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Data-Driven Supply Chain: Practical Tips. Real Results.

19
September
2024

Chat-GPT, self-driving vehicles and delivery drones are the headline-worthy faces of a data-driven supply chain. Yet for most of us, these innovations won't be rocking the boat in our day-to-day duties any time soon.

Although it seems data science has infiltrated every industry, in logistics, it seems to have only scratched the surface. This begs the question, how can data realistically transform and strengthen your supply chain?

1. Tracking Process

Just as a captain wouldn't set sail without a compass, a logistics manager shouldn't run their operations without objectives. Without them, you might be sailing blindly, unsure of your direction or progress.

Key Performance Indicators (KPIs) are like the GPS of logistics, guiding you towards success and helping you avoid inefficiency and/or disruption. Some of the most popular KPIs include:

Without KPIs, businesses would be adrift, at the mercy of unpredictable currents and tides of the logistics industry. By measuring performance and providing valuable insights, KPIs keeps the freight moving forward, ensuring that companies stay on course.

2. Shipping Management

Historically, shipping lines have been notoriously secretive. But with the rise of reliable shipping data, the barriers to transparency are being broken down. We�re no longer in the dark about how shippers stack up against their competitors. So, how are logisticians capitalizing on this emerging data?

Real-time Tracking and Monitoring

With real-time visibility of supply chains, companies can optimize shipping routes and respond promptly to any unexpected issues. The latest iteration of shipping visibility takes it one step further, allowing customers to track their orders in real-time.

Carrier Competitor Analysis

Companies are collecting and analyzing past data related to carriers' cost and performance, which includes factors such as packaging, location, discounts, seasonal rates, delays, and communication. Finally, armed with this data, businesses can negotiate better carrier rates that without compromising speed or service.

3. Inventory Management

In a perfect world, predicting the demand for goods would be straightforward. But we all know that's not the case. As the pandemic has shown, even the most accurate forecasts are no crystal ball into the future.

Fine-Grain Forecasting

Consumer preferences, economic conditions, seasonality, marketing and promotional activities, and product availability all influence consumer demand. Tracking more variables and their impact on a granular level is elevating how demand is forecasted.

Inventory optimization

Distorted information throughout the supply chain can cause large inefficiencies in inventory. To avoid the bullwhip effect, predictive analytics is empowering logistics companies to optimize inventory levels, reducing stock outs and overstocking to improve warehouse efficiency [1].

IoT Integration

The integration of Internet of Things (IoT) devices, such as sensors and RFID tags, into warehouse operations, provide real-time data on inventory levels, equipment performance, and order fulfillment [2].

4. Supply Chain Strategy

A data-driven supply chain revolutionizes the way businesses interact with their customers. More efficient supply chain strategies not only save time and money, but also boost customer satisfaction.  

Route Optimization

By harnessing the power of data, we're revolutionizing shipping. We're using it to streamline routes, get your cargo to you faster, save you money, and even reduce our collective impact on the environment.

Customer Personalisation

With data-driven personalization, businesses can provide an exceptional customer experience that sets them apart from the competition. By collecting and analyzing customer data, companies can gain valuable insights into their needs, preferences, and behaviors.

5. Sustainability

In light of the logistics industry facing increased scrutiny to improve their environmental impact, data has become crucial to ensure compliance with new regulations [3]. Logistics workers are harnessing the power of sustainability data to cut down green premiums and pave the way for a greener and more efficient supply chain.

End to End Carbon Footprint Visibility

Surprisingly, a relatively short trucking leg can generate more emissions than a container's journey over thousands of kilometers at sea. By measuring each segment of your supply chain, you can strategically achieve the maximum impact on reducing emissions.

Optimizing Resources

By analyzing data on transportation routes, fuel consumption, and emissions, logistics companies can make informed decisions about how to reduce their environmental impact such as shipment, consolidation, slowsteaming and route optimization.

What this means for you

As the world becomes increasingly interconnected, the importance of building the foundations for a data-driven supply chain cannot be overstated.

In short, data is the lifeblood of the logistics industry, and companies that don't leverage it risk being left high and dry.

Deploying data in your supply chain is easier than every before, but that doesn't make it easy. "Bad data in, bad data out" is an adage for a reason. Finding a partners with expertise in data and logistics, like Explorate' make it easy to collect the right data - whether it be PO Management, carrier performance or emissions per shipment - and use it to move your business forward.

If you have any questions or would like to learn more about streamlining your supply chain, reach out to us today.  You can also follow us on LinkedIn for more freight forwarding insights.  

Data-driven supply chain FAQs

What's stopping adoption of data-driven logistics?

The adoption of data-driven logistics is still facing some challenges. One of the main obstacles is the lack of data, which makes it difficult to make informed decisions. Additionally, poor data display and visualization can make it hard to interpret and act on data insights. Furthermore, security concerns around data privacy and cyber threats make some companies hesitant to fully embrace data-driven logistics.

How will we overcome adoption barriers?

By sharing data across the supply chain, companies can gain valuable insights into their operations and make more informed decisions. Data visualization tools can help stakeholders better understand complex information and identify areas for improvement. Changes in legislation around data privacy and security can also increase trust and encourage adoption. Finally, upskilling employees with the necessary data analysis and interpretation skills can ensure that companies are fully equipped to leverage data for competitive advantage.

References

[1]  Ohio University. (2022). How the Bullwhip Effect Impacts the Supply Chain.  https://onlinemasters.ohio.edu/blog/how-the-bullwhip-effect-impacts-the-supply-chain/

[2]  Biz Intellia. (2022). 6 Widespread Applications of IoT in Logistics Industry. https://www.biz4intellia.com/blog/6-widespread-applications-of-iot-in-logistics-industry/

[3] International Maritime Organization. (2022). Rules on ship carbon intensity and rating system enter into force. https://www.imo.org/en/MediaCentre/PressBriefings/pages/CII-and-EEXI-entry-into-force.aspx

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