BirdzAI’s Master Data Management Module Streamlines Data Validation, Rules, and Processes

by Brian Fitzgerald | Last Updated: September 19, 2022 | 1 min read

If harnessing the power of artificial intelligence (AI) is at the top of your to-do list, you’re not alone. Pharmaceutical teams, from R&D through to Commercialization, are in a race to find AI solutions that will give them a clear advantage. As a matter of fact, there is so much interest in the technology that researchers estimate the pharmaceutical industry will spend nearly $9.2 billion on AI-powered innovations¹ by 2030. But unfortunately, if those organizations’ data management practices aren’t in order first, much of that money will be misspent.

No matter how innovative an AI’s algorithms are, results will be disappointing if they are running on top of scattered, inconsistent, and outdated data. And this is an industry-wide concern that executives acknowledge. According to a recent study by PwC², the majority of executives surveyed reported major gaps in their data analytics capabilities. They want to use technologies like AI and machine learning, but they know that their data isn’t in good working order.

BirdzAI is the Remedy for Data Management Woes

The good news is that there’s a solution: the BirdzAI Data and Analytics platform! The powerful yet flexible solution has even been recently updated with four new pre-built modules for Master Data Management, Insights & Analytics, Sales Operations, and Marketing Operations. And although AI gets the bulk of the attention, the real magic begins at the data layer. That’s why it’s important to note that BirdzAI supports pharmaceutical commercial operations with rapid, end-to-end data management capabilities, including the ingestion, storage, processing, and analysis of data derived from commonly used sources like first and third-party prescription data, specialty pharmacy data feeds, CRM systems, marketing interactions reports and more.

These are important features because an organization’s data often comes from a wide variety of sources and is touched by many people. If not effectively managed, this can result in redundant and even conflicting information. To help eliminate this issue, BirdzAI integrates easily with any commercial operations workflow and creates a single source of truth by bringing all of an organization’s commercial data together into a state-of-the-art master data management ecosystem. This is what enables the platform’s advanced AI and machine learning algorithms to then turn data into insights for real-time sales and marketing operations decision-making, including forecasting, brand propensity analysis, next best action insights, customer alignment, customer and territory planning and sizing, and incentive compensation strategy, and much more.

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Creating a Modern Data Estate

Developing a modern data estate can be an extremely complex process. However, with BirdzAI’s data management module, pharmaceutical companies can ingest all data types (structured, unstructured, semi-structured) and easily derive insights from that data. BirdzAI also supports data operations and enables organizations to implement and adhere to governance frameworks. This includes streamlining data validation, rules and processes, and maintaining security and compliance.

Supporting Data Validation, Rules & Processes. BirdzAI’s data validation processes support sound data governance. Using rules and process automation, BirdzAI ensures data is being utilized within acceptable values for data ownership and stewardship.
Enabling Scalability While Maintaining Security and Compliance. With BirdzAI, organizations can apply corporate security standards and compliance standards to all data easily and efficiently. These standards are stored in a dedicated cloud tenant in Microsoft Azure, enabling compliant, scalable, and secure data governance.

These are critical features because as companies begin to rely more heavily on data-driven techniques, the integrity of data becomes increasingly important. The inability to trust the data gathered from a variety of sources can sabotage an organization’s efforts to enhance revenue and improve operational efficiencies. That’s why proper data validation is a must.

What is Data Validation?

Data Validation is the process of ensuring that data is accurate and up to date before using, importing, or otherwise processing it. Depending on the destination constraints or objectives, different types of validation can be performed. And validation techniques cleanse and eliminate unnecessary data, as well as provide an appropriate structure to the dataset for the best results. In other words, validation is a type of data cleansing.

When migrating and merging data, it is critical to ensure that data from various sources and repositories conforms to business rules and does not become corrupted. The goal is to generate data that is consistent, accurate, and complete in order to avoid data loss and errors. Without validating data, organizations risk making decisions based on imperfect information. And BirdzAI helps streamline this process, and much, much more.

About P360

Delivering a 360 view through the pharma-to-physician ecosystem, P360 designs and deploys capabilities that ensure the highest efficiencies and returns on sales operations, data management, and IoT innovation. With expertise in supporting commercial operations for companies of all sizes, P360 has built an industry-leading platform that gives customers ownership of their data and the ability to leverage artificial intelligence and machine learning capabilities.

For more information, visit P360.com/BirdzAI.

References:

1. https://www.globenewswire.com/en/news-release/2022/03/09/2400167/0/en/AI-in-the-Pharmaceutical-Market-Size-to-Hit-US-9-241-34-MN-by-2030.html

2. https://www.strategyand.pwc.com/de/en/industries/health/future-of-health-2021.html

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