复杂性红利：企业如何将规模与复杂性转化为营收、利润与市场份额

The

complexity

dividendHowcompaniesturnscaleandcomplexityintorevenue,

marginandmarketshareContentsInbrief4Governing

theungovernable:Three

places

to

start10Bigger

is

better,except

whenit

isn’t5

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareRethinkingcomplexityin

the

age

of

AI243InbriefOrganizationalscalehasadvantages,buttheycomeatacost.

For

manygrowingcompanies,operationscangetsocomplexand

layered

thatdecision-making

slows

to

a

crawl.Costs

can

getembedded

so

deeply

in

processes

and

workflowsthatthey’re

hiddenfromview,

puttinga

relentlessandinvisibledrainon

productivityand

profits.AIisbuiltforcomplexenvironments.It

makesit

possiblefordecision-makerstosurface,analyzeandconnectvastamountsof

data

andworkstreams,

providingvisibilityinto

businessunits,supply

chains,operational

systems,internal

andexternalteams,customer

behaviorsandmore.AIturnsoperationalcomplexityinto

a

strategicadvantage—soorganizationsstay

nimble,

responsive

and

profitable

no

matter

how

largeor

howfastthey

grow.Theinsights

inthis

reportaredrawnfrom

our

clientwork,aswell

asfromour

recentsurveyof500senior

executives

atcompanies

with

revenuesofat

least$1

billion,

fromour30in-depth

interviewswithC-suite

leadersandfromour

empiricalanalysisof1,444

global

companies.

For

moreon

our

methodology,

please

see“Aboutthe

research”

on

page26.Thereisadualimperativeinthe

age

of

AI.Growingcompanies

mustfirstshifttheirthinkingaboutcomplexity:

ratherthanfocusingon

removing

it,theyshould

useAItoamplify“good”complexity—

the

kindthatdrivesgrowth,

revenueand

margin—andsimplifyorsunset“bad”complexitythatdrainsprofit.Second,they

must

rethinkthe

roleofAI

itself.Deployedcorrectly,AIcan

betheXfactorthat

allows

top-heavyorganizationsto

befullyincontrol

of

their

performance. Biggerisbetter,ungove

rnable:complexity

exceptwhenitisn’tThree

p

lacestostartin

the

age

of

AI

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareGove

rn

ingtheRethinking4Bigger

is

better,except

whenitisn’tThecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareGove

rn

ingtheungovernable:RethinkingcomplexityThreep

lacesto

startexceptwhen

it

isn’tBiggeris

better,intheage

of

AIIn

brief5manygrowingcompaniesisthatscalecandevolveintocompetitiveliabilities.Decision-makingslows.Responsivenessgetscompromised.Products,servicesandinvestmentsbecomehardto

manage.Enterpriseprioritiesgetclouded.Experiencesgetdilutedacrosschannelsandtouchpoints.Thecostimplicationsarereal.

Insteadof

being

nimbletrailblazers,largerorganizationstendtogetslowerandmoremethodicalastheygrow.Their

growthmindsetsgetoverwhelmedbyoperationalcomplexity,withlowermarginsandfrustratedcustomerstoshow

for

it.Largerorganizationsshouldhaveformidableadvantagesoversmallerfirms.Theyoftenhaveaccesstodeepfinancialresourcestofundnewideas,researchand

projects.

Economiesof

scaleallowthemtonegotiatebetter

pricesand

build

strongersupplierpartnerships.Poolsoffirst-partydatagivethemvaluableinsightsintotheircustomers,products,suppliers,workers,processes,andevenpartnersandcompetitors.Theseadvantagescanbesignificant,buttheycomeatacostandoftenremain

unrealized.The

realityfor

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshare

exceptwhenitisn’tThree

p

lacestostartintheageofAI

Inbriefungove

rnable:complexityGove

rn

ingtheRethinkingBiggeris

better,6Tosolvethecomplexitypuzzle,top-heavyorganizationstypicallyturntoarangeoftactics.Theyoftencentralizedecision-making,standardizetheirprocessesandintroducenewtechnologiestohelpmanageteamsandworkflows.Whilethesemethodscanhelptamecomplexity,rampantgrowthcreateschallengesthatoutpacethesetactics.Forexample,manylargeorganizations

