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Oracle SCM Cloud: Optimizing Your Supply Chain Performance

QFDE Cloud Week

As part of Quest Forum Digital Event: Cloud Week, Rahul Asthana, Senior Director of Product Marketing for Oracle SCM, presented how to optimize your supply chain performance with Oracle Cloud Supply Chain Management (SCM).

He deliberately mentioned the name change from Oracle Supply Chain Management Cloud to Oracle Cloud Supply Chain Management at the beginning of the presentation. This change explains how your performance is enhanced by the ability of supply chain management to sit on top of the Oracle Cloud and its single digital thread.

Optimize Supply Chain Performance with Cloud SCM

The success of your business is inextricably linked to your supply chain performance. In fact, 79 percent of companies with high performing supply chains grow revenue faster than average. Only 8 percent of companies with low performing supply chains grow revenue faster than average. Therefore, 92 percent of companies with low performing supply chains underperform in the market and ultimately get beaten by the competition.

The question then becomes how to improve your supply chain performance. At its core, the ultimate goal of supply chain management is to make the following statement true: Supply = Demand. While simple in statement, this is very hard to achieve. Your company must seek to answer:

  • What products do customers want?
  • From which location?
  • Can we get the supplies needed at the exact time we need it to meet demand— or as efficiently as possible?

The solution to this difficult problem in supply chain management has two parts. First, you need to know more with actionable intelligence. This involves understanding customer demand—know with greater certainty what your demand is going to be. You must consider manufacturing needs—when will machines start to fail? You also need to now procurement—exactly where are supplies and at what quality?

Second, you must execute better, making sure nothing falls through the cracks at any stage in the process. To do this well, you must reduce unnecessary delays in your supply chain and improve coordination among supply chain functions.

Know More

Actionable Intelligence by way of emerging technologies creates exciting opportunities for Supply Chain Management. Three key emerging technologies are:

  1. The Internet of Things
  2. Blockchain
  3. Artificial Intelligence/Machine Learning

They are the path to knowing more.

Internet of Things (IoT)

Internet of Things marries data drawn from sensors on equipment with the internet. Data becomes geographically and contextually available.

Your car has sensors that tell you if something is wrong–low fuel, flat tires, etc., but this information stays localized to you. IoT takes this type of information and makes it actionable. It can search for visual patterns and anomalies. Machine Learning-based asset health predictions enable you to predict the maintenance of machines. Predictive analytics save you money and make you more efficient.

You can do this through another application of IoT—the digital twin. A digital twin is a complete representation of your machine on a digital platform. Furthermore, it can act as an X-ray for your machine. Imagine a service person looking at your machine to see what is wrong, while being prompted by the digital twin with ways to fix the issue.

Digital Twin

You can take this paradigm factory-wide. Collect information across your entire production line to understand the source of performance issues. Extend it again to view your factories around the world. In some sense, IoT brings information from different geographic locations to a central source so that you can contextualize it and manage your entire business more efficiently.

You can take the same IoT paradigm and apply it to your logistics network. Imagine having a real-time view of all of your supplies, their location, and status. This gives you the ability to adjust based on what you see.

Supply Chain Visibility

For a traditional product and business model, buying a product immediately depreciates the value. Interestingly, the consumer and manufacturer have no relationship in this model. The company does not know who the customer is, nor do they know the way the customer interacts with the product.

In the new age of IoT, companies such as Tesla, Apple Watch, MRI machines manufacturers, and more, create and maintain a relationship with the customer. The company can see how the customer uses their product and provide assistance when needed. There are even options for IoT monitored pay per use in the case that the customer can’t afford to buy the product (such as an MRI machine for a low-income country).

Additional benefits include product updates via software, big data on customer usage patterns, predictive repairs, and immediate big data collection for flaws.

In short, IoT enables customer knowledge and insight.

Artificial Intelligence/Machine Learning

Artificial Intelligence has two main functions. It understands unstructured data and improves predictions to reduce uncertainty. The three common classes of AI algorithms include feed-forward neural networks, convolution neural networks, and recurrent neural networks. These algorithms recognize images and make predictions about them. They also allow you to understand text and sound. These are capabilities of machines that were previously available only to humans.

In manufacturing lines, most products are still made by humans in an assembly line. The fundamental question is, “How well are your humans performing?” AI allows you to place cameras and AI image analysis (computer vision) near your workers to monitor the efficiency of your production lines.

Additionally, you can use AI and meta-language processing to scan through social media posts to understand customer sentiment toward your product. This information allows you to look for demand surges or falls.

To better understand the benefits of AI, consider this baking analogy:

Like manufacturing, baking is a process. It begins with materials (ingredients), goes through a process (mixing, baking, frosting), and produces a finished process. Several bakers may use the same equipment and ingredients in an effort to make the same cake, but with very different results.

The reason for the inconsistency is a difficult question to answer. Even in cake-making, there is an enormous number of variables to consider, like ingredients, batter consistency, frosting, preheating your oven, etc.

