SCMG301 Week 6 DQ

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11 Using Big Data and Analytics to Manage Risk

By.now.you’ve.probably.heard.about.or.have.had.some.experience.with. something.called.“big.data.”.While.we.may.have.heard.of.the.concept,.tak- ing.advantage.of.the.treasure.trove.of.data.that.resides.at.most.companies. remains.an.evolving.challenge..With.an.estimate.of.more.than.15.million. gigabytes.of.new.information.collected.every.day.(15.petabytes),.which.is. eight.times.the.information.in.all.U.S..libraries,.it’s.no.wonder.most.com- panies.are.wondering.how.to.use.big.data.to.their.advantage.1

But. is.using.big.data.going.to.be.that.straightforward?.A.report. titled. Big Data Insights and Innovations Report revealed. some. findings. that. relate.directly.to.big.data.and.its.uses.2.First,.many.organizations.are.chal- lenged. by. data. overload. and. an. abundance. of. trivial. information.. And. important. data. are. not. reaching. practitioners. in. efficient. time. frames.. Current. technology. is.also.not.yet.at. the. level.of.providing.measurable,. reportable,. and. quantifiable. data. in. areas. including. production. sched- uling,. inventory,. and. customer. demand. across. the. entire. supply. chain.. Furthermore,.despite.the.sophistication.of.current.systems,.data.are.not. always. easily. accessible. to. internal. users.. Finally,. noticeable. gaps. are. present.in.many.end-.to-.end.supply.chain.flow.models..Other.than.these. “minor”.issues,.everything.is.working.just.fine.in.the.world.of.big.data.and. risk.management.

In. this. chapter.we’ll. advance. some.definitions.and.an.overview.of.big. data.and.predictive.analytics;.talk.about.the.process.for.successfully.lever- aging.big.data;.present.barriers.and.challenges.with.big.data;.and.present. tools,.techniques,.and.methodologies.that.support.big.data.and.analytics.. The.chapter.concludes.with.examples.of.companies.using.big.data.and.how. these.companies.are.leveraging.their.data.to.help.manage.supply.chain.risk.

Schlegel, Gregory L., and Robert J. Trent. Supply Chain Risk Management : An Emerging Discipline, Taylor & Francis Group, 2014. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/apus/detail.action?docID=1680353. Created from apus on 2023-05-08 04:41:53.

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204 • Supply Chain Risk Management: An Emerging Discipline

What iS Big data and pRediCtiVe analytiCS, Really?

To.some.observers.big.data.got.its.start.around.2003.with.the.advent.of.the. Data.Center.Program.at.Massachusetts. Institute.of.Technology. (MIT).3. Before.this,.most.of.the.early.research.in.the.late.1990s.used.the.term.data analytics. as. a.key.descriptor.. It.becomes.critical. to.define. the. terms.big data.and.predictive analytics.

According. to. the. Leadership. Council. of. Information. Advantage,. big data. is.not.a.precise.term. This.group.sees. it.as.data.sets.that.are.grow- ing.exponentially.and.that.are.too.large,.too.raw,.or.too.unstructured.for. analysis.using.relational.database.techniques..So,.where.is.this.unbeliev- able.amount.of.unstructured.data.coming.from?.According.to.one.source,. the.amount.of.data.available.is.doubling.every.two.years.and.is.emanat- ing.from.not.only.traditional.sources.but.also.industrial.equipment,.auto- mobiles,. electrical. meters,. and. shipping. crates,. just. to. name. a. few. The. information. gathered. includes. parameters. such. as. location,. movement,. vibration,.temperature,.humidity,.and.chemical.changes.in.the.air.4

Predictive.analytics.(PA).encompasses.a.variety.of.techniques.from.sta- tistics,.data.mining,.and.game.theory.that.analyze.current.and.historical. facts.to.make.predictions.about.the.future..In.business,.predictive.models. exploit.patterns.found.in.historical.and.transactional.data.to.identify.risks. and.opportunities..Models.capture.relationships.among.factors. to.allow. assessment.of.risk.or.potential.associated.with.a.particular.set.of.condi- tions,.guiding.decision.making.for.specific.transactions.5

Predictive. analytics. has. been. traditionally. used. in. actuarial. science,. financial. services,. insurance,. telecommunications,. retail,. travel,. health. care,.and.pharmaceuticals..Yet.it.is.barely.mentioned.in.the.manufacturing. and.supply.chain.arenas..One.of.the.best.known.and.early.applications.of. PA.is.credit.scoring,.which.is.used.throughout.financial.services..Scoring. models.process.customers’.credit.history,.loan.applications,.customer.data,. and.so.forth,.in.an.effort.to.rank-.order.individuals.by.their.likelihood.of. making. future. credit. payments. on. time.. A. well-.known. example. is. the. FICO.score.

IBM,.a.leading.provider.of.big.data.systems,.maintains.that.more.than. 90%.of.the.data.that.exists.in.the.world.today.was.created.within.the.last. two.years..We.are.in.an.age.where.more.than.2.5.quintillion.bytes.of.data.

