EDSC (Efficient Digital Supply Chain)
Reimagining the supply chain system for the largest QSR(Quick Service Restaurant) chain in the world.
Problem Statement
Envision an EDSC (Efficient Digital Supply Chain) platform to establish trust, responsiveness, and user-centricity for the client’s supply chain network ensuring–Hyper-personalization for each persona keeping in mind their roles specific information and data analysis needs.
Project Makeup
Role – UX Researcher, UX Designer
Stakeholders - IBM IX, McDonald's Retail
Timeline – 2 months
Handling the supply chain network for the largest QSR chains in the world could be a nightmare if it does not perform like a well-oiled machine. In the current system there were problems that crept in from time to time which included non-compliance issues and exceptions. This in turn brought down the efficiency quite considerably.
Our job was to reimagine the system to make it more efficient and future looking, improving transparency and visibility in operations and data, to the stakeholders that are part of the ecosystem.
My Contributions...
Our team in IBm was approached to design the platform that showcase the strength of IBM solutioning suit that included ML(machine Learning) working in tandem with IOT(Internet Of Things), that will aid in handling the world's largest supply chain networks.
My role in this project encompassed.
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Mapping the requirements, understand the current system and its flaws, define the problem statements around them and envision the solution, balancing the user-experience as well as the business objectives.
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Understanding and Unpacking the Big data that flows in the system at any point in time and break it up into clusters for easy system handling and optimised user interaction using design tools and strategies.
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Developing WFs that showcase the story.
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Work in tandem with the Dev team to identify the strengths and constrains of the solution package that we were pitching, and finally using the information to convert that to simplified task flow and easy to navigate UI for the end user.
Understanding the Users
"You always design for the USERS."
We looked into 4 kind of users.
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Farmers/Suppliers
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Distribution Chain manager
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Quality Analysis Team
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Store/Restaurant managers
Their Pain points...
"Lacks visibility around changes in demand further down the supply chain"
Maria, Fresh Meats
"Early detection of problems are not possible now."
QA Team
"Inadequate lead time for restaurants to be notified of replacement stock deliveries."
Rob, DC Manager
"No reliable way to know the status of the order placed and its ETAs."
Sally, Store Manager
"No clear visibility on stock needing recovery from a problem"
Rob, DC Manager
"By the time we take action on spoilt goods its already too late."
Sally, Store Manager
Our Solution
The idea was to create an interactive instance of a solution that demonstrates how data is ingested, processed, stored, and modelled for use in consumption layer by various personas (supplier, distributor, McDonald’s corporate, etc.) via dashboards or other data products. Efficient Digital Supply Chain* (EDSC) will introduce near real-time, serialized data and will delineate clearly between transactional capabilities or business intelligence capabilities.
This is achieved via Internet of Things (IoT), tracking of product cases through critical tracking events (CTEs — such as shipment, receipt, and usage) throughout our supply chain.
1. Macro 360 degree Network View
The macro ecosystem view maps all the key network entities–suppliers, distribution centres
and Client's restaurants across the US, to enable a holistic view as well as the ability to
query for specific questions using conversational analytics.
2. Predictive & Contextual Anomaly Detection
Contextual exceptions in existing data and predicting anomalies based on the historical trends along with recommended solutions will enable users to act with confidence and speed.
3. Drill Downs For Deeper Insights
Intuitive drill-downs at all levels in the network will enable users to instantly shift between
overview and granular view of the dataset.
4. Advanced Data Analysis
Data analysis doesn’t have to be hard and overwhelming! Using smart tables, the users
will be able to customise and tailor the complex datasets to suit their analysis needs, gain clarity and maximise the data’s potential without having to jump between other data tools.
5. Automated Next Best Actions for Known Problems
Existing business rules combined with machine learning will activate automated best action to help each persona with process orchestration. For new business situations, the system will learn the recurring patterns and add to the list of rules to inform the future best actions.
6. Recommended Action for Critical Decisions
Critical decisions that need human interventions will be notified to the users in the order of priority they need to be addressed in without overwhelming them thereby simplifying their
everyday workflows.
Reminance of Validation Sessions with the Stakeholders...
User Flows...
User Flows for Cold Chain Compliance Issue Detection and Resolution within our EDSC system...
DC Manager
QA Team
Store Manager
Farmer/Supplier
Scenario Mapping...
Scenario 1:
Cold Chain Compliance Issue Detection and Resolution:
Distribution Center - Needs to know in advance when there are temperature variance that could affect product quality before it arrives at the DC so that measures can be taken to get replacement product to the store ASAP
EDSC Role - Provide data during transport specific to temperature of the transport vehicle and alert the DC ahead of time anytime there is a temperature issue that take the product out of cold chain compliance
EDSC will provide distribution centers with more information on a product’s cold chain compliance, including its history and risks to its status. This will allow the system to react more quickly to violations and gives the system precious time to develop a strategy.
Above and Beyond - Is there a way for us to save the product by providing real time data so quickly that any issue that might affect temperature of the product (monitored by the EDSC and IOT) could be addressed in a way that the product is saved and waste is reduced? Sending a replacement vehicle, redirecting to a closer DC, redirecting to a closer store
Scenario 2:
QA Understanding Severity of Issues
McD Quality Assurance -
McDonald’s Quality Assurance is responsible for creating product standards, ensuring customers have the best possible experience. For example, a QA manager might stipulate that a given product needs to remain below 30 degrees Fahrenheit during its travel through the supply chain. QA managers also contribute to decisions to quarantine or refuse products in the supply chain.
EDSC Role - In the future, EDSC will be able to automatically log all violations, regardless of size. To avoid creating too much noise in the system, it will also have the capability to only alert the QA team of violations of a certain, predetermined degree. Yet this data will make it possible to trace back any more significant product issues that may later occur. The system will learn about how other nodes can affect the final restaurant quality of a product.
EDSC will monitor and record the temperature of products as they move throughout the supply chain, logging instances of violations. It will then alert relevant partners in the supply chain, including alerting the quality assurance team to those that are severe.
Above and Beyond - Recommend the next best actions to solve violations faster and to have the easiest way to filter views and access violation information so that Quality Assurance can be as efficient as possible.
Scenario 3:
DC Manager Staying Up-To-Date on Stock Recovery Process
Distribution Manager - Needs to know when a stock recovery occurs because replacement products must get to restaurants as quickly as possible to ensure customers get what they need.
EDSC Role - When the quality team identifies a critical risk in the system and decides to go forward with stock recovery, the EDSC utilizes case-enabled IoT data to find products that match the affected product throughout the system and generate alerts to affected partners. Additional product is scheduled to be shipped out to affected restaurants.Relevant stakeholders can monitor the status of the stock recovery via EDSC, allowing restaurants time to prepare for the extra delivery of product.
EDSC will help us pinpoint the location of the affected products within minutes, eliminating the risk that these products move further into the supply chain or into customer hands.
Above and Beyond - IBMs solution could enable the store to know where the replacement product is, the exact product details to arrive, and the precise time that the replacement will get there. Kinda like how a consumer and the store know details for curbside pick-up.
Data Leading the Story..
Low fidility WF's
showcasing the systems
capabilties and features.
(Click on the play button to view the video)
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Flinko Final Creatives
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Additional Designs