The the client is a global FMCG brand which has established itself as a leader in the sales of various food and drink products. It operates out of more than 80 countries. In India, the client has 10+ warehouses situated across various cities.
Time intensive, manual, and sub-optimal resource scheduling in the pre-Dista days
Each of the warehouses in India caters to multiple Distribution Centers (DCs) and large retailers within the cities. Earlier, the operations team manually planned each delivery run to the DCs.
The long, manual process involved scheduling a huge fleet of vehicles and manpower based on the pin codes of the DCs. It was a complex and time-intensive activity that had to consider a variety of constraints like – vehicle type, opening and closing time of the DCs, resource availability, loading and unloading times, bay constraints among others.
Additionally, the vehicles were required to follow fixed routes that could not be changed or adjusted based on changing circumstances and emergencies. Manual scheduling and fixed routes resulted in limiting the number of deliveries in each timeframe.
Remodeling and revamping the scheduling process with Dista’s location intelligence
The the client wanted to automate the manual efforts in daily scheduling of deliveries to their Distribution Centers and orchestrated this on Persistent’s location intelligence platform – Dista. Dista platform is built on Google Cloud products like – App Engine, BigQuery, Cloud Datastore, Google Maps and more. Among the 9 products built on the Dista platform, Dista Schedule was deployed for the customer to automate and simplify their scheduling process.
After a thorough study of the drawbacks of the previously used manual process, we deployed automated and intelligent scheduling of deliveries to the client’s warehouses and distribution centers.
To begin with, a master file with all the details like – SKU, quantity, volumes of the shipment to each DC was uploaded to the platform and trial field runs were scheduled to check the effectiveness of the algorithm. The algorithm scheduled based on more than 30 practical constraints like – variable unloading time for each customer, no-entry time at various locations, traffic conditions, and more. Gradually, the results of the field runs were fed phase by phase into the algorithms as learnings. These learnings facilitated seamless scheduling of the field runs.
Furthering operational efficiency with highly visible results
The new way of scheduling needed an organization-wide change management for the operations team and that required extensive coordination with the warehouses and the Distribution Centers.
As a result of which, the client not just achieved ease in planning, they also saw the Vehicle Fill Ratio increase to 90% (from the previously noted 70%) and almost 20% reduction in the number of vehicles.
Currently, 7 warehouses have been boarded onto Dista’s scheduling platform. Predicting or changing the routes dynamically based on practical constraints and subsequently reducing the number of trips made to the DCs and their costs are the key watchpoints to optimize further with other products on the Dista platform.