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Using Big Data and Analytics to Manage Risk • 205

are.created.every.day!.We.are.increasingly.becoming.familiar.with.terms. such.as.follows6:

•. gigabytes.(a.unit.of.information.equal.to.one.billion.(109).or,.strictly,. 230.bytes)

•. petabytes.(250.bytes;.1,024.terabytes,.or.a.million.gigabytes) •. exabytes.(a.unit.of.information.equal.to.one.quintillion.(1018).bytes,.

or.one.billion.gigabytes) •. zettabytes. (a. unit. of. information. equal. to. one. sextillion. (1021). or,.

strictly,.270.bytes) •. yottabytes. (a. unit. of. information. equal. to. one. septillion. (1024). or,.

strictly,.280.bytes)

Don’t. be. concerned. if. these. definitions. are. confusing.. They. confuse. us.also.

IBM.has.been.at.the.forefront.of.articulating.the.concept.of.big.data.7.In. one.of.its.analyses,.the.company.concludes.that.big.data,.which.admittedly. means.many.things. to.many.people,. is.no. longer.confined.to. the.realm. of.technology..It.has.become.a.business.priority.given.its.ability.to.affect. commerce.in.a.globally.integrated.economy..Organizations.are.using.big. data.to.target.customer-.centric.outcomes,.tap.into.internal.data,.and.build. a. better. information. ecosystem.. IBM. has. created. a. topology. that. looks. at.big.data. in.terms.of. four.dimensions.that.conveniently.start.with.the. letter.V.

The. first. dimension. of. big. data. is. volume,. which. represents. the. sheer. amount.of.data..Perhaps.the.characteristic.most.associated.with.big.data,. volume. refers. to. the. mass. quantities. of. data. that. organizations. are. try- ing.to.harness.to.improve.decision.making..As.mentioned,.data.volumes. continue. to. increase. at. an. unprecedented. rate.. However,. what. consti- tutes. truly.high.volume.varies.by. industry.and.even.geography.and.can. be.smaller.than.the.petabytes.and.zettabytes.often.referenced.in.articles. and.statistics.

Next, variety.refers.to.the.different.types.of.data.and.data.sources..This. dimension.is.about.managing.the.complexity.of.multiple.data.types,.includ- ing. structured,. semistructured,. and. unstructured. data.. Organizations. need.to.integrate.and.analyze.data.from.a.complex.array.of.both.traditional. and.nontraditional.information.sources.within.and.outside.the.enterprise.. With.the.proliferation.of.sensors,.smart.devices,.and.social.collaboration. technologies,.data.are.being.generated.in.countless.forms.such.as.text,.web.

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206 • Supply Chain Risk Management: An Emerging Discipline

data,.tweets,.sensor.data,.audio,.video,.click.streams,.log.files,.and.much. more..The.bottom.line.is.that.data.come.in.many.forms.

The.third.dimension,.velocity,.refers.to.data.in.motion..The.speed.with. which. data. is. created,. processed,. and. analyzed. continues. to. acceler- ate.. Contributing. to. this. higher. velocity. is. the. real-.time. nature. of. data. creation,. especially. within. global. supply. chains,. as. well. as. the. need. to. incorporate.streaming.data.into.business.processes.and.decision.making.. Velocity.impacts.latency—the.lag.time.between.when.data.are.created.or. captured.and.when.they.are.accessible.and.able.to.be.acted.upon..Data.are. continually.being.generated.at.a.pace.that.is.impossible.for.traditional.sys- tems.to.capture,.store,.and.analyze,.resulting.in.the.development.of.new. technologies.with.new.capabilities.

Finally,.veracity.refers.to.the.level.of.reliability.associated.with.certain. types. of. data.. Striving. for. high-.quality. data. is. an. important. big. data. requirement.and.challenge,.but.even.the.best.data.cleansing.methods.can- not.remove.the.inherent.unpredictability.of.some.data,.like.the.weather,. the.global.economy,.or.a.customer’s.future.buying.decisions..The.need.to. acknowledge.and.plan.for.uncertainty.is.a.dimension.of.big.data.that.has. been.introduced.to.executives.to.better.understand.the.uncertain.world.of. risk.around.big.data..Veracity.requires.the.ability.to.manage.the.reliability. and.predictability.of.imprecise.data.types.

A. good. portion. of. the. data. within. global. supply. chains. is. inherently. uncertain..The.need.to.acknowledge.and.embrace.this.level.of.uncertainty. is.the.hallmark.of.big.data.and.supply.chain.risk.management..An.exam- ple. is. in.energy.production.where. the.weather. is.uncertain.but.a.utility. company. must. still. forecast. production.. In. many. countries,. regulators. require.a.percentage.of.production. to.emanate. from.renewable. sources,. yet. neither. wind. nor. clouds. can. be. forecast. with. precision.. So,. what. to. do?.To.manage.this.uncertainty,.analysts,.either.in.energy.or.supply.chain. management,.need.to.create.context.around.the.data.

