potential alternatives.
- Supply chain visualization: AI supply chain tools allow analysts to use data from different sources to create models and visualize the supply chain. Some common visualization methods include graphs, maps, and dashboards. Visualization allows the user to identify and take advantage of opportunities while ironing out existing inefficiencies.
- Optimized supply chain solutions: By applying advanced machine learning algorithms, AI solutions allow users to perform detailed analysis and optimization of the results.
- Supply chain response assessment: Once an optimized supply chain has been designed, the user can alter certain parameters and test the model through simulation to ascertain that it functions as planned. This is an important way to manage risk by developing and testing different mitigation measures before implementation.
Supply Chain Solutions: The Bottom Line
The success of any business during uncertain times depends on how well it can manage its operations and related costs. Coupa Supply Chain Design & Planning helps users to understand the interactions between costs, identify trade-offs, locate sensitive supply chain areas, and apply the “what-if scenario modeling” to develop optimized solutions.