Businesses need to change the way they evaluate risk to their global supply networks. Social network analytics provide the data and tools they they need.
The Ukraine war and COVID have badly damaged many supply chains. We’re encountering an energy and food crisis with much higher prices. This has caused serious problems for many companies. This is especially true for companies that have done business with Russia and have supply chains there.
Many CEOs and executive team members claim that it was impossible to anticipate this kind of risk. That is quite a naïve claim. But it illustrates how poorly many companies have evaluated their risks and global supply chain networks.
With proper big data and network analyses, they could do it much better. In fact, they could learn a lot from social network analytics.
Geopolitical risks matter
Many enterprises have been lazy to evaluate geopolitical risks. Also, as I wrote earlier, since the Cold War era many executive teams have lived under an illusion that politics have no serious impact on their business, and therefore they can ignore it. We have also seen large companies – partly state-owned or having no strong shareholders – where the management has been willing to take high risks when the main upside is their bonuses and options if things go well. If they don’t go well, the shareholders pay the consequences.
COVID-19 was a more surprising disruption than Russia’s invasion. Of course, there were warnings and scenarios about a future global pandemic, but the timing and impact were obviously hard to predict.
But it is intellectually unsustainable to claim that it was impossible to see risks in Russia. The invasion of Georgia in 2008, and then Eastern Ukraine and Crimea in 2014, to say nothing of the Russian state taking over companies owned by oligarchs (e.g. Mikhail Khodorkovsky) who criticized Putin, foreshadowed what is happening in Ukraine now.
Maybe investors, businesses, and executives have now learned a valuable lesson. They cannot ignore geopolitical and global disruption risks. We are back in the time of realpolitik. So, what can they do in practice?
Reports are just snapshots
Traditionally, investors and businesses follow the reports prepared by governments, consulting firms, and think tanks to understand geopolitics and international risks. Larger companies have in-house analysts and also buy projects from the leading consulting firms when they make an investment decision in a new country.
These types of reports and consulting projects can help to make better decisions. But they have some fundamental problems:
Social networks also matter
Over 15 years ago, I was a founder of a startup business to analyze social networks between people. We focused mostly on marketing and advertising, but in some cases we also looked at risk management (e.g., criminal or terrorist networks). The idea was to analyze individual people, how they are connected to each other and how they have an impact on each other.
We all know that word-of-mouth and the influence of other people are important. At the same time, we also know one person can influence us in one thing (say, choosing a car) and another person can influence us in something else (going to a doctor). This model can be applied to countries, industries and businesses; they are linked to each other, they have dependencies on each other and links in different matters.
It is surprising that we are in a very fledgling phase when it comes to better analyzing those networks and links, and making proper risks analysis and scenarios based on them, when a lot of data is already available. There are probably many more analytics tools to analyze networks between people for advertising purposes than real life big data analyses of global business networks. Also, social network analytics of people is important to analyze the spreading of diseases too, as we saw with Covid.
Lessons from social networks
Some important lessons from social network analytics include the following:
Network analytics underutilized
The last two years should have been a wake-up call for businesses and executives that they must better understand and evaluate their global political environment. Most businesses are now a part of global networks. They should be able to evaluate their networks and understand how events outside their immediate network can have an impact on them.
It is not enough to make snapshot analyses when making an investment or selecting a new supplier. It is necessary to analyze the situation all the time, and also pick up on weaker signals that can become significant.
Basically, we need better big data network analytics for businesses and economies, and we need better scenario tools to make fast decisions when something significant in our network happens.
Open source has played an important role in software development over the last thirty years. It also matters in some other areas, such as intelligence. Open source intelligence has become increasingly important – especially since 9/11, but recent wars in Syria and Ukraine have made it more well known. Can open source intelligence expand to become much more systematic in tracking and predicting world events?
Bellingcat is an investigative journalism organization become the best-known user of open source intelligence. Bellingcat started in 2014 by investigating weapons used in the Syrian war. It analyzed photos from the war, trying to not only identify weapons and items in them, but also confirm the photo’s location.
Later Bellingcat became especially famous after it discovered who was guilty of the downing of Malaysia Airlines Flight 17, the Skripal poisoning, and the poisoning of Alexei Navalny. In those cases, Bellingcat combined information from many sources – not just pure open source intelligence, but also information from Russian passport and travel databases.
On the whole, open source intelligence has been the most important data source for Bellingcat. This open source intelligence consists of data from many sources, including social media updates, satellite photos, photos and information people are willing to share.
Most intelligence data is already publicBut of course, open source intelligence is much more than Bellingcat. It even has its own acronym: OSINT. Some countries have laws and regulations for OSINT. For example, in the US, the law defines OSINT as “intelligence derived from publicly available information, as well as other unclassified information that has limited public distribution or access.” After 9/11, the CIA launched an open-source directorate. Now US spy agencies have a foundation for this kind of activity.
Collecting intelligence from public sources is nothing new – it has been said that during the Cold War era, 80% of information collected by the intelligence services came from public sources, like newspapers, media, public documents and public speeches. What has changed during the last twenty years is that technology has developed significantly to enable collection of a lot of data that was not available earlier.
Publicly available satellite photos and videos, radar information, social media content, web cameras, public government data, academic databases and many other sources have made a lot of new data available. Nowadays, basically anyone can use powerful tools to search and combine data from many sources. This is what makes open source intelligence such a significant development.
Is the world safer or more dangerous with open source intelligence?Has open source intelligence made the world safer or more dangerous? Opinions are sharply divided. Some people say open source intelligence can hamper secret diplomatic negotiations that have sometimes been important to solve conflicts. When all parties can see the other’s actions, they must make countermoves rapidly, which can escalate quickly.
However, another opinion is that open source intelligence can prevent parties from taking action – or at least enable the public to see what they’re doing them early, which consequently makes it harder for them to prepare for something secretly. For example, last winter we saw public information that Russia had amassed a lot of troops and weapons at the Ukraine border. Nonetheless, many parties didn’t want to believe Russia would (or could) actually start a large-scale invasion.
The Ukraine war is also an example of where military personnel become sources of open source intelligence when they publish information on social media. There are even examples of how some Russian soldiers published photos of the entire route from their military base to a battlefield. As a result, such information could be helpful to anyone who seeks to determine which troops are used and how their logistics work. It also looks like some soldiers have published photos that could be used against them as evidence in war crimes cases.
Opportunities for more systematic models
Clearly, open source intelligence is already very important for investigative journalism and for intelligence services. But it can be much more in the future. Nowadays, a lot of this information is still analyzed partly manually.
When there is so much data available all the time, it is also possible to automate many analyses, and we’re starting to detect unusual events automatically and making various predictions based on data. This in turn could also expand the use of data and data analyses. For example, companies could better evaluate risks to their supply chains. Also, investment funds could evaluate risks for their funds, and companies could take into account the latest information in their investment decisions.
This requires complex data models, as well as the ability to combine information from many sources and understand the dependency between different events and objects. But at least for certain purposes, this is already very feasible. It is more important to make sure that some parties can start developing this systematically and find good business models for it. It could be something like Palantir, but based more on open source software and intelligence, and more transparent.
Open source software has changed the software industry. Open source intelligence has become an important tool for investigative journalism and intelligence agencies. But when the use of data is automated better, open source intelligence can be applied to many other use cases, including business. There is so much information available in the world nowadays. The question really is: who can make better models and tools to utilize it systematically?