Metal Trading

Design Process

Overview

This company was launched in 2017 to enable the metals industry with cloud-based technology solutions that significantly streamline business processes.

The company recognized that the industry was using legacy or inefficient ERP systems that created massive inefficiencies in the customer-facing quoting process.

Metal Networks realized that AI and machine learning would change the way we work with large volumes of data and transactions - a key challenge for a volume-intensive industry. So they developed the material industry's first AI search & and matching engine that translates product description nomenclatures (shorthand) for describing products and matches them with a Supplier's catalog, thereby significantly reducing data input and the time required to search for the right product by over 80%.

Metal Networks' vision is to enable the industrial B2B space with cloud-based, AI-driven technology solutions.

The mission is to enable metals distributors, service centers, mills, and traders with machine learning technology that removes the friction of buying and selling metals.

Role & Responsibilities

Product Designer
User Research, Interaction, Visual design, Prototyping & Testing

Project Team

UX Designer, Product Manager, React Native Developer, Backend Developer, QA, Scrum Master, Engineering Architect

Client

https://metalnetworks.ai/

Project Summary

Business Objective

Create a platform for metals distributors, service centers, mills, and traders that removes the friction of buying and selling metals.

Success Criteria

Create and validate prototypes with prospective users before implementing solution

Use Goals

Marketplace where metal distributors and buyers can connect in one place for buying materials.

Challenges

Understand the domain
Testing of application with stakeholders
Usability testing

Outcome

Successful beta release of the application for modules such as sample tracking, Toxicology, and Covid Testing.

The Problem

Distributors, including service centers, often have situations when the items requested by their customers are either not available in stock or not carried by them. In such situations, to avoid losing the customer, distributors typically try to procure the missing items from fellow distributors. Delays may result in the customer placing the order on a competitor. Speed in locating the right supplier and closing the transaction is of the essence.

Currently, the distributors’ sales or purchasing personnel reach out to their limited circle of contacts at other distributors or suppliers to find someone who can fill the buyout requirement at the earliest. If successful, they can then send a quote to their customer for their complete requirement. The current process can significantly distract the distributor’s personnel, besides the delays and uncertainty of finding the required item.

User Research

Stakeholder workshop

A 5-day workshop was conducted with the DUII stakeholders, Product Manager, and Engineering Architect. My research encompassed -

• Understand overview of the Laboratory ecosystem and high-level

workflow from collecting samples to dispatching test results.
• Roles and responsibilities of members at each level
• Day to Day tasks that need to be accomplished
• Product Roadmap

Fig: Screenshot of product ecosystem with various process visualised using Miro (Digital collaboration tool) as one of the outcome of the workshop

Competitor Analysis

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Fig: Screenshot of Competitor Analysis using Miro

Work Flows

Based on operational efficiency and interviews, workflows identified and validated with stakeholders. It helped to define information architecture.

Fig: Screenshot of Workflows using Miro

Task Flows

Based on operational efficiency and interviews, workflows identified and validated with stakeholders. It helped to define information architecture.

Fig: Screenshot of different taskflows discussed and visualised using Miro

Information Architecture

Information Architecture helped to detail each workflow into features. After identifying these features, the product roadmap is refined with additional information coming from user interviews, insights and workflows

Fig: Screenshot of Information Architecture using Miro

Concepts

I started creating low-fi concepts for primary use cases. After having a go-ahead from the Product Manager, developers, and Stakeholders on the mockups, we began to conduct usability tests with the low-fidelity mockups. Once we had confidence in the design, we began digitalizing designs.