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Analytics: How to solve supply chain problems with smart data (Part 2)

Analytics: How to solve supply chain problems with smart data (Part 2)

Update: Shipwell analytics are now powered by Snowflake. Users now enjoy nearly real-time data loading times – 10x faster than previously available. Get a demo and see analytics in action.

The supply chain was once cursed with a lack of modern technology.

Everyone had their own isolated system to run their portion of the chain, usually on papers locked in a drawer. The entire economy was struggling because shippers, 3PLs, and carriers weren’t communicating with each other. Even when migrating to spreadsheets, there is an extreme lack of connectivity.

Today, with the onset of machine learning, artificial intelligence, and cloud-based storage, the freight industry is becoming more interconnected and transparent across the board. With an overwhelming amount of data coming in, it can be difficult to determine what data provides solutions to which supply chain issues.

In part one, we talked about how Shipwell’s dashboard and analytics can give users visualizations of their logistics data.

For part two, we wanted to talk about the high-level impact that big data can have on the complete operations and management of your business.

We will narrow down the data points so you can answer critical supply chain questions with the information you have.

Optimizing planning and operations

Planning and operations are some of the most data-driven processes in the supply chain. Fortunately, there are new ways to approach these early phases.

By analyzing point-of-sale data, inventory data, and production rates, we can monitor the fluctuation of ratios in supply and demand. With this insight, production can be realigned on the fly.

You can also use data sources to forecast demand and plan accordingly. By knowing that you’ll be selling more products ahead of time, you can source your freight capacity sooner and lock in better rates with priority carriers.

For e-commerce businesses, you can take demand forecasting and inventory data to inform which products you predominantly advertise to customers.

You can create demand for high-inventory products using real-time data analytics.

Carrier prioritization

By targeting several data points, businesses can learn how well their supply is moving.

For instance, if a shipper or 3PL has been using a specific carrier for a long time, they are likely not seeing a diverse performance data set. By expending to new carriers and determining transit performance, shippers could end up saving time, money, and have greater visibility to their freight.

Over 800,000 drivers operate in the Shipwell network, making it easy to stay competitive and use the carriers that will be the best fit for your business.

Carriers connected in the Shipwell network can enable shippers to track performance that can inform their inventory systems and warehouse schedule.

Understanding data sources

Because supply chains are generating so much data across the board, it’s good to know which data impacts a process (or processes) in your supply chain.

Supply chain managers today have little or no experience with analyzing data the way data scientists do. Because of this, they might not even know what to do with the data right in front of them. Having data scientists to explore and expand on opportunities presented in the data can mean volumes for the supply chain.

Here are just a few of the categories you can find answers in using data:

  • Warehouse data focuses on storage capacity, best practices for equipment usage, and personnel scheduling and efficiency. This data can solve everything from monitoring forklift actions to improve traffic in the warehouse to reshuffling pallets to optimize upcoming load schedules.
  • Inventory data can collect information on product volume, value, and distribution center allocation if companies store products in more than one location.
  • Logistics data will help make a huge freight spend to benefit the shipper even more. It monitors the volume of product inbound, in transit, and on delivery. On top of that, it can determine money lost in load wait times, and carbon emissions and fuel consumption to determine environmental impact.
  • Demand data determines forecasting of production and analysis of historical data to know when the market may shift.
  • Qualitative data helps business operations run with greater efficiency. Accessing data from customer service, lead times, other business requirements.

When analyzed properly, companies can use supply chain data for risk analysis in manufacturing, shipping, and delivering of goods. Then, businesses can create key performance indicators to monitor complete orders, accurate shipments, on-time deliveries, and payment processing speed.

What to do with all this data

It isn’t just the quantity, but the quality of data you are receiving that can make your decision-making more precise. Use data that is clean, accurate, and delivered in real-time. Never underestimate the number of data points you need to start making strong conclusions about your supply chain efficiency.

Of course, not every business can staff an entire data science team to accurately process all of this data. It’s hard to gather the information you need to grow with limited time and resources. Fortunately, using Shipwell as your TMS can provide visibility into new ways to run a business.

Greater visibility into your data helps uncover hidden or new freight hauling opportunities. Shipwell can help analyze that data and offer tools to automate your processes.