In manufacturing, the situation is even worse. McKinsey & Company claimed there could be a combination of 5 million factors that influence yield and quality of a product. This is where machine learning can be a great help. It can look at the outcomes to better determine issues.

Machine Learning determines which combination of factors led to your yield. If there are 5 million possible factors, this is an impossible practice for a human to perform. In a nutshell, AI can do the following:

  • Identify the most influencing factors that affect the quality
  • Predict what kinds of problems the product will have
  • Recommend or prescribe actions to ensure a perfect product
  • Continuously learn from every product that is made to improve knowledge

Application: Improving Demand Forecasts

Accurate demand forecasting is one of the most important functions in a company. Unfortunately, demand forecasting is hard, and often inaccurate. Traditional forecasting relies on historical data instead of actual demand. Demand from the past could have been influenced by any number of factors that no longer impact your company. Traditional forecasting has been dependent on traditional sales data, current sales data, and any grapevine information. Machine learning, on the other hand, has the potential to learn the root cause factors underlying true demand.

Artificial intelligence receives algorithm inputs from these factors:

  • Traditional sales data
  • Current sales data
  • Trade promotions
  • Social chatter and media messages
  • Complementary products
  • Competitive product introductions
  • Economic or political changes

The implications for supply chain management are huge, as you can use this information to make more accurate predictions.


Blockchain is a way to simultaneously update, distribute, and share a set of immutable records. This ability to store and share unchangeable data is very useful in supply chain management. You can ensure the authenticity and quality of raw materials in the supply chain.

For an analogy that better explains blockchain, consider Microsoft Word versus Google docs:

The traditional information transfer of data not visible across supply chain partners is similar to collaborating with others through Microsoft Word. You send copies to several individuals. They track changes and send copies back to you. It is very possible that you will lose version control.

For a blockchain information transfer, data is immediately available to all supply chain partners. This is similar to collaborating with Google docs. There is one version of the truth. Everyone can see what everyone else is doing. There is transparency.

Take this back to the enterprise system. Essentially, you have flattened the complete system so that you can view changes as they happen. The image below illustrates how blockchain simplifies the supply chain process.

Blockchain Supply Chain

If you understand that supply chain performance is proportional to the visibility and speed of information flow for supply chain, then blockchain in your supply chain is going to be a key strategy for transforming your performance.

At Oracle, the aim is to help you learn more about your supply chain by embedding IoT, AI/ML, and blockchain into all supply chain applications. This diagram represents a simplified view of the architecture. All apps include these emerging technologies, which sit on a single data model connected by a single digital thread.

SCM Cloud Diagram

Execute Better

The second way to improve supply chain management is to execute better. Two key approaches to executing better include:

As mentioned, all applications are on a single data model and can communicate seamlessly as a result. Planning is often executed with the approach shown on the left:

Planning Execution

A better way is shown above on the right. It utilizes the single data model.

To explain how a single data model can help you, consider the following example:

An MRI manufacturer has placed a machine at a hospital. To maximize revenue, they need to ensure the machines are running. Once ensured, the quality of the machine is extremely important. The manufacturer is responsible for the uptime of the machines.

Quality is not a single function. As the slide below illustrates, quality is a multi-function process. It is best done when every actor is working from the same data and can communicate seamlessly between functions. The single data model has allowed Oracle to build just such a production model.

Multi Function process

From the example, this screenshot shows product data specifying the requirements of torque. Using IoT, we can monitor the torque to see if it is out of bounds. If so, there is a prompted requirement to replace the motor. You can change the AML. Because everything is on one platform, you can run a complete business process seamlessly.

Example 1

Example 2

Stay Modern

The Cloud completely disrupts the notion of innovation. In the days of legacy systems, upgrades occurred every five to ten years. It was like climbing a mountain each time you upgraded. By the time implementation occurred, the system was out of date. There was a massive disruption to operations at each upgrade.

With Cloud SCM, the system is continuously up to date with the latest technology. Each version is seamlessly adopted. New feature cycles occur every three months. Instead of climbing a mountain for upgrades, updates can be considered a small speed bump. There is much advantage to your organization. SCM Cloud is completely modern all the time. The user interface is intuitive. Embedded business intelligence allows you to contextualize information, and guided decision allows you to stay modern all the time.

Key Takeaways

To summarize, the most difficult venture of supply chain management is matching your supply to demand. Oracle helps you to know more through natively embedding emerging technologies into SCM Cloud. Internet of Things, AI/ML, and Blockchain transform the actionable insights you have of your supply chain and allow you to react with greater intelligence. Oracle also empowers you to execute better with the unique product strategy. This strategy includes a single data model with a single digital thread and Cloud. The combination of these features enables you to run seamless Supply Chain Management processes efficiently with constantly up-to-date capabilities.

To learn more about how to optimize supply chain performance with Oracle Cloud SCM, check out the presentation and additional resources attached below.