evolve

intoconglomerateswithseparatebusinessunitsthathavecompetingpriorities,dilutingthestrategicdirectionoftheorganizationandimpactingfinancial

performance.Inothercases,businessesthatexpandintonewregions—thinkretail

outlets

or

infrastructureinvestments—seedeclinesinoperationalexcellenceandinconsistentcustomerexperiences,evenwithintheircoremarkets.Othersectors,suchastechnologyandbanking,oftenseeinnovationslowastheyjuggle

regulationsandnewbusiness

models.Theramificationscanbefar-reaching:takeoversoflargecompaniesareatanear-two-decadehigh,

and

firmswithweakrevenue-to-costdisciplineareseven

timesmorelikelyto

betargeted.1

The

impactsofactivistinvestorsoverthepast18

monthsshowsjusthowseriousthesechallengeshavebecome.“What’sreallyslowing

thecompanydownisbureaucracy:toomanylayers,toomany

signatures.”ManagingDirector,Strategy

andPlanning,

GlobalBankThe

relentless

leak

of

operational

complexity

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshare

exceptwhenitisn’tThree

p

lacestostartintheageofAI

Inbriefungove

rnable:complexityGove

rn

ingtheRethinkingBiggeris

better,7Complexityisn’tsimplya

byproductof

scale—it’sbuiltintotheveryenginesmeanttodrive

growthacrossproducts,channels,marketsandexperiences.Managedcorrectly,complexitycanbetransformedintoasignificantcompetitiveadvantage.Butto

makethathappen,organizationsmustfirstrecognizewherecomplexitycomesfromandwhyitpersists.Growth-drivencomplexitycomesfromworkflows,reportinglayersanddecisionforumsthatarefocused

onallocatingcapitalandhelpingorganizationsmeettheirstrategicgoals.Complexityshowsupintheformofnewprocesses,teamsanddatasetsthat

layer

ontopofcurrentwaysofworking.Layersstack

upasgrowthcontinues,expandingthenumberofoperatingdriversthatneedtobe

managedand

making

it

more

difficultfor

leaderstoseeandunderstandwhat’shappeningacrossteams,projectsandbusinessunits.Two

forces

allow

this

typeofcomplexityto

growunchecked:Performance

variability

gets

hidden

insideaggregatedreports,makingit

hardto

differentiate

betweenhigh-performingandunderperformingassets.Thiscumulativereportingmethod—thenormforlargeorganizations—masksanomaliesanddeflectsaccountability,causingorganizationstoreactslowlytoopportunitieswhileincreasingcosts-to-serve.Relentlessdatasprawlandever-increasingmanagementlayersmaketheproblemworse

each

year.Inertiaallowsinefficientprocessesandbad

habitstohardeninplace,

leadingcapital

investments

togetmisaligned.Resourcesgetfragmentedacrosstoomanyinitiatives,productivitystumbles

undertheweightoftedioushandoffsandconfidenceerodesascustomers,partners,employeesandinvestorsbegin

toquestiontheorganization’sabilitytodelivervalue.“Totrulyenabledata-drivenaction,weneedtheintegrateddatamanagementandAIplatformstoprocessvast,disparatedataforstrategicclarity

andstandardizedinsights."ChiefMarketingOfficer,GlobalFoodCorporationTheroot

causes

of

complexity

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshare

exceptwhenitisn’tThree

p

lacestostartintheageofAI

Inbriefungove

rnable:complexityGove

rn

ingtheRethinkingBiggeris

better,8Thehidden

costs

of

complexityComplexitydrivesupcostsin

subtlewaysthat

arehardtoquantify.Accentureresearch

shows

thatmostexecutivesstrugglewith:2•

Executiondisruptionsduetofrequentchangesinreportinglines

ororganizationalstructure•

Operationalfrictionduetofragmentedprocessesandreporting

requirementsacrossfunctionsandbusinessunits•

Inabilitytogettimelyinsightsduetodisconnectedsystemsor

sources•

Misalignmentacrossteamsduetodifferinggoals,incentivesor

leadershipstylesTransforming

complexityinto

advantageArtificialintelligence(AI)wasdesignedforthismoment.

