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JP Doggett

Perfect Delivery - multichannel order orchestration, incorporating 3rd party data & scenario planning
SupplyChainINTENT Virtual Boardroom Discussion 03/03/21
With Expert Input from Vikram Singla, Oracle

Multichannel / D2C order orchestration

  • Drivers for multi-channel / D2C models
    • Investments in this area are often easiest to justify in the context of customer experience and the data/insight that direct contact brings, particularly if channel partners are providing limited data on end customers
    • Customisation and personalisation can both help establish a D2C offering but also add a layer of complexity
    • Lower hurdles for offering exclusives or testing NPDs that traditional channel partners may be reluctant to accommodate
    • Brand loyalty can be built in different ways, often based on the consumer's desired to learn how best to use the products and get the most out them
  • Challenges
    • Order orchestration: how to fulfil across multiple channels?
      • Ideally, a single stock but this is often difficult to achieve in practice, especially where they are serving multiple markets with different compliance requirements
      • From a data perspective, putting a single 'order management' layer in place which handles order-to-cash irrespective of where the orders are coming from or how the logistics are executed

Order Management Cloud.png


  • Investment required
    • D2C customers expect a higher level of service - how is that possible without major investment? For example, personalisation for a beverage D2C product needs specialist machines in each fulfilment centre
    • Is D2C here to stay or is it a by-product of the pandemic such that customer behaviour reverts as normality returns?
    • Cross-channel pricing to encourage the desired customer behaviours and mitigating against 'gaming' where, for example, a B2B customer may demand an online price
    • Challenges for 3PLs to adapt to D2C as they're used to dealing with full truckloads of commoditised goods, not multiple shipments of customised products, especially when compliance checks must be made at the point of delivery

Incorporating external data, inc. from 3PLs, and leveraging ML & AI

  • 3rd party data: how are emerging technologies enabling data integration?
    • AI is increasingly baked into point solutions so a key consideration should be on the interoperability of systems or ecosystems of solutions, not dissimilar to app marketplaces on a single platform
    • Additional challenges when delivery is direct from a stockholder who may not want to reveal other deliveries so some form of visibility that alerts ETAs without disclosing location data would be useful
  • Supply disruption: how best to get early warning of port closures or other adverse events?
    • IoT is increasingly being used to track flow data. For example, Nestlé have IoT fleet monitoring on top of TMS

Scenario planning

  • Managing demand spikes and skews across categories and channels, including retailers' reluctance to commit to orders
    • It's helpful to take a working capital perspective as part of a routine S&OP/IBP process to better manage these trade-offs
  • Supply volatility, exacerbated  by Brexit, magnifies the need for greater visibility to highlight risks to OTIF

Maintenance & service

  • On the receiving end, how to get better visibility on when spare parts are going to arrive, especially in challenging locations?

See also previous discussion summary:

Case studies and technology applications covered are available in the attached pdf with additional materials here:


https://www.oracle.com/product-navigator/?product=supply chain %26 manufacturing (scm):logistics

If you are interested in any of these areas and would like to discuss them further with your counterparts or subject matter experts, we’re very happy to put you in touch.


210303 Perfect Delivery OM Oracle Intent roundtable discussion v2.pdf

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