On October 31, 2017, Terry Hay, patriarch of the Hay family and leader of the family business, was diagnosed with stage four pancreatic cancer and given three weeks to live. This grim prognosis placed the Hay family on an unexpected trajectory and forced them to confront Terry’s health crisis while grappling with the impending transition of their family business, Scandinavian Building Services Ltd. (SBS), based in Edmonton. Although the family had already planned for leadership succession, Terry’s sudden illness forced them to accelerate their plans and adapt to unforeseen circumstances. How could the family navigate the leadership transition while responding to the urgency of Terry’s illness? What strategic decisions would they need to make to stay competitive and grow market share? Most importantly, how could they preserve Terry’s legacy and solidify the business’s future across generations?

On October 31, 2017, Terry Hay, patriarch of the Hay family and leader of the family business, was diagnosed with stage four pancreatic cancer and given three weeks to live. This grim prognosis placed the Hay family on an unexpected trajectory and forced them to confront Terry's health crisis while grappling with the impending transition of their family business, Scandinavian Building Services Ltd. (SBS), based in Edmonton. Although the family had already planned for leadership succession, Terry's sudden illness forced them to accelerate their plans and adapt to unforeseen circumstances. How could the family navigate the leadership transition while responding to the urgency of Terry's illness? What strategic decisions would they need to make to stay competitive and grow market share? Most importantly, how could they preserve Terry's legacy and solidify the business's future across generations?

One of the players in the 2008 financial crisis was a phenomenon the authors call algorithmic inertia: when organizations use algorithmic models that are meant to account for a dynamic environment but fail to keep pace with critical changes. In this article, the authors explain algorithmic inertia, identify its sources, and suggest practices that organizations can implement to overcome it.

Organizations that aim to develop and deploy responsible AI systems must begin by considering what implicit and systemic biases reside in a technological system itself. Not doing so can result in catastrophic failures resulting from unintended consequences of the system's normal operations. The authors advise managers on how to mitigate the risk that algorithmic systems can cause organizational or social harm if left unchecked.