Ithasevolvedquickly—fromclassicaltogenerativetoagenticandnowphysicalAI—to

alloworganizationstobettermanagecomplexityatscale.

WithAItoolssupportinghumanroles,

businessesnowhavetheframeworktheyneedtocapitalizeon“good”complexitythatdrives

marginand

marketdifferentiationwhileidentifyingandaddressing“bad”complexitythatslowsinnovationanddrainsprofit.AIisthe

linkthatturnsanorganization’s

scale

andcomplexityintoitsstrongestcompetitiveadvantage.Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareGove

rn

ingtheungovernable:RethinkingcomplexityThreep

lacesto

startexceptwhen

it

isn’tBiggeris

better,intheage

of

AIIn

brief9Governing

the

ungovernable:

Threeplaces

to

startThecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareGove

rn

ingtheungovernable:comp

lex

ityintheage

of

AIThreep

lacesto

startexceptwhen

it

isn’tBiggeris

better,RethinkingIn

brief10In

briefB

iggeris

better,exceptwhenitSortcomplexityintogood,badorgoneNotallcomplexityis

bad.

It’simportantto

understand

andcategorizecomplexitybecausesomeofit

isworthgrowing(figures1and2).Goodcomplexityincludesfoundationalaspectsofthe

business,suchasthe

types

of

customersand

industries

served,the

range

of

products

andservices

offered,the

languages

used(both

humandialectsandtechnicaldisciplines)and

regional

and

local

market

nuances.Goodcomplexity

underpinsinnovation

and

market

differentiation,allowingorganizationstodeliver

unique

products,servicesandsolutionstospecificcustomers

or

regions.

Thistype

of

complexity

is

vital

to

generating

revenueandstrengthening

market

relevance.1.Leanintocomplexity,

don’trun

fromitForyears,complexitywasseenastheenemyofefficiency.Butinaworldofdynamicmarkets,digitalinfrastructureandAI-drivenorchestration,complexity

isnolongerjustacosttomanage—it’sastrategicassettomaster.Theorganizationsthatwintomorrowwillbethosethatcanmanagemorelayers,tailormore

experiencesandmarketsandbalancemoretrade-offs

withoutbreakingstride.Badcomplexityaddseffort,costandconfusionwithout

improvingoutcomes.

It’softenthe

resultof

legacydecisions,siloedsystems,duplicatedprocessesor“just

incase”layersof

control.

Badcomplexitycreepsin

unnoticedand

compoundsover

time,clogging

decision-making

and

draggingdown

productivity

and

profits.Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareGove

rn

ingtheungovernable:comp

lex

ityintheage

of

AIThreep

lacesto

startexceptwhen

it

isn’tBiggeris

better,RethinkingIn

brief11Insteadofbeingan

expense,complexityandscalecandeliverareturnoninvestedcapital(ROIC)

byreducingoperatingcostsandimprovinghowworkforcesandcapitalinvestments

aredeployed.This“complexitydividend”allowscompaniestogenerateROICbyusing

AI

agents

and

otheremergingtechnologiestoorchestrate

chaos—togoverntheungovernable.

