A little while ago I was asked how well I handle ambi­gu­ity. My impuls­ive answer was that I prefer to resolve ambi­gu­ity by ana­lys­ing the situ­ation. I answered from the per­spect­ive of an engin­eer – using reason and logic to resolve the ambi­gu­ity inher­ent in real­ity. I did not real­ise at the time that this was the ‘wrong’ answer as I was expec­ted to embrace ambi­gu­ity and seek oppor­tun­ity or some­thing fuzzy like that.

Philo­soph­ic­ally the world is ambigu­ous, e.g. light is sim­ul­tan­eously a wave and a particle; eth­ical judge­ments are rel­at­ive and based on cul­tural pref­er­ences and the notion of abso­lute truth is philo­soph­ic­ally unten­able. How­ever, our brains are wired to resolve ambi­gu­ity. As soon as we observe light it will col­lapse into either a wave or a particle and within a given cul­ture, eth­ics are pretty much abso­lute. Inside a par­tic­u­lar frame of ref­er­ence there can be only one truth. The most effi­cient tool to resolve ambi­gu­ity is reason. But reason itself has its lim­it­a­tions and some­times ambi­gu­ity remains no mat­ter how much we ana­lyse the situ­ation. It is at those point that intu­ition comes into play.

Man­age­ment is a frame of ref­er­ence in which ambi­gu­ity in most cases needs to be resolved. Cus­tom­ers don’t appre­ci­ate organ­isa­tions that are ambigu­ous and require pre­dict­able qual­ity. Ambi­gu­ity in pro­cesses also means a busi­ness is not work­ing effi­ciently as employ­ees need to spend time assess­ing each situ­ation in order to make a decision.

Man­age­ment the­or­ist David Wilkin­son argues that lead­ers need to embrace ambi­gu­ity in order to ini­ti­ate change. This is cer­tainly true, but only to the extent that recog­ni­tion of ambi­gu­ity is needed to be able to gen­er­ate pos­sible out­comes and the manager’s abil­ity to recog­nise the best solu­tion. A pref­er­ence for res­ol­u­tion of ambi­gu­ity does not pre­clude tol­er­ance for vague situations.

Suc­cess­fully man­aging a busi­ness is based on being able to make clear decisions. Without clear decisions a busi­ness will not achieve its object­ives but without a recog­ni­tion of ambi­gu­ity a busi­ness can not evolve.

One of the great prob­lems in man­age­ment the­ory is that there is quite a bit of hum­bug. just a quick look at the man­age­ment sec­tion in the local book­shop will prove this point. Man­age­ment think­ing is, due to its very nature, entre­pren­eur­ial and every­body who has an idea wants to ensure that it is read by as many people as pos­sible and maybe make a few bucks is the pro­cess. More than any other sci­ence, man­age­ment ideas are primar­ily developed to make money and people are will­ing to pay good money for them, as good ideas can sig­ni­fic­antly impact the bot­tom line.

How­ever, not many man­age­ment the­or­ies are under­pinned by solid sci­entific research. As a work­ing man­ager you need to be equipped with a pretty good ‘bull­shit radar’. Look­ing around the man­age­ment sec­tion of the aver­age book­shop the volumes on sale do not seem to meet the rigour of aca­demic research. Pop­u­lar man­age­ment books give you ‘simple solu­tions’ to suc­cess. Good to Great by Jim Collins is one of the best selling volumes in this genre.

The Busi­ness Pun­dit blog provides a great cri­ti­cism of Collins’ work which is basic­ally pseudo-scientific. The book is touted to be based on solid sci­entific ana­lysis of data, but in fact relies on Jim’s intu­ition (p. 11):

“We all have a strength or two in life, and I sup­pose mine is the abil­ity to take a lump of unor­gan­ized inform­a­tion, see pat­terns, and extract order from the mess — to go from chaos to concept.”

