The Gist

Gist

Neu­roe­co­nom­ics, neu­ro­fi­nance, behav­ioral eco­nom­ics and so on… All the fields at the cross­road of cog­ni­tive or neuro– sci­ences and other sci­en­tific dis­ci­plines are increas­ingly pro­duc­tive. The aca­d­e­mics in these fields seek to under­stand how the brain is pro­cess­ing the infor­ma­tion needed to make a deci­sion. As it turns out, we must do with scores of “Cog­ni­tive Biases” that stem from our brain design and shape all of our per­cep­tions and choices.

Impos­si­ble to elim­i­nate, hard to even con­sciously cor­rect, you can no longer ignore them: an increas­ing pro­por­tion of busi­nesses have incor­po­rated them into their deci­sion mak­ing processes (ie these processes have been designed to cor­rect any bias). If you don’t do it as well, you will soon lag your competitors.

Ori­gins

Our brain per­ceives the world around us through heuris­tics, which are gen­er­ally help­ful but often lead us astray. Think of a heuris­tic as a short­cut your brain is tak­ing to reach a deci­sion. For exam­ple, your eyes send 2 dis­tinct images to your brain, but what you per­ceive is a sin­gle one. It does the same with choices, though, and can mis­lead us.

At Stake

If you are involved in deci­sions or choices, you are influ­enced, often in the wrong way, by these biases. Their knowl­edge should be required for any­one involved in strat­egy (at the firm, busi­ness unit or small busi­ness level). Pro­fes­sion­als in finance and asset man­age­ment should also mas­ter this field. In both cases, this is increas­ingly hap­pen­ing and is now a required ele­ment to achieve a lead­er­ship position.

Action­able ?

Learn, this is the easy part. Than mod­ify your decision-making processes to account for the known biases and heuris­tics. Any deep strate­gic choice or invest­ment deci­sion should be insu­lated, as much as pos­si­ble (won’t be 100%), from these.

More Details

Ori­gins

Let’s use McKinsey’s Charles Rox­burgh intro­duc­tion to Cog­ni­tive Biases:

The brain is a won­drous organ. As sci­en­tists uncover more of its inner work­ings through brain-mapping tech­niques, our under­stand­ing of its aston­ish­ing abil­i­ties increases. But the brain isn’t the ratio­nal cal­cu­lat­ing machine we some­times imag­ine. Over the mil­len­nia of its evo­lu­tion, it has devel­oped short­cuts, simplifications, biases, and basic bad habits. Some of them may have helped early humans sur­vive on the savan­nas of Africa (if it looks like a wilde­beest and every­one else is chas­ing it, it must be lunch), but they cre­ate prob­lems for us today. Equally, some of the brain flaws may result from edu­ca­tion and social­iza­tion rather than nature. But what­ever the root cause, the brain can be a decep­tive guide for ratio­nal deci­sion making.

These impli­ca­tions of the brain’s inad­e­qua­cies have been rig­or­ously stud­ied by social sci­en­tists and par­tic­u­larly by behav­ioral econ­o­mists, who have found that the under­ly­ing assump­tion behind mod­ern eco­nom­ics “human beings as purely ratio­nal eco­nomic deci­sion mak­ers” doesn’t stack up against the evi­dence. As most of the the­ory under­pin­ning busi­ness strat­egy is derived from the ratio­nal world of micro­eco­nom­ics, all strate­gists should be inter­ested in behav­ioral economics.

At Stake

We’ll use one exam­ple to con­vince you.

Con­sider this lit­tle exper­i­ment, imag­in­ing your the Pres­i­dent of the US and have to make a choice:

Imag­ine that the U.S. is prepar­ing for the out­break of an unusual Asian dis­ease, which is expected to kill 600 peo­ple. Two alter­na­tive pro­grams to com­bat the dis­ease have been pro­posed. Assume that the exact sci­en­tific esti­mate of the con­se­quences of the pro­grams are as follows:

If Pro­gram A is adopted, 200 peo­ple will be saved.

If Pro­gram B is adopted, there is a 1/3 prob­a­bil­ity that 600 peo­ple will be saved and 2/3 prob­a­bil­ity that no peo­ple will be saved.

Which of the two pro­grams would you favor ?

Now imag­ine, one year later, you’re faced with another tough choice:

Imag­ine that the U.S. is prepar­ing for the out­break of an unusual Asian dis­ease, which is expected to kill 600 peo­ple. Two alter­na­tive pro­grams to com­bat the dis­ease have been pro­posed. Assume that the exact sci­en­tific esti­mate of the con­se­quences of the pro­grams are as follows:

If Pro­gram C is adopted 400 peo­ple will die.

If Pro­gram D is adopted, there is 1/3 prob­a­bil­ity that nobody will die, and 2/3 prob­a­bil­ity that 600 peo­ple will die.

Which of the two pro­grams would you favor ?

