Through our outreach channel of the Supply Chain Matters blog, The Ferrari Consulting and Research Group announces the release of a part two June 2018 Research Advisory Report: Orchestrating Digitally Enabled Response Network Capabilities in Other Industry Settings- Case Study Examples.

Purpose and Overview

There is little doubt that the inescapable movement toward online is having compelling implications on B2B, B2C and B2B-to-B2C customer fulfillment expectations and required experiences. Competing in the new retail economy requires closing the gaps between sales, marketing, supplier, and supply chain teams in responding to actual B2B and B2C required customer experiences and expected service levels.  How such experiences are supported, managed, and synchronized leads to what we have termed as Digitally Enabled Response Networks. Digital Networks

The objective as stated in our previously published first advisory was to put into context the process, the people and the information technology implications needed to achieve the full aspects of digitally enabled response networks.  We addressed specific implications for end-to-end supply chain and integrated business planning information and decision-making needs. We further provided a case study example of how an innovative telecommunications network and retail services provider has embarked on the initial foundational business planning and customer fulfillment capabilities needed for such capabilities.

In the second research advisory in this series, we explore three other diverse industry examples of leading-edge organizations building the foundations of digitally responsive customer fulfillment capabilities, each with unique market needs.

They include a case study of more responsive healthcare involving one of the world’s largest healthcare organizations, the United Kingdom’s National Health Service (NHS), and specifically NHS Blood and Transplant Services (NHSBT). This unit has a somewhat unique supply network and customer fulfillment model in that on average, 35,000 units of whole blood are collected each week through a network of fixed sites and mobile blood collection teams. The blood is then processed at one of five regional manufacturing centers and distributed via a network of 15 “issue centers” to over 200 NHS managed hospitals.

We highlight a case study involving a well-known, innovative, online home goods retailer, Wayfair.com, often described as the largest and fastest online only U.S. retailers. This online provider has experienced 50 percent year-on-year sales growth and has begun efforts to retail products globally. The online provider soon began to understand that it was fast out-growing its planning and response management process capabilities. The retailer additionally outlined a longer-term goal for more automation of the overall planning and customer fulfillment process through the application of machine-learning technology applied to managing daily and weekly shipping volumes.

The final case study analysis involves automated coffee beverage demand sensing, specifically Costa Express, the U.K.’s largest and fastest growing coffee shop brand. Its business model provides airports, railway stations, hospitals, and universities with a business presence as: “Irresistible coffee on the go” with Costa Express self-serve coffee kiosks located across the United Kingdom, Europe, Asia, and the Middle East. This fulfillment channel allows partners and franchisees to deliver a customer experience serving a product described as the perfect cup of coffee, and assurances that Costa Coffee bars have the same authenticity found in a Costa coffee shop. This services provider unmanned coffee bars leverage integrated telemetry that provides real-time reporting network of individual machine performance and drink sales, yet such data was not being totally leveraged for automated supply network replenishment needs.

Common Learning

Across all three of these multi-industry examples of orchestrating more digitally-enabled response network capabilities, some discernable common learning themes came to the surface. They include, among others:

  • A need for moving towards a service-level led supply network fulfillment support capabilities.
  • A compelling strong vision of what dynamic customer response should be among customer fulfillment channels.
  • A detailed understanding of supply, demand, and customer fulfillment network models both currently and in future needs.
  • Selection of supporting technology that can address item-level planning granularity, and scale to the data and information volumes required for supporting a more dynamic responsive fulfillment network.

 

Implications and Takeaways

Our interviews with early adopter businesses and technology enablers continue to reflect added reinforcement that on-demand services and consequent expected service levels have quickly become table stakes in the new gig economy. The online customer expects fulfillment expectations to be seamlessly met across multiple retail channels, either online, or combined online and physical retail presence. It requires a purview that extends beyond just supply chain planning or supply chain execution to dimensions of network response management that literally integrate multi-enterprise or B2B planning and execution capabilities towards synchronized action and response. It requires retailers and service providers to be able to continually monitor point-of-sales product demand, and dynamically align the response network to changing customer preferences or inventory needs at the lowest possible cost.

Today, many retailers and services providers are hamstrung with marginal product demand forecasting, limited planning and multi-channel inventory management capabilities required in an omni-channel fulfillment process. They need to raise the bar on anticipating customer needs with the most-timely response to such needs.

In other words, the status quo of traditional retail supply chain customer fulfillment is no longer an option for industry competitiveness or revenue growth.

 

Obtaining Your Copy

This follow-on Research Advisory is being provided as a thought leadership resource in conjunction with the support of Supply Chain Matters sponsor ToolsGroup.

The report can be downloaded on a complimentary basis from this dedicated web link. Some basic user registration data will be requested.

 

Bob Ferrari

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