Collins did not use any advanced stat­ist­ical ana­lysis of the data, there are no indic­a­tions of the valid­ity of his find­ings. Although he repeatedly emphas­ises the data, his inter­pret­a­tion of the data is not sci­entific, but based on intu­ition. There is noth­ing wrong with using intu­ition to make spe­cific decisions, but you can not call it sci­ence and gen­er­ate gen­eral rules for good busi­ness man­age­ment, unless find­ings have a solid foundation.

The reason pseudo sci­entific books like Good to Great are pop­u­lar is because our brains are not nat­ur­ally wired to be crit­ical thinkers. The suc­cess of a lot of busi­ness lit­er­at­ure is based on con­firm­a­tion bias and the Forer Effect. We prefer inform­a­tion that con­firms our  pre­con­cep­tions. Also, most pop­u­lar man­age­ment the­ory does not go bey­ond self-fulfilling proph­ecy and broad sweep­ing gen­eral state­ments and its pop­ular­ity is in essence based on the same psy­cho­lo­gical prin­ciple that explains the suc­cess of astro­logy and other forms of divination.

Another prob­lem is that the aver­age man­ager does not have the cap­ab­il­ity or motiv­a­tion to fully under­stand com­plex the­or­ies that under­pin human beha­viour. Man­agers don’t want to read com­plic­ated sci­entific the­or­ies and good advice to those who seek to write a man­age­ment best seller is to stay away from using any com­plex analysis.

Man­age­ment is in essence a social sci­ence that aims to influ­ence human beha­viour in order to achieve a col­lect­ive goal, whether that be increas­ing profit or cre­at­ing a great piece of orches­tral music. Man­age­ment seeks to influ­ence the beha­viour of cus­tom­ers to con­vince them to pur­chase goods or ser­vices. Man­age­ment seeks to influ­ence employ­ees to ensure goal ori­ented beha­viour. Man­age­ment the­ory is also about influ­en­cing or anti­cip­at­ing beha­viour of the external world, i.e. the stake­hold­ers and pos­sible competitors.

As a social sci­ence, man­age­ment does not fol­low the strict rules of the nat­ural sci­ences. There are no simple for­mu­las to ensure staff motiv­a­tion, increases sales volumes or ensure cus­tomer sat­is­fac­tion. Man­age­ment is about human beha­viour, which is intrins­ic­ally unpre­dict­able. Collins and other pop­u­lar man­age­ment writers do not use  sci­entific meth­ods, but there are nat­ural lim­its to what the sci­entific method can achieve in man­age­ment. All we can hope to achieve is to develop  stat­ist­ical mod­els. These mod­els do, how­ever, not pro­duce nice state­ments about nice sound­ing con­cepts such as ‘Level 5 Lead­er­ship’ and the ‘Hedge­hog prin­ciple’. At best, sci­entific ana­lysis provides par­tial insights into a very spe­cific phe­nomenon instead of the organ­isa­tion as a whole.

There are also too many prac­tical and eth­ical issues with under­tak­ing full scale man­age­ment exper­i­ments that would be required to make the sort of claims that Collins pro­moted in Good to Great. Simply look­ing at sets of data from the past can not gen­er­ate such claims because there are too many con­found­ing vari­ables that are not covered by the data. In other words: the prin­ciples dis­tilled by Collins might not be the only reas­ons these hand picked com­pan­ies were successful.

The­ory does, how­ever, remain an import­ant means to reg­u­late our intu­ition. Before we had a con­sist­ent the­ory of grav­ity, archi­tects were very lim­ited by the size of build­ings they could cre­ate. As our the­or­et­ical and prac­tical know­ledge of phys­ics increased, so did the size and com­plex­ity of struc­tures. The­ory is required to pro­pel human know­ledge and even though man­age­ment is many times more com­plex than sky­scrapers, using only intu­ition will not improve our know­ledge of man­aging organisations.

In con­clu­sion, because man­age­ment is a social sci­ence, we can not rely on the­or­et­ical mod­els alone. Work­ing with people requires insight and intu­ition that can only be obtained by life exper­i­ence. How­ever, the­ory is an import­ant under­pin­ning of our intu­ition and in the end, there is noth­ing more prac­tical than a good theory.