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5 principles for taking action in the face of uncertainty

Etienne Minvielle
Etienne Minvielle
Director of the Centre de Recherche en Gestion at Ecole Polytechnique (IP Paris)
Hervé DUMEZ
Hervé Dumez
CNRS Research Director and Professor at Ecole Polytechnique (IP Paris)
Key takeaways
  • Faced with the unknown, organisations are forced to make decisions without reference to prior knowledge.
  • Management of such is based on pragmatic rationality based on five principles, including taking practical action and rapidly assessing its effectiveness.
  • During the COVID-19 crisis, for example, the method used consisted of testing hypotheses in the field, updating them as the first results became apparent.
  • By agreeing to take part in large-scale collective surveys, stakeholders must also develop an attitude of humility and caution in the face of simplistic assertions.
  • These principles form a specific management style within organisations known as High-Pragmatic-Organisation (HPO).

While there are known prin­ci­ples for man­ag­ing sit­u­a­tions of rel­a­tive uncer­tain­ty, it is less clear how to deal with sit­u­a­tions of great uncer­tain­ty, i.e. where the unknown reigns supreme. In these rare cas­es, there is no longer any ref­er­ence to exist­ing knowl­edge (these are known as ‘unknown unknown’ sit­u­a­tions, as opposed to ‘known unknown’ sit­u­a­tions where there is an exist­ing ref­er­ence). In such cas­es, man­age­ment requires rules to those already used in the past.

The first wave of the COVID-19 cri­sis was an exem­plary case of this type of sit­u­a­tion1. Dur­ing this peri­od, it was impos­si­ble to refer to a past event. Dubbed the ‘flu bug’ for a short time, the high mor­tal­i­ty rates observed quick­ly con­tra­dict­ed this asser­tion. What’s more, hos­pi­tal stays in inten­sive care were much longer than those usu­al­ly observed for oth­er infec­tious res­pi­ra­to­ry virus­es, and loss of smell was a pre­vi­ous­ly unknown symp­tom. There were innu­mer­able ‘sur­pris­es’, mak­ing any rea­son­ing by ref­er­ence to exist­ing knowl­edge tricky.

In response, organ­i­sa­tions grap­pled their way through the process and made, often rushed, deci­sions. Some con­sid­ered that these actions were based on intu­ition and flair. How­ev­er, on clos­er inspec­tion, they reveal a cer­tain form of man­age­ment. This is shown by a study based on inter­views with more than 120 play­ers in the French hos­pi­tal sys­tem, pub­lished recent­ly in the Euro­pean Man­age­ment Review2.

The man­age­ment in ques­tion is based on a ratio­nal­i­ty that is nei­ther Carte­sian nor close to the con­cept of High-Reli­a­bil­i­ty-Organ­i­sa­tion (HRO), which is often used in uncer­tain sit­u­a­tions. Rather, it is a prag­mat­ic ratio­nal­i­ty, which con­sists of con­duct­ing a col­lec­tive inves­ti­ga­tion to test hypothe­ses in the field. Five prin­ci­ples emerge, reflect­ing the abil­i­ty of French hos­pi­tal play­ers to demon­strate real­ism in the face of the unknown.

#1 Undertake practical actions as part of a survey 

This first prin­ci­ple encour­ages us to design actions with­out wait­ing for per­fect infor­ma­tion. The actions envis­aged at this stage rep­re­sent hypothe­ses. They are derived from the ini­tial results of the sur­vey, which selects them on the basis of the fol­low­ing meth­ods: (i) learn­ing from unusu­al events that can be observed in the field (anom­alies such as the abnor­mal­ly long dura­tion of stays in inten­sive care for patients with COVID-19, which is sur­pris­ing giv­en our knowl­edge of the effects of infec­tious virus­es of the res­pi­ra­to­ry sys­tem); (ii) con­sol­i­dat­ing the reli­a­bil­i­ty of the infor­ma­tion gath­ered by tri­an­gu­lat­ing dif­fer­ent sources or by assess­ing the pro­file of the issuer of the alert (what some peo­ple call ‘epis­temic vig­i­lance’); (iii) and when the hypothe­ses are con­tra­dic­to­ry, to organ­ise debates between the var­i­ous stake­hold­ers in order to reach a col­lec­tive deci­sion (as in the case of the recep­tion of the Chi­nese curves on the inci­dence of the pan­dem­ic, which led to sev­er­al med­ical spe­cial­ists and epi­demi­ol­o­gists being brought togeth­er to com­pare their points of view). In this activ­i­ty, any mod­el­ling effort is also use­ful, but it is not suf­fi­cient alone, because it can nei­ther pro­vide reli­able con­text (the rela­tion­ship between nation­al pro­jec­tions and a local sit­u­a­tion), nor pro­vide a suf­fi­cient­ly con­sis­tent pre­dic­tion, due to a vari­ety of new cri­te­ria that dis­rupt the ‘mod­el’.