One.way.to.manage.data.uncertainty.is.through.something.called.data fusion,. where. combining. multiple,. less-.reliable. sources. creates. a. more. accurate. and. useful. set. of. data. points,. such. as. social. media. comments. appended. to. geospatial. location. maps.. Another. way. to. manage. uncer- tainty.is.through.advanced.mathematics.that.embrace.uncertainty,.such. as. probabilistic. modeling,. discrete-.event. simulation. and. multivariate,. nonlinear.analyses.coupled.with.failure.mode.effects.analysis.(FMEA).

Most.observers.predict.a.major.impact.of.big.data.and.predictive.ana- lytics.on.the.global.economy..In.a.recent.Fortune.article,.an.expert.from.

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Using Big Data and Analytics to Manage Risk • 207

Gartner.suggested.that.over.a.relatively.short.time.period,.more.than.four. million.positions.worldwide.will.emerge.for.analytic.talent,.of.which.only. about.one.third.will.be.filled.8 Dice.com.has.identified.the.Top.10.techni- cal.skills.big.data.will.need.over.the.next.several.years..By.a.large.margin. the.first. is.Hadoop.plus. Java,.which. is.not. surprising. since. Java.powers. Yahoo,.Amazon,.eBay,.Google,.and.LinkedIn..After.that.it. is.Developer,. NoSQL,.Map.Reduce,.BigData,.Pig,.Linux,.Python,.Hive,.and.Scala.

The.shortage.of.professional.skills.in.Hadoop.and.NoSQL.has.given.rise. to.higher.pay.for.qualified.hires,.topping.$100K.on.average..The.real.win- ner.here.could.be.the.U.S..economy..Anticipating.a.multiplier.effect,.one. observer.predicts.that.for.every.big.data–.related.role.in.the.United.States,. employment.for.three.people.outside.IT.will.be.created.9.While.the.rise.of. big.data.presents.opportunities,. a. shortage.of.qualified. IT.professionals. also.exposes.an.organization.to.risk.

As. we. conclude. this. overview. of. big. data. and. predictive. analytics,. it. would. be. appropriate. to. close. this. section. with. some. key. findings. from. IBM’s.research.into.big.data..First,.across.multiple.industries,.the.business. case.for.big.data.is.strongly.focused.on.addressing.customer-.centric.objec- tives..Second,.a.scalable.and.extensible.information.management.founda- tion. is. a.prerequisite. for.big.data.advancement..Third,.organizations.are. beginning.their.pilot.and.implementation.programs.by.using.existing.and. newly.accessible.internal.sources.of.data..Next,.advanced.analytics.capa- bilities. are. required,. yet. often. lacking,. for. organizations. to. get. the. most. value.from.big.data..And.finally,.as.organizations’.awareness.and.involve- ment. in. big. data. grows,. four. stages. of. adoption. emerge,. which. the. next. section.presents.

the pROCeSS Of SuCCeSSfully leVeRaging Big data fOR MaxiMuM Benefit

Many.of.the.cases.we.describe.later.in.the.chapter.maintain.the.hallmarks. of.supply.chain.analytic.implementations..These.hallmarks.include.a.clear. business.problem.with.supporting.metrics;.a.focus.on.fact-.based.decision. making.and.on.improving.business.key.performance.indicators.(KPIs);.and. the.establishment.of.an.end-.to-.end,.enterprise-.wide.process.that.is.champi- oned.by.C-.level.management..Other.characteristics.include.forward-.looking. scenarios. and. causal. analysis. to. understand. variability. and. performance.

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208 • Supply Chain Risk Management: An Emerging Discipline

drivers.without.getting.lost.in.the.data..Scenarios.are.performed.iteratively. to.demonstrate.value.and.self-.fund.subsequent.improvement.opportunities.

Many. organizations. start. with. spreadsheets. as. a. proof-.of-.concept. (POC). and. then. migrate. to. some. form. of. business. intelligence. tool. to. perform.more.rigorous.analysis..Why?.According.to.the.Hackett.Group,. world-.class. procurement. organizations. on. average. spend. less. than. 30%. of.their.time.compiling.data,.compared.with.60%.for.the.bottom-.quartile. companies.. In. other. words,. while. typical. companies. still. compile. data,. world-.class.organizations.spend.more.of.their.time.analyzing.the.data.and. making. informed.decisions..The.CIO.of.a. leading.company.argues. that. 75%. of. the. effort. and. cost. when. managing. data. is. process. reengineer- ing.and.data.cleansing.and.creation,.and.the.other.25%.is.the.IT.portion.. He. further. states. that. when. people. say. their. systems. didn’t. deliver,. the. chances.are.they.missed.the.75%.part.they.should.have.been.working.on.

An.adoption.process.or.continuum.has.emerged.through.observation.of. big.data.and.predictive.analytic.projects,.or.what.IBM.calls.the.Four.E’s:. Educate,.Explore,.Engage,.and.Execute.”.Figure 11.1.depicts.this.emerging. adoption.continuum..We’ll.briefly.touch.on.the.key.elements.of.each.stage.

