Data and analytics have arrived.
The number of devices connected to the internet – already in the billions – will grow at breakneck speed over the next few years. The amount of accessible data being generated from phones, sensors, payment systems and cameras is projected to double every three years.
Machine learning is also becoming ubiquitous. Large data sets can now be analyzed more effectively using artificial intelligence and predictive modeling, 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 top companies and the rest of the pack.
John Bruno, chief executive officer, Data & Analytic Services, Aon, underscores the opportunity: “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.”
The stakes are high. Companies across industries – such as health care, insurance and logistics – are being redefined by the Internet of Things and analytics revolution. C-suite executives that can capitalize on the potential of data and analytics will differentiate themselves in the market; those who fall behind risk becoming irrelevant.
“What data is most valuable and how are we analyzing it to create value? How can I reorient my business model to capitalize on the potential of machine learning? What are the implications to our company culture, portfolio mix and value proposition?” C-suite leaders around the world are asking these questions – and for good reason. Data and analytics have the potential to upend existing business models across industries, and many executives are struggling to understand how. The need is urgent.
Improving Patient Experience And Cutting Costs: Health Care
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 health care systems, the focus is on using data and analytics to enhance the quality of care for patients while also managing increasing health care costs. New technologies and predictive analytics can help prevent and manage chronic diseases and provide early identification of potentially life-threatening conditions, such as post-surgical infections.
For payers, such as employers and insurance providers, the opportunity lies 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.”
Kuhn emphasizes the need to design effective technology systems to support analytics activities at scale. “Information technology and data architecture is often the difference between companies who use data effectively and those who don’t,” Kuhn says. “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.”
Managing Risks And Improving Product Delivery: Insurance
The insurance industry has historically collected vast amounts of data, and companies have started to deploy new analytics solutions to better understand risk and improve claims outcomes.
Enter InsurTech – the term used to describe the use of technology innovation in insurance. “We’re seeing huge investments in InsurTech designed to improve the customer experience on the consumer side and improving overall risk management on the commercial side,” states Jobay Cooney, senior managing director, Aon. “This type of industry disruption can be an opportunity for all involved, as carriers can forge new partnerships with startups to leverage emerging technologies.”
For example, insurers struggling with “claims leakage” – the difference between the actual cost of a claim and what the claim should have cost – are finding that digitizing the claims process can assist carriers in adjudicating claims, reducing costs and designing a 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.
For any industry to tap into the full potential of data and analytics, prioritizing data quality and governance is paramount. “Data exists everywhere, but not all of it is actionable or organized in a useful way,” says 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.”
Improving Supply Chain Efficiency And Transparency: Logistics
Thanks to the multitude of variables in a supply chain – from rolling stock to the goods themselves – 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 and opportunities to redesign supply chains.
Once the data have been collected, predictive and prescriptive 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. “You have to start with the business problem you’re trying to solve,” Meyrick states. “Your data and analytics strategy should serve your larger business strategy. 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 enterprise value. Look 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 yet aren’t being properly valued for that effort,” 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.
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