Pareto On Steroids

12 April 2017 | Think­ing in New Ways

Vilfre­do Fed­eri­co Dama­so Pare­to was born in Italy in 1848,” wrote Kevin Kruse (@Kruse) for @Forbes [link] about a year ago. And he does as good a job as any­one at sum­ming up why Pare­to’s think­ing is remem­bered today.

Leg­end has it that one day he noticed that 20% of the pea plants in his gar­den gen­er­at­ed 80% of the healthy pea pods. This obser­va­tion caused him to think about uneven dis­tri­b­u­tion. He thought about wealth and dis­cov­ered that 80% of the land in Italy was owned by just 20% of the pop­u­la­tion. He inves­ti­gat­ed dif­fer­ent indus­tries and found that 80% of pro­duc­tion typ­i­cal­ly came from just 20% of the com­pa­nies. The gen­er­al­iza­tion became:

80% of results will come from just 20% of the action.

While the Pare­to Prin­ci­ple may not be uni­ver­sal­ly accept­ed, I have been amazed at how often the 80/20 rule seems to work out in my own obser­va­tions. So, what’s new? Michael Schrage recen­ty wrote a mind-stretch­ing arti­cle on what hap­pens when AI (arti­fi­cial intel­li­gence) inter­sects with Pare­to. The arti­cle is fea­tured on Har­vard Busi­ness Review (@HarvardBiz) [link]. Says, Schrage: “As machine learn­ing and AI algo­rith­mic inno­va­tion trans­form ana­lyt­ics, I’m bet­ting that next-gen­er­a­tion algo­rithms will super­charge Pareto’s empir­i­cal­ly provoca­tive par­a­digm. Here are three impor­tant ways that AI and machine learn­ing will rede­fine how orga­ni­za­tions use the Pare­to prin­ci­ple to dig­i­tal­ly dri­ve prof­itable inno­va­tion to lev­els beyond con­ven­tion­al analytics.”

Please be sure to read Schrage’s expla­na­tion of (1) “Smart Pare­tos”, (2) “Super-Pare­tos”, and (3) “Supra-Pare­tos”. On the lat­ter top­ic, he says, “Increas­ing­ly, the surest way to rethink and revi­tal­ize a Pare­to is to link it to anoth­er Pare­to.” And he pro­vides exam­ples that will make you won­der why your own enter­prise isn’t apply­ing the same log­ic. As he notes, “Rig­or­ous­ly apply­ing the Pare­to ana­lyt­ics to Pare­to ana­lyt­ics seems obvi­ous, but few orga­ni­za­tions demon­strate that dis­ci­pline every day. That must change.”

There are, as you might expect, some nextsens­ing prin­ci­ples at play here. The unknow­able is a favoured domain of the Nextsen­sor; and, while no one can know what impact AI will have on the future, or on Pare­to’s 80/20 prin­ci­ple, it is crit­i­cal­ly impor­tant to be using human imag­i­na­tion today to fore­sense how it might shape tomor­row. Advance­ments such as AI have the poten­tial to dra­mat­i­cal­ly improve our under­stand­ing of emerg­ing pat­terns in real time and accel­er­ate our move from under­stand­ing yes­ter­day to under­stand­ing today. This is a crit­i­cal, if not sub­tle, shift to pro­vid­ing the fuel for fore­sens­ing the future, what Schrage calls a move toward “pre­dic­tive and pre­scrip­tive statistics”.

If Schrage’s spec­u­la­tions prove to be valid (I’d bet yes), AI could indeed super­charge things. How­ev­er, what I believe might be super­charged more than any­thing else is human inge­nu­ity. By tak­ing the pow­er of machine learn­ing and feed­ing it into human beings in new ways, it will be peo­ple (and not just algo­rithms) that will mat­ter even more, by:

  • Help­ing peo­ple think dif­fer­ent­ly — using data to chal­lenge the sta­tus quo and devel­op mean­ing­ful aspi­ra­tions about a dif­fer­ent set of future possibilities
  • Illu­mi­nat­ing human imag­i­na­tion and cre­ativ­i­ty to pro­vide the (super­charged) fuel required for women and men to gen­er­ate break­through inno­va­tions per­haps unimag­in­able with­out the aid of AI
  • Pro­vid­ing just enough fore­sense about what is desir­able and what is fea­si­ble to pro­vide the impe­tus for action — in oth­er words, mov­ing from a data set to a “learn­ing set”