This is one of the exper­i­ments you’ll find in the sem­i­nal arti­cle in Sci­ence by Amos Tver­sky and Daniel Kah­ne­man (full details in the ref­er­ences) on fram­ing effects. Now, in real­ity, this exper­i­ment was done on dif­fer­ent peo­ples to avoid them see­ing that the prob­a­bil­ity struc­tures are sim­i­lar. The only dif­fer­ence is in the fram­ing of the choice: prob­lem 1 is framed in terms of gains (lives saved), and prob­lem 2 is framed in terms of losses (deaths). Let’s con­sider the answers in the actual experiment:

Prob­lem 1: A = 72% ; B = 28% / Prob­lem 2: C = 22% ; D = 78% .

What does this means ? That when we are pre­sented with a choice framed in terms of gains, we tend to be risk-adverse, and when pre­sented with a choice framed in terms of losses, we tend to be risk-seeking. This cog­ni­tive bias is actu­ally so pow­er­ful that it even makes sur­geons choose a dif­fer­ent type of oper­a­tions based on how the prob­a­bil­i­ties of suc­cess are framed when pre­sented to them. You read that well: sur­geons will choose to oper­ate you or not, based not pri­mar­ily on the life and death prob­a­bil­i­ties but on how they’re framed. If for life and death mat­ters, by highly trained physi­cians, the fram­ing of the choices make them choose dif­fer­ent solu­tions, ask your­selves how pow­er­ful it may be when con­sid­er­ing your next busi­ness strat­egy choice (or how this per­son on your team is pre­sent­ing the dif­fer­ent options available…).

Action­able ?

Sim­ply know­ing the com­mon biases is a start but obvi­ously not enough. You have to incor­po­rate them in your busi­ness processes. This is what Bridge­point, a major pri­vate equity man­ager, did for their most impor­tant deci­sions: to invest or not in a deal.

When con­sid­er­ing a major invest­ment deci­sions, man­agers tend to dis­cuss among them and to reach a con­sen­sus on what’s the best choice. This leaves them vul­ner­a­ble to a num­ber of cog­ni­tive biases such as group­think, the con­fir­ma­tion bias, over­con­fi­dence, pseudo­cer­tainty effect, etc.

To coun­ter­act this, Bridgepoint’s invest­ment process has been designed to min­i­mize their effect. For each deal, they hold their meet­ing in “court room” mode, with two sides: the pro­po­nent of the deal and the devil’s advo­cate. The pro­po­nent is a part­ner sup­port­ing the invest­ment. The devil’s advo­cate is another part­ner ran­domly cho­sen and tasked to con­vince the oth­ers NOT to invest in the pro­posed deal. The two sides have equal air time and the remain­ing part­ners may ques­tion them before vot­ing. Of course, the devil’s advo­cate is actu­ally judged and has objec­tives on how well he does a job essen­tially destroy­ing the invest­ment thesis.

This results in a bril­liant way of tak­ing deci­sions over major invest­ments. One that should be fol­lowed even within large cor­po­ra­tions on mate­r­ial invest­ment decisions.

Example(s)/Exhibit(s)

I won’t go in details here. Instead, here are some resources where you’ll find scores of inter­est­ing and enter­tain­ing examples:

• Rox­burgh. Hid­den flaws in strat­egy. The McK­in­sey Quar­terly (2003) (2): pro­vides a nice busi­ness intro
• Lovallo et al. Dis­tor­tions and decep­tions in strate­gic deci­sions. McK­in­sey Quar­terly (2006) (1): good follow-up with Dan Lovallo, an aca­d­e­mic on the subject
• List of Cog­ni­tive Biases: wikipedia page list­ing the dif­fer­ent cog­ni­tive biases, good ref­er­ence list but each page is a bit light
• Kah­ne­man et al. Delu­sions of suc­cess: How opti­mism under­mines exec­u­tives’ deci­sions. Har­vard busi­ness review (2003) vol. July: very good as well
• Horn et al. Learn­ing to let go: mak­ing bet­ter exit deci­sions. McK­in­sey Quar­terly (2006) (2): good use case for a spe­cific situation
• Horn et al. Beat­ing the odds in mar­ket entry. McK­in­sey Quar­terly (2005) (4): same for another case
• Pre­dictably Irra­tional, Dan Ariely, 2008: great “enter­tain­ing” book by a top scholar. Start with this one if you like behav­ioral economics.

Ref­er­ences

More on the aca­d­e­mic side:

• Kah­ne­man et al. Prospect the­ory: an analy­sis of deci­sion under risk. Econo­met­rica (1979) vol. 47 (2): sem­i­nal but not so easy
• Tver­sky et al. The Fram­ing of Deci­sions and the Psy­chol­ogy of Choice. Sci­ence (1981) vol. 211 (4481) pp. 453–458: sem­i­nal and easy to read
• Maps of bounded ratio­nal­ity, Daniel Kahneman’s Nobel Prize lec­ture: very good and easy
• Judg­ment under Uncer­tainty: Heuris­tics and Biases, Daniel Kah­ne­man (editor)
• Choices, Val­ues, and Frames, Daniel Kah­ne­man and Amos Tver­sky (editors)
• All the works of Daniel Kah­ne­man, Amos Tver­sky, Colin Camerer, Dan Ariely, Georges Lowen­stein, Drazen Prelec, etc. (google them!)