iQ Solutions

User Research for Contextual Design

Team Members: Anup S, Hayleigh Moore, Shenghan Gao, Harmit Sampat, Rijuta Dighe

Role: Largely fluid - Conducting interviews, interpreting interviews, consolidating data, creating models

Skills picked up: Contextual Design, Contextual Interviews, Affinity Diagrams, Data Models

This project was completed as part of a UX Research Methods course.

A major part of user-centric design is conducting user research effectively. This research can be done using many frameworks or methods. For our UX Research methods, we chose to focus on Contextual Design formulated largely by Dr. Karen Holtzblatt.

IQ Solutions is a full-service firm that specializes in public health communications and health information technology, with a dedication towards improving the quality of life for underserved communities. IQ Solutions have successfully established a strong foundation in this domain, combining their 25-years of expertise with technical know-how. One of their primary functions is facilitating live, person-to-person assistance, in both English and Spanish on behalf of the National Institutes of Health (NIH) through their custom-built Information Resource Center (IRC) platform.

IQ believes that the existing Information Resource Center (IRC) platform no longer meets their needs and is planning to transition towards a commercially available Software as a Service (SaaS) that fills the shoes of the current system and adds extra functionality in order to increase task efficiency. IQ’s employees primarily communicate with individuals who are suffering from an illness/disease looking for resources, clinicians or “intermediaries,” and researchers. With this objective, IQ seeks to improve the user experience for their employees, especially the Contact Center team, so that IQ employees can focus on more intricate efforts.

The goal of our research team was to assess business needs and individual requirements, model a modern IRC solution, and potentially provide a roadmap with recommendations on a new platform. Our study is based on qualitative methods as they are much better suited for answering questions about why or how to fix a problem. Our research involved understanding the current state of the system by identifying the issues, the way it is used and the impact it has on employees at IQ Solutions. The following questions were explored by our research team:

  • How can IQ’s inquiry system for phone, email and chat communication be streamlined?
  • How can the new IRC system and privacy regulations be appropriately interwoven?
  • How do the employees use the system?
  • How does the current system hinder or slow down the call process?
  • What tasks can be achieved using the current system?
  • How does the system affect the call center employees’ ability of empathy?

Due to the time constraints and scope of IQ’s requirements request, we did not investigate how external audiences (patients, clinicians, etc.) will be interacting with the IRC and its various functions. The primary focus was on internal use cases and scenarios to improve the tasks of IQ’s employees. We also did not carry out any comparative analysis between different existing products that IQ may choose from.


The Contact Center team communicates daily with an audience that includes: 1. Customers (60%) requesting links to resources related to a disease that they or their close ones are suffering from, 2. Clinicians (15-20%) who call to place orders for a large quantity of medical research publications, 3. The remaining audience comprises of researchers, sometimes even students, looking for very specific information – researchers often contact requesting resources and grants.

The major platforms used to accept these inquiries are through phone calls and emails. Employees at the call centers must then appropriately handle each request by knowing where to look for the information that is being requested by the customer, copy-pasting and sending links to resources via email, or reading them out over the phone. According to our client, this process is unsatisfactory and has the potential of hindering the empathetic nature required by the call center team.

IQ Solutions also manages warehouses for their clients and uses a management system that keeps track of pamphlets, booklets and exhibit materials in stock at the warehouse. This system should ideally work in conjunction with the IRC.

Methods and Outcomes

Overall Study Design

We conducted contextual interviews with the IQ Solutions Call Center and warehouse employees to learn about user requirements and come up with affinity diagrams and subsequently help us build the sequence and collaboration model. Participant Summary

We interviewed a total of seven (7) IQ employees. Five (5) work at IQ’s main headquarters in the Call Center - two (2) employees were Information Specialists (IS) and three (3) were Managers. Information Specialists complete inquiry forms based on the stakeholders who contact IQ for a variety of purposes through the phone, email, letters, or social media. Managers work with the ISs and warehouse to review, validate and approve publication orders, work directly with clients and warehouse for exhibit items, and collaborate with varying IQ teams to implement best practices. Managers occasionally take on the role of an Information Specialist when necessary.