There’s no ques­tion that Michael Schrage is spot on when he notes that “Pare­to ana­lyt­ics around prod­uct attrib­ut­es and fea­tures, not just the prod­ucts them­selves, offered more provoca­tive insights.” Even with today’s cur­rent lev­el of digi­ti­sa­tion, it is pos­si­ble (and wise) to test and val­i­date the dri­vers of cus­tomer val­ue in the launch phase of new prod­ucts and ser­vices rather than wait­ing for a post hoc analy­sis focused on more effi­cien­cy gains. Such efforts mean waste can be tak­en out of the sys­tem much, much ear­li­er — dri­ving inno­va­tion toward val­i­dat­ed cus­tomer out­comes and chang­ing the mind­set from con­tin­u­ous improve­ment to con­tin­u­ous learning.

It was Joseph Juran [link], in 1941, who alert­ed the world to the wis­dom of Pare­to. And there’s a les­son there: it took a human to eval­u­ate the worth of Pare­to’s break­through. All the tech­nol­o­gy under the sun will not pro­duce pos­i­tive effects in and of itself. Tech­nol­o­gy needs to be accom­pa­nied first by an uncom­pro­mis­ing growth mind­set, one com­mit­ted to the con­tin­u­ous search for cus­tomer val­ue-based growth oppor­tu­ni­ties. Then, tech­nol­o­gy needs a spe­cial kind of fuel to super­charge its poten­tial: the human imag­i­na­tion, which allows for a spec­trum of out­comes giv­en the nature and cir­cum­stances of the context.

When you com­bine a growth mind­set and human imag­i­na­tion with pre­vail­ing tech­nolo­gies (AI or oth­er­wise), you have the mak­ings of a tra­jec­to­ry of unend­ing val­ue creation.

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Want to stretch your mind fur­ther? Here are two relat­ed links you might also find valuable.

Time Crys­tals? Char­lie Wood (@walkingthedot) took me to a whole new plane of sci­en­tif­ic think­ing with this arti­cle for (@csmonitor): “Sci­en­tists con­firm: Time crys­tals def­i­nite­ly exist — Two teams have cre­at­ed a new form of mat­ter, open­ing up a whole new realm of physics.” While the head­line itself makes you want to check this out, try this thought from Wood: “The idea that you can shift a train sched­ule for­ward or back a minute or an hour with no phys­i­cal con­se­quence (oth­er than frus­trat­ed trav­el­ers) is called tem­po­ral sym­me­try, and time crys­tals break it.” Thanks to Lau­rence Tribe (@tribelaw) for help­ing us find this. [link]

The Next Cloud? Dina Bass (@dinabass) and Mark Bergen (@mhbergen) report that AI is not just for big com­pa­nies. Read about this on Bloomberg [link]: “Beer, Bots and Broad­casts: Com­pa­nies Start Using AI in the Cloud — The next cloud bat­tle between Ama­zon, Microsoft and Google is about bring­ing AI to all busi­ness­es.” Say the authors: “AI soft­ware used to require thou­sands of proces­sors and lots of pow­er, so only the largest tech­nol­o­gy com­pa­nies and research uni­ver­si­ties could afford to use it. An ear­ly Google sys­tem cost more than $1 mil­lion and used about 1,000 com­put­ers.… Only when Microsoft, Ama­zon and Google began offer­ing AI soft­ware over the inter­net in recent years did these ideas seem plausible.”

The Ulti­mate Break­through? James Walk­er (@jamesofilmiont) report­ed on a speech by the CEO of Microsoft that you might have missed. The head­line in @BlastingNews: “AI the ‘ulti­mate break­through,’ says Microsoft CEO — Satya Nadel­la has described arti­fi­cial intel­li­gence as the “ulti­mate break­through” in tech­nol­o­gy, owing to its trans­for­ma­tive capa­bil­i­ties.” [link] Says Walk­er: “For Microsoft, the key in is giv­ing machines a robust under­stand­ing of human lan­guage. Talk­ing freely with com­put­ers could be the next rev­o­lu­tion in input devices, enabling new kinds of expe­ri­ence that aren’t pos­si­ble with a key­board and mouse.”

Joseph PistruiJoseph Pistrui (@nextsensing) is Pro­fes­sor of Entre­pre­neur­ial Man­age­ment at IE Busi­ness School in Madrid. He also leads the glob­al Nextsens­ing Project, which he found­ed in 2012. 

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