GSAM's Fundamental Equity and Fixed Income teams discuss how big data can be a strategic advantage or disruptive force in companies and sectors.
Steve Waxman: We believe big data can provide a competitive edge for companies. For example, airlines were early adopters of using big data to optimize revenues through targeted pricing, which is now gaining traction across the transportation industry as a whole. As another example, we consider a well-developed customer loyalty program to be a positive indicator of strong future revenue in the consumer products, retail and hospitality industries. We think the quality of these loyalty programs and other forms of consumer purchasing data can be significant differentiators in these businesses.
Larry Tankel: Within the technology sector, vast amounts of infrastructure, computing power and storage are necessary to capture and process big data. Hyperscale Cloud providers are currently big winners. They allocate computing and storage resources dynamically based on demand and are increasingly the platforms on which these big data analytics programs run. Some of the legacy software and hardware players are also pivoting their businesses and adding cloud services to their offerings. Increased demand for computing power could also benefit semiconductor companies.
Large social media and e-commerce companies are another place we see opportunity. The large datasets inherent to these businesses position them well to leverage big data and provide faster services, more targeted advertising and a customized online experience. This should enable them to gain market share over time, creating longer-term profitability improvement and growth opportunities. Pure-play analytics companies also have an advantage stemming from the breadth of their services, which spans from security to business operations.
Steve Waxman: Big data may lower costs for companies by creating efficiency gains, particularly in the energy and utilities sectors. US shale oil producers are using technology to record well data from every hole made in the ground, which could help refine processes, reduce drilling times and lower costs. Utilities are increasingly deploying ‘smart meters’ that amass data on energy usage and could soon help curb outages and smooth demand periods. In the renewables space, European wind farms are eyeing big data for efficiencies in operation and maintenance, such as anticipating supply and preempting necessary repairs.
Larry Tankel: Retailers are also using big data to synchronize the flow of product from supplier to shelf. Better synchronization can improve the accuracy of inventory management, reduce lead times and lower the costs of transportation, handling and other fulfillment costs. Using big data to improve forecasting can also allow companies to lower safety stock levels in distribution centers and stores. When these initiatives are used together, we think big data can drive incremental cash flow and lower logistics and transportation expenses.
Larry Tankel: We believe a variety of businesses including healthcare, financials, advertising and industrials will be impacted to varying degrees. For example, the healthcare industry could see significant disruption through the advancement of data analytics, which should help improve the quality, efficiency and outcome of patient diagnoses while also reducing costs. Gene sequencing has become exponentially faster, more efficient and cheaper, leading to new possibilities in DNA sequencing and diagnosis. In 2000, the Human Genome project was completed in 13 years at a total cost of $3.8 billion, but today the human genome can be sequenced for approximately $1,000 per genome in less than three hours.
Steve Waxman: The insurance industry could see significant disruption. Consider ‘telematics,’ a technology for collecting data on driver behaviors, including speed and abruptness of braking. Most large European motor insurers are now offering the technology, which can be a standalone device or function as a phone app, as a way for safer drivers to get better prices. In the near term, this technology benefits early adapters and likely improves loss ratios and therefore margins. In the long term, the initiative could be a negative for the sector if it keeps premium rates depressed, especially since insurers are more likely to withhold discounts for bad drivers rather than increase prices. Some insurance startups are even moving towards providing ‘on-demand’ insurance for single items, which is based on their ability to use big data. To some extent, every insurer is going to have to be a software and analytics company in the future.