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Proteus

Thesis project - F(hybrid) 2022, SVA interaction design

This clip is recorded from the thesis festival at SVA Theater on May 18, 2022. f(HYBRID), the 2022 MFA Interaction Design Thesis Festival at the School of Visual Arts, celebrates work from interaction design graduates who declare their thesis explorations in a public forum.

A special note of thanks to Vineet Gupta, my thesis adviser and Aishwarya Mor for his supply chain operations expertise

Proteus is an AI-SaaS platform for multi-enterprise supply chain networks* that enables visibility and actionable insights to help you spot issues/alerts at a bird's eye level. Deep dive into resolving these critical problems in real-time with our intelligent, collaborative workflow. Executives can take a step further to deliver the ultimate value chain by minimizing the carbon footprint through our KPI scorecards and supplier(s)/service diversification.

*Source - Gartner, MESCBN marketplace study 2021

My Role: Led the project from 0 to 1 (MVP design phase)

"Almost 80 percent of [surveyed supply-chain executives] said they need to improve and invest in digital planning to increase supply-chain visibility."

- Knut Alicke, McKinsey & Company Insights.

Supply-chain disruptions cost the average organization 45 percent of one year's profits over a decade. The recent unpredictabilities of the COVID-19 pandemic have led to soaring demand for agility and visibility to achieve operational excellence. Modern technologies like OMS, TMS, RMS, and ERP often operate in silos while focusing on discrete areas of the supply chain process. These existing systems have deprived executives of the big picture and their ability to see this process as a whole.

Ex: Supply chain process for a cotton t-shirt

Some common disruptions across this process

Primary Research Goal(s)

Understand users' pain points in their day-to-day operations/supply chain activities. Ask for examples wherever possible.

Learn how COVID has accelerated the need for a resilient & agile supply chain

2-4 participants

Secondary Research

Survey: Supply chain bottlenecks - https://ez8ucbluotc.typeform.com/to/SVFMblGc.

With rising inflation and supply chain disruptions, we want to identify solutions that can reduce the cost pressures businesses face and aspire to improve customer experience.

Min 20 participants

Research synthesis highlights issues in visibility, predictability, finances, management and tracking health across supplier/vendor, logistics/warehouse and manufacturing/quality control

Research synthesis highlights experience mismatch workflows/conflicts - issues in workflow management and technology/ data challenges

Mapping the product architecture

Low-fidelity wireframe to map the structure visually

Incoming orders: Predicted issues along the journey, supply chain health score, order details, supplier score

Active orders: sample list of supply chain issues, scoring, order details, supplier score, map view and KPI modules

Active orders: Individual order module - scoring and issues breakdown

Individual order view

Issue resolution panel: AI/ML actively recommends the best options

Supplier database and profile

Basic supplier management capability

Proteus as a control tower adds a layer of visibility, intelligence over the current supply chain process to optimize it

Final design

Incoming Orders

• Executives can map the entire supply chain and optimize it before the supplier accepts the order

• The control tower panel provides a high-level summary of issues by critical, important and moderate

Active Orders

• Map-based view for disruption monitoring and KPI scorecard for business

• Sub-process visibility through individual orders and active issues mapped in the journey

Order history

• Shows the final status of each order and issues resolved

• Highlights the cost/time saved by resolving the issues

Supplier info

List of suppliers by industry and individual supplier profile

Manage supplier profile, add/edit documents

Individual order journey

Order details and issues along its journey

Issue details with AI/ML recommendations to resolve it

Key learnings and takeaways

Unifying data from disparate systems would be a challenge. Understanding, extracting and transforming data from disparate systems into a unified centre. ML models recommend actions that can mitigate risks.

Built-in collaboration tools to agree and implement a decision. Creating an internal system/approval process to mitigate losses caused by poor communication and implement decisions faster. Teams share notes on risk information.

Supplier/service diversification and demand planning. Supplier/Service diversification strategy serves as a form of insurance for the supply chain. Demand planning helps to avoid excess inventory costs and waste.


Next Project

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