Businesses need to change the way they evaluate risk to their global supply networks. Social network analytics can 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:
- They’re expensive: only big companies can produce them, and typically only when they make decisions about new projects, investments or suppliers. Also, they don’t offer continuous analyses and trends about how situations and risks change.
- The analysis typically focuses only on one country, region and/or industry sector. They don’t analyze how it is linked to other places, and how risks or disruptions can be initiated elsewhere.
- It’s hard to build proper scenario tools from these reports. For example, if something happens in Country A and it has an impact on Country B and C, and we have an important supply chain in Country B, what do we do? Is it better to establish a new supply chain from Country D or E?
- Often the risk analysis focuses only on a few well-known factors – e.g., if there is a serious political risk of some resources being nationalized, the banking system is unstable, or the currency and tax environments are risky. But there can be other factors that start a chain reaction. Sometimes it can be quite unexpected, but some other (weak) signals can help to estimate that something unusual but significant is happening.
- The network analysis is poor – i.e., many analyses focus on the nodes of a network, but the links between nodes and their characteristics have not been analyzed properly.
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:
- Local Alphas (those who have an important impact on others in their own communities) depend on context – i.e., people have an impact on others on certain topics, but not the same people on all topics
- Weak links are important for networks. They basically make something spread from one community to another (we saw this in practice with COVID too)
- Impacts spread through many routes. Something spreading in a network can have a very small impact on some nodes, but those nodes can still spread the impact to other nodes that could then feel a stronger influence. These aspects are probably relevant for economies and businesses too.
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.