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Innovation

Business Decisions Made Easier: Key Areas of New Tools and Functionality

Julien Broucke
October 18, 2023
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min read
The modern supply chain is under pressure to reduce costs, increase volume, and speed up operations: a modern tech stack is needed.

The challenge of making great, fast and informed decisions in supply chain management is most important as it can have a major impact on customer service.

In today's fast-paced business environment, companies must be able to quickly adapt to changing market conditions and consumer demands in order to maintain a competitive edge. Serving your customers with short lead times, large portfolio and at the appropriate price is difficult, and keep smiling to them as they come back to you with issues that you could not prevent is even harder!

This requires not only a deep understanding of the various factors that influence supply chain performance, but also the ability to make timely and effective decisions that optimize operations and improve customer satisfaction.

In this blog post, we will explore some of the key technologies that will help you in making great, fast and informed decisions in supply chain management to improve Customer Experience.

·        Digital twins

·        Orchestration of people, information and systems

·        Artificial intelligence and machine learning

Digital Twins – Let Decision Makers See the Future and Execute

Digital twins are sets of data that provide an accurate and dynamic representation of a real-world entity, it can be something physical like a factory or a mirror of an organization with all its reporting layers.

This virtual representation enables businesses to optimize their operational supply chain, through:

  • Predict outcomes using simulated data,
  • allowing them to test different scenarios and
  • providing contextualized information for faster decision making

Digital twins can represent:

  • An asset such as a production line or supply chain flow
  • A product such as a car or medication being manufactured
  • An organization, with its multidimensional connections between processes, people, and data

The ability to model and predict the impact of business decisions, external factors like weather or equipment downtime, is crucial to building resiliency in supply chain management. Digital twin capabilities integrated into logistics planning tools can help users better understand potential problems and business opportunities, and proactively mitigate challenges or volatility, such as closed ports, unusually large customer demands, or communication team problems. Digital twins can also improve risk management by helping organizations map and prepare for disruptions.

Enabling organizations to see their impact from country of origin to delivery is most important in a globally interconnected supply chain.

Companies equipped with digital twin technologies can contextualized information, support scenario planning and drive execution at scale to better focus on what's truly important and mitigate costly problems.

Human inputs, combined with system and IoT integration, can take digital twins to the next level. This can be used to monitor inventory quality and identify issues that would impact customer satisfaction or cause a loss in revenue due to stock-outs.


Orchestration - or how to dispatch activities with the right info at the right time to the right people in real time

The increasing complexity and speed of supply chain management has created significant strategic business risks for companies. To become more resilient and agile, logistics organizations need real-time visibility and the ability to seamlessly share information in context.

In organization with large product portfolio, short lead times and decentralized teams across geographies, it is impossible not to work by exception, and even working by exception require a constant alignment in synchronization between teams.

With orchestrated business process management systems, companies can streamline collaboration and synchronization among supply chain planners, buyers, managers, and leaders, as well as with internal and external stakeholders. Data orchestration helps companies automate and streamline data-driven decision making, optimize the use of all available data sources, and increase operational efficiency and performance.

It also enables allocating the right activities to the right persons given their roles, their knowledge and available resources whether we are talking talking trucks, production lines, equipment or warehouse capacities.

Orchestration gives customers and providers, shipping companies, production sites and hubs easy ways to leverage their data to optimize and automate processes.

How AI, ML and Blockchain are Working in Real Enterprise Operations

AI and machine learning are advancing quickly and finding applications in various industries, including logistics. These technologies can be used to process any information across the supply chain network. By using AI, logistics organizations can create automated scenarios that react to conditions like traffic or environmental data. Intelligent decision solutions or decision support systems will improve agility in supply chain operations and logistics operations and alert users about potential damage, breakdowns, maintenance requirements, and future events that might cause operational changes.

The next step is to generate machine learning-based recommendations for dealing with these scenarios, known as next best action (NBA) recommendations. These recommendations aim to minimize errors and maximize productivity. Imagine you have a stock risks, a system will be able to suggest a few number of likely best way to deal with the issue such as whether to amend customers orders, delay them, rejig production plans, and so on.

Machine learning is becoming increasingly important in logistics as more data becomes available. ML algorithms can learn and adapt to new information over time. They may not initially know how to handle unknown situations, but they can learn from experience. Machine learning algorithms can identify patterns, tie them together, and adjust actions based on new information. They can also continuously learn and improve decision making without being programmed with predetermined scenarios, making them ideal for managing unexpected situations.

The modern supply chain is under pressure to reduce costs, increase volume, and speed up operations.

To meet these challenges, a modern tech sack is required to overcome this fast paced and complex environment. Technologies like digital twins, orchestration, automation, AI, machine learning, and blockchain are useful ingredients. If assembled in the right way, these technologies can revolutionize supply chain operations and transportation logistics.

However, when taken independently to the key business processes of an organization, it often fails to deliver benefit after an initial proof of concept. They need to serve the day to day of the supply chain managers.

At Metronome we bring these ingredients together in the right way to make your processes work in the real world.

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Julien Broucke
Co-founder & CEO, Process Metronome

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