Education. is. the.first. stage. in. the.continuum.. Its.primary. focus. is.on. awareness.and.knowledge.development..In.this.stage,.most.organizations. are.studying.the.potential.benefits.of.big.data.technologies.and.analytics. and. trying. to. better. understand. how. big. data. can. help. address. impor- tant.business.opportunities..Also.within.the.first.stage,.the.potential.for. big.data.has.often.not.yet.been. fully.recognized.and.embraced.by.busi- ness.executives..Exploration,. the.second.stage,.defines. the.business.case. and.roadmap..Almost.50%.of.respondents.in.an.IBM.study.report.formal,. ongoing.discussions.within.their.organizations.about.how.to.use.big.data.

Focused on knowledge

gathering and market

observations

Developing strategy and

roadmaps based on business

needs and challenges

Piloting big data initiatives

to validate value and

requirements

Deploying two or more big

data initiatives and

continuing to apply

advanced analytics

Educate Explore Engage Execute

figuRe 11.1 The.Four.E’s.of.big.data.adoption.

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Using Big Data and Analytics to Manage Risk • 209

to.solve.important.business.challenges..Key.objectives.in.this.stage.include. developing.quantifiable.business.cases.and.creating.a.big.data.blueprint.or. roadmap..Most.organizations.in.this.stage.are.considering.existing.data,. technology,.and.skills.and.are.contemplating.where.to.start.and.how.to. develop.a.plan.aligned.with.their.organization’s.business.strategy.

Engagement,.the.third.stage,.is.about.embracing.the.value.of.the.data.. In. this. stage,. organizations. begin. to. prove. the. business. value. of. big. data.as.well. as.performing.assessments.of. their. technologies. and. skills.. Companies.in.this.stage.usually.have.one.or.more.proof-.of-.concept.proj- ects.under.way..These.companies.are.working.within.a.defined.scope.to. understand.and.test.the.technologies.and.skills.required.to.capitalize.on. the.new.sources.of.big.data.

Execute.is.the.final.stage.of.the.continuum..In.this.stage,.big.data.and. analytics. capabilities. are. more. widely. operational. and. implemented. within.the.organization..Many.organizations.here.manage.at.least.two.or. more.big.data.solutions.at.scale,.which.seems.to.be.a.threshold.for.advanc- ing. in. this. stage..The.companies. in. the.execute. stage.are. leveraging.big. data.to.transform.their.businesses.and.thus.are.deriving.the.greatest.value. from.their.information.assets.

Most. organizations. are. in. the. early. stages. of. big. data. development. IBM’s.research.concludes. that.24%.of.companies.are. focused.on.under- standing. the. concept. and. have. not. begun. the. journey,. while. 47%. are. planning. big. data. projects. and. developing. roadmaps.. Another. 28%. of. companies.are.developing.proofs.of.concept.or.have.already.implemented. full-.scale.solutions.

BaRRieRS and ChallengeS MOVing fORWaRd

The.challenges.to.utilizing.big.data.differ.as.organizations.move.through. each.of.the.four.stages.as.featured.in.Figure 11.2..A.consistent.challenge,. regardless.of.stage,.is.the.ability.to.articulate.a.compelling.business.case.. At.each.stage.big.data.efforts. rightfully.come.under.fiscal. scrutiny..The. current.global.economic.climate.and.supply.chain.risk.landscape.has.left. businesses. with. little. appetite. for. new. technology. investments. without. measurable. benefits.. After. companies. begin. their. proof. of. concept,. the. next.biggest.challenge.is.finding.the.right.skill.sets.to.operationalize.big. data,.including.technical,.analytical,.and.governance.skills.

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210 • Supply Chain Risk Management: An Emerging Discipline

As.shown.in.Figure 11.2,.different.obstacles.surface.as.companies.move. through.the.continuum10:

•. Acquisition of data..Data.are.available.from.so.many.sources.and. end.users.must.constantly.decide.which.will.be.useful.

•. Choosing the right architecture. This.involves.balancing.cost.and. performance.to.obtain.a.platform.based.around.programming.tech- niques.far.different.from.those.of.the.normal.desktop.environment.

•. Shaping the data to the architecture..This.involves.spending.time. capturing,.compiling,.and.uploading.the.data.to.be.aligned.with.the. architecture..With.all.the.new.technology,.transforming.the.data.can. be.a.time-.consuming.process.

•. Coding. This.includes.selecting.a.programming.language,.designing. the.system,.deciding.on.an.interface,.and.being.prepared.for.a.rap- idly.changing.environment.

•. Debugging and iteration. This.is.the.process.of.looking.for.errors.in. code,.architecture,.and.making.modifications.quickly.

tOOlS, teChniQueS, and MethOdOlOgieS SuppORting Big data

Let’s.profile.the.techniques.that.are.being.utilized.by.organizations.running. big.data.projects..Figure 11.3.gives.us.a.sense.of. the.tools.and.techniques. that.are.being. leveraged..More. than.75%.of.companies. report.using.core.

