Simulations provide a method of digitally modelling a scenario that has or could happen in the real world.
A simulations takes a range of inputs from the customers existing supply chain network, such as historical demands, providers/accounts and Fulfilment locations. These actual network inputs can be taken as a standard input or blended with a range of generated/hypothetical inputs, such as forecast demands or alternative fulfilment locations.
Using this information it allows us to simulate a certain scenario that the customer wants to model, and gives an output that can be analysed to help inform decision making around supply chain network set-up & configuration.
There are three core types of simulations; Optimised, Procurement & Custom. Each of these broad simulations are made up of multiple simulations or scenarios that can be compared and analysed to find the most optimal supply chain and logistics design configuration.
- Optimised - This simulation type contains two simulations: Forecast & Optimised
- Forecast - This simulation takes historical demands inferred from historical shipments in the 7bridges platform and uses the customers existing live rate cards to fulfil the these demands. The simulations engine then creates a demand forecast using the historical shipment data and then, learning the shipping SOPs from the historical shipments, is forced to fulfil these selected demands using the same provider & service that the customer is predicted to have implemented if there is no change in behaviour or operating procedure. This helps model what the customer ‘should’ have been charged if the model is applied to historical data and it also helps forecast what the customer will be charged if they change nothing. This acts as the basis for savings an impact calculations for other scenarios. The key 7bridges differentiator here is that the forecast is calculated using real-world historical data which means it's grounded in fact and doesn't require definition or design by a user. This is both faster and leads to a more accurate forecast to which other scenarios can be compared.
- Optimised - This simulation takes the same data used in ‘Forecast’ and frees the simulation engine to fulfil the demands in the most optimal way possible, using any existing provider available in the customers supply chain network. This should help identify opportunities for the customer to make performance and cost improvements, within the customers network, utilising the existing fulfilment locations, providers and services available to them.
- Procurement - These types of simulations focus on analysing provider responses when responding to an RFI for pricing. The simulations engine will use the RFI data and provider responses to model the most optimal way to procure new providers and utilise their services across the customers network. This analysis will include negotiation insights, costs and performance analysis, etc.
- Forecast - as above to act as the baseline
- Sole provider - we calculate the performance of each individual logistics provider as a the sole fulfilment provider for the entire network. This gives an indication of strength of each provider relative to one another.
- Optimal - this simulation finds the optimal provider, mode, service, shipping location for each demand within the constraints of the simulation to find the most optimal mix of providers for the network in question.
- Custom - The 7bridges technology can be leveraged in multiple ways to handle more complex optimisation problems and networks. 7bridges has multiple models it can leverage or stitch together to handle a wide range of scenarios across multi-modal first, middle and last mile logistics and include stock optimisation as well as purchase, transfer and sales order optimisation. In these instances custom data pipelines are defined and simulation outputs can be bespoked or sent via API to ERPs or pushed to data warehouses depending on how the customer wishes to consume the outputs. A list of some example uses cases of how this technology can be leveraged can be found here.