Logistics Analytics: Benefits, Types Examples & Use Cases

Logistics analytics is all about using data to make your logistics operations better. It focuses specifically on how to move goods more efficiently, keep inventory at just the right levels, and even predict future demand.

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Amazon ships millions of packages every year. The fulfillment centers are filled with humans and robots working together to box and ship packages. It has around 12 million items in its inventory, ready to ship across categories anytime.

And they rarely miss a delivery.

How do you think Amazon is pulling this off?

They use logistics analytics to make data-driven decisions and plan strategically. According to a recent study by McKinsey, companies that have invested in logistics analytics have seen up to a 20% increase in profits

If you want to see similar results for your business, stick around as we dive into examples and use cases of logistics analytics.

What is Logistics Analytics?

Logistics analytics is all about using data to make your logistics operations better. It focuses specifically on how to move goods more efficiently, keep inventory at just the right levels, and even predict future demand. 

It gives you actionable insights to make smart decisions that save money, time, and sometimes, even your reputation. Understanding analytics is a must if you want to scale your logistics operations without losing your sanity.

Related Read: Data Analytics in Logistics: Benefits, & Challenges

Benefits of Logistics Analytics

Now, let’s see how logistics analytics will fundamentally improve your business operations.

  • Cost Savings: Keeping tabs on logistics costs is crucial, and analytics can help identify where you're spending too much.
  • Improved Efficiency: By analyzing delivery times and warehouse activities, you can find the best ways to streamline your operations.
  • Improved Customer Satisfaction: When you know where every package is at every moment, you can keep your customers in the loop.
  • Real-Time Adaptability: Things change fast. Logistics analytics helps you pivot just as quickly to meet new challenges.
  • Strategic Planning: With logistics data at your fingertips, long-term planning becomes less of a guesswork and more of science.
  • Risk Mitigation: By analyzing patterns and trends, you can identify potential risks before they become problems, allowing you to take preventive measures.
  • Regulatory Compliance: Keeping up with laws and regulations is much easier when you have data to guide you.

So, from cutting costs to ensuring you're following the rules, logistics analytics never lets you miss anything and helps you get things right.

See it in action
Checkout Interactive Vertical Dashboards

Types of Logistics Analytics

Understanding the various types of logistics analytics is crucial for anyone in the business. Each type gives you a specific lens to view your operations, helping you make informed and effective decisions.

Descriptive Analytics

Descriptive analytics gives you a detailed look at what has already happened in your logistics operations. By examining past data on various metrics like shipping times, overall costs, and warehouse efficiency, you can create an accurate picture of how things have been running. 

This type of analytics allows you to understand the current state of your operations completely. It serves as the starting point to analyze the strengths and weaknesses of your processes. 

Predictive Analytics

Predictive analytics uses algorithms and statistical methods to analyze historical data and identify patterns. The goal is to predict what could happen next in your logistics operations. 

For example, it can forecast potential delays in shipping during the holiday season, giving you a heads-up to prepare in advance. It can also anticipate demand fluctuations so you can manage inventory better. 

With these predictions, you can preemptively address issues and save time and resources.

Prescriptive Analytics

Prescriptive analytics goes beyond telling you what has happened or what could happen. It gives recommendations on what you should do to achieve your logistical goals. 

 prescriptive analytics in a warehouse could tell you how many people you need for the night shift or how to cut down on overtime. It helps you make smarter choices to save time and money.

Related Read:

Actionable Insights from Logistics Analytics Examples and its Use Cases

Knowing specific use cases for logistics analytics can pave the path for logistics success. Here are 7 Ligistics Analytics Use Cases,

  1. Inventory Optimization
  2. Warehouse Slotting
  3. Market Penetration
  4. Supplier Evaluation
  5. Workforce Productivity Analysis
  6. Revenue Growth
  7. Customer Experience

This section will provide you with actionable ways to solve real-world challenges in logistics with analytics. 

1. Inventory Optimization

Keeping the right amount of stock is a balancing act. Too much and you're wasting valuable warehouse space, not to mention the costs of storing items that aren’t moving. Too little, and you risk losing sales and, in turn, customers.

By gathering and analyzing data on your inventory, sales patterns, and even external factors like seasonality, logistics analytics helps you make more informed decisions. You can understand which products are fast-moving and which are taking up unnecessary space. 

For example, the analytics dashboard shows that a particular product’s sales drop significantly in the summer months. You can reduce the stock levels for that item during the summer, freeing up warehouse space for more in-demand items. 

By using logistics analytics for inventory optimization, you make data-driven decisions that can significantly reduce costs and increase efficiency.

See it in action
Transport Management Dashboard

2. Warehouse Slotting

Running a warehouse isn't as simple as stacking boxes. You've got to consider various elements like the ease of access, weight distribution, and even the frequency at which items are picked. 

Logistics analytics gathers data on your inventory, how quickly items move, and other key variables. With this data, you can figure out the most efficient ways to store items, especially when it comes to warehouse slotting.

For example, say you have two products: one that flies off the shelves and one that moves slower. You can place the fast-moving product closer to the packing area to speed up the fulfillment process. This is not a one-time setup - as the sales data changes, the system gives updated suggestions accordingly. 

Along with speed packaging, you are also optimizing space in the warehouse and reducing overhead costs. Less time searching for products means your staff can handle more orders in less time. 

