Addressing an organization’s overarching end-to-end supply chain management operation is paramount to the success of any company, as it protects businesses against demand volatility, overstocking, stockouts, and lost sales. However, forecasting is not typically a one-size-fits-all process but requires a combination of tools, techniques, data, and human judgment to predict future demand patterns. But what if you could remove human subjectivity and use data from multiple sources, including your ERP platform and external data, to predict a supply chain disruption more accurately, even months before it occurs?
In this article, we will take a closer look at what data sets are helpful to predict disruptions and the types of data you need to get started with Ceres Technology.
How can purchase order data in an ERP be used to indicate if suppliers will be late on delivery due to supply chain issues?
Visionary astronomer Carl Sagan once famously said, “You have to know the past to understand the present.” And some would say that history does repeat itself.
The most accessible data available to look at to potentially predict future outcomes is typically your purchase history. Purchase order data in an ERP system can be used to indicate if suppliers will be late on delivery due to supply chain issues by tracking and analyzing the supplier’s actual lead time and delivery performance. The lead time is the time between the placement of the order and the delivery of the goods, while the delivery performance is the time the supplier takes to deliver the goods.
Suppose the lead time of a particular supplier has increased. In that case, this may indicate supply chain issues, such as delays in the procurement of raw materials or transportation disruptions. Additionally, if the supplier’s delivery performance has decreased, this may indicate supply chain issues, such as inventory or quality issues.
By analyzing this data, the ERP system can alert the purchasing team, which can proactively manage the supplier’s delivery expectations, such as communicating with the supplier and setting up contingency plans to mitigate potential delays. This can help to ensure that the organization’s supply chain is running smoothly and that there are no disruptions to the production or delivery of goods.
How does external data influence whether supply will be disrupted?
External data, such as geopolitical events, weather patterns, and raw material shortages, can significantly impact supply chain disruptions. For instance, political instability, trade disputes, or natural disasters in one country can disrupt the transportation and distribution of goods across borders, causing delays and inventory shortages.
Similarly, severe weather conditions, such as hurricanes or blizzards, can interrupt the movement of goods, leading to delivery delays and increased costs. In addition, raw material shortages or price fluctuations can affect the availability and cost of inputs, leading to production delays or increased prices for finished products.
To mitigate the risks of these external factors, supply chain managers must monitor and analyze relevant data sources, collaborate with partners, and develop contingency plans to minimize the impact of disruptions.
How complicated does my data model need to be to get accurate forecasting?
Simplicity is crucial to forecasting, especially since complex models can obscure errors and hinder adjustments. To improve forecasting accuracy, it’s vital to keep the process as straightforward as possible by employing an easy-to-understand model concentrating on the essential variables that influence demand. By prioritizing simplicity over complexity, businesses can reduce forecasting errors and enhance their ability to adapt to changing market conditions.
What if your data is incomplete or unavailable?
When we designed Nostradamus to manage inbound supply chains, we focused on the historical purchase order information. With this information, our team augments the provided data with over 17,000 external data sets (as of this writing), such as geopolitical, economic, commodities prices, and other data, for the system to learn your supply chain and begin making predictions about potential delays.
Customers that don’t have purchase order information can still reap the benefits by working with the data you do have. In this case, you’ll need to provide information about your suppliers, the product, the supplier location, the destination, and historical delivery times.
Our AI platform, NostradamusTM, can use any data from multiple sources to make its predictions. But don’t worry – we don’t ask for a crystal ball. We’ve designed a platform with some relatively straightforward data requirements. In fact, Ceres Technology only needs a few essential data fields to get started.
It’s important to note that the more historical data we have, the more accurate our predictions will be. We ideally prefer to work with 3-5 years of data and, if possible, pre-Covid and post-Covid data. However, we understand this may not always be feasible, and we can work with as little as 1-2 years of data.
The great thing is that this information can be in any format, structured or unstructured, meaning you can supply spreadsheets, databases, and even data from ERP systems.
Once we have the data it needs, Nostradamus turns it into predictive features, which are used to “learn” your supply chain. As a true AI, Nostradamus is constantly learning, so the more data you provide, the better the predictions will become over time.
This data is presented as a dashboard to view and manage the system once it’s set up. The dashboard delivers the results of its analysis back to you in the form of test results, which you can use to evaluate the accuracy of the predictions. All relevant data is presented in one place, with built-in flexibility, allowing you to tweak and manage the system however you like, with no coding necessary.
A simple formula for this process is shown below.
Getting started with Ceres Technology is a relatively straightforward process. You only need data from a few key fields; Nostradamus will handle the rest.
Today’s dynamic business environment requires organizations to react faster with more accurate data to remain competitive and profitable. With Ceres Technology’s advanced predictive analytics system, businesses can gain a real-time, data-driven understanding of their supply chain risks and take proactive measures to prevent or minimize disruptions.
Whether you want to improve inventory management, optimize production schedules, or enhance supplier relationships, our powerful tools and expert support can help you achieve your goals. Don’t wait to secure your supply chain’s future – contact us now to get started!