Healthcare CRM development: x2 faster data migration

Innowise refined and expanded a healthcare CRM platform, focusing on automating data migration processes and implementing AI-driven operational and analytical enhancements.

Customer

Industry

Healthcare

Region

Client since

2023

Our client is a prominent player delivering IT solutions for pharmaceutical companies. The company has established itself as a key technology partner, offering cloud-based BI and AI-driven solutions tailored to the specific needs of the life sciences market. For over two decades, they have been supporting major multinational pharmaceutical corporations by creating and implementing innovative software aimed at improving business operations.

Challenge

CRM data migration, data quality assurance, and UI optimization

The primary challenge our client faced was the seamless migration of data from existing CRM systems of various pharmaceutical companies into their specialized CRM system based on Microsoft Dynamics 365. This task involved more than just data transfer. The client required comprehensive data quality assurance, transformation, and loading into a new environment to ensure the integrity and usability of the migrated data. Additional issues stemmed from:

The need for a standardized yet customizable approach to accommodate the specific requirements of each pharmaceutical company;
Ensuring continuous operation and support for clients across different countries with varying data structures and standards;
The client expected us to provide a comprehensive solution that would facilitate smooth data migration. They also aimed to enhance their CRM’s functionality, making it more accessible and user-friendly for global pharmaceutical companies.

Solution

Custom migration framework, data transformation, and enhanced UI for healthcare CRM

To address the client’s challenge, we concentrated on three key components within healthcare CRM development: developing a custom migration framework, conducting quality assurance and data transformation, and optimizing the user interface.

Custom migration framework

Our team created a custom migration framework – a scalable solution for integrating diverse CRM systems into Microsoft Dynamics 365 and Azure, specifically designed to meet the complex needs of the pharmaceutical industry.

Initial country initialization and data setup: To begin the migration process for a new country within an existing client’s CRM system, we deploy new SQL Server schemas tailored to the country’s specific requirements. This involves configuring pipelines in Azure Data Factory to handle the initial data load, which includes a mix of Excel files from clients and API calls. This stage is critical for establishing a foundational data structure that can be tested and validated in a “sandbox” environment, allowing select customer representatives to perform beta-testing and training with partially complete datasets.

Data verification and transformation: Our approach to handling incoming data involves a meticulous verification process. Files, standardized to include common data types and codes, are first visually inspected for anomalies such as missing mandatory fields or irregular codes. Following this initial check, the files are uploaded to SQL Server, where they undergo a detailed review and transformation into tables formatted for Dataverse loading. This process is semi-automated, with manual adjustments made as necessary to cater to country-specific variations. We compile detailed reports on data discrepancies and communicate these to the client in understandable language, sometimes awaiting corrected files or proceeding with available data and making subsequent modifications.

Integration and production roll-out: For countries utilizing API calls, we set up data import mechanisms and validate the accuracy of data transformations before loading the finalized data into Dataverse. The transition to production involves the parallel operation of the test and production environments, with the former serving mainly for training and feature testing purposes. This phase marks the culmination of initial setup efforts, transitioning to a state where new data inputs from client users either directly enter Dataverse through the client’s products or continue to be sourced from API calls, with minimal intervention required on our part.

Automated data mapping and AI-powered cleansing: Our solution leverages Azure’s capabilities for automated data mapping, reducing manual efforts and the risk of errors by identifying data field correlations across various CRM systems. An AI-powered data cleansing module further ensures the integrity of the migrated data by identifying duplicates, incomplete entries, and other inconsistencies.

Custom integration APIs and Azure services utilization: We developed custom integration APIs within the Azure environment to accommodate the diverse data formats and structures encountered across different pharmaceutical CRM systems. These APIs, alongside Azure services like Data Factory, Blob Storage, and SQL Server, provide the scalability and security necessary for efficient data migration and management. As a result, we achieved a seamless data transfer and high-quality ETL processes.

Industry-specific focus: Our framework is specifically tailored to meet the unique needs of the pharmaceutical industry, incorporating considerations for handling sensitive data such as patient information, drug details, and sales records, in compliance with standards and regulations.

Quality assurance and data transformation

Our team harnessed Azure Data Factory (ADF) to automate and refine the data preparation process for the client’s CRM. The strategy included:

Automated validation checks: Using ADF, we set up automated scripts to perform validation checks, ensuring data met the CRM’s requirements. The automated checks help identify and flag discrepancies, such as inconsistencies or missing information, significantly reducing manual review time.

ETL processes with ADF: We designed data pipelines for efficient movement and transformation of data. Schema mapping automatically adjusts data structures from various sources to fit the CRM’s schema and ensures compatibility. For data cleansing, we applied rules within ADF to clean data, like standardizing formats, removing duplicates, and enhancing data quality.

Complex data transformations: For intricate data scenarios, we used ADF’s Mapping Data Flows to create code-free transformation logic, handling operations like joins and conditional splits to ensure data integrity.