3. Market Penetration

When expanding your business, guesswork rarely works. You need targeted efforts to enter new markets or segments, and that’s where logistics analytics is helpful. It collects and analyzes data on customer buying patterns, geographical demands, and even socio-economic factors that might influence purchasing decisions.

For instance, suppose your data says a particular product is gaining traction in a specific zip code. You could strategically place your inventory closer to that area to speed up delivery times and reduce transportation costs. 

Ongoing analytics will help you monitor how well these strategies are performing. 

  • Are sales picking up in that zip code? 
  • Are customers happier with the shorter delivery times? 

These metrics are continuously analyzed to inform future decisions.

Now, your expansion into new markets is more calculated and likely more successful. With logistics analytics, you always have a competitive edge in today's competitive market.

4. Supplier Evaluation

Maintaining a reliable network of suppliers that deliver quality goods on time is a challenge. Businesses are stuck in partnerships that may seem cost-effective but are counterproductive due to frequent delays or quality issues.

Logistics analytics can evaluate suppliers based on several KPIs like on-time delivery rates, defect percentages, and compliance with contractual terms. Compiling all this information into easy-to-read dashboards helps you make quick and well-informed decisions. Learn more on Top Transportation KPIs and Metrics to Monitor in 2024

You can either renegotiate terms, find alternative suppliers, or adjust your inventory levels to account for these inconsistencies. 

Over time, having this data at your fingertips helps build a network of reliable, cost-effective suppliers, and that's a huge advantage in today's competitive markets.

Supplier evaluation through logistics analytics optimizes your supply chain from the ground up, ensuring a smoother flow of materials, reduced operational hiccups, and, ultimately, happier customers.

5. Workforce Productivity Analysis

Logistics operation isn’t always about managing goods. It is also about managing the people who make that happen. One of the real challenges is making sure that your workforce is as productive as they can be. 

After all, time is money.

Logistics analytics track various performance metrics for your staff, from warehouse employees to drivers. These can include the time taken to complete specific tasks, absentee rates, or even incidents of workplace accidents. It also highlights strengths, allowing you to deploy your most effective employees where needed most.

For example, if a particular team is exceptionally efficient at packing and labeling items, those staff members could be rotated to other tasks that require a high level of detail and speed. This type of internal benchmarking allows you to leverage your human resources most effectively, helping you to save money, meet deadlines, and maintain quality standards.

6. Revenue Growth

The ultimate goal of any business is to grow revenue. But in logistics, it is not always a straightforward task. But with logistics analytics, you can achieve your revenue goals easily. 

By analyzing sales data alongside logistics metrics, you can identify which products are not just popular but also easier and less costly to ship.

For example, when a certain product category has high demand and fits perfectly in your shipping containers, you can focus on promoting that product more. You can also optimize your pricing strategies by understanding the complete cost-to-serve for each product, considering the production, shipping, and handling costs.

This data can lead to strategic decisions about product development, marketing campaigns, and even supplier partnerships. 

7. Customer Experience

Understanding your customer's experience is key to the success of your logistics operations. It is not just about timely deliveries but about the entire interaction with your brand. 

By gathering data points from different stages of your logistics process, from order placement to final delivery, you can identify bottlenecks or inefficiencies affecting the customer experience. 

  • Are items frequently out of stock? 
  • Is the packaging not robust enough, leading to damaged goods? 

Analytics can answer these questions for you.

For instance, if you're getting customer complaints about late deliveries, your analytics tool can help you trace back to the root cause. Maybe a particular warehouse is consistently underperforming, or a specific delivery route is inefficient. Once you identify these issues, you can take the necessary steps to rectify them.

So, logistics analytics does not end with streamlining the operational processes but also takes care of the customer experience. 

After all, a satisfied customer is a repeat customer, and that's good for the bottom line.

Recommended Read: Use Cases of Transportation Analytics

How Databrain Helps to Implement Logistics Analytics?

We've taken a deep dive into the ins and outs of logistics analytics examples, exploring everything from optimizing your inventory to forecasting demand. The easy way to transform your logistics operations with these use cases is by adding analytics functionality to your existing logistics software. 

And what is better than using embedded analytics software?

Databrain is an embedded analytics solution that effortlessly becomes part of your existing software. You no longer have to flip between applications when all your analytics live comfortably within the software you're already familiar with.

Here's why Databrain is your go-to choice for implementing logistics analytics:

  • Seamless Integration: There's no need to rework your current data models or duplicate data. Your databases - SQL, MongoDB, or Elasticsearch, can easily connect with Databrain.
  • Accelerate Time to Deploy: The plug-and-play functionality of Databrain's embedded analytics can add analytics features without spending months developing them. 
  • Secure Access Control: With role-based access, Databrain ensures that only authorized personnel can view sensitive metrics. It maintains data integrity and ensures compliance with privacy laws, giving you peace of mind.
  • Visual Analysis: Databrain offers a range of chart types and interactive dashboards, making data exploration not just effective but also engaging. Users can explore data at multiple levels and identify hidden patterns and outliers, which ultimately aids informed decision-making.
  • Streamlined Reporting: Databrain can send you real-time alerts when there's a significant change in data, ensuring you're always up-to-date and can act swiftly.

Get ready to supercharge your logistics operations with the power of analytics and make data-driven decisions.

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