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareIllustrative

example

from

a

manufacturing

company

Good

complexity

examples:

Bad

complexity

examples:Tailoredproductdesignforlocal/OverengineeredbillofmaterialswithregionalmarketsredundantSKUsFigure

1:FromCAPEX

toROIC—cashing-in

on

the

complexity

dividendRedundantdashboards,datalakesandlicense

sprawlUnderusedmanufacturingassetsbuiltfor

scale,not

agilityBloatedinventoriesfromfragmentedplanningorlackofvisibilityFlexibleinventorybufferstailoredtovolatiledemandprofilesAccretiveIPportfoliosthatsupportdifferentiated

pricingSpecializedanalyticsorAIservicesthatimproveforecastingUnderusedoroutdatedassetswithoverlapping

capabilitiesAdaptive,modularplantfootprintsalignedtodemandOne-off

freelance

and

project

spendscatteredacrossfunctionsAgilepodstructuresthatimprovecustomer

responseAcquisitionswithoutintegration,creating

hidden

duplicationsExcessivelayersofapprovalandreportinglinesCentralizeddatainfrastructuresupportingcross-unitAINet

PPECOGSSG&AOther

expensesWorkingcapitalNetotherassetsGoodwill&intangiblesDepreciationEBITDAEBITCapital

efficiencyROICModularequipment

based

depreciationGove

rn

ingtheungovernable:RethinkingcomplexityThreep

lacesto

startexceptwhen

it

isn’tSource:AccentureBiggeris

better,intheage

of

AIallowingusage-In

brief12Thisvaluematrixisastartingpointforinvestigatingoperationalcomplexity.Complexity

thatappearsin

the

tophalfof

thematrix

warrants

furtherinvestment

orrefinementandshouldbeprioritized,

givenitspotential

togenerate

value.Elementsin

thebottomhalfarecandidatesforsimplificationorelimination.For

a

deeperinvestigation,

examine

theunderlying

drivers

of

value,

thematurity

and

constraints

ofkey

enabling

technologiesandinterdependencies

across

functionsandprocesses.Meaningfulinsights

will

then

come

from

structured

analysis,

stakeholder

inputs

and

a

willingness

tointerrogatelong-

standing

assumptions.Low

organizational

burdenLightweight,

self-contained

complexityKeep

and

scalePreservecoredifferentiators,monitor forandcutoffcreep,empower

autonomywithguardrailsandfeed

withricherdatasignalstostay

aheadofchangeKeep

andreplatformEmbedAI-drivenorchestrationbycodifying

rule-basedprinciples,automatingroutinehandoffsandaugmentinghumandecisions

withmachineagentsMonitoror

fold

inKeepaneyeon

low-impact

rules

andapprovals,treatas“noise”andmonitorforcomplexitycreeps,while

resistingaddingnew

layersSunsetRetirelegacyapprovalsandfragmented

organizationallayers—sunsetcumbersomeworkflowsandredeploy

resourcestohigh-impactareasHighorganizationalburdenCostly,

brittleormanualatscaleSource:AccentureThecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareLow

strategic

valueNiceto

have

but

littlestrategic

liftFigure

2:

Separating

good

complexity

frombadHigh

strategic

valueCoretogrowthor

marketedgeexamples

examplesBadcomplexity

GoodcomplexityGove

rn

ingtheungovernable:comp

lex

ityintheage

of

AIThreep

lacesto

startexceptwhen

it

isn’tBiggeris

better,RethinkingIn

brief1314Fromwhispertoroar:HowleadersdiscussandmanagecomplexityWhenwelookatcompanieswiththehighestprice-to-earnings(P/E)levelsandthefastestP/Egrowth,andthenreadadecadeoftheirearningscalls,twothingsstandout.First,marketleaderstalkaboutcomplexityfarmorethanothers—over60%moreoften—andthatfocushasrisensharply(theshareoftheircallsthataddressitisup~80%since2015).Thetopicsaren’tabstract.Theyfocusonthehardpartsofscale:thebreadthof

productsandcustomersegments,andhowdecision

rightsandoperatingstructureskeeppace.3Second,asignificantseparationshowsupintechnologyanddata.Marketleadersdiscusstech/datacomplexityroughlythreetimesmorethanpeers—

coveringintegration,datamodels,performanceanalyticsandAI.Andtheiremphasison“good”complexityinthisdomain(thekindthatenablesdifferentiationandspeed)hasquadrupledsince2015,

