Data Warehousing for Pharma Manufacturing Industry.
Data powers every industry. However, true to the saying, if data is left unrefined, it is worthless. Today, the pharma and healthcare industry leverages massive amounts of data to address challenges associated with operational inefficiencies, healthcare costs, and care quality. It should not come as a surprise that pharmaceutical companies are using data to increase the effectiveness and success of clinical trials as well as the approvals process as R&D is at the core of their business.
To do this successfully, pharma companies are increasingly deploying data warehousing. In this blog post, we tell you why data warehousing is the future of the pharma industry. Read along!
What Is Data Warehousing?
The definition of a data warehouse differs across industries. However, the crux stays the same: they are central repositories of integrated data from multiple disparate sources through complex architectures. They store current and historical data in one place, leveraged to create analytical reports. These reports then help optimize processes, increasing the operations' overall efficiency. The pharmaceutical industry is notoriously data-intensive and known to utilize and generate critical data constantly. Data warehousing can catapult their efficiency and productivity without compromising integrity or security.
Why data warehousing and analytics are vital for the Pharma industry?
Pharma companies must be pioneers and early adopters of technology if they want to reap the rewards of data analytics. However, there are significant obstacles that must be overcome:
- Removing data silos and merging siloed processes to provide cross-functional insights
- Establishing the infrastructure necessary to transform large data into smart data.
- Obtaining and making use of unstructured clinical and drug distribution data.
- Gaining knowledge from clinical trial data to provide estimates and reports that meet the financial needs of investors
- Establishing guidelines for consumer data engagement and data privacy.
To understand the importance of any process, we need to dive into the key benefits it provides. Here are the top reasons why data warehousing is the future of the pharma industry.
Pharma companies require data for various reasons. These could be for clinical trials, regulatory compliance, or even sales. Data warehousing helps them retrieve the necessary information to analyze and interpret data.
Quick Drug Development And Discovery
There is abundant data available in the pharma industry. Be it from clinical trials or focus groups, these data points are hard to access, leading to a scathing delay in the discovery of new drugs. Having a centralized platform, like a data warehouse, to access, analyze, and retrieve this information can revolutionize the process of drug discovery. Pharmaceutical Analytics also uses predictive algorithms to analyze the data.
It is dangerous how unorganized data can affect the pharma industry. With the stakeholders and decision-makers spread across boundaries, it is imperative to have a single source of truth for all critical data. Data warehouses help reduce the risk of wrong interpretation of data and increase its accuracy.
Let’s face it— today, data is siloed across various legacy systems. Siloed data can lead to data discrepancies and inefficient processes. With data warehousing, pharma companies can transform their processes and ensure quick, data-led decision-making.
Data mining is the method used to search for and identify patterns in massive data sets. Patterns and interconnections in data are discovered through the application of programs and modeling approaches, assisting with accurate forecasts in R&D, marketing, and problem-solving in clinical trials. To increase the quality of drug research and delivery techniques, data is altered using a variety of algorithms such as clustering, associating segmentation, and classification.
Providing personalized medication is key to ensuring proper care to patients. With data warehousing, companies can sift through unstructured genomic data and spot patterns to help create more effective and personalized medication for their patients.
Increased efficiency in production
Producing drugs and medication is expensive; we all know that. With robust analytics in the data warehouse, pharma companies will be able to increase efficiency and reduce production costs significantly.
The role of BI in helping pharma companies achieve their best
Pharmaceutical firms are beginning to understand the value and function of BI solutions in enhancing research with the aim of fostering organizational growth and reducing costs.
Pharmaceutical business intelligence solutions remove the requirement for departments to be interdependent on one another and make it simple for them to get information as needed.
Business users don't have to rely solely on their coworkers to access data and build dashboards. Instead, they always have easy access to important metrics and data. This improves their ability to compare research data from across the firm to measure how well various operations are performing in accordance with government criteria. This enables pharmaceutical businesses to efficiently maintain compliance and promptly inform any departments or procedures that do not adhere to the standards.
Bottom Line: Data Warehousing Is The Need Of The Hour
Data warehousing, as complex as it sounds (and is), is the easiest way to simplify your operations. It helps you store a multitude of data and analyze them to create meaningful reports.
With the ocean of data available in the pharma industry today, it has become necessary to organize and synthesize the available data for maximum efficiency. Data warehouses act as a single source of truth for all your data and pave the way for accurate, data-driven decision-making.
From implementing specific data rules to creating complicated data models, the right data warehouse can transform your operations like never before. If you are looking to develop a data warehouse for your pharmaceutical company, talk to us today.