Case Study
BR - SP
2009 - 2025
CDC - Consultant's channel
www.dasa.com.br
Nov 2023 / Jun 2024
Type: Responsive platform
Comissioned by: Dasa S.A
Related metrics
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Rollout/ Share
-
TMO
-
Csat
Context
The platform is used to schedule medical exams and clinical consultations by telephone or in physical units. It is also possible to conduct searches to view patient histories and offers of exclusive and specific services.
Its main user is an internal team of customer service staff (around 2,000 people).
Challenge
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Realise a rollout of around 40 diagnostics brands to this new platform
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Ensure updated and correct information, as well as quick responses to searches done
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Reduce call handling time
Team
Davi Januário
Product Designer
Pedro Victor Pereira
Project Manager
Marina Zilli
Product Owner
Guilherme Davi Lima
Tech Leader
My responsabilities
I collaborated in the final stages of this rollout process, improving functionalities and creating new features focused on the needs of users and the business to accelerate and enhance the perceived value in relation to usability.
Impacts
Result of the all development done during the period I worked in the squad.
Saving bigger 1 M
with licences that wasn't renewals
from 55% to 80%
Rollout / Share increase
72%
TMO
85
Csat
Work effort
Some numbers to make the effort during my time in this squad tangible.
• 7 months (Nov 2023/ Jun 2024)
• 2 quarters
• 14 sprints
• 15 days each sprint
• Highly complex tasks
2 - 4
Initiatives
6
Epics
20
Stories
60
Tasks
Example
of outcome
High complexity
Pain
Checking and applying the rules for exams to schedule them is not done smoothly and requires prior knowledge of the rules, making the process time-consuming and impacting patient satisfaction on the phone.
Job to Be Done
View and apply rules for scheduling exams, vaccinations and medical appointments in an orderly and simplified manner during telephone service to schedule appointments.
Design process
BR - SP
2009 - 2024
Tools
Design
process
Duration
2 sprints (30 days)
Tools
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72% of medical records were complete and up to date.
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5.3 seconds was the average time to find a patient’s history during a call.
0.0/ 5
Average Time for Data Retrieval: Time taken to retrieve a patient’s medical history during a consultation
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Adding automatic rule checks to the scheduling platform will make bookings faster and more accurate. This helps reduce mistakes, shortens service time, and improves patient satisfaction.
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Complex rules make scheduling hard. Staff need to know many details for different types of appointments.
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Manual steps slow things down and cause errors.
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Limited training and tools mean staff can’t work as efficiently.
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The platform doesn’t guide staff with rules or suggestions.
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Patients expect fast, simple service—but the current system doesn’t deliver that.
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Build a smart rule engine that applies the correct rules automatically.
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Automate the process to reduce manual tasks and errors.
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Add tooltips and guides inside the platform to support staff.
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Include a smart search for quick access to rule details.
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Design a faster and easier interface to improve the booking experience for patients and staff.
Expected Results: -
Increase complete medical records from 72% to 90%
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Reduce average data retrieval time from 5.3s to under 2s
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Improve NPS by +15 points
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Reduce TMO by 20%
0.0/ 5
Average Time for Data Retrieval: Time taken to retrieve a patient’s medical history during a consultation
-
Service blueprint mixed with journey map
At the end of the design process, to maintain an updated alignment with the external stakeholder and the squad team, I recorded the pain points, solutions and impacts on the process throughout the entire journey of initiatives that I worked on during the sprint, to serve as a source for continuous discovery and planning of new activities for the next quarters.
Learning
User-Centric Design: Working on a platform used by a large internal team highlighted the importance of designing with user workflows and ease of use in mind. This required extensive user research and iterative testing to ensure the platform effectively reduced call handling time and improved user satisfaction.
System Integration: Ensuring seamless integration of the platform across various diagnostic brands was crucial. This taught me the value of designing flexible and scalable systems that can accommodate diverse data sources and interfaces.
Information Accuracy: Given the sensitivity of medical information, maintaining updated and accurate data was critical. I learned the importance of robust data validation processes and clear communication to ensure reliability.