versusa60%increaseforpeers(figure3).4Fuelgrowth,notoverheadOrganizationsthatlearntomanagecomplexitycanservemorecustomersandmarketswithhyper-personalizedproducts,withoutinflatingunitcosts.They’rebetterequippedtoadaptglobalmodelstolocalnuances—whetherregulatory,culturalorchannel-

related—withoutfragmentingoperations.Theyempowertheirdistributedteamstoact

autonomously

whilestayingalignedinrealtime.Andbecausetheycanreconfigureprocessesontheflyandput

morecontrolinthehandsofcustomers,companies

canlaunchnewproductsandservicesfasterwhile

enablinghypercustomizationandpersonalization.Fortheseorganizations,theirvarietyofproductsandservicesactsasagrowthengine,nota

tax.Tofuelthatgrowth,complexitymustbepreventedfrommultiplyinguncontrollably.Newofferingsandoptionsshouldplugeasilyintoastablecore,notcausedisruptionsthatcascadeacrosstheenterprise.

Thatway,changesindecisionlogicbecomesimple

configurationupdates,notcodechanges,allowingguardrailsandthresholdstobeupdatedreliably.

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshareexceptwhenitisn’tThree

placestostart

intheage

of

AIInbrief

ungovernable:complexityGoverningthe

RethinkingBiggeris

better,4x

3x1.6x Market

Leaders2015 Market

Leaders2024 Rest

2015 Rest2024Figure

3:

Talk

the

talk—averagenumber

of

earnings

callsreferencing

technology

and

data

complexityThecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshare0.70.60.50.40.30.20.10.0Goodcomplexityrelated

to

tech

&

dataBadcomplexityrelated

to

tech

&

dataAveragenumberofearn

ings

cal

lsGove

rn

ingtheungovernable:comp

lex

ityintheage

of

AISource:Accenture

ResearchThreep

lacesto

startexceptwhen

it

isn’tBiggeris

better,RethinkingIn

brief15localizedpricingandofferings,

special

deliveries,inventorymanagementandmore.Interactionsacross

warehouses,

stores,regionsandchannels

arehighly

automated

andcanbe

tailored

tocustomerneedsinreal

time.

Theever-

increasingcomplexityof

SKUs

and

vendorsismanaged

precisely—keptwhenitpays,prunedwhenitdoesn’t.Airlines

&

logistics—Airlines

andlogisticscompaniesmustcoordinatean

array

ofinterconnected

systems

inreal

time,underrigidrulebooks

thatguideoperations.Aglitchanywherein

thesystem—such

as

a

weather

delay

or

unplannedrepair—canaffectcrew

schedules,maintenance

plansand

theentire

transportationnetwork.Withdataina

varietyof

formats,scattered

across

siloed

systems,it

canbehard

topinpoint

therootcauseofaproblemorgaugeits

truecosts.Now,

withAIlivenetworkorchestrationfusing

weather,air-trafficcontrol,

crewpolicies,

aircraftmaintenancerequirements,gateavailability

and

connection

points,driftcanbe

spotted

asithappens.

Operations

canberevisedinreal

time—swappingaircraftorreroutingdeliveries,changingcrewrosters

withinrulesandre-routing

passengers

withconnections,

withpolicy-as-codekeeping

safetyandunionconstraintsintact.Automotive

&

mobility—Vehiclecomplexityandregulatoryandsafetyrequirementsmakeitdifficult

toreconfigurevehicles

fordifferentbuyersorregions.But

with

software-Buildthebrainpower,unleashAI'spowerTounlockAI's

fullpotential,companiesneed

togiveAIagents

the“brainpower”theyneed

toworkalongsidehumans—theorganizationalintelligence

toorchestrateworkflows,analyzereal-timedata

fromrobotsandsensors,

makedecisionsand

act

autonomously.