The remaining two (2) employees work at IQ’s warehouse. One (1) is the primary Manager who oversees publication and exhibit requests, distributes pick slips to contractors for packaging, verifies and validates orders, and assists with quality check. The second warehouse employee is a recent hire who works on two contracts - FDA and NCI - and completes quality checks on exhibit items, oversees new shipments and works with vendors to negotiate shipping costs.

Contextual Inquiry

Each interview lasted 45-60 minutes, with the interviewer asking the employees to sit with the system, and at the same time observe them go through their daily tasks. We probed the user based upon their actions or decisions. This helped us fully understand the requirements of the system, the various user tasks, and any other obstacles not made apparent in the initial meetings. An interpretation session was held after each round of interviews. We interpreted our data from the interviews, made notes that were then used in the development of the affinity diagram and the experience models.

Final outcomes and deliverables

After the conclusion of the contextual interviews, we put together an affinity diagram from the data that was captured and interpreted. Using the affinity diagram as a reference, we also composed two different Experience Models.

Affinity Diagram

This diagram acts as a collection of all raw data (yellow notes) gathered during the contextual interviews. The yellow notes are broken down into various categorical levels by grouping similar actions and “I” statements together. The green notes at the top of the diagram tell the “big picture” story so that those who didn’t participate in a contextual interview or interpretation session can easily latch onto the project and make meaningful contributions. The green notes also encompass the blue and pink categories beneath them. The purpose of the Affinity Diagram is to make sense of all data collected and display it in a way that is collaborative, fluid and is the basis for the experience models which will illustrate the findings in a more cohesive manner.

Building the Affinity Diagram

Experience Models

The experience models provide a context for the user’s perception of how an ideal system works.

To maintain confidentiality, these models cannot be displayed here.

A. Sequence Model

The Sequence model attempts to capture users’ actions while doing a task. It helps define the scenarios in which the product will be used. The Sequence Model for IQ has been broken down into two main segments or “workflows.” The first detailing the process of setting up for work, completing an inquiry and interacting with the system to provide resolutions for the inquirers’ requests. The second details the process of receiving orders for publications or exhibit items that must be shipped out to the stakeholders from the warehouse.

B. Collaboration

This model will demonstrate the collaboration between various entities (i.e. call center employees, warehouse employees, managers). This model will reveal how the people in the user’s world communicate and coordinate tasks within an ideal IRC system.


Challenge 1: Lack of necessary automation

  • Information specialists must validate address when submitting publication orders
  • Creating reports requires IT support and/or third-party software (i.e. MS Excel)
  • Search function is case and hyphen sensitive

Challenge 2: Excess complexities in Knowledge Management System

  • Too many fields within inquiry forms
  • “Save and Continue” button doesn’t save data already entered
  • Switching between contracts is tedious
  • Multiple VPNs cause issues when working from home

Challenge 3: Inconsistent Warehouse Data

  • Missing quality check system for exhibit items
  • Absence of real-time inventory numbers
  • Warehouse manager is a single point of failure

Possible Solutions

Solution 1: Make automation a top priority

  • Incorporate machine learning/chatbot that can begin searching for resources based on inquirer conversation/text
  • When an information specialist is on the phone, redirect chats to the next available information specialist, and vice versa
  • Implement a fuzzy search function to find relevant resources/pubs
  • System that can track the current system being used and the actions being completed

Solution 2: Reduce system complexity

  • Centralized system to avoid VPN and reliance on third party software issues
  • Omit drop-down menus and use design variations to distinguish contracts
  • Centralized system with built-in search engine for pubs

Solution 3: Make warehouse data more accessible

  • Hand-held devices for mapping, receiving pick-slips, reporting, and quality check tasks
  • New relational barcode system for tracking and storing exhibit items
  • Dynamic inventory system where warehouse employees can check-in/out pubs and exhibit items


Conducting user research in the environment that they normally work in is really beneficial. It allows the interviewers to catch things that the user wouldn’t bring up by themselves when asked in a setting outside the environment that the task occurs in. Overall, this was a very benifical foray into user research and the importance of it.