Operationalizing Data, Pt. 1: Harnessing Exponential Growth

People generate 328.77 quintillion bytes of data daily.¹  That’s enough data to fill more than 800 million 1TB drives each day. Almost everything we do creates data — from the 1.7 megabytes generated every second we spend on the internet to the unknown amounts of data created when we ask voice assistants like Alexa to turn on our lights or play our music — known as “digital exhaust.”

Most people have embraced this trend toward datafication — the process of collecting, analyzing, and using data to make informed decisions. We have smart watches to measure our exercise and sleep. We rely on real-time driving apps like Waze to reduce our commute time. We regularly buy goods recommended to us via algorithms optimized to our interests and life stages. We even experiment with how generative AI chatbots like ChatGPT could make common tasks easier.

However, most of us aren’t using data in these same ways at work, as companies are still striving to understand the ethical, legal, and technical implications of these capabilities on their businesses. Many organizations are strategizing how best to leverage data and machine learning (ML) capabilities effectively and compliantly. Unfortunately, the policies, procedures, and IT capabilities that will enable organizations to seize the unprecedented opportunities available are still a work in progress.

To meet the extraordinary complexities and opportunities the future holds, public- and private-sector organizations must accelerate and modernize their data strategies to take advantage of this mission-critical megatrend.

In the first part of this two-part series, we explore the advantages and opportunities of putting an organization’s data into action. We also cover essential steps to construct a robust ecosystem that can fully harness the potential of an organization’s data.

Maximizing Data: A Transformational Megatrend

The rise in importance of data ecosystems is one of five interconnected global trends that present government entities and commercial businesses with an array of opportunities and challenges. In fact, it may be the most significant of the megatrends we’ve identified. By today's standards, data is required for tackling the complex challenges — from building equity in communities through data-informed improvements, to leveraging ML in threat intelligence.

What will it look like when corporations are transformed the same way datafication has transformed our personal lives? In biotech, it will translate into novel pharmaceuticals identified with the help of generative AI that will treat or cure common diseases. In healthcare, it will mean proactive and personalized care models based on predicted health risks. The financial services industry may realize vastly improved real-time fraud detection, leading to billions of dollars in global savings. In the energy sector, it will mean better visibility into all aspects of supply and transmission, ensuring the grid won’t fail during the next heat wave.

Across all organizations optimized use of data will drive proactive vs. reactive customer service, better supply chain visibility and management, and the ability to solve complex business challenges by operationalizing disparate sets of data.

Imagine a world where a hurricane is about to make landfall as data from hundreds of federal, state, and public sources is being centralized and fed into an ML model that predicts which homes are likely to be damaged by flooding. Consider how a hospital system could use their organizational, public health, and supply chain visibility data to build digital twins that model potential natural disasters and public health emergencies. Hospitals could ensure they have the medical stockpiles, responsive supply chains, and workforce management plans in place to meet every possible disaster.

Collaboration and cooperation — not only between functions, but across sectors, between business and government, and among nations — will be an integral driver of generative insights in these data ecosystems via data sharing and data licensing. Data that can be harnessed for insights and decision making will also empower the workforce and drive value and growth for organizations in unprecedented ways.

Mastering Data Ecosystems

Today, we are using data in ways we couldn't imagine just a year ago. Outmaneuvering the future’s many obstacles requires businesses and government entities to prepare now by rearchitecting their end-to-end data ecosystems to ensure the data, technology, people, processes, and strategies are all in place to leverage data in transformational ways.

The first step is integrating data strategy into all other forms of organizational planning. This will enable organizations to become data driven. But that policy needs to be backed up by robust data systems and comprehensive end-to-end strategies for capturing, storing, processing, presenting, and leveraging data.

Data integration will also be key. Public and private entities will increasingly rely on the unprecedented interconnection of their data architectures, as well as on a symbiotic collaboration of people and technology, to unlock vital opportunities for growth.

For many organizations, this will require a complete transformation, not just of how organizations collect and use data, but also of the people, processes, technologies, and infrastructures that govern, manage, and enable the movement and transformation of that data.

Charting the Transformation

With the pace of innovation accelerating, organizations can no longer plan for a future technology state they can predict or understand. Leaders and chief data officers must chart a more flexible data future, one that maximizes agility and velocity, while maintaining privacy, security, and corporate ethics.

Rather than working toward a concrete future technology state, they should focus on building the capabilities necessary to quickly take advantage of the next revolutionary technology or ML application. They will also need to build a workforce able to imagine and deploy data-driven initiatives rapidly to outwit competitors.

Organizations must plan for how this inevitable techno-human symbiosis will impact the workforce. Jobs, and the workers required to fill them, will change when the workforce is assisted by increasingly powerful, but imperfect, technologies. Leaders should consider policies and procedures on the use of generative AI, hiring for adaptability rather than current skills, retraining workforces, and implementing organizational change management strategies.

Having a robust data ecosystem will simply be table stakes in the future. As organizations strive to overcome complexity, data will be at the heart of every solution. And only by maximizing the collaboration between people, organizations, and technology will we begin to reap data’s full promise.

As data will be critical to most organizational strategies, central to understanding, evaluating, and reducing risk, and a driver of growth and performance going forward, crafting a strong data ecosystem must be an investment priority. It’s time for all organizations to build a resilient data architecture made to meet the manifold challenges they’ll face today and tomorrow.

Read part two of this series to learn how a phased approach can help organizations successfully enable ecosystem-wide datafication.