Implementing a Dispatch Planning Tool for Improved Forecasting
The Situation
A U.S.-based transportation and logistics solutions provider did not have visibility into their recurring demand. Because of this, they were procuring all the necessary transportation resources on an ad-hoc basis and at short notice, leading to higher costs and a significant time investment from the planning team. Merilytics (an Accordion Company) partnered with the client to analyze the demand patterns for each lane and build a demand planning tool to provide the forward-looking baseline demand.
Services
Reporting & Analytics
The Execution
- Analyzed the historical lane-day level dispatch volumes and benchmarked the lanes based on their volatility (Very Low to Very High).
- Calculated a custom percentile for each volatility bucket across each day of the week based on the allowed over-forecast limit for the bucket.
- Captured the seasonality (weekly, yearly) of demand in each lane and arrived at the baseline demand for each lane day.
- Built a time-series model to forecast the minimum baseline demand for each lane based on the historical dispatch volumes.
- Integrated the option to view grouped or individual lanes based on a destination grouping provided by the client, yielding improved forecasts for grouped lanes where individual lanes did not have sufficient dispatch activity for reliable planning.
- Developed and delivered a dispatch planning model using the time series forecast when the volatility method predicted zero demand.
The Results
As a result of the implemented dispatch planning tool, the client was able to identify and plan for the baseline demand across lanes in pursuit of lowering costs. The tool covers ~55% of the total dispatch volume and could potentially reduce shipping costs by ~10%. What’s more, the client’s planning team now has free hours to focus their efforts on the procurement of additional transportation assets required for the lanes with higher lane-day variability. Leveraging the new tool, the client was also able to identify terminals with sub-optimal performance in dispatch KPIs and take measures to improve operational efficiencies and optimize costs.