In this contributed article, Chonchol Gupta, CEO, Rebirth Analytics, believes that if enterprises want to identify and swerve risk, they require a radical rethink of how they obtain the data that fuels their analytics engines. With a long pedigree in Fintech, InsureTech, and supply chain innovation, Chonchol has more than a decade’s experience as a consultant to both foreign and domestic government financial organizations, and as advisor to public and private financial institutions. Among his previous roles, Chonchol has served as Vice-Consul for the United Kingdom’s Department of International Trade, where he was charged with assisting the British Government’s interactions with finance and insurance institutions in the Southeast United States. He is an in-demand speaker, presenting at many of the world’s most important financial conferences, and co-author of the Federal Reserve Bank of Atlanta’s white-paper on Faster Payments.
STANDFIRST: If enterprises want to identify and swerve risk, they require a radical rethink of how they obtain the data that fuels their analytics engines
If business analytics delivered what it promised, why were so many enterprises unable to swerve or mitigate the chaos of the last three years? The answer is simple. It’s not a problem with the box – it’s what we feed it.
Like an elite athlete or a high-end sports car, analytics needs the right fuel to reach peak performance. Fully fed with the right data, AI brings a wealth of meaningful, comprehensive and above all contextualised analytic insight across the entire range of enterprises’ operations and relationships.
But all too often, that’s not what’s happening. Instead of using reliable data from multiple trusted sources (including the organisation’s own data), analytics systems get a trickle of thin gruel. As a result, the insight they produce is, if not exactly untrue, then a skewed and incomplete version of the truth – and certainly not enough on which to base strategic decisions.
Enterprises urgently need to unleash the power of analytics to identify and react to risk and opportunity, wherever it arises. To do that, they need to feed the AI beast.
Digital transformation delayed
For years, businesses have been undertaking long-overdue “digital transformation”; the problem has been that many didn’t grasp the urgency of these initiatives – and by the time the pandemic hit, the real work had barely begun.
Today, data that should be answering powering analytics engines often sits uselessly in silos, compiled in multiple formats, and unable to be integrated into a single, horizontal vision of reality. One of our customers even admitted they wanted to buy five licences for our risk analytics system so that they could apply it across their various silos. That’s not how it works.
If you deploy five versions of the same software in five departments, you’ll get five versions of the truth. Moreover, the “insight” provided will be stripped of any context and meaning, because the AI is only chewing on single, siloed sources of data.
The stakes are immeasurably higher now, with the management processes of just-in-time supply chains severely disrupted during the pandemic, posing difficult questions for senior management about how to rebuild more resilient yet still-lean procurement. Meanwhile the burden of complexity grows ever heavier, with more uncertainty, more regulation, and more obligations than ever before. From ESG to KYC to AML, from EU regs to health and safety standards, businesses need not only to know but to prove their entire supply chain is compliant.
How can businesses set their data free? The answer lies less in technology than it does in something distinctly old-fashioned: relationships.
Compiling data from across various departments is a relatively simple endeavour. Organizations need much more than this, however. They require a comprehensive understanding of all the risks they face across their supply chains and trading relationships to identify potential problems before they become crises. Crucially, they also need a real-time view of various financial, macroeconomic, legal, and geopolitical risks – and, crucially, how they interact – for this insight to be truly valuable.
Most of this information resides outside the corporate firewall. Some of it lies with specialist organizations that monitor politics, climate, and the changing patterns of international trade; most of the real “gold,” however, sits with enterprises’ suppliers. One of the most important things a business needs to know is the financial health of their partners; for example, whether they are struggling with cash flow and may be in danger of failing to fulfil their orders.
Gathering this information is mostly legwork. Suppliers must be convinced to share their financial, compliance, sustainability, and other metrics with a trusted analytics vendor, which then combines this with other trusted third-party sources to create a layered, holistic view of an organization’s current and future risks – as well as the risk profiles of individual suppliers.
Suppliers may be initially reluctant to share this data because they worry that they’ll get the chop if they reveal temporary financial difficulties (or they will feel like they will get circumvented if they disclose their ops). But that’s the very opposite of why businesses need to understand risk. Anyone can react to events, but it’s proactivity that turns your supply chain into a competitive advantage – when it’s based on reliable data. Chopping and changing suppliers is disruptive; instead, buyers should much rather find creative ways to help suppliers, such as more flexible payment terms.
All the data and all the technology already exist to understand risk more minutely and more accurately than ever before, and to reimagine and strengthen relationships across the supply chain. One day, this transparency will be taken for granted, and we’ll have a global risk information system to which every business will happily contribute. Until then, any business can understand the full range of evolving risks they and their partners face, simply by unlocking the information to feed their analytics – and so transform their strategic decision-making.
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