Educate Explore Engage Execute

Articulating a compelling business case

Understanding how to use big data

Management focus and support

Data quality

Analytic skills

Technical skills

figuRe 11.2 Big.data.primary.obstacles..(Source:.Adapted.from.IBM.2013.Big.Data.Executive.Report.)

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Using Big Data and Analytics to Manage Risk • 211

analytics.capabilities,.such.as.querying.and.reporting.and.data.mining.to. analyze.big.data,.while.more.than.67%.report.using.predictive.modeling.

These.foundational.methods.are.a.pragmatic.way.to.start. interpreting. and.analyzing.big.data..The.need.for.more.advanced.visualization.tech- niques. increases. with. the. introduction. of. big. data. because. datasets. are. often.too.large.for.business.or.data.analysts.to.view..The.next.highest.usage. of.techniques.and.tool.sets.are.optimization.models.and.advanced.analyt- ics.to.better.understand.how.to.transform.key.business.processes..Many. organizations.are.embracing.simulation.and.pattern.recognition.to.ana- lyze.the.many.multivariate,.nonlinear.relationships.within.big.data.

As. you. can. see. from. Figure 11.3,. more. and. more. organizations. are. focusing. on. unstructured. data. to. analyze. text. in. its. natural. state,. such. as.transcripts.from.call.center.conversations..These.tools.and.techniques. include.the.ability.to.interpret.and.understand.the.nuances.of.language,. such.as.sentiment,.slang,.and.intention..And.with.the.tools.emerging.to. analyze.these.new.and.unstructured.forms.of.data,.it’s.no.surprise.that.the. skills.to.manage.these.techniques.are.in.short.supply..It.seems.apparent.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Voice analytics

Video analytics

Streaming analytics

Geospatial analytics

Natural language text

Simulation

Optimization

Predictive modeling

Data visualization

Data mining

Query & reporting

IBM Big Data Executive Report 2013

Percentages %

figuRe 11.3 Big.data.analytics.capabilities.and.tools.

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212 • Supply Chain Risk Management: An Emerging Discipline

that.there.are.a.host.of.tools.and.techniques.emerging.to.support.the.big. data. effort.. Techniques. such. as. standard. reporting,. ad. hoc. reporting,. query.drill-.down,.cloud-.based.analysis,.classical.deterministic.forecasting. techniques,.predictive.modeling,.simulation,.optimization,.pattern.recog- nition,.and.artificial.intelligence.are.all.coming.on.board.at.an.accelerat- ing.rate.

Changing.gears.a.bit,.but. still. remaining. in. the. tools,. techniques,. and. methodologies. arena. of. big. data,. it. appears. that. organizations. that. are. embracing. Software-.as-.a-Service. (SaaS),. or. cloud-.based. technology,. are. utilizing. those. tools. much. more. pervasively. throughout. their. organiza- tions,.partly.because.they.are.able.to.make.better.use.of.scarce.IT.skills.11.We. mentioned.earlier.the.lack.of.technical.skills,.in.house,.as.an.obstacle..Also,. it.appears.that.organizations.that.leverage.outsourced.IT.tools.and.consult- ing.skills.are.experiencing.a.much.richer.and.more.complete.solution.when. compared.with.organizations.that.are.not.using.the.SaaS.approach.

Here.is.a.quick-.hit.definition.of.the.SaaS.concept:.With.SaaS.or.cloud-. based.business.intelligence.(BI),.the.software.itself.is.not.licensed,.owned,. or.installed.by.the.organization..Instead,.the.software.resides.in.a.remote. third-.party.data.center.and.the.functionality.provided.by.the.software.is. accessed.over.the.Internet.and.rented..This.service.is.typically.paid.for.as. a.monthly.subscription.

One.research.group.has.concluded.that.the.use.of.SaaS.to.drive.big.data. analytics.offers.advantages.across.many.dimensions.12.More. than.60%.of. organizations.using.a.SaaS.solution.were.satisfied.or.very.satisfied.with.ease-. of-.use.of.this.approach.as.opposed.to.only.41%.of.companies.not.using.SaaS.. Just.over.80%.of.SaaS.BI.users.have.access.to.drill-.down.to.detail.capability. as.opposed.to.58%.for.non-.SaaS.users..And.just.over.60%.of.SaaS.BI.users. are.able.to.tailor.their.solution.quickly.as.opposed.to.only.41%.of.non-.SaaS. users..Companies.that.utilize.SaaS.BI.tools.say.that.they.can.find.informa- tion.they.need.in.time.to.support.their.decisions.within.one.hour.of.raw.data. being.captured,.or.what.is.called.time- to- decision.and.time- to- value,.84%.of. the.time.as.opposed.to.only.70%.of.the.time.with.organizations.not.using. SaaS.BI..Finally,.organizations. that.use. the.SaaS.approach.are.40%.more. likely.than.others.to.exchange.data.openly.and.easily.across.business.units.. Other.findings.not.mentioned.here.also.reveal.the.value.of.Saas.

