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How to use graph database and analytics to manage effectively during turbulent times

(Image credit: Image Credit: Shutterstock/Sergey Nivens)

Covid-19 has impacted all of us on multiple levels. Headlines about the rising number of global cases, government stay-at-home orders and job losses are reminders that we are living in turbulent times. “Uncertainty” seems to be the operative word worldwide right now -- uncertainty about our overall physical health and economic health.

Major economic powerhouses such as the State of California (fifth largest economy in the world with $2.747 trillion in GDP contribution) and several other U. S. states have issued stay-at-home or shelter-in-place orders, bringing the daily activities and economic consumption to a grinding halt. Also, every major country has or is in the process of implementing social distancing measures, with 1.3 billion Indians urged to stay home in a curfew/quarantine by the Indian authorities and the government of Greece restricting all non-essential movements. The United States Government announced a 30-day suspension of travel from the majority of the European countries including the UK and Ireland, an unprecedented move that’s likely to broaden if the Covid-19 infections continue to rise in the next few months.

The result of all these actions? A major disruption to the global economy. This disruption is unprecedented, as it delivers two major shocks at the same time. The first shock pertains to the global demand for goods and services. From bars, restaurants, and hotels to planes, trains, and automobiles, a sudden drop in economic activity is leading to a sharp drop in the demand for goods and services. How big is the drop in economic consumption and demand? Taking the oil industry as a proxy for economic demand, the economic consumption appears to have fallen by around 10 million barrels a day or a 10 percent drop in the global economic activity in a single month. In 2008/2009, U.S. industrial output declined by almost 20 percent from its pre-recession peak, but the decline was stretched over a period of roughly 18 months. That makes Covid-19 the biggest demand shock ever for the global economy.

A shock for the economy

The second major shock is to the global supply chain with reduction or total shutdown in factory output. This supply disruption has affected copper mines in Peru, Samsung and Apple supply factories in South Korea and automotive manufacturers across the globe from the United States to Europe, bringing parts of the global supply chain down with no immediate backup plans. Supply chain impact on finished goods as well as the value chain supplying the parts is especially acute since the entire manufacturing industry has optimized and lowered the inventory with just-in-time production models over the last two decades. These lean value chains do not have a lot of excess inventory that can make up for the shortfall in production.

What do these two major shocks -- a steep drop in demand for multiple segments and a sudden disruption in the global supply chain -- mean for the local, state, national and global economy? These shocks will test and expose vulnerabilities within three key areas of the financial infrastructure:

Cash flow and resulting liquidity crunch for small businesses -- Most small businesses have the cash on hand for operating 10 days or so without the daily revenue influx. An abrupt pause in economic activities cuts the revenue for multiple small business segments such as hotels, bars, and restaurants to less than half of their regular daily income. All of these businesses have loans that were used to buy the equipment, furniture, and supplies for the business as well as pay insurance, worker wages, leasing costs and a host of other financial responsibilities. A prolonged softening of demand will lead to delayed or missed payments on the loans, furloughs, and layoffs of the daily workers, which in turn puts these loans in jeopardy.

Modeling the impact

Graph database and analytics solutions can model these complex interdependencies, modeling the impact of the drop in daily revenue for various small business segments. These include the servicing of loans. We can track the loans back to the financial institutions -- banks, credit unions, governments, and other creditors -- that are holding those loans as a part of their portfolio. These institutions will bear the brunt of the worsening credit risk associated with the loans. The financial crisis of 2008-2009 was caused by an insufficient understanding of how home mortgages were bundled. Mortgages were sliced and sold broadly, making the risk assessment a very complex process. The financial institutions, as well as the government, can avoid a repeat of the 2008 scenario by modeling a 5+ level-deep financial dependency and impact analysis of small business loans using a graph database and analytics solution.

Excessive debt and corresponding risks for manufacturers, distributors, and retailers -- Global economic expansion since March 2009 has resulted in the rapid increase of corporate debt, especially for manufacturers across the globe and in the U.S. Since Q1 2011, outstanding debt among nonfinancial corporations in the U.S. has grown by an average of 5.6 percent per quarter year-over-year. At 46.4 percent of GDP in Q3 2018, non-financial corporations are carrying more debt today by this measure than they were just prior to the Great Recession of 2008-2009.

As the manufacturers deal with global supply chain disruptions as well as factory output drops or shutdowns, graph database and analytics solutions can model the impact on the global value chain. This value chain includes the manufacturer of the parts in Germany, Italy or South Korea, the finished goods (such as an automobile or an iPhone), the factory, the freight business, original equipment manufacturer as well as the distributors and retailers who sell those products. New information, such as Covid-19 spread through local communities or border transport restrictions imposed by governments, requires agile supply chain planning solutions. These solutions must be capable of performing what-if analyses on the fly across complex global value chains. Native parallel graph database and analytics solutions were built to address these challenges, as they provide corporations as well as governments with a single pane of glass through which to view the entire global commerce value chain -- and analyze and plan responses for each event as it unfolds.

Staying one step ahead

Rising short-term unemployment and household debt servicing -- Currently, Goldman Sachs predicts a steep 24 percent drop in GDP for the second quarter of 2020 for the U.S. The unemployment rate is likely to spike up to 9 percent in the short term. Experts predict economies around the world will suffer a severe near-term contraction, resulting in soaring unemployment for the short term. The global economy is expected to recover in a few quarters, but the timeline is driven by multiple factors, including major uncertainty involving Covid-19. When will the infection rate slow down globally? When will a vaccine be available? These are all still open-ended questions. 

Native parallel graph database and analytics solutions can model the multiple levels of dependencies, beginning with layoffs in specific industries, the sharp increase in unemployment benefits and the resulting burden on counties, states and the federal government. Also, mortgage, credit card, automobile, student and other loan payment delinquencies result in a liquidity crunch for the financial institutions holding the paper on the loans. Modeling the what-if scenarios using the graph database and analytics solutions allows the governments and financial institutions to be prepared with possible next steps. These next steps will be key to soften the blow for the affected consumers and protect the liquidity for our complex financial value chain.

As the emergence of Covid-19 has taught us, one event can have a far-reaching effect on the many intertwined components driving our economy -- from global supply chain disruptions to fluctuating employment numbers and consumer spending patterns. We can work to stay one step ahead by examining economic “what-if” scenarios -- and graph database and analytics can help us do that. While we can’t control all the variables within the economic ecosystem, graph is our best line of defense to prepare, plan and manage during turbulent and uncertain times.

Gaurav Deshpande, VP of Marketing, TigerGraph (opens in new tab)

Gaurav Deshpande is the VP of Marketing at TigerGraph. Deshpande brings to TigerGraph a proven track-record in leading teams in creating new products, establishing new markets and dominating industries. Previously, he spent 15 years overseeing marketing for IBM's Artificial Intelligence, Blockchain and Cloud portfolios for the Banking and Financial markets, Telecommunications and Retail. He also built out and positioned IBM’s Big Data and Analytics portfolio, driving 45 percent year-over-year growth. Before IBM, Deshpande led two startups through explosive growth, i2 Technologies and Trigo Technologies.