iscover
Team decision making is critical to team performance, and you should start planning today how you are going to take advantage of the opportunity, writes Bryan Whitefield.
While every one of us is entitled to make a mistake, behavioural scientists have known for decades the core influences of poor decision making. Our biases and how our changing environment and its impact on our emotions can affect our decisions hour to hour, week to week, month to month. Daniel Kahneman, Olivier Sibony, and Cass Sunstein coined this “noise”, in their 2021 book by the same name.
For example, the same decision made a month apart might be made differently because you or the team are under much less, or much more, pressure than the month before. The result is a less-than-stellar scorecard for team decision making and team performance.
The statistics range from a 50 per cent success rate for strategic decisions, according to various surveys from the likes of McKinsey, to 86 per cent for complicated decisions, according to engineering reliability studies. This is a high distinction in universities. However, the 14 per cent we get wrong is an immense cost to our productivity due to the impact on people’s time, energy, and distraction from important work.
AI is already a proven antidote to suboptimal decision making.
Data-driven decisions
The most obvious is data-driven decisions. You will be familiar with the term “it’s a black box”, which refers to a data model that you can’t see into, to know how it works. Yet, study after study has shown it provides answers that are more reliable than humans, provided they are built, tested, and implemented correctly.
With rapid improvements in machine learning, the black box is now more like a black hole. An increasingly dense object in space sucking in data from all around it. Only the most advanced scientific brains can analyse it to understand some of its inner workings. Regardless, ignore their power at your peril.
AI for the data-starved
Unfortunately, you, like many, many organisations, are not data-ready. You don’t have data, or the data you have is not reliable or is in disparate systems that don’t talk well to each other. Notwithstanding that the best time to start a digital transformation was yesterday, AI can help with team decision making.
The simplest and most beneficial use of AI in these relatively early days of AI tool availability at our fingertips, and at the sound of our voice, is to use AI to help us think and write. Take any decision, and with an appropriately framed question to an AI tool like Copilot or Chatsonic, you can get a summary of a diverse set of opinions on the topic. Chatsonic also allows you to utilise its AI to improve the question you are asking. See the call out for an example using Chatsonic.
Warning. The “facts” presented by AI need fact checking. Regardless, the real benefit is in the angles it ensures you consider. In this case, aspects of market growth, competition, consumer sentiment, inflation, and economic trends. These are all things you are likely to have considered but with different stimuli to your thinking.
AI to counter ‘noise’
Neuromarketer Roger Dooley reported on a study of over 1,400 advertising campaigns from a database held by the Institute of Practitioners in Advertising in the UK that ads selling on emotion only were twice as effective (31 per cent versus 16 per cent) as ads selling using rational only content, and even outperformed ads that combined emotion and rationale (31 per cent versus 26 per cent). That is, people make decisions based on emotion over logic. If people are not emotionally ready to consider the logic, they don’t.
The implications for your team’s decision making are that you need to be aware of your team’s emotional state, and that is where AI can help; however, you could be entering a minefield. AI is increasingly capable of analysing written communications using natural language processing (NLP) tools to analyse emails, chat messages, and other written communications. Applications are available to help gauge the emotional tone of team interactions and sudden or slow-burning shifts in sentiment that may indicate underlying issues.
AI is also capable of analysing facial expressions during video calls or in-person meetings to provide near real-time insights into emotional states. This method has shown promise in accurately detecting emotions such as happiness, sadness, and frustration.
AI can also be used to create the interventions required when a team’s emotional state has shifted to a place where team decision making may be adversely affected. These can be in the form of a chatbot working as a coach.
Utilising these tools can create a minefield of ethical and regulatory challenges, not to mention some team members may simply choose to leave rather than be subjected to such a level of intrusion. A Cornell University study found that if you can positively frame the technology as assisting each team member and the team to develop, these approaches can be successful. Much depends on how the information is utilised and explained to the team to digest and act on.
Opportunity or risk
There is no doubt that AI presents both an opportunity and a risk for enhancing team decision making. It is still early days for many organisations, while others have jumped at the opportunity. Mistakes have been made. However, no risk – no magic. Team decision making is critical to team performance, and you should start planning today how you are going to take advantage of the opportunity.
Bryan Whitefield is an author, chemical engineer, and leadership specialist.
