How can you build resilience in your supply chain? The COVID-19 pandemic is one of the global crises that has affected the supply chain by causing an insane level of uncertainty and unprecedented stress.
In fact, according to a survey by Gartner, more than 70% of supply chain leaders say that their supply chain is experiencing more impactful and frequent disruptions due to the COVID-19 pandemic.
Business leaders need to take appropriate measures to streamline supply chain operations that will be sustainable in a post-COVID-19 period.
Minor supply chains disruptions, such as shortages in transportation capacity and late deliveries can be addressed promptly and with ease, but to detect, analyze, and respond to more impactful business disruptions, you require supply chain analytics.
Supply chain analytics simply refers to the collection of data that provides essential insights into logistics performance like order fulfillment and inventory management.
In this article, we’ll discuss 5 supply chain analytics best practices to adopt post-COVID-19.
1. Integrating Data Sources
Supply chain analytics software depends on data from different sources. This includes information from warehouses, manufacturers, and order fulfillment operations.
However, managing this data manually when demand is constantly shifting due to the global COVID-19 pandemic can be resource and time-intensive as well as error-prone, which could lead to severe consequences, such as overstocking or understocking.
For you to get a clear view of how your supply chain is running, you need to integrate data sources to get accurate supply chain analytics that relates to better performance.
Fortunately, the COVID-19 pandemic has led to digitization with new technologies such as content intelligence solutions being leveraged to gain real-time insights into the supply chain performance.
In fact, according to the World Economic Forum, core technologies of the Fourth Industrial Revolution, such as the Internet of Things, Big Data, Cloud Computing, and Blockchain are building a more resilient supply chain management system for the future by ensuring data accuracy and encouraging data sharing.
In the post-COVID-19 period, leveraging these technologies to gather real-time data on your supply chain will enable you to derive actionable insights to boost your transparency and ultimately your performance.
2. Extracting Localized Insights
In a post-COVID-19 period, the shift from globalization to localization will cause the most significant impact on the supply chain. According to a press release by the World Bank, the COVID-19 pandemic will plunge the global economy into its worst recession since World War II.
The recession will, therefore, result in a drop in global product demand compounded by the effect of governments protecting their markets. In addition, trade-in products and services involving shipping are expected to reduce in the short to medium term with regard to prices and volume.
As a result, logistics hubs will materialize in regional areas. Component suppliers, product integrations, and sub-system suppliers will start assembling and supplying their products from localized areas to eliminate single-source dependencies and create flexible supply chains.
In this case, if you are distributing inventory across different warehouses, extracting local insights can be effective for your supply chain success.
Accessing local inventory allocation data will enable you to keep track of how specific locations are performing, their challenges, and appropriate solutions that apply to them.
By powering your logistics network with a warehouse management system, you can automatically access inventory allocation data on the latest distribution and acquire actionable insights for an ideal distribution strategy.
Courtney Lee had a challenging shipping experience with her first 3PL that led her to partner with ShipBob’s free analytics tool. Now her team can get the fulfillment data they need in real-time for better decision-making.
3. Forecasting Demand Levels
Supply chains mainly depend on customer demand data to set the ideal minimum inventory levels.
This prevents understocking that can negatively impact the customer experience and overstocking can lead to loss of supplies through theft or expiration.
However, the COVID-19 pandemic has created a lot of uncertainty around customer demand, especially due to loss of employment, export bans, and fluctuating prices of goods.
As a result, managing inventory without the ability to forecast demand is challenging and can result in loss of goods and wastage of resources, thereby affecting the stability of a supply chain.
It is, therefore, essential to forecast customer demand levels during a post-COVID-19 period to optimize inventory levels.
By leveraging content intelligence solutions, such as predictive analytics, you can forecast future demands and prepare for changes down the line.
In fact, according to a recent industry report by MHI, the number of companies using predictive analytics has grown by 76% from 2017 to today to fine-tune their supply chains.
When you combine insights from data like production lead times, average units sold daily, and receiving turnaround times, you can predetermine reorder quantities as well as set reorder points to streamline your inventory restocking process.
4. Predictive Route Planning
The supply chain industry is more competitive than ever as businesses try to acquire new customers while also retaining existing ones.
One of the ways to ensure you’re achieving this is by eliminating possible delays in the distribution of goods to enhance the customer experience.
However, with the disruption of supply chains due to COVID-19 restrictions, such as strict regulations on cross-border shipping, companies fear they won’t meet contractual obligations on time, resulting in shipping delays.
In fact, according to a 2020 survey by Statista, 49% of the respondents reported experiencing severe delays in acquiring critical supplies, which had a limited impact on their businesses.
Businesses, therefore, need to structure their own responses to avoid expected delays in the supply chain.
Leveraging a Contract Analysis platform is, therefore, one of the supply chain analytics best practices to adopt post-COVID-19 to ensure you are meeting contractual obligations.
A contract analysis platform enables you to manage large amounts of contracts coming from different businesses, understand the language through natural language processing, point out possible errors, and set timers to enable you to keep track of deadlines.
In addition to that, using a predictive route planning platform can also help you optimize your supply chain by accounting for expected delays. This way, you can speed up your shipping process to ensure faster order fulfillment for a better customer experience.
5. Sentimental Data Analysis
Online shopping is on the rise due to COVID-19 protocols such as maintaining social distancing that was imposed in a move to combat the spread of the virus. In fact, according to a survey by UNCTAD, at least 75% of online shoppers make an online purchase every two months ever since the outbreak.
This has seen a significant impact on online migration by customers to social media platforms like Instagram and Twitter, both for communication and shopping. As a result, businesses have also moved to online platforms to optimize their business for their target audiences.
However, businesses mainly depend on logistics firms for the movement, storage, and flow of goods. With the disruption of supply chains across borders due to the pandemic, there has been a direct impact on the customer experience due to challenges such as product delays.
Post-COVID-19, analyzing customer discussions and reviews on social media platforms can therefore be a great way to supplement quantitative data as they sometimes provide qualitative data on the performance of supply chains.
Through supply chain analytics, such as sentiment analysis, you can gain insights into the needs and pain points of your customers, as well as find opportunities to strengthen your social commerce strategy and optimize your supply chain.
Supply chain analytics best practices refer to the strategies and techniques that organizations use to optimize their supply chain operations and decision-making processes through the use of data and analytics.
These best practices can have a significant impact on eCommerce 3PL fulfillment, as they can help companies improve their visibility into their supply chain operations, reduce costs, and increase efficiency.
By adopting these practices, eCommerce companies that use 3PL fulfillment can improve their supply chain operations and better meet the demands of their customers. This can help them increase customer satisfaction, reduce costs, and improve their competitiveness in the market.
Additionally, by using data and analytics to inform their decision-making, eCommerce companies can make more informed decisions about their supply chain operations, enabling them to respond quickly and effectively to changes in the market and customer demands.
Conclusion
The COVID-19 pandemic has caused major disruptions in the supply chain, and business leaders need to find ways around them to ensure that they are running smoothly.
In fact, according to a case study by PWC, transforming the supply chain for a Fortune 500 retailer to improve the customer experience could support an estimated 43% revenue increase in the long term.
Supply chain analytics gives you the ability to make accurate decisions based on real-time data or that is provided by data analysts.
Having gone through the supply chain analytics best practices for adoption post-COVID-19 such as forecasting demand and integrating data sources, I hope you can implement them for better supply chain performance.
However, if you are completely new to supply chain automation, you can START by leveraging content-intelligent solutions for the better supply chain management.