How Do You Turn Supply Chain Data Into Actionable Information?

You’re committed to rolling out an analytics platform across your supply chain and you have tons of data. So how do you turn that data into actionable information?

There is a continuum in terms of the presentation of data that allows for continuous sophistication in understanding and interpreting data. There are many ways to view data, but those that are particularly useful in supply chain analytics are reporting, score carding, dashboarding and benchmarking. Once these are embedded, deeper, more granular data analysis can be performed with the power of advanced analytics.

Reporting and Score carding

The simplest form of looking at data is the all-too-familiar reporting. Back in the day, reporting consisted of numbers printed out on green bar paper, but today’s analytical reports are far more detailed and dynamic than in the past. For instance, a modern report for a manufacturer might display all the data about transportation providers as usable information, in a scorecard format. Factors such as on-time delivery, freight cost per unit shipped, and transit time are assigned metrics and weighted averages to help users determine how well carriers are performing overall.


Operations managers and executives who want a quick, daily overview of what is happening in their supply chain use dashboards to provide information in near real time to help users understand what is happening within their network. This supports them to make proactive decisions to remedy problems as they occur. Where reporting is really like looking in the rear-view mirror, dashboards are used to see what’s going on now, and make it easier for users to identify trends and exceptions, and to intervene before something goes wrong.

Dashboards can be implemented by companies to track all their real-time data and provide detailed reports of information such as claims as a percent of freight cost, space utilization, fuel efficiency, or vehicle time utilization. Essentially, the dashboard determines whether a transportation system is effective. Significant cost savings can occur when KPIs are monitored and the data is accessible in a format that allows users to make informed decisions. The biggest advantage of using dashboards to present data is the time-saving factor – dashboards give companies the advantage of allowing users to make decisions without having to wait for someone to pull and send reports.


An analytics platform for the supply chain also allows for benchmarking. Comparing data on factors such as freight rates and on-time delivery percentages against peers allows companies to gain a more complete picture of their performance in the marketplace. Take freight rates, for example. Rates have fluctuated with the disrupted economy, so your job is really to assess whether a deal offered by a vendor is good or not. By benchmarking carriers against each other, you can easily see who is offering you the best deal. Consistently monitoring and making informed decisions based on data means you are fully leveraging your analytics platform.

Advanced Analytics

As you become more mature in your supply chain analytics adoption, you will be able to apply predictive and prescriptive analytics to find patterns in historical data that yield insights into future risks and opportunities in your supply chain and transportation networks. This predictive analysis capability uses real-time, data-driven insights to speed up decision-making and help create an optimized and responsive supply chain.

So as you think about rolling out an analytics platform, think in terms of the applications, not the data. Think about what reports are important and how scorecards could improve your visibility into data. Develop dashboards to give you a look ahead and use scorecards and benchmarking to make sure that you are getting the best deal from your vendors and suppliers. And work towards using advanced analytics to focus on improving your forecasting and finding trends and patterns in your data to determine, and plan for, what might happen in the future.

Take a moment to read this real-world example of how a Logility customer solved complex supply chain challenges with analytics and collaboration.