The.idea.of.augmenting.what.you.already.have.in.house.with.third-.party. companies.is.gaining.traction,.especially.with.analytics..Many.companies.

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have.packaged.and.outsourced.supply.market.intelligence.while.others.have. developed. hosted. analytics. tools. and. bundled. professional. services. and. analysis.across.the.entire.supply.chain.spectrum.

We’d. like. to. close. this. section. with. some. comments. on. analytics. in. manufacturing. from. the. vice-.president. of. Invensys. Solutions.. He. talks. about.big.data.for.manufacturing.by.comparing.big.data.for.consumers. and.the.use.of.Google..He.says.we.start.Google.maps.on.our.phone.and.it. immediately.knows.where.we.are..We.click.a.box.and.it.shows.the.traffic. from.here.to.the.airport..If.we’re.hungry,.it.can.pull.down.restaurants.and. menus..Now,.take.this.into.the.supply.chain.arena..All.that.information.is. available,.but.instead.of.restaurants,.we’re.looking.for.the.best.batch,.opti- mal.production.run,.and.more..A.good.analytics.manufacturing.system. has. to. show.what. is.out. there,.display. the. information. that. is. available,. interpret.what.it.means,.how.to.react.to.it,.and.then.help.predict.what.is. coming.next.

hOW eaRly adOpteR COMpanieS leVeRage Big data

With.a.broad.definition.of.big.data.now.established,.we.want.to.provide. examples.of.industries.that.are.leveraging.big.data.for.competitive.advan- tage..In.this.section.we’ll.touch.on.several.industries.and.dig.a.bit.deeper. into.a.few.name-.brand.companies.that.are.leveraging.this.approach.for.a. competitive.advantage.

During.our.initial.evaluation.of.the.big.data.landscape,.we.speculated. that.there.might.be.an.industry.that.is.far.and.away.the.leader.in.leveraging. big.data.for.competitive.advantage..With.that.hypothesis,.we.attempted.to. gather.data.and.profile.the.use.of.big.data.by.industry..The.hypothesis.that. one. industry.might.dominate. the. landscape. is. far. from.reality..The. top. four. industries.within.our.sample.that.use.big.data.are.consumer.pack- aged.goods. (CPG)/grocery. (16%.of.firms),. electronics. (10%),. automotive. assembly. (10%),.and.energy. (10%)..All.other. industries.were.7%.or. less.. It’s. evident. that. these. industries. are. leading. the. way. toward. leveraging. predictive.analytics.to.solve.operational.problems,.followed.by.additional. industries.beginning.their.use.of.big.data..Overall,.we.have.a.long.way.to. go.before.the.use.of.big.data.becomes.routinized.

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214 • Supply Chain Risk Management: An Emerging Discipline

Consumer packaged goods

A. large. multibillion. dollar. CPG. company. with. razor-.thin. margins. was. facing.highly.volatile.commodity.prices.on.the.supply.side.of.its.business. and.unforgiving,.price-.sensitive.retailers.on.the.demand.side..The.compa- ny’s.approach.was.to.develop.an.integrated.Sales.&.Operations.Planning. process. and. link. it. to. the. supply. market. by. integrating. supply. market. intelligence.and.purchase.price.forecasts..The.company.used.this.forward-. looking.supply.intelligence.to.create.robust.scenarios,.perform.additional. analyses,. and. then. optimize. all. options. associated. with. each. scenario.. It. attempted. to. mitigate. risk. by. finding. substitute. materials,. modifying. specifications,. reconfiguring. its. product. mix,. changing. its. supply. chain. network.and.delivery.methods.where.possible,.hedging.on.the.financial. side,. as.well. as.modifying. strategies. throughout. the.planning.horizons.. This.effort.resulted.in.minimizing.millions.of.dollars.of.product/.customer. profit.erosion.and.more.robust,.predictable.strategies.

dell Computers

Most.of.us.know.that.Dell.is.a.company.in.transition..After.dominating. the.enterprise.PC.market.for.decades,.the.Texas-.based.configure-.to-.order. manufacturer.is.making.a.definitive.move.away.from.the.product.side.of. the.business.and. toward.services.and.solutions..Unfortunately,.over. the. past.decade,.Dell’s.strategy,.options,.and.variants.in.models,.software.con- figurations,.memory,.screens,.and.other.customizable.features.has.resulted. in.over.seven.septillion.possible.configurations.of.Dell’s.products!.A.sep- tillion.is.equivalent.to.1,000,000,000,000,000,000,000..Obviously,.product. portfolio.complexity.had.become.a.major.risk.for.the.company.

To.trim.its.product.portfolio.Dell.began.to.utilize.its.abundance.of.big. data.. A. Dell. team. created. a. new. system. called. optimized configuration.. Dell’s.analytics. team.clustered.high-.selling.configurations. from.histori- cal.data.to.create.technology.roadmaps..The.team.also.created.automated. algorithms.to.identify.what.configurations.Dell.should.build.to.order.and. what.Dell.should.produce.for.inventory..The.analysis.leveraged.historical. data.and.ran.cluster.analysis.to.identify.the.most.common.configurations. sought.by.customers.

