Logistics Decision-Making Backed by Data Science: 4 Keys to Success

By: Matt Harding, Senior Vice President, Data Science, Transplace

During a time of significant supply chain disruptions, logistics leaders rely on data to make informed business decisions. Advancements in AI and machine learning allow process automation and petabytes of information to be inspected and interpreted with incredible speed and accuracy.

However, supply chain decision-makers don't have the time or resources to plow through mountains of data, they need results. They need real-time visibility into their transportation networks, risk prediction analytics, forecasting, and easily accessible reports. 

Leaders in logistics are investing in data science disciplines to make smarter decisions and accelerate business goals. Here are four steps to harness the power of data to propel logistics success.

1. Assess KPIs and data needs in the context of industry best practices

Due to an abundance of data available, the challenge is not what to measure, but what to ignore. 

For example, Transplace's account managers, engineers, operations and customer support teams manage over 150 daily key performance indicators (KPIs) that measure and analyze transportation metrics across many distinct industry sectors. 

In addition to highly varied measurements across companies, shippers within the same industries may also have cost and service objectives that can vary significantly. Understanding how companies approach change and continuous improvement in the context of their industry and individual business strategy is the first step in aligning analytical capabilities.  

1. Deploy transportation management technology with data assets in mind 

Launching new transportation technology takes tremendous effort across the organization. New processes, system architecture and integrations must be developed, tested and deployed rapidly. With the enormous amount of data created during system upgrades, logistics leaders need to consider how future process changes and pre-go live decisions will support or hinder data requirements into the future.  

As new systems are deployed, consider these points to maximize data and analytics:

• Transportation providers must be able to deliver accurate input including reason codes, and check call information – making training, compliance audits and corrections key
• Internal departments and external logistics partners must be aligned to how KPIs are defined, developed and managed to gain actionable insights 
• Pre-deployment baselines and KPIs must be aligned and are key to capturing success and targeting potential opportunities for improvement 

1. Measure the network

To maintain progress after transitioning to new logistics systems and processes, supply chain leaders must stay focused on continuous improvement. TMS systems provide a wealth of data supporting root cause analysis and issues resolution.

Shippers frequently turn to the Transplace TMS for answers to platform-level data and analytics, including:

• Which carrier are most compliant with automated check calls, accurate reason codes and timeliness?
• What is the level of route guide compliance and tender rejections for committed and uncommitted volumes?
• Are on-time issues tied to a particular provider, location or known reason?
• What are the specific drivers of spot rate premiums and overall inflationary impacts?

• Are current cost pressures related to other factors besides the carrier base, including pick-up or delivery practices, or volume spikes? 
• Are there better cost or service options in the marketplace?

A continuous focus on KPIs is necessary for adapting and adjusting network designs to add the highest value to customers and stakeholders. Enabling this intelligence over hundreds of shipper networks provides a platform to assess and improve, which brings us to the final and most important step.

1. Measure the market

Organizations that focus solely on their own transportation networks' budget targets and internal performance measures may be missing important data about market forces that are impacting performance goals. 

It's important to monitor market-based cost and service measurements to prevent over-reaching when conditions warrant more caution. Measuring cost inflation and on-time performance is important, but when measuring against the backdrop of the market, shippers will understand if the issue is a result of the overall state of capacity. 

Market data can also help align finance and company executives to the realities of logistics constraints far beyond the four walls of an organization. 

Shippers are better prepared for disruptions and market fluctuations if they strengthen partnerships with logistics solutions providers investing in data scientists and leading-edge technology. With ongoing turbulence across the supply chain and around the world, logistics leaders who take advantage of deep data insights and advanced predictive analytics will improve decision-making and drive success.

To learn how you can incorporate data-driven decision making into your business, connect with a Transplace expert here: https://www.transplace.com/contact/connect-with-an-expert/

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