Thisrequiresbuildingacognitive

foundation

thatdigitally

translatesinstitutionalknowledgeand

workflowsintoa

formAIcaninterpretandactupon.Likeacentralnervoussystem,

this

intelligencelayerconnectspeople,processesand

datathroughstreamlined,modularsystemsbuilt

toadapt—allanchoredin

trusteddata,clear

governance

and

well-definedinterfaces

thatmakehuman-machinecollaborationseamlessandpredictable.

Theprize

forgettingitrightisgrowth—inmarketshare,margins,innovationandreputation.Thisisn’ttheory.Companiesare

creating

these

organizational“nervoussystems”thatprocesscomplexity

inreal-time,connectingdisparateoperationsandenabling

AI

torespond

withspeed

andprecision.Retail

&

CPG—Monthlyplanning,siloedoperations

andunstructureddatahistoricallymadereal-timeorchestration

unrealistic

forretailersandconsumerpackaged

goods(CPG)companies.

Thesecompanies

arenowusingorchestratednetworks

tocollaborateacross

channelsandcoordinateactivitiesaroundseasonalpromotions,defined

vehicles,manufacturersarenowable

to

offer

awiderangeof

variants—different

trims,regions,regulations,

safety

features—andusecontinuousover-the-air(OTA)updates

tokeep

theirproductscurrent.AI

orchestratesproductconfigurationand

compliance

acrossmarkets,schedulessoftwareupdates

for

vehiclesbasedon

fleetdataandrisk,adapts

supply

andproduction

wheneverthere’sachangeinregulationsorparts,andusespolicy-as-code

tokeep

vehiclecertificationand

safetyregulations

intact.Banking—Banksandcapitalmarkets

firms

facerelentlesspressure

froma

volatilemacroenvironment,ongoingdigitaldisruptionand

theneed

to

scale

complexlegacyoperationsandinfrastructure

tomeet

thenextchapterofgrowth.

Tomeet

thesechallengeshead

on,banks

areembracingagentic

AI

to

tacklecomplexity

and

accelerate

their

transformationefforts.

Thisreinventionincludesmodernizinglegacyinfrastructure

toreduce

technicaldebt,

streamliningcompliance

throughcontrols

assessmentandautomation,andreducing

overall

complexity

andfragmentation

throughagenticAI-poweredprocessre-engineeringand

workfloworchestration.Notonlyisagentic

AIenablingleadingbanks

toaccessnew

frontiers

ofperformanceandcustomer

engagement,it

is

alsoaccelerating

thespeed

to

value

for

those

thatare

at

thestartof

their

transformation.

Thecomplexitydividend:Howcompaniesturnscaleandcomplexityintorevenue,marginandmarketshare

exceptwhenitisn’tThree

p

lacestostartin

the

age

of

AI

Inbrief

ungove

rnable:complexityGove

rn

ingthe

RethinkingBiggeris

better,162.Orchestrate

workflowsand

amplify

goodcomplexityMorecomplexity—goodorbad—createsmorework.ThepromiseofAIissimple:

it

takes

on

that

extrawork.

Itembedsitselfacrossbothanorganization

and

itsvaluechaintowatchfordrift,adaptontheflyand

amplifywhat’sworking.AIisthe

keyto

movingfastwithoutlosingcontrol.

Itallowsgrowingcompanies

tobethenimble,responsive

powerhousestheywere

meantto

be.DrivevarietyupandcostsoutInthepast,operatingcostsscaledwithvariety.Morevarietyinacompany’sproducts,services,channels,

marketsandoffersmeantmore

sales—and

morecoordination,handoffsandrework.

Ratherthanintroducingeconomiesofscale,varietyactuallydrove

unitcostsup.ButAI

runningon

a

stable,

modular

core

allowsahigherpercentageofworkto

be“configured”

ratherthanhandcrafted.Sotasksgofaster,rework

isreducedandmargincostscomedown.WithAI-enabledorchestrationacrosstheentirevaluechain,thecoordinationloadthatotherwisewouldbehandledby

additional

management

layersisautomatedwithAI.

Itincreaseshow

muchworkca