the health strategist
institute for strategic health transformation
& digital technology
Joaquim Cardoso MSc.
Chief Research and Strategy Officer (CRSO),
Chief Editor and Senior Advisor
October 31, 2023
What is the message?
The article titled “The Power of Data Agility and Organizational Transformation” discusses the importance of data agility in the healthcare and life sciences industry, emphasizing the need for organizations to adapt to rapidly changing times and leverage data to improve decision-making and innovation.
The article emphasizes the importance of data agility and digital transformation in the healthcare and life sciences industry, with a focus on the positive impact it can have on decision-making, innovation, and ultimately, patient outcomes.
It encourages organizations to embrace these principles and leverage data to create positive change in the healthcare sector.
What are the key points?
- Data-Powered Organizational Agility: The article highlights how data-powered organizational agility has been crucial in responding to emergencies, such as the development of diagnostics and vaccines during the past two years. This agility has allowed the healthcare industry to make significant progress at a remarkable pace.
- The Role of Data Agility: It stresses that in the modern landscape, it’s not just about collecting vast amounts of data but leveraging it quickly and effectively to support new operating models. Data agility is about bringing the right data to the right place with contextual insights, shortening workflows, timelines, and improving user experiences.
- Data Transformation and Digital Technologies: The article advocates the adoption of digital transformation and technologies like Artificial Intelligence (AI), Machine Learning (ML), and Big Data analytics to support informed decision-making and personalization in healthcare.
- Organizational Change and Dynamic Data: It encourages organizations to embrace data automation, big data analytics, data science models, and platform solutions to create data agility. This involves integrating and analyzing data through AI and ML capabilities, possibly using modern architectures like data lakehouses.
- Challenges in Digital Transformation: The article acknowledges that digital transformation isn’t without challenges, including issues like ownership and shared goals, skilled personnel, cost, and data quality. It stresses the importance of workforce digital literacy and participation from all stakeholders to overcome these challenges.
- High-Performing Cross-Functional Teams: The article suggests that organizations should focus on creating a network of high-performing cross-functional teams driven by outcome-based goals, prioritizations, rapid learning, resource mobility, and next-gen technologies. This approach empowers enterprises to act quickly and co-construct great outcomes with all participants.
- Data Democratization and Governance: It calls for a paradigm shift towards creating a digital-first, data-driven culture that includes appropriate technologies, change management strategies, and safeguards at every level. Expanding data governance is seen as essential for data management across the enterprise.
- Unlocking Improved Outcomes: The ultimate message is that when done right, data agility benefits everyone in the healthcare ecosystem, from researchers and care providers to patients and the entire population. Data agility can lead to improved health outcomes, reduced costs, and an enhanced healthcare experience.
DEEP DIVE
The power of data agility and organizational transformation
Oracle Health
Stephanie Trunzo – Senior Vice President and GM
“We must adjust to changing times and still hold to unchanging principles.” – President Jimmy Carter.
How we, as individuals, choose to adjust to change is influenced by the impact change has on us and the people close to us. Having access to trusted sources of data to inform time-sensitive decisions and behaviors is foundational to effective emergency response planning and implementation. In the past two years, were it not for data-powered organizational agility and accelerated innovation, development of diagnostics and vaccines would have taken a phased multi-year approach and data innovation in population health wouldn’t have taken off. But through an agile product development approach, backed by the urgency to learn and work faster, the healthcare industry has pushed forward at a remarkable pace.
As we look to the future, we must sustain and accelerate organizational agility and innovation within healthcare and apply key learnings towards operating models, including – data agility.
Systems of Intelligence
As the quantity of data and data resources increases exponentially, healthcare and life sciences organizations must reevaluate their approach on how to utilize the power of dynamic data to support new operating models. It is no longer about how much data you can collect to create insights, but how fast you can leverage it to bring the right data to the right place with the right layers of contextual insights. After all, if you could use the data as, when, where, and how you need it, wouldn’t it shorten your workflows, timelines, and create a better end-user experience?
In other words, data agility applied to healthcare quickly bridges the gap between high volumes of data and meaningful decision-making through a cohesive mixture of business intelligence and clinical intelligence insights.
Not only that, clean and de-fragmented data that is pulled together at each stage of the healthcare-life sciences value chain creates a cohesive, single source of truth that underpins data-backed agility. And the key to unlocking that potential is digital transformation. Digital analytic technologies promote data agility, that in turn helps organizations become agile and dynamic, and ultimately transforms healthcare for patients, providers, payers, and the population overall.
Go Digital, Go Agile: Bring Insights
The critical drivers in an organization’s digital transformation are data explosion, adoption of technologies, such as Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) analytics, and secure and swift data processing applied to their business processes. These are further fueled by industry drivers, such as value-based care and digital disruption. Healthcare practitioners and organizations that adopt these technologies accelerate informed decision making and are able to differentiate through personalization. Many questions that would have otherwise remained unanswered can now be explained by AI, ML, DL, and big data analytics:
Organizational Change + Dynamic Data = Agility
Organizations should embrace the power of dynamic data through data-automation, big data analytics, data science models, and platform solutions that can be automated through APIs and data processing pipelines. Automated platforms, such as data lakehouse, provide a modern architecture where organizations can bring together, store, and understand their data. A data lakehouse can be built on Oracle Cloud Infrastructure (OCI) to provide an automated and efficient platform where all data can be integrated and analyzed through AI and ML capabilities integrated with industry standard business processes.
Digital transformation isn’t easy, and it takes time.
Besides evolving regulatory requirements and privacy concerns, organizations can face several challenges in successful adoption of digital technologies to create data agility:
• Lack of ownership, shared understanding of goals
• Lack of skilled data personnel
• Lack of swift iterations and experimentation
• Costs of digitalization
• Lack of adequate and quality data
While investment in digitization is critical, technology alone cannot pave the way to agility. Successful transformations invest in workforce digital literacy and encourage participation from all stakeholders across an enterprise.
Organizational transformations that embrace data agility at scale promote a network of high-performing cross-functional teams. These interconnected teams are driven by outcome-based goals, focused on creating value, and equipped with the right skills and tools. Putting people at its center, organizations can create a dynamic people model that fuels innovation. Embedded in this operating model is a shared vision of common goals, frequent prioritizations, rapid learning, resource mobility, and next-gen technologies. This empowers enterprises to act quickly and at the same time co-construct great outcomes with and for all participants (i.e., customers, employees, partners, communities).
Integrating dynamic data technology into every aspect of an organization is a paradigm shift from the traditional operating models that separate business from technology. Healthcare companies need to create a digital-first, data-driven, data-democratization culture that includes appropriate technologies, change management strategies, and safeguards at every level of the enterprise. Data agility further necessitates expanding data governance to create a robust foundation for data management across an enterprise.
Data agility, when done right, empowers everyone in your ecosystem – from the researchers, nurses, physicians, and care providers through to the administrative professionals, suppliers, and vendors. But most importantly, data agility can unlock improved outcomes for patients and, ultimately, the entire population.
Originally published at https://blogs.oracle.com/healthcare
