Senior Vice President, Data and Analytics, Infosys
The world is transforming with physical, digital, and humans seamlessly becoming intertwined as one large, connected universe with data at the center, propelling and sustaining business growth and changing how we function as individuals and businesses. Data is the glue that is connecting the new world.
A data native connected enterprise is about capturing the micro-moments from this large volume of data – processing, understanding, and drawing (often predicting) insights in real-time. Events – human or machine initiated – trigger data backbone to understand the user’s persona, build context with the event and other (un)related events and draw actionable insights to power interactions – now and in the future.
A connected and data-centric approach brings meaning and context to different types of data. It aligns them with specific functional needs, creating an intelligent ambiance that can maximize the potential of data.
Innovation in Data Management with Cloud
Given the volume, velocity, and agility needed to work in real-time, a lot of this data is gravitating towards the cloud. It provides the necessary infrastructure to store, analyze, disseminate insights, and perform actions. As a result, the market sees tremendous growth of unified data and insights driving new business models, new data-driven products and services, and monetizing data in new ways in the data economy.
The Steps to Become a Data-Driven Connected Enterprise
The journey to a data-driven connected enterprise needs to be nimble, agile, and scalable. Cloud computing and virtualized infrastructure can play a key role in connecting data originating from different parts of a business.
For illustration, let us understand what it means from a healthcare company’s perspective. Cloud can gather data from health monitoring systems, wearables, sensors, and other IoT smart medical devices and process them with speed to determine the next best course of action. A connected healthcare system dramatically reduces the time needed to gather, process, and analyze data, making information available near real-time, making it very convenient and efficient for its users. The aim here would be to improve the patient experience or effective management of the health of the population being covered.
The first step is to identify the actors or personas working in conjunction with digital and AI-powered solutions. In a healthcare organization, it would be the ecosystem of care providers, agents, and enabled patients. Each set of users will be working on different kinds of systems and AI-powered platforms. Therefore, to create an experience that is consistent across users and systems, it is essential to practice the following steps through concepts like design thinking and experience workshops:
- Envision the journey of experience across all stakeholders (agents, benefits managers, care providers, payers, members/ patients, and industry ecosystem)
- Define the data standards of interaction based on topics
- Define the boundaries of interactions, either for every function or for specific actions such as events
- Communicate the interaction method (API’s, pull vs push, and others)
- Increase dealing with exceptions than dealing by rule to enhance the experience
Building this ecosystem requires a multitude of capabilities, high scale engineering, economics, and local compliance. Cloud has matured to provide these comprehensive features at hyper-scale, meeting all the requirements.
The second step is to find a technology partner who can provide an ecosystem that is flexible and scalable to accommodate multiple personas and stakeholders innovating on making data exchanges easier. The technology partner must be platform and region agnostic. In short, it should be able to provide all the infrastructure required for sharing data and staying connected.
The third and probably the most important step in the journey is to categorize all of the information and make smaller pools of data based on who needs the information and for how long, such as short-term, mid-term, or long-term. It is also crucial to create learnability in this connected ecosystem.
The fourth and final step is to measure and improve the value of these capabilities on the ecosystem to move from saving a patient to preventing any health incident.
While we recommend these four steps for transforming into a connected data enterprise, it is essential to take small iterative steps in bringing this attribute to every function of the business. It is advisable to cover data from IoT, ERP, CRM, and demographics as an initial step. Once the foundation is laid, one can expand the scope to compliance, finance, and other key strategic areas.
DISCLAIMER: The views expressed are solely of the author and ETHealthworld.com does not necessarily subscribe to it. ETHealthworld.com shall not be responsible for any damage caused to any person/organisation directly or indirectly.