This approach minimized manual interventions, expedited the migration process, and ensured the migrated data was immediately usable within the CRM.

User interface optimization

To enhance the user interface of the CRM for the pharmaceutical sector, we focused on several key improvements:

First, we adapted the interface to be responsive across all devices using CSS Grid and Flexbox and ensured every user had a smooth experience, whether on a desktop or mobile.
Our next step was to refine responsiveness with media queries, optimizing for touch screens and small devices essential for field representatives on the move.
We streamlined the navigation to minimize the steps needed to access vital information, making the CRM more intuitive and user-friendly.
Introducing customizable dashboards was another focus. Dashboards allow users to personalize their workspace for their unique needs and workflows.
To make data retrieval fast and accurate, we enhanced the search functionality with advanced filters and predictive text.
Recognizing the need for timely updates, we integrated push notifications to keep field representatives informed with real-time alerts.
We embedded interactive data visualization tools within the CRM to provide users with immediate access to analytics and insights for informed decision-making.
Lastly, we added offline functionality to the mobile app, ensuring uninterrupted access to critical data, with automatic syncing once online connectivity is restored.

Technologies

Back end

.NET, Microsoft Dynamics 365, MS Dataverse, Azure Dynamics365, Azure Functions, Azure API Management

Data Management

Azure Data Factory, Azure Storage account, SSMS, XrmToolBox, MS Azure Storage Explorer

Databases

MS SQL Server, MS Azure SQL Database

Python, NLP, Matching Models, GPT-3, OpenAI API, Azure Cognitive Services, Azure Data Factory, Databricks

Security

Azure Active Directory, Azure Key Vault

UI Optimization

CSS Grid, Flexbox, media queries

Process

Our healthcare CRM development process was executed in stages to ensure a seamless migration and integration experience for our client. Throughout this process, our adherence to the Agile methodology allowed for flexibility in making iterative improvements. We employed MS Teams for communication with the client and Jira for task tracking to maintain transparency at every project stage:

Discovery phase

We began with a thorough assessment of the existing CRM systems used by the pharmaceutical companies. It was vital to understand the data structures, workflows, and specific needs of each company. Our team collaborated closely with the client to define the requirements and expectations for the migration process and healthcare CRM development. Our deliverable at this stage was a comprehensive Vision and Scope document outlining the project roadmap, timelines, and expectations.

Design and planning

Our specialists designed a custom migration framework that aligned with the specificities of the pharmaceutical industry. We developed detailed data mapping and transformation strategies to address the diverse data formats and standards according to the architecture diagrams and a data migration plan.

Implementation

We created custom APIs for seamless data integration. We utilized automated tools and processes for data cleansing and transformation to guarantee data integrity and compatibility.

UI enhancements

Our team worked on optimizing the CRM applications across web, tablet, and mobile platforms, focusing on improving user experience and accessibility. We delivered a fully functional, tested, and validated migration framework along with enhanced CRM apps ready for deployment.

Testing and deployment

Innowise conducted a pilot migration for select data sets to validate the migration process and framework effectiveness. During User Acceptance Testing (UAT), we engaged with end-users to test the enhanced applications, gathering feedback to make adjustments. Then, we rolled out the migration framework and updated applications across client environments, ensuring minimal disruption to existing operations.

Post-deployment support

We provided comprehensive training sessions for end-users and IT staff, along with detailed documentation on the new system functionalities and maintenance procedures.

Team

Project Manager

Big Data Engineers

Front-End Developer

Python Developer

QA Engineer

Data Analyst

Results

95% higher data accuracy and x2 faster data migration for pharmaceutical clients

The implementation of our solution brought significant improvements in the client’s CRM capabilities. As a result, we enhanced operational efficiency and data management across their pharmaceutical company clientele:

The custom migration framework reduced the data migration timeline by over 50%, enabling quicker CRM deployment for new pharmaceutical clients.
Automated data cleansing and transformation processes increased data accuracy by 95% and significantly reduced manual data correction efforts post-migration.
Optimization of CRM applications for web, tablet, and mobile platforms resulted in an increase in user engagement, demonstrating improved accessibility. Post-deployment feedback showed a 90% satisfaction rate among end-users, highlighting the effectiveness of the UI/UX enhancements in meeting the needs of pharmaceutical representatives.

By delivering a tailored solution that addressed both the technical and user experience aspects of the CRM migration, we contributed to our client’s ability to offer a more effective CRM system to their pharmaceutical clients. Our team is continuing the process of migrating data from pharmacy networks to our client’s upgraded CRM system. Currently, we are focusing on the migration process for four specific healthcare clients and pharmacies, tailoring our approach to meet the unique needs and data intricacies of each.

Project duration

March 2023 - Ongoing

faster data migration

95%

higher data accuracy

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