Organizational Analysis Tool

Developed an analytical program designed to support 6,000+ consultants to generate data-driven solutions for clients they consult for in a faster, more intuitive way.

Year

Feb - May 2021

Agency

Cornell University

Project Type

Product / Data / Research

Role

UX Designer
UX Researcher

Project Overview

Creating a custom analysis tool

Our team was tasked with creating a product that is market differentiating, intuitive, and feasible analysis tool that that can be accessed by consultants at the advisory firm. Over the course of the 12-week project timeline, we followed the design process and handed off a research deck, MVP prototype, and future considerations that has since been taken to upper managmeent stakeholders and is in the process of being developed.

Problem

The Global Business Advisory Firm is frustrated with the current software (OrgVue) they use to conduct organizational analysis and create data visualizations. While there are other programs that aim to solve these issues, none successfully provide users with all the features they want to make holistic recommendations for their clients in one seamless experience.

Solution

Our Organizational Analysis Tool (OAT) integrates and improves upon the most used features of competing products to solve consultants pain points. Simplifying the process of collecting data, organizing information into data visualizations, collaborating with other analysts, and sharing the findings with clients.

Team Structure

I worked alongside 4 other masters students and we split the roles into:

1 Project Manager
3 UX/UI Researchers & Designers (me)
1 Data Analyst

Research & Planning

Understanding the current landscape & identifying user needs

After looking at the competitive landscape and interviewing 5 analysts to identify pain points, needs, and areas of improvements our main takeaway was that

Consultants switch from different software and programs to search and cross validate findings making the current workflow clunky and time-consuming.

competitive analysis of industry standard software

interviews with entry-level to expert analysts

Defining features

After understanding the current market and conducting user interviews, our findings were synthesized to identify goals, opportunities, and features that OAT can focus on:

Foundational Features

• data ingestion, transformation, cleansing, linking, and visualization
• data dashboard
• project dashboard

Future Ideas

• automated data-driven strategies
• task management system
• industry benchmarking and comparison

Platform Architecture

We outlined the structure of what would be essential to the process of analyzing data via this program. This included 4 major tasks our tool would support (2.1-5.1).

Wireframing

Mapping out the structure of key pages

From our detailed journey map, we split up the design of pages by specific sections and each worked on different sections of the product:

dashboard & project view*
dataset import journey*
data visualization playground
comparison tables

*pages I worked on

Usability Testing

After our mid fidelity wires, we began gathering feedback through usability testing with the analysts interviewed at the beginning of the project.

We then synthesized insights from each test and made improvements the following iterations.

Visual Design

Establishing a simple & fresh design system

We developed a basic typeface and color palette to have cohesion with the company’s brand identity but used a modern typeface for an updated look.

MVP Design

Designing for value, usability, and efficiency

The final design reduces the friction typically experienced when working within multiple platforms to complete different tasks. By consolidating these tasks into one unified platform collaboration is easier, workflows are more efficient, and projects are more organized.

main dashboard

project dashboard

data import (assign attributes step)

dataset view

data visualization (org tree)

industry comparison tool

Outcomes & Reflection

Testimonials

Towards the end of our project scope, we presented our process, prototype, and future considerations to project stakeholders including our client, other analysts, and professors from Cornell who played a part in organizing the project.

“Usually when companies start just on a technical level building a product like this, what’s lost on them is validating the need. From the research your team has provided its crystal clear that there is a need out there. Not only that, you explored the seamlessness and usability that an end user would really respond to which your team had delved into with those personas and user testing...”

- Client Senior Consultant

“This was an excellent display of user experience and the design process working together in a team with a client.”

- Cornell Course Professer

Learnings

01. Spend more time during the research phase and understanding the project space

Since everyone on the team was not familiar with organizational data analytics platforms or how to do advanced analytics tasks, it was a big hurdle to get the basic understanding with what we were designing. Additionally, we were not able to get access to OrgVue (what analysts are using), so we could not explore all the features except through their website resources. What helped the most was talking with analysts as they delved into detail what it is they do and having them break down the process into simple steps.

02. Have a open line of communication with the client

As we were working as outside consultants to our client, so we did not always have the opportunity to meet all the time. To keep both teams connected, our project manager sent weekly emails with our meeting agenda, notes, and any files for the client to review. This flow of communication worked well for both teams to know what was happening and what to expect during our next check-in.

Future Iterations

If given the opportunity to continue working with our client, I would like to shadow more consultants in their day-to-day and understand how our tool and future ideas could integrate and ease the busy workflow. Taking those insights to reevaluate our design and continue to iterate.

Additionally, since our design system and components were built by a need basis, I would rebuild it so it’s more flexible to the products growing features.

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