01. Overview

Honeywell Connected Enterprise (HCE), was developing a suite of SaaS solutions focused on Site Operations and Asset Performance Management. These solutions aim to improve facility safety, supply chain efficiency, and decision-making through predictive analytics, reducing downtime and optimizing resources.

Product page: https://www.honeywellforge.ai/us/en

Responsibilities

• Defined and executed an end-to-end research strategy using mixed-methods (qualitative interviews, journey mapping, and quantitative usability testing) and facilitated cross-functional workshops to converge stakeholder visions, and frame opportunities through systems thinking.

• Led the development of the design strategy, contributing to the creation of scalable information architecture, scenario mapping, and storyboards.

• Partnered closely with product managers, designers, and engineers across multiple product pillars, ensuring alignment on both the "right product" (problem-solution fit) and the "right way to build it" (feasibility, usability, scalability).

• Supported the iterative design process across low, mid, and high-fidelity prototypes, anchoring every decision in real user behavior and validated insights.

02. Problem

Distributed centers require dozens of independent systems to operate, which creates complexity, hinders, valuable reporting and analysis and makes remote management impossible. Without optimization leaders have to manage these facilities, and Silos and the possibility of strategic decision-making is limited, especially when they have to manage across portfolio of sites.

• Business challenge: Companies were shifting toward integrated solutions for monitoring the entire warehouse—focusing more on stock optimization, order fulfillment, and throughput than just machine health monitoring.

• User challenge: Users lacked access to real-time data, leading to slow decision-making, inefficiencies, and prolonged downtime. The system’s disconnected processes and poor visibility into asset performance hindered operational efficiency.

03. Approach: Discover —> Define —> Ideate —> Design —>Test —> Iterate —> Scale

Discover —> Define —> Ideate —> Design —> Test —> Iterate —> Scale

Personas

Experience Outcomes

Journey Mapping

The next phase of the workshop was for us to select a scenario that would help us draft the workflow for our Operations manager’s persona. I helped the product identify the slice of a user’s journey based on user need and business prioritization, which we converted into a storyboard that would help us visualize the solution could fit into our user’s life.

Storyboarding

04. Solution Explored: Discover —> Define —> Ideate —> Design + Test —> Iterate —> Scale

Mid-fidelity prototypes

By the end of two weeks, we had mid-fidelity concepts that we worked with the prodduct managers and developers to get the screen requirements and feasibility. Lot of the discussion during this phase was to understand what KPIs were available that we could add on the screen for MVP.

Mid-fidelity testing

Once we had the prototypes we created a study plan, recruiting, and moderated a live conversation via the UserTesting platform for concept testing. The goal was to get initial feedback on the designs before investing in high fidelity prototypes to test with customers.

• Identify any content that was confusing or unclear • Validate/Invalidate our assumptions about design patterns

05. Decision Making: Discover —> Define —> Ideate —> Design —> Test —> Iterate —> Scale

Information Architecture

After drafting storyboards and user requirements, the next phase was to think about the information architecture of the product. These features were going to be a part of a larger EPM product, so we had to think about the scalability of the product and potential workflows they could within the product. With my industry experience in supply chain products, we were able to create assumptions and hypothetical scenarios to create an inventory of features and set up a map of different navigations paths for different EPM product users. This exploration helped us look at the product from different levels of zoom.

06. Implementation: Discover —> Define —> Ideate —> Design + Test —> Iterate —> Scale

Hi-fidelity Designs

07. Measurement - Product impact

• 30–50% Improved Decision-Making Speed by Reducing Data Latency

• 25% Reduced Task Completion Time and User Frustration and Navigation Errors

• Stakeholder Alignment Led to a Unified Product Roadmap Across Two Distinct Business Units

• Accelerated Time-to-Validation with RITE (Rapid Iterative Testing)

08. What I learned - Personal growth & insights

The journey through the Honeywell Connected Enterprise project was not just a path towards creating a product; it was a deep dive into the complexities of user experience (UX) research, design synthesis, and stakeholder alignment.

• The first major hurdle was blending the distinct perspectives of two product owners. Through empathetic and in-depth interviews, a story emerged where their visions converged, leading to a unified product roadmap.

• The absence of direct user data could have been a roadblock. However, turning to SME insights, we crafted proto-personas, painting a vivid picture of our users that resonated with all stakeholders.

• The real essence of UX research unfolded as we pieced together the user journey. Lacking real user interaction, we relied on the narratives shared by SMEs, effectively capturing the user’s voice through a qualitative lens.

• With time as a pressing factor, rapid iterative testing (RITE) became our go-to strategy. This approach enabled us to weave in quick, yet impactful, feedback, ensuring the product remained user-centric within the limited timeframe.

• The project also brought forth the challenges of remote teamwork. Establishing robust communication channels and mastering digital collaboration tools like Miro, we not only overcame the physical distance but also strengthened our team dynamics.

This project emphasized the importance of empathetic and adaptable UX research approaches in aligning diverse stakeholder visions and approximating user needs, even in the absence of direct user data. These learnings have been instrumental in refining our approach to user-centric design under various constraints.