Leveraging Big Data in Your Organization

Robert Daymon, senior vice president of operations at Transplace, offers these tips to get the most out of big data for your supply chain.

1. Gather the right information.

Understand what data you need to capture, track, and act upon. Having timely, accurate, and complete data can create a holistic view of operations and improve collaboration. And, it's critical to organize that data.

2. Set goals and map out a plan.

Data is not worth collecting without a clear plan. It's important to establish key performance indicators, implement specific goals, and identify what you need to accomplish.

3. Trust your instincts.

Pair non-quantifiable information, such as what you may be hearing throughout the industry and your gut instincts, with what you see in the data.

4. Make raw data actionable.

Using business intelligence tools and reporting can help make reacting to operational concerns more actionable. What makes data truly valuable is how you use it to drive meaningful change and enhance an agile supply chain.

5. Plan in advance and forecast.

Preparing for the future is a must for your supply chain operations. Using data for advanced planning can help anticipate what will occur in 12 to 18 months and beyond. Conducting what-if scenarios can help mitigate risk when unplanned disruptions arise.

6. Use TMS data to improve the flow of materials.

A transportation management system (TMS) can track meaningful data to make improvements. A TMS can help anticipate future shipping patterns, secure much-needed capacity, and make sure you have the right amount of inventory.

7. Shape your own demand.

During the procurement and bidding process, advanced analytics can help mold a network. The ability to forecast these activities can help lower carrier costs. And, if handled correctly, data can help manage variations.

8. Increase end-to-end visibility.

An efficient supply chain must track and trace the end-to-end flow of goods. Data from a TMS can help with continuous move routing or tracking the location of each shipment. And, if unexpected events occur during a multi-stop delivery, this information can identify real-time load locations and enable route adjustment.

9. Enhance customer service.

Data analysis allows for transparency with customers - helping them gain insight into any cost or service fluctuations. And, using predictive analytics to automate processes allows for improved appointment setting and can help track product deliveries, ensuring the end customer receives the final product on time, every time.

10. Compare and adjust.

Use the data to compare final shipping results against initial goals and key performance indicators. Utilizing the expertise of a third-party logistics partner can help shippers glean deeper insights into their supply chain and optimize transportation strategies to increase efficiency, reduce costs, enhance customer service, and improve carrier relationships.

(Source: Inboundlogistics)