With rare events , organizations may not have relevant prior experiences to draw inferences and aid decision - making . The Covid-19 pandemic represents such a rare event . Responding to rare events requires organizations to mobilize and adjust existing resources quickly as well as develop new capabilities ( Henningsson et al . , 2021 ) . Further , rare events ( such as the Covid-19 pandemic ) are usually characterized by less available data ( Oehmen et al . , 2020 ) . For example , in the case of the Covid-19 pandemic , retailers may not have accurate epidemiological data on transmission and may have to use other heuristics , such as consumer mobility patterns , to optimize retail decisions . During the early days of the COVID-19 pandemic , due to potential and actual social distancing policies , including mandated lockdowns or potential lockdowns , consumer trends were disrupted , which also affected retail activities globally ( OECD , 2020 ) . As the epidemic growth showed geographic variation , some states , e.g. , New York ( NY ) , observed early surges in hospitalizations and early long - term state - wide lockdowns . Meanwhile , other states , e.g. , Nebraska ( NE ) and Texas ( TX ) , observed increased cases and deaths sometime later than NY . These geographic variations in cases and deaths also produced varying demands on certain items , such as hand sanitizer and masks , as well as varying mobility patterns , including retail activity patterns .