TY - JOUR
T1 - Forecasting unknown/unknowns by boosting the risk radar within the risk intelligent organisation
AU - Marshall, Alasdair
AU - Ojiako, Udechukwu
AU - Wang, Victoria
AU - Lin, Fenfang
AU - Chipulu, Maxwell
PY - 2019/4/1
Y1 - 2019/4/1
N2 - This theoretical perspective paper interprets (un) known-(un) known risk quadrants as formed from abstract and concrete risk knowledge. It presents these quadrants as useful, both for categorising risk forecasting challenges against levels of abstract and concrete risk knowledge typically available, and for psychometric research measuring perceived levels of abstract and concrete risk knowledge available for forecasting. Drawing on some cybersecurity risk examples, a case is made for refocusing risk management forecasting effort towards raising unknown-unknowns into known-knowns. We propose achieving this by developing the ‘boosted risk radar’ as organisational practice where suitably ‘risk intelligent’ managers gather ‘risk intelligence information’, such that the ‘risk intelligent organisation’ can purposefully co-develop both abstract and concrete risk forecasting knowledge. We illustrate what this can entail in simple practice terms within organisations.
AB - This theoretical perspective paper interprets (un) known-(un) known risk quadrants as formed from abstract and concrete risk knowledge. It presents these quadrants as useful, both for categorising risk forecasting challenges against levels of abstract and concrete risk knowledge typically available, and for psychometric research measuring perceived levels of abstract and concrete risk knowledge available for forecasting. Drawing on some cybersecurity risk examples, a case is made for refocusing risk management forecasting effort towards raising unknown-unknowns into known-knowns. We propose achieving this by developing the ‘boosted risk radar’ as organisational practice where suitably ‘risk intelligent’ managers gather ‘risk intelligence information’, such that the ‘risk intelligent organisation’ can purposefully co-develop both abstract and concrete risk forecasting knowledge. We illustrate what this can entail in simple practice terms within organisations.
KW - risk intelligence
KW - competitive intelligence
KW - military intelligence
KW - risk radar
UR - http://www.scopus.com/inward/record.url?scp=85055112287&partnerID=8YFLogxK
U2 - 10.1016/j.ijforecast.2018.07.015
DO - 10.1016/j.ijforecast.2018.07.015
M3 - Article
SN - 0169-2070
VL - 35
SP - 644
EP - 658
JO - International Journal of Forecasting
JF - International Journal of Forecasting
IS - 2
ER -