You’ve worked with the logistics teams for years to implement reporting and optimization tools for forward logistics.

To arrange for the transition to a circular economy, they’ve additional requests to administer collection and sorting processes.

What are the extra processes that we’d like to watch and optimize?

On this section, we’ll briefly cover several examples of process design requirements with the associated analytics solutions.

Descriptive Analytics: Product tracking and traceability

Due to regulations, you have to be certain that products are used and processed in probably the most sustainable way possible.

Subsequently, the logistic teams have to have the option to track and trace products throughout their lifecycle.

For forward logistics, products are tracked from the factory to the shop

• Master data databases will include (Stock Keeping Unit) SKU Number, product information (size, color, packaging)
• Production Systems can provide the batch number (useful if that you must call items), production date and factory location.
• Warehouse and Transportation Management can track the product along the logistics chain, from warehouse receiving to store delivery.

How will you support the tracking of returned items with advanced analytics?

For reverse logistics, the logistics request your support in monitoring the flow of “returned” products from the collection box to the sorting centre.

Different logistics systems which can be recording transactional data could be used as data sources to construct automated flow monitoring tools:

• Enterprise Ressource Planning (ERP) records the shopper returns at the shop with Store Location, SKU ID, Quantity, Collection Box ID and Collection Time.
• Transportation Management Systems records the pick-up of collection boxes, including store location, collection box ID and collection time.
• Warehouse Management Systems tracks the items from receipt to the top of the sorting process with the SKU ID, Collection Box, Receiving Time, End of Sorting Time, and Final Destination.

Business Intelligence methodologies using a central data warehouse can support the creation of harmonized tracking data sources that could be used for audits or reporting.

When you need more details on the right way to implement it, have a take a look at this text.

Now that you may have provided transparency to the operations, let’s concentrate on process optimization.

Prescriptive Analytics: Sorting Network Design

The logistic teams would love to design a network of sorting centres that minimizes the environmental impact of the reverse flow.

The optimal network may differ from the present one as that you must collect items after sales and reintroduce recycled materials into the chain.

They shared with you

• A listing of potential sorting locations with their capability (Units/Day)
• Forecasts of reverse flow volumes from the stores (Units/Day)

Query: Where should we place the sorting centers to attenuate costs and CO2 emissions?

This may remind you of the Supply Chain Network Optimization Problem for which that you must design a network of factories.

The market demand should be fulfilled by factories with limited capacities and different costs to provide and deliver goods.

Linear programming is used to pick out the appropriate factories that minimize the general costs while respecting a set of constraints.

For more details, have a take a look at this detailed example

How can we adapt this solution to the sorting network design problem?

This could be easily adapted to this recent problem

• Demand => Units Collected from the Stores (Units/Day).
• Factories Capability => Sorting Capability of every Centre (Units/Day).

You possibly can then select the optimal set of sorting locations depending on the target you may have

• Minimizing the overall costs?
  The algorithm will consider the transportation costs (from the stores to every sorting location) and the sorting costs of every centre.
• Minimize the CO2 emissions?
  The algorithm will attempt to minimize the gap from the shop to the chosen centres.

Now that you may have chosen the optimal set of sorting centres, you’ll be able to organize the reverse flow.

Prescriptive Analytics: Reverse Flow Optimization

The transportation team requests your support in designing a tool to allocate the appropriate sorting centre to every store.

Indeed, because the volumes and capacities evolve, you’d higher dynamically allocate a sorting centre to every store on a weekly or day by day basis.

Query: For every store i, which centre should sort the returned items to attenuate the transportation costs?

In a previous article, I tackled an identical problem: The Supply Planning Problem.

Several factories replenish distribution centres that store goods and deliver stores.

To reply this problem, we also use linear programming to

• Optimize upstream flows from the factories to the distribution centres
• Deliver each store from the appropriate warehouse

This solution could be used after slight adaptations

1. Define (or forecast) the volumes from the sorting centres to the ultimate recycling location
2. Define the capability of every sorting centre

You possibly can then follow the approach (and use the code) detailed in this text.

Now that we’ve got designed the network of sorting locations and developed a tool to optimize reverse flows, we are able to work on performance monitoring.