#2 Test the hypothesis in the field, ensuring rapid feedback of findings

This prin­ci­ple requires the hypoth­e­sis to be test­ed in the field, which is the only way to judge its rel­e­vance. Such recourse to the field takes place despite the sur­round­ing igno­rance, and con­di­tions for action that are rarely opti­mal. The objec­tives are guid­ed by a search for evi­dence and learn­ing, while the imple­men­ta­tion con­sists of cir­cum­scrib­ing the test in var­i­ous small stages, each of which is fol­lowed by a rapid return. This incre­men­tal approach opti­mis­es the assess­ment of the rel­e­vance of the action, wast­ing as lit­tle time as pos­si­ble and avoid­ing obvi­ous errors. One exam­ple at the start of the COVID-19 cri­sis was the pri­or­i­ty actions tak­en in the health hos­pi­tal sec­tor (lim­it­ing patient vis­its to hos­pi­tal, set­ting up quar­an­tine mea­sures, staff pro­tec­tion pro­ce­dures, increas­ing the num­ber of inten­sive care beds, to name but the main ones).These mea­sures quick­ly proved their worth. At the same time, they revealed the weak­ness of actions tak­en in EPHAD estab­lish­ments, where many elder­ly and vul­ner­a­ble patients were exposed to the risk of the virus. This obser­va­tion led to the rapid exten­sion and rein­force­ment of actions in this sec­tor, as rec­om­mend­ed in the fol­low­ing principle.

#3 Revisit initial hypotheses through collective deliberation

This prin­ci­ple ensures that organ­i­sa­tions trans­late the results of field tests appro­pri­ate­ly, adapt­ing their actions if nec­es­sary. Depend­ing on the feed­back and the col­lec­tive delib­er­a­tion that fol­lows, the play­ers main­tain the ini­tial hypoth­e­sis or mod­i­fy or even refor­mu­late it. The mul­ti­dis­ci­pli­nary nature of the col­lec­tive delib­er­a­tions and the open-mind­ed­ness of the par­tic­i­pants are essen­tial cri­te­ria in this revi­sion. The more the delib­er­a­tion involves a vari­ety of expert view­points, the more like­ly it is that the update will be rel­e­vant.  Sim­i­lar­ly, the more the atti­tudes expressed accept the con­clu­sions of the delib­er­a­tion, the more like­ly it is that the cho­sen hypoth­e­sis will be adopted.

This third prin­ci­ple con­cludes an over­all approach. Com­pris­ing of three stages: (i) def­i­n­i­tion of a hypoth­e­sis; (ii) field test­ing; (iii) updat­ing of the hypoth­e­sis on the basis of the results, it is char­ac­ter­is­tic of an abduc­tion method. We start with a hypoth­e­sis, check its rel­e­vance by glean­ing observ­able facts, and then deduce whether it should be main­tained or replaced by anoth­er. This approach is even more like­ly to be effec­tive if the inves­ti­ga­tion is car­ried out col­lec­tive­ly in order to cap­ture as many clues as pos­si­ble. It is also large­ly depen­dent on the atti­tudes of the mem­bers involved, as the fol­low­ing prin­ci­ple makes clear. 

