The number of devices connected to the internet will grow rapidly over the next few years. And the amount of accessible data generated from these devices, like phones, sensors, payment systems, and cameras, is projected to double every three years.
The data and analytics revolution is already redefining companies across industries, including healthcare, insurance, and logistics. Understanding how these industries are adapting to the potential of this revolution will prepare leaders for improving their business and increasing its value.
“Companies that are able to extract insights from data and act on them to manage volatility and improve operational performance will build significant enterprise value,” according to John Bruno, chief executive officer, Data & Analytic Services, Aon.
Big data sets can also now be analyzed more effectively using machine learning, turning data into insights that enable better decision-making. Increasingly, the ability to sift through masses of data, recognize patterns, and drive insight into unmet customer needs will be a key differentiator between companies.
Healthcare: improving patient experience and cutting costs
The human body contains approximately 150 billion zettabytes of genetic data. Advances in wearable technology like smartwatches and predictive analytics found in mobile health (mHealth) apps are making it possible to collect, structure, and process this high volume of data to improve health outcomes.
For providers, like doctors and healthcare systems, data and analytics can enhance the quality of care for patients while also managing increasing healthcare costs. New technologies and predictive analytics can help prevent and manage chronic diseases and identify potentially life-threatening conditions earlier, such as post-surgical infections.
For payers, like employers and insurance providers, the opportunity is in cutting costs and incentivizing value over volume. “Health plans and insurance companies are using claims and service delivery analytics to better detect fraud and eliminate claims abuse,” says Geoffrey Kuhn, senior vice president and actuary, Health & Benefits, Aon. “Advanced analytics can help incentivize the delivery of value-based care.”
In healthcare, effective technology systems design is key to support analytics activities at scale, which is true across industries. Kuhn emphasizes, “Companies that succeed at achieving their analytics objectives are able to integrate traditional data warehousing with new technologies to support real-time data collection and insightful analytics.”
Insurance: managing risks and improving product delivery
The insurance industry has historically collected vast amounts of data, and companies have started to use new analytics solutions to better understand risk and improve claims outcomes.
The increasing investments in Insurtech, the term used to describe the use of technology innovation in insurance, signals the use of emerging technologies to improve customer experience and overall risk management, according to Jobay Cooney, senior managing director, Aon.
For example, insurers struggling with “claims leakage”—the difference between the actual cost of a claim and what the claim should have cost—find that digitizing the claims process can help carriers adjudicate claims, reduce costs, and design more consumer-friendly engagement.
The industry is also beginning to use aerial imagery through satellites, drones, and piloted aircraft to understand and underwrite risk and expedite claims payments after catastrophic events.
Data quality and governance is important in the insurance industry, but all industries need to prioritize it to tap into the full potential of data and analytics according to Cooney: “When exploring new data sources, it’s important to define the use case, where it’s coming from, and who owns it. You need to mandate data hygiene to ensure you’re able to drive new insights that are actionable and result in improved outcomes.”
Logistics: improving supply chain efficiency and transparency
Thanks to the multitude of variables in a supply chain, data and analytics have become a critical tool in ensuring the efficient delivery of products around the world. As a product makes its way along the supply chain, RFID tags, GPS, and scanners at every step generate data that can provide companies with unprecedented visibility into the movement of goods.
Once data has been collected, analytics can be used to identify potential issues in the supply chain. Disruptive technologies such as blockchain can also be used to help increase understanding of overall flow of trade, track specific items, and provide companies with the insights to better manage and mitigate risk.
“Forward-thinking companies are already making sense of the vast amounts data and finding ways to better manage and mitigate supply-chain risks,” says Lee Meyrick, chief executive officer, Global Marine Specialty, Aon. Understanding all the opportunities associated with data is essential, notes Meyrick. “Entire business processes can be re-written and optimized if the right technology and the right information are in place.”
When applied to the right business challenges, insights from data and analytics can help organizations create significant value. Looking at the top stock indexes today, data-driven technology firms dominate the top 10 as intangible assets such as intellectual property have replaced tangible ones as the major source of corporate value.
And it’s not just tech firms that have the opportunity: “Many companies are adopting technology-enabled business models,” says Bruno. “Data and analytics can help organizations anticipate opportunities to create value and manage volatility in ways that customers, investors, and ratings agencies will ultimately reward over time.” With more than 84 percent—$19 trillion—of the S&P 500’s market cap defined by intangible assets, there’s clearly dollars in the data.