Clustering. around. commonality. of. product. ordering. allowed. Dell. to. trim. the. seven. septillion. options. to. several. million. and. provided. the. company’s. marketing. and. supply. chain. teams. with. agreement. on.

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Using Big Data and Analytics to Manage Risk • 215

preconfigured. products. built. for. inventory. and. ready. to. ship.. This. new. supply.chain.strategy,.driven.by.data.analysis,.also.supports.the.company’s. make-.to-.order.strategy.

Still.another.use.of.big.data.at.Dell.has.been.inside.the.company’s.online. ordering.system..Dell’s.business.intelligence.team.ran.analytics.on.click. stream.data,. tracing.every.move.and.path.taken.by.customers..The.out- come. showed. that. customers. navigate. through. more. than. 40. clicks. to. place.an.order..The.team.used.that.information.to.optimize.the.site.and. reduce.the.number.of.clicks.to.five.

Western digital

Western. Digital,. a. global. manufacturer. of. disc. drives,. is. obsessed. with. quality..To.serve.that.obsession.the.company.has.transformed.its.manu- facturing.process. to.allow.scanning,. recording,. testing,.and. tracking.of. every.disc.drive.produced.while.still.on.the.production.line..By.running. real-.time.shop-.floor.analytics,.the.company.can.locate.and.remove.non- conforming. discs. before. they. reach. the. customer.. Even. if. a. disc. passes. an.initial.analytical.review,.if.further.analysis.reveals.a.problem,.the.disc. can.be.located.and.pulled.from.inventory.bins..This.capability,.supported. by.big.data,.has.resulted.in.the.lowest.warranty.return.rate.in.the.entire. industry..It.has.also.helped.make.Western.Digital.the.supplier.of.choice.for. many.computer.manufacturers.

harley davidson

Harley. Davidson,. the. king. of. the. hogs,. introduced. software. that. tracks. even.the.minutest.details.on.the.assembly.floor,.such.as.the.speed.of.fans. in. the. painting. booths.. When. the. software. detects. that. the. fan. speed,. temperature,.or.humidity.has.deviated.from.the.optimal.settings,.it.auto- matically. adjusts. the. operations.. This. allows. a. consistency. on. the. shop. floor.by.staying.within.preestablished.parameters..The.software.has.also. been.used.to.identify.bottlenecks.on.the.assembly.floor..One.of.Harley’s. goals.is.to.complete.a.motorcycle.every.86.seconds..A.recent.study.using. shop. floor. data. revealed. that. the. rear. fender. assembly. time. was. taking. longer. than. planned.. The. company. changed. the. factory. configuration. so.the.fenders.would.flow.directly.to.the.assembly.line.rather.than.being. placed.on.carts.and.moved.across.the.floor..This.is.but.one.example.of.how.

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216 • Supply Chain Risk Management: An Emerging Discipline

Harley.Davidson.is.using.big.data.to.streamline.its.operations.and.avoid. operational.risk.

Raytheon

Raytheon,. a. household. name. in. the. aerospace/.defense. manufacturing. arena,.is.betting.on.big.data.to.reduce.the.risk.of.quality.and.operational. problems.. In. its. Huntsville,. Alabama,. missile. plant,. if. a. screw. is. sup- posed.to.be.turned.13.times.after.it.is.inserted.but.instead.is.turned.only. 12.times,.an.error.message.flashes.and.production.of.the.missile.or.com- ponent.stops..“Manufacture.of.a.missile.is.either.right.or.it’s.not;.there’s.no. in.between,”.says.a.Raytheon.executive..Many.manufacturers.are.install- ing. sophisticated. automated. systems. to. gather. and. analyze. shop. floor. data,.known.as.manufacturing.execution.systems.(MES)..Manufacturers. are.looking.harder.at.data.partly.because.of.increasing.pressure.from.cus- tomers. to.eliminate.defects.and. from.shareholders. to. squeeze.out.addi- tional. cost.and.mitigate. risk. to. the.brand..These.new.capabilities.mean. Raytheon.is.catching.more.flaws.as.they.occur..Raytheon.also.keeps.data. for.each.missile,. including. the.names.of.all. the.machine.operators.who. worked.on.any.part.of.it,.as.well.as.the.humidity,.temperature,.and.more. at.each.workstation.

