Avadel Pharmaceuticals is a specialty pharmaceutical company based in the US and Europe. In 2017, Avadel reached out to MEV to develop an automated solution to process sales and market datasets to streamline the operations of their sales team.
Avadel relied on manual methods to process the large amounts of data produced by their sales operations team. Here are the main two challenges that they encountere:
[01]
The Avadel sales operations team primarily utilized Excel and manual processing to manage their sales territory data sets.
[02]
Their inefficient methods often led to inaccuracies that increased their workload and inhibited their payroll.
Avadel needed to automate its data pipeline to support its sales operations. Avadel also needed a solution that did not require a massive investment in expensive enterprise data warehouses (EDW) and reporting solutions. Avadel’s leadership contacted MEV to develop an automated processing and reporting pipeline.
Data Pipeline Automation
Cost-Effective Solution
Robust Reporting
[ the challenge/ ]
Build an Automated Data Processing Pipeline
To support Avadel’s sales operation, we needed to build a solution to process data sets quickly, accurately, and simultaneously. Avadel’s data processing pipeline:
01.
Zipcode to Territory Mapping
02.
Market Definition (what products are attributed to which markets)
03.
Rx Data Ingestion Automated for IMS
[ the solution/ ]
Using AWS Elastic MapReduce, S3 and Hive, MEV built a product to ingest and process Avadel’s data, automated their manual checking process, and optimized their processing and reporting.
[
01
]
Pharma Data Expertise
Our engineering team had prior experience working with industry-standard datasets and data pipelines, allowing us to develop quickly. We were able to create and test a working prototype in a matter of weeks, which we used to process sample data to identify anomalies in the mapping process.
[
02
]
Fast Feedback Loop
We collaborated closely with Avadel’s team to build and test the data pipeline using agile principles and processes. While obtaining data from Avadel’s data vendors took time, our development strategy allowed us to build, test, and get valuable feedback quickly and iterate the cycle.
[
03
]
Pragmatic Approach
We focused on practicality with the initial data pipeline to ensure Avadel’s data sets were processed conveniently and correctly. After establishing a functional, end-to-end pipeline, we focused on process efficiency, system robustness and data quality. Our partnership with Avadel allowed us to collaborate effectively and deliver value to key stakeholders without wasting time or resources.
The final solution includes:
Robust data processing pipeline and an automated data ingestion system with quality checks
Data processing time was cut down to just 30 minutes, having previously taken many days to complete.
[ outcome/ ]
Our solution helped reduce Avadel’s data processing time by 95%. The data anomaly detection mechanism identifies issues quickly and allows us to address the problem before processing completion. Data management automation helped to free up time, allowing Avadel’s employees to focus on other priorities. We also built a product that was inexpensive compared to a large data warehouse, saving Avadel money and time.
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