Four Steps to a Data-driven Connected Enterprise for True Digital Transformation
In November 2019, Dr. Ray Emerson, a 79-year-old veterinarian from Texas escaped a stroke because his smart phone alerted him to irregular heart beats much before he noticed any symptoms. There were two critical elements at play here – data and connected devices. The heart monitor shared data with the smart watch that the doctor was wearing which then triggered the alert.
Many of us use Amazon’s Alexa, a cloud-based voice service whose success is greatly dependent on the data flowing between connected devices and that’s how you can use the personal assistant to control the Philips light bulbs in your living room or book an appointment with the doctor.
The examples don’t stop here. There are abundant use cases of data native connected enterprises across industries driving efficiency and new revenue subscription-based business models.
The world is beginning to change with physical, digital, and humans working in tandem as one large connected universe; where data acts as the fuel propelling and sustaining business growth and in turn changing the way we function as individuals and businesses.
Data is the glue that connects the world
A data native connected enterprise is about capturing the micro moments from this large volume of data - classifying, processing, and drawing insights in real-time. From the time a user logs in to a system or an application, every action is gathered and studied in a seamlessly orchestrated manner to define the persona of the user and the insights drawn from such data provides the basis for future interactions.
A connected and data centric approach brings meaning and context to different types of data and aligns them with specific functional needs, creating an intelligent ambience that can maximize the potential of data.
Innovation in data management with cloud
A lot of this data is gravitating towards the cloud as it provides the necessary infrastructure to store, analyze, and disseminate information. As a result, the market is seeing an interesting trend of unified data and insight as service on cloud that are not only addressing the challenges around data storage and analytics but bringing additional value by helping organizations monetize their data.
An example would be the data platform offered by our partner, Snowflake that runs on a cloud infrastructure, storing and managing all structured and unstructured data in one place made available to every user and application with near-zero management and a comprehensive enterprise-class SQL database. It democratizes data empowering users to decide on the data they need or seek without having to rely on any kind of IT intervention. We helped a client transition to Snowflake to leverage its data platform-as-a-service for ~500 sales representatives resulting in business of USD ~3 billion dollars.
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’s 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 in near real-time making it very convenient and efficient for its users. The aim here would be to improve patient experience or effective management of the health of the population being covered.
The first step is to identify the actors or personas – For a healthcare organization, it would be the ecosystem of care providers, agents, and enabled patients. Each set of user will be working on different kinds of systems or platforms. Therefore, to create an experience that is consistent across users and systems it is important to practice the following steps through concepts like design thinking and experience workshops:
Building this eco system requires 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 multiple stakeholders and which can innovate on making data exchanges easier. The technology partner must be platform agnostic and region agnostic. In short it should be able to provide all the Infrastructure required for sharing data and staying connected.
Referring once more to Snowflake, the Data Marketplace solution allows users to have granular control over their live, read-only data sets as they share it with data consumers. As Matt Glickman, Snowflake VP of Data Marketplace and Customer Product Strategy says, “Traditional data transfer methods produce data that is stale the moment it's copied or moved. Snowflake's Cloud Data Platform allows organizations to exchange data without moving it, which results in increased agility and accuracy without running the risk of data becoming irrelevant or stale. Snowflake Data Marketplaces enable organizations to then find one another leveraging this capability.”
The third step 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, whether, short term, mid-term or long term It is also important to create learnability in this connected eco-system.
The fourth and final step in the journey is to measure and improve the value of these capabilities on the ecosystem to move from saving a patient to preventing the occurrence of any health incident.
While we recommend these four steps for transforming into a connected data enterprise, it is important 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 and once the foundation is laid, one can expand the scope to compliance, finance, and other key strategic areas.
Author: Sunil Senan