The.system.is.designed.to.prevent.any.operator.from.performing.a.task. for. which. he. or. she. is. not. certified.. According. to. Raytheon,. leveraging. big.data.systems.is.a.form.of.risk.mitigation.and.management..Millions. of.dollars.have.been.spent.in.the.past.to.rework.items.that.did.not.meet. specifications. If.Raytheon’s.experience.is.any.indicator,.cost.containment,. real-.time.event.monitoring,.and.process.optimization.are.but.a.few.of.the. key. drivers. supported. by. big. data.. Tracking. physical. items. and. people. throughout.the.supply.chain,.capturing.and.acting.on.streaming.data,.and. enabling.faster.reaction.to.specific.problems.before.they.escalate.in.major. situations.is.becoming.the.norm.rather.than.the.exception.

european electrical utility

A.major.European.electric.utility.company.sought.to.improve.the.man- agement.of.budgeted.versus.actual. spend. for.nonfeedstock.and. indirect. spending.. It. wanted. a. single. system. that. separated. consumption. varia- tion,. within. a. contract. and. across. contracts,. external. market. pricing. variation,. and. procurement-.led. pricing. impacts.. The. company. used. a.

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Using Big Data and Analytics to Manage Risk • 217

third-.party.tool.for.spend.analysis.and.procurement.performance.analysis.. These.data.were.cross-.referenced.against.an.external.database.with.thou- sands.of.price.indexes..This.approach.of.combining.internal.and.external. data.and.benchmark.indexes.allowed.for.fact-.based.discussions.and.deci- sion.making.for.continuous.improvement.in.its.cash.flow.management.

This. approach. confirmed. that. analytics. works. best. when. integrated. with.external.information..The.utility.company.concluded.that.integrat- ing. internal. and. external. data. through. the. use. of. big. data. analytics. is. an.enabler.for.managing.supply.risk,.supplier.risk,.regulatory.risk,.com- petitive.risk,.and.intellectual.property.risk..Managing.these.risks.should. include. analytical. approaches. such. as. scenario. planning,. Monte. Carlo/. probabilistic. modeling. to. quantify. the. probability. of. occurrence. and. impact,.segmenting.and.visualizing.risk.using.heat.maps,.and.predictive. analytics.to.manage.risk.

Schneider

Schneider.National,.a.$3.billion.transportation.and.logistics.company,.has. developed.a.computer.model.that.mimics.human.decision.making,.help- ing. the.company. to.assign. trucks.and.drivers. in. the.most.cost-.effective. way.possible..At.any.given.time,.Schneider.has.10,000.trucks.on.the.road. with.over.30,000.trailers.waiting.to.be.picked.up.or.delivered..Drivers.work. alone.or. in.pairs,.and.Schneider.must.get. them.back.home.by.a.certain. date.and.time..Drivers.also.need.to.conform.to.the.government’s.hours-. of-.service.regulations.regarding.rest.periods.and.breaks.

With.the.help.from.several.Princeton.University.researchers,.Schneider. developed.a.simulator.utilizing.dynamic.programming,.which.takes.into. account.the.presence.of.uncertainty..The.simulator,.which.took.two.years. to.develop,.runs.forward.in.time.for.three.weeks.to.approximate.the.value. of.having.a.truck.and.driver.at.a.certain.location.at.a.certain.time..The.out- put.from.the.report.is.a.called.a.first-.pass.cost.estimate..The.tool.then.runs. backward. in. time,. something. called. postanalysis,. to. reconcile. the. past. results.with.those.that.were.determined.in.the.future.estimate..The.simu- lator. then. runs. forward. again. for. three. weeks. and. then. backward. as. it. seeks.to.improve.the.total.cost.estimates..This.forward–.backward.process. encompasses.hundreds.of.thousands.of.iterations.

Schneider. estimates. its. big. data. tool. has. saved. the. company. tens. of. millions.of.dollars.as.well.as.increased.revenue.by.justifying.price.hikes. to. customers. with. specific. service-.level. constraints.. The. simulator. also.

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218 • Supply Chain Risk Management: An Emerging Discipline

provides.a.quantifiable.methodology.to.exercise.what-.if.analyses,.such.as. determining.the.marginal.value.of.hiring.new.drivers.in.a.certain.region. to.handle.growing.volume..Moving.forward,.Schneider.expects.to.use.the. simulation. tool. to.help. identify.new.businesses. to.pursue..As.an.opera- tions.research.analyst.at.Schneider.says, “The.tool.is.so.powerful.that.when. someone.presses.us.on.the.impact.of.different.customer.policy.changes,. we.have.the.facts.and.we.have.the.data..The.value.of.this.big.data.tool.is. to. be. able. to. take. these. complex. business. issues. and. opportunities. and. give.them.a.good,.solid.analysis.”13.Schneider.understands.clearly.the.link. between.data.management.and.strategic.risk.management.

COnCluding thOughtS

Few.should.disagree.with.the.notion.that.big.data.and.predictive.analyt- ics.are.here.to.stay..Big.data,.predictive.analytics,.and.many.of.the.tools. and. techniques.discussed. in. this.chapter.and. in.Chapter 10.are.provid- ing.approaches. for.codifying,. classifying,. analyzing,.and.acting.on.vast. amounts.of.data,.most.of.which. is. the.size.many.of.us.have.never.dealt. with.in.our.professional.careers..We’ve.witnessed.an.increasing.number. of. companies. that. have. leveraged. their. data. and. predictive