#4 Develop an attitude of fallibilism and anti-dualism

Accord­ing to this prin­ci­ple, play­ers are encour­aged to express their doubts and to show humil­i­ty (fal­li­bil­ism), because the knowl­edge they have acquired is extreme­ly frag­ile, sub­ject to the appear­ance of new observ­able facts. Sim­i­lar­ly, they are urged to avoid sim­pli­fi­ca­tion by dichotomies between yes and no (dual­ist posi­tions), as these gen­er­al­ly reduce the abil­i­ty to select and inter­pret clues. With­out these two atti­tudes, there is a high risk of mak­ing erro­neous deci­sions and giv­ing them too much weight.

An exam­ple of the impor­tance of this prin­ci­ple was the debate on hydrox­y­chloro­quine as a treat­ment for the virus. The fact that the hypoth­e­sis of such a treat­ment was put for­ward was not in itself shock­ing. It was even jus­ti­fied in the light of what was known about the sub­ject. On the oth­er hand, the fail­ure to ques­tion it when the tri­als car­ried out had not pro­duced con­vinc­ing results is evi­dence of an over­ly assertive, dual­is­tic posi­tion in favour of the ‘yes’ option. 

In this quest for appro­pri­ate atti­tudes, the envi­ron­ment out­side the play­ers involved in the sur­vey plays an impor­tant role, like­ly to trig­ger harm­ful pressures.

#5 Protecting expertise from external pressures

Unknown sit­u­a­tions must be man­aged by those who have the most pre­cise knowl­edge of the event. In par­tic­u­lar, if those on the ground have the exper­tise that is being built up (which is often the case), they must be giv­en pri­or­i­ty in the actions to be tak­en. One con­se­quence of this is that they need to be pro­tect­ed from exter­nal pres­sures out­side the scope of the inves­ti­ga­tion. The lat­ter can in fact ham­per the effort under­tak­en. The COVID-19 cri­sis high­light­ed two such pressures:

  1. Insti­tu­tion­al pres­sure, which may have called into ques­tion local actions in the name of giv­ing pri­or­i­ty to deci­sions from high­er hier­ar­chi­cal lev­els, even though these are irrel­e­vant in terms of their respec­tive expertise.
  2. Pres­sure from the media, which may have steered debates towards con­fronta­tions devoid of nuance, because of the forms of expres­sion imposed. Once again, the debate on hydrox­y­chloro­quine is a good exam­ple: the exchanges on TV often turned into car­i­ca­tured oppo­si­tions between the for and against, lock­ing the play­ers into posi­tions of defend­ing a point of view, far removed from the atti­tudes of fal­li­bil­i­ty and anti-dual­ism that are nec­es­sary, but also dam­ag­ing. As a result, peo­ple work­ing in the field have found them­selves faced with patients who want to under­go treat­ment at all costs, even though there is no evi­dence to sug­gest otherwise. 

Unknown sit­u­a­tions must be man­aged by those who have the most pre­cise knowl­edge of the event. 

The pre­ven­tive mea­sures against these exter­nal pres­sures are to be found at the lev­el of col­lec­tive delib­er­a­tions organ­ised by the play­ers hold­ing the exper­tise. They need to be cau­tious about mak­ing over­ly sim­plis­tic state­ments about the envi­ron­ment. They must also pro­tect them­selves from pres­sure by unit­ing col­lec­tive­ly. How­ev­er, this organ­ised pro­tec­tion must not cut off the exper­tise from infor­ma­tion pro­duced else­where. The prin­ci­ple of col­lec­tive inves­ti­ga­tion means that clues can be gleaned. They must there­fore strike a care­ful bal­ance between pro­tec­tion and selec­tion of sur­round­ing information. 

A ”High-Pragmatic-Organisation” to manage the unknown?

The five prin­ci­ples are inspired by the the­o­ret­i­cal approach­es of prag­ma­tism, a North Amer­i­can school of thought from the ear­ly 20th Cen­tu­ry. Tak­en togeth­er, they form a spe­cif­ic form of man­age­ment at hos­pi­tal lev­el, known as High-Prag­mat­ic-Organ­i­sa­tion (HPO), in ref­er­ence to this school of thought. An HPO organ­is­es col­lec­tive sur­veys, engages in abduc­tion process­es, relies on play­ers whose atti­tudes cul­ti­vate doubt and humil­i­ty, and pro­tects itself from exter­nal pres­sure34. By act­ing in this way, French hos­pi­tal stake­hold­ers have shown that hos­pi­tals can oper­ate accord­ing to their own prin­ci­ples to face up to the unknown.

This new con­cep­tu­al term also alludes to anoth­er con­cept, that of High-Reli­a­bil­i­ty-Organ­i­sa­tion (HRO), which is often used to express the man­age­ment required in sit­u­a­tions of uncer­tain­ty5. An HRO is an organ­i­sa­tion capa­ble of deal­ing with cri­sis sit­u­a­tions where uncer­tain­ty reigns, by apply­ing dif­fer­ent prin­ci­ples (a hos­pi­tal, but also a nuclear pow­er plant or a sys­tem for organ­is­ing air flights, can thus be assim­i­lat­ed to HROs in the event of a crisis).

With­out going into detail, the pro­posed prin­ci­ples dif­fer from those just described on one essen­tial point: the absence of a ref­er­ence, and there­fore of the pos­si­bil­i­ty of express­ing reli­a­bil­i­ty. As a reminder, reli­a­bil­i­ty aims to min­imise devi­a­tions from a nor­mal state that sets per­for­mance stan­dards6. It refers to antic­i­pa­tion by trig­ger­ing pre­ven­tive actions7. With HROs, nuclear pow­er plant con­trol oper­a­tors can, for exam­ple, shut down reac­tors if they think that oper­a­tions have entered these zones. Sim­i­lar­ly, aero­plane pilots can refuse to fly if they think the equip­ment or weath­er con­di­tions are dangerous.

How­ev­er, when the play­ers are faced with the unknown, this rea­son­ing is inop­er­a­tive, because the very pur­pose of action is to define what these stan­dards are, and by deduc­tion the prin­ci­ples of pre­ven­tion. For exam­ple, when a remote mon­i­tor­ing sys­tem was set up for patients with mild forms of COVID-19, the ini­tial feed­back showed just how rel­e­vant the sys­tem was. Pre­vi­ous­ly, man­agers had admit­ted these patients with­out real­is­ing that they were occu­py­ing beds unnec­es­sar­i­ly and increas­ing the risk of the virus spread­ing. The pre­ven­tive nature of the action could only be judged fol­low­ing the empir­i­cal test.

Final­ly, it can be said that although the prin­ci­ples of ORH man­age­ment can be found, the absence of a ref­er­ence to nor­mal­i­ty lim­its the appli­ca­tion of the con­cept in the event of an unknown sit­u­a­tion. In these sit­u­a­tions, the ref­er­ence is not deter­mined in advance but is con­struct­ed a pos­te­ri­ori. For this rea­son, the con­cept of HPO, and its five prin­ci­ples, seems more appro­pri­ate to deal with them.

1Van Damme, W., R. Dahake, A. Delam­ou, B. Ingel­been, E. Wouters, G. Van­ham, … and Y. Asse­fa, 2020. “The COVID-19 pan­dem­ic: diverse con­texts; dif­fer­ent epidemics—how and why?”. BMJ Glob­al Health, 5(7), e003098. doi:10.1136/bmjgh-2020–003098.
2https://​onlineli​brary​.wiley​.com/​d​o​i​/​f​u​l​l​/​1​0​.​1​1​1​1​/​e​m​r​e​.​12665
3Peirce, C. S., 1992b. Rea­son­ing and the log­ic of things: The Cam­bridge con­fer­ences lec­tures of 1898. Cam­bridge, MA: Har­vard Uni­ver­si­ty Press.
4Dewey, J., 1938. Log­ic, the the­o­ry of inquiry. New York: H. Holt and com­pa­ny.
5Weick, K. E. and K. M. Sut­cliffe, 2001. Man­ag­ing the unex­pect­ed (vol. 9). San Fran­cis­co: Jossey-Bass.
6Roberts, K. H., 1990. “Some Char­ac­ter­is­tics of One Type of High Reli­a­bil­i­ty Orga­ni­za­tion”. Orga­ni­za­tion Sci­ence, 1(2): 160–176. doi:10.1287/orsc.1.2.160.
7Roe, E. and P. R. Schul­man, 2008. High-reli­a­bil­i­ty man­age­ment: Oper­at­ing on the edge. Palo Alto, CA: Stan­ford Uni­ver­si­ty Press.

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