Presentation given during the UN General Assembly 2017, at an event of the US department of Commerce.
Abstract: Leaders face high, continuous, and sometimes contradicting demands from all different stakeholders. Managing all these demands is walking a fine line, which in today's changing world is not a straight one.
A network view that includes human intuition allows for an approach that is forward-looking in an increasingly interconnected, uncertain and dynamic world. Based on the latest academic works in finance, mathematics, as well as the social sciences, Dynamic Risk Assessment (DRA) provides the credibility to convince shareholders and investors of the potential in shared value, including financial potential.
Dynamic Risk Assessment offers a comprehensive and quantitative analysis to determine strategic focus for realizing this potential without significantly damaging short-term profitability, while taking into account the interrelated nature of the SDGs, the internal corporate environment, as well as the world that the client does business in.
An organization can base its core strategy, as well as philanthropic focus on the output of DRA, so that the entire company, from R&D to the C-suite to the charity department, is doing their part in making the most of the organizations’ internal and external connections.
This is what leaders of all organizations face: high, continuous, and sometimes contradicting demands from all different stakeholders. Managing all these demands is walking a fine line, which in todays changing world is not a straight one.
Dynamic Risk Assessment is new method that allows our clients to map their risk/opportunity network. Dynamic Risk Assessment (DRA) combines the power of mathematics with human intuition in order to come to a more forward-looking way to quantify systemic risk.
I will start with a summary of the DRA method, and then make concrete what DRA can do for SDG strategy setting within businesses.
The Genesis of DRA stems from the Global Financial crisis of 2007-2008. The biggest financial institutions, regulators, and Credit Rating Agencies, all with very smart people working in them, did not see the systemic risks until it was too late. Our models, with their seductive level of certainty, had done little more than lull us into a false sense of safety.
So, in 2009, some people started to wonder how we can predict the future in a better way.
This led to the insight that many of our models, such as VaR, has been tested on a period of unusable stability. We can call it abnormal normality (As a side note: remember, normality was also an assumption made on distribution of errors in the models on slide 4).
It is not the world we live in today.
Our world is increasingly interconnected. Technologically, financially, socially, and of course environmentally.
An increasingly interconnected world is also an inherently dynamic, unstable, and thus unpredictable world.
So why do we still often view risk in this way? As if a risk occurs in isolation? As if its impact and likelihood are constants?
DRA supplements the old way of looking at risks with an a network view. Because risks do no occur in isolation, they influence each other.
How do we arrive at the network?
We use expert elicitation. ONE expert is about as accurate as a dart-throwing monkey. However, science tells us that A GROUP of experts, a diverse group that is, is the best forecaster you can get in an unstable world.
The World Economic Forum sues expert elicitation as well for their Annual Risk Report, for example.
Once we have the connection overview, and the forward-looking input form participants, only then do we apply mathematics in order to arrive at metrics usable to base business decisions on.
DRA has already been successfully applied by KPMG to major clients in both Audit and Advisory. DRA is industry agnostic, and has been applied in U.S., Europe, Japan, Australia and New Zealand, with interest from Canada, South Africa, and Brazil.
Typically clients have been those that have learned relatively early on (sometimes the hard way) the importance of connection and how they can be impacted by external forces,.
Why apply DRA to the SDGs?
The dynamic systems thinking that is at the DRA’s core is really applicable to sustainability challenges. Relationships aren’t stable, and they’re not predictable based on past data. We know that not achieving the Paris accord, for example, is going to be harmful, but nobody knows exactly how the climate change.
Secondly, the use of expert elicitation aligns with major sustainability trends. This goes being the theme of inclusivity. It goes to the latest insights on how we need to organize ourselves. The notion of iterative policy setting, of the need for enhanced communication and collaboration. To be nimble and resilient, rather then dominate and stick to top-down strategies.
Current hierarchical structure can get too focused on self-preservation. By talking to a diverse group of experts throughout the organization, we tap into what Harvard professor Leith Sharp calls the “sensing capacity” of an organization, allowing leadership access to their knowledge and intuition so they can respond to emerging issues quicker.
What will the output of DRA on the SDGs look like?
Firstly, we have the old familiar look at risk.
Please note that the nodes in this graph have been plotted randomly, for illustrative purposes only. No conclusion whatsoever can be drawn from this particular plot.
A cluster is a group of risks that tend to occur together. So when one risk materializes, the likelihood of the other risk increases as well.
The cluster analysis will help you avoid underestimating how the combined impact of sustainability trends hurt your business. We saw how this happened in the financial crisis, and we believe that the underestimation from many companies of the cluster risk stemming from sustainability challenges is real threat to economic stability today as well.
The centrality part of the analysis tells us which risk (or: nodes) are most influential or influenced.
The nodes that are most influential have the most effect within the network. In other words: focusing on these nodes will indirectly influence the entire network. We have seen clients turn around their entire business by focusing on the 3 most influential nodes. The most influential nodes in an SDG network are a way to not only safely practice sustainable business with optimal focus, but an opportunity to turn these efforts into a core strategic advantage.
Then there are the most or influenced nodes. These are a company’s vulnerable nodes. An organization does not have much influence here; directing efforts here will be inefficient because the entire network is working against you. Yet, these nodes are very important to the organization, because if these risks materialize it will likely be the end of it. This is where a company will want to focus its philanthropic efforts, to raise awareness around this SDG. It should partner with organizations that have more direct influence on this risk.
In many companies, philanthropy is a separately operating unit in the company, maybe connected with HR and PR, but quite divorced from core operations. But stakeholders these days are asking more. The new message is that sustainability, or specifically the SDGs, are good business, i.e., it should be at the core of what a company does. Still, no business can focus on all 17 SDGs. So companies are still struggling with where to focus and invest. With DRA we use the latest in network mathematics and social science to help an organization determine its core strategy, as well as philanthropic focus so that these two are working coherently, mutually reinforcing, and thus effectively.
Finally, we add the aspect of velocity. This will help manage the typical trade-off of profit loss due to investments in the short term versus safeguarding long-term profitability. It will also avoid, again the underestimation of how fast a risk will materialize. Because note that the velocity of a cluster is…. The minim velocity of any risk in that cluster.