TMS users in transportation logistics organizations are sitting atop a gold mine of actionable data captured by their TMS solutions. The shrewd operators are leveraging these data to support predictive analyses with the goal of achieving more accurate planning and execution of logistics as product moves through their supply chain. Here are four ways smart TMS users can harness the power of their data for predictive analytics.
Avoiding the Pain of Seasonal “Swings” | Peaks and valleys in shipping volume are nothing new. However, being prepared well in advance leveraging the historical data captured in your TMS is an innovation with significant benefits to high volume shippers. Patterns revealed by the analysis of historical data are useful in lining up carrier capacity ahead of time as well as determining optimal timing for allocation to secondary and tertiary carriers. Predictive capabilities help shippers protect access to necessary support during critical seasonal times.
Spot Market Timing | Just because all shippers are inevitably exposed to the spot market for critical expedites or during times of tight capacity doesn’t mean they have to “over a barrel” when it comes to paying the premiums associated with spot movements. Leveraging predictive analytics in the TMS a shipper can use historic tendering metrics and spot quote reporting data to identify areas where contracted rates can be bolstered and avoid budget-busting over-utilization of the spot market. Think of it as hedging bets by preemptively establishing secondary rates with primary carriers – based on accurate predictions of seasonal capacity constraints.
Private Fleet Optimization | The data captured in TMS can be used to make informed decisions about when and where to situate equipment and drivers to ensure the most efficient use and utilization of costly resources. Data reveals frequency of use and availability/location of assets over time across the shipper’s network is analyzed to help achieve the “right size” of both equipment and staffing levels. It can be used to justify decisions surrounding whether to engage in short-term vs. long-term equipment leases; whether to field a “pop-up” fleet vs. longer term equipment deployments and even balancing the use of contingent workforce drivers or full time employees.
Appointment Scheduling & Dwell Times and Pickup/Delivery Locations | Dynamic premise time reporting looks at historical arrival and departure events stored in the TMS and enables calculation of the average premise time for trucks on a location-specific basis./ This data can be analyzed and leveraged to help reduce dwell times and improve DC throughput. Where data patterns reveal seasonal bottlenecks or other factors that suggest future delays, a shipper can engage preemptive conversations with consignees to address these issues.