Sailboat racing has come a long way since the America’s Cup was first run in 1851 (making it the world’s oldest international sporting trophy). Today’s boats are typically fitted with over 1,000 IoT sensors that measure everything from weather conditions and boat position to the forces being exerted on the boat’s structural components.
These sensors generate hundreds of gigabytes of data during each day of sailing – and provide key insights for improving race strategy and minimizing risk. As we know, the willingness to use analytics in sports has been going on for quite some time now.
The world’s total data continues to explode in volume, velocity, and variety and is expected to reach around 44 zetabytes by 2020 (and keep in mind that 1 zetabyte alone is approximately 1,126,000,000,000,000 megabytes).
The challenge for business leaders is to make sense of this ‘noise’, or more specifically to mine the data for the precious insights it contains.
Risk management is one of the areas in which big data joins forces with analytics. And it’s here that business executives have requirements not too dissimilar from a sailboat crew, as both groups search for:
Risk management and big data has been a combination that’s flourished principally in the area of financial services, driven by operational concerns that include:
Fraud detection: and using analytics tools to interrogate huge chunks of data to spot patterns and behaviors. The emphasis here being to identify any deviation from ‘business as usual’ which could offer a warning of malicious activities.
Cyber security: where real-time analysis of big data can help monitor events against predetermined rules to identify signs of potential danger, backed up by mechanisms for preventing data loss.
Scenario analysis: which in the past has been challenging to create, but where big data enables larger samples to be used to enhance accuracy – alongside predictive analytics that deliver more intuitive insights and faster decision-making.
The risks of getting hacked, poor planning, or being a victim of fraud are worrisome for any organization. Risks that become more systemic as the business universe becomes ever more interconnected, and where one problem can quickly infect whole ecosystems of production.
As a result, the use of analytics and big data has expanded beyond traditional risk areas and into more operational scenarios, including:
The examples above offer a clear indication of the risk management insights available from big data. It’s also a tech segment that continues to grow – the big data market alone is set to be worth $56 billion by 2020.
The simple truth for business leaders and sailboat captains: if you’re not exploiting all the data assets available to you, chances are the competition is.
But the race to becoming a ‘risk aware organization’ begins the moment you install the capabilities needed to kick-start your big data platform. Which is where a partner like COMPAREX can help you get off to a flying start.