Data analytics has reached a tipping point. With the quarantine winding down, the need for first class data analytics is clear.
Only the fittest companies will emerge from the disruption caused by the Coronacrisis.
And those businesses will face an adverse operating environment.
The market will continue to be increasingly complex and fast-paced. Successful supply chains will call for precision made possible by data-driven businesses. Now is the time for embracing data analytics.
Data analytics offers promise because logistics lends itself to the direct application of logistics/supply chain issues. Add to that, data analytics is faster, better, and cheaper to adopt and use than ever before. Finally, volumes of data are available. This enables you to extract value and convert data into useful information.
Data analytics for logistics can help you reduce risks from disruptions. Data analytics can also simplify operations, and create opportunities. Specifically, you’ll be able to cut costs, grow profits, and increase your competitive advantage.
Let’s dive into five persistent logistics problems that can benefit from data analytics.
5 Logistics Problems That Data Analytics Can Solve
#1 Re-balancing Containers for Improved Availability
Having the right number of containers available in Chinese and U.S. ports is imperative to seamless cargo flows. As a result of Covid-19, visibility of container availability has become skewed. It is neither optimized for nor synchronized with the coming surge in economic activity.
First, Chinese manufacturers shutdown operations due to the virus outbreak. Then came the Chinese New Year. Finally, the fast-spreading Coronavirus led to further extended factory shutdowns. That led to increased blank sailings over the expected seasonal blank sailings.
To help re-balance container availability, you can use data analytics to forecast demand. That improves visibility of container availability. And that will improve agility and responsiveness. It also reduces volatility, facilitating smoother flows of cargo and improves customer service.
Data analytics enables data-based decision-making replaces instinct. In this case, data analytics enables re-balancing of containers that promotes seamless cargo movement.
#2 Timely Movement of Cargo from Manufacturer to Final Destination
Seamless cargo movement is a critical logistics and transportation process. Container availability will impact cargo movement. But as operations return to normal, the surge in economic activity will negatively impact seamless cargo movement. And the sharp decline in China’s manufacturing activity presents a tremendous challenge.
According to the National Bureau of Statistics, China’s Purchasing Manufacturers Index (PMI) fell to 35.7 from an average of 50. Additionally, Supplier Delivery Time Index dropped off a cliff from an average of 50 to 32.1.
Shippers and carriers will have their hands full in adjusting as the economy picks up. To help manage shipments meet promised delivery times, data analytics can dynamically change routes as requirements change. Data analytics also helps improve customer satisfaction with predictive analytics.
#3 Managing Supply Chain Complexity
Supply chain complexity comes in many forms. And complexity is increasing, not decreasing. Government regulations change often and loom large internationally and nationally. The International Maritime Organization’s low sulfur mandate has a potentially huge international impact. Also, a pending Federal Maritime Commission regulation on demurrage and detention will affect the domestic market.
Trade wars also add complexity with new tariffs being levied on a variety of goods. Complexity comes in figuring out which products are under tariff and which are exempt.
Also, even though the U.S. and China came to a Phase One Agreement, that was just a first step. Based on that, many companies doing business in China have decided to either move out of China completely or partially.
The NIKKEI Asian Review reported fifty companies are moving out of China. Most of them are technology companies like, Apple, Dell, and HP. Other multinationals reshoring are Skechers, Asics, GoPro, Citizen Watch, to name a few.
Data analytics can help identify optimal ways of meeting governmental regulations, while avoiding penalties. Data analytics can also help identify alternative sources of labor and materials to diversify outside of China. Finally, data analytics can help you simplify and streamline your supply chain while cutting costs.
#4 Improving Supply Chain Resiliency and Risk Management Planning
Another area where data analytics is useful is in improving resilience and risk mitigation. All supply chains are vulnerable to internal and external factors. And risks fall into two categories: known and unknown.
For known risks, data analytics can compare scenarios that offer the optimal solution. You can compare costs and benefits of avoiding or eliminating risk. For unknown risks, data analytics can run “what-if” scenarios. Evaluating “what-ifs” helps you better understand possible outcomes. It addresses anticipation head-on, which helps build resilience into your supply chain.
As we saw with Covid-19 and with the Tsunami that hit Japan a few years ago, Just-in-Time (JIT) logistics isn’t foolproof. Data analytics can help you address these contingencies using a data-based approach to balance stockage requirements with JIT.
#5 Improving Decision-making and Reporting
Data analytics helps you steer your business confidently with a data-based approach. Real-time data and predictive analytics, for instance, are still in early stages of usage. But they will soon become standard for all businesses.
As the logistics industry favors speed, the need for dynamic decision-making is increasing. Keeping executives, operators, and customers informed is paramount to supply chain management. Thus, real-time data informing real-time analysis will become the norm rather than the exception.
Business intelligence is gradually becoming “intelligent”. Data analytics tools and technologies allow for both macro and micro analysis. That former focuses on processes and the latter focuses on customer level information. Micro analysis makes deeper analysis possible and enabling customization and innovation.
That means you can segment performance, financial, and customer service metrics. In other words, data analytics provides meaningful information about targeted user groups.
Put differently, you can operate more effectively and efficiently while increasing service quality. Data analytics can increase revenues by improving existing business operations and identifying innovative solutions.
Data analytics offers a window into improving 5 long-standing industry issues.
Data analytcis can transform daily operations, financial costs and benefits, and customer service. Although data analytics haven’t reached their peak, they’ve reached a tipping point.
Improved technological development, increased volumes of data, and the market’s increasing complexity and demand for speed have spurred the need for data analytics.
Deeper analysis can make sense of large and small sets of data, providing hidden insights. That will lead to improved operations, reduced costs, and improved customer service. And don’t forget innovation.
You should care about data analytics because it’s a gamechanger.
It can differentiate your business from the competition. All in all, it can improve your company’s responsiveness and resilience. Both are important in today’s complex, fast-paced business environment.
Data analytics can do more than navigate supply chain disruptions. When you capitalize on the untapped value of your data, it can create opportunities. You’ll be able to cut costs, improve operations, and increase competitive advantage. Moreover, predictive analytics and real-time data can drive further gains.
A well-run business depends on a well-run supply chain. A well-run supply chain depends on data-driven decisions. With the proper use of data analytics, you can take your business to the next level.
Contact American Global Logistics to learn how we can assist you in enhancing your competitive advantage with data-driven insights.