What was once known as knowledge is power has now become data is power. It’s enough to say that about 90% of the available data has been created only in the last two years. Back in the day, Gutenberg’s printing press hastened the pace at which knowledge was produced. Today, data science is not only pushing the knowledge processing limits, it is also delivering knowledge in a more concise manner, customised to one’s particularities. In the world of negotiations, one cannot function without knowledge, but one can be more effective by receiving information at the right time and in the most appropriate format. Data science presents an opportunity to achieve that. However, the question is how agile negotiators and policy-makers can be in embracing the innovation data science would bring to the table.
How are negotiations today?
In today’s negotiations, teams follow an iterative process before reaching a deal:
- Preparation (gathering information)
- Discussions (within the team)
- Deliberations with the counterpart (negotiation rounds)
While each stage of the process has a unique value towards the final agreement, the first one is the foundation for the entire negotiation. Hence, if the negotiation is well prepared with the right information and probable scenarios, its success rate is higher.
However, success of the preparation stage is conditioned on how negotiators collect and process the needed information. Most often, they use their cognitive abilities to gather the different pieces relevant to the topic. And as much as that is commendable and natural to the human being, negotiators risk losing some vital information. Indeed, they are subject to a plethora of information channels: the lobby during a coffee break, the dinner table, etc. If around 90% of information learned gets dissipated within a week, one could imagine what that means for an entire negotiation where interactions are unstructured, information is scattered, impartiality is irrationally assumed and attention is studiously required most of the time. A lot is demanded for the limited brain capacity.
As a consequence, the team enters the deliberations stage with incomplete and biased information. This causes the negotiations to either last longer or end with a less attractive compromise. The agreement, if reached, would likely be far from the Best Alternative To a Negotiated Agreement (BATNA). The negotiation, should it continue, would then favor one party over the other. To have a “Nash” negotiation - one in which both parties win - a proper understanding not only of one’s position (priorities and preferences) but also that of the counterpart is required. That means the team would need to gather and process more information in a dynamic manner, and look for trends and patterns to produce less biased insights for decision-making. With the advancement of technology, and data science to be more specific, that is possible.
Why should negotiators capitalise on data science?
Data science is already changing many fields in life. Google searches provide hints of where the next flu outbreak will take place, which segments of the population will vote for this or that politician, where and when the next public strike will erupt and when travelers can purchase a plane ticket at a certain cost. The list of examples can go on. Now, imagine negotiators well equipped with data science tools that would enable them to extract the right information and transform it into actionable insight at the right time. However, the use of data science to negotiators is not limited to tools one has to learn in order to be the savvy negotiator of the future.
In fact, more important than data science tools (which go beyond the scope of this article) is the mindset of a data scientist. It is what a negotiator could tremendously benefit from. Mindset refers to the negotiators’ ability and willingness to develop a rigorous process for organising, exploring, filtering, triangulating and transforming information into insights (OEFTTI). Each team member contributes to the pool of information, but they need a well-designed information system to optimise the use of that raw data. To kick-start the development of data science in their team, negotiators have to adopt an innovative mindset and rethink the cross-functionality of their skillset.
All in all, data science can be highly valuable to negotiators and policy-makers. Nevertheless, deriving benefits from the burgeoning field will depend on how much resource (financial, time, effort and flexibility) one is willing to allocate to merge both worlds of applied negotiations and data science. During that process, the negotiator would have to learn about that new hybrid world and can thereafter become an insights-driven negotiator. After all, data science is not here to inhibit a talented negotiator from being spontaneous in a given situation; to the contrary, it is meant to expand and refine the knowledge repository of the team.
WALID LUTFY, INP '14
Behavioral Economist & Data Scientist, Behaviour (Sydney, Australia) and UAE Federal Government
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the position of The Graduate Institute Geneva.