Connect data across your organization with master data management and data warehouse capabilities, and transform the way you make business decisions.
The advancement of data technology and its capabilities is taking place at an incredible speed. Life sciences organizations can unlock new opportunities to gain insights by effectively managing complex data sets through creative modeling. To handle the vast amounts and diverse types of data from an increasing number of sources, a fully integrated Master Data Management (MDM) system at the core is imperative.
One of the most impactful recent technological trends, which for many companies is still unfolding, is the transition from multichannel to omnichannel operations. While access to new data and technology made multichannel engagement possible, individual channels and the departments using them remained fragmented and siloed. Inevitably, isolated data sets being used for isolated channels produced a disjointed, disharmonious engagement experience. The need to improve engagement engendered the need to:
Successfully implementing these three functions enables the transition from multi- to omnichannel operations; and from uncoordinated to coordinated interactions. Companies that have fully made this transition have already gained a massive competitive advantage.
Effective omnichannel engagement empowers organizations to:
It’s important to note that as technology, and specifically artificial intelligence (AI) and large language models (LLMs) continue to evolve, establishing a well-organized and well-functioning omnichannel solution built upon a superior MDM platform will be an absolute necessity.
The next stage in the evolution of life sciences data technology is already being integrated by disruptors and early adopters from both pharma and medical technology companies. Many future possibilities have not even been imagined, but today’s preliminary iterations already reveal that generative AI (GenAI) can significantly accelerate many data-driven tasks. A 2023 McKinsey article, “The Data Dividend: Fueling Generative AI,” suggests data management is a key enabler for generative AI applications.
Another clear and impactful change is that AI combined with tailored LLMs can greatly expand the capabilities and value of data with their cumulative ability to ingest, process and leverage unstructured data from previously untapped sources like online chats, customer text, email and phone exchanges, videos, code, and a rapidly growing list of touchpoints. And as data professionals become increasingly proficient in feature engineering, improved machine learning and model training will rapidly gain greater levels of accuracy and provide deeper levels of insights.
A close examination of the effectiveness of any AI use case will always produce the same conclusion – there is a direct relationship between the quality of the input data and the capabilities and effectiveness of generative AI’s output.
McKinsey Data and AI Summit 2022
As the power and capabilities of data technology continue to explode, the need for data management excellence becomes exponentially more vital. For companies that have yet to invest in an effective MDM, or need to rework an outdated MDM strategy, now is the time to put a robust MDM strategy in place. Just as it would be impossible to attempt complex math equations without first learning to add and subtract, the prospect of managing and processing the quantities and varieties of data made possible with generative AI and LLMs will become virtually unthinkable without a solid MDM foundation established to facilitate feature engineering for selecting and transforming the variables that drive the models.
Connect data across your organization with master data management and data warehouse capabilities, and transform the way you make business decisions.
A purpose-built life sciences information management solution leveraging a multi-domain approach to manage enterprise data for consistent, reliable and faster access to insights.
Rapidly connect siloed data networks to drive deeper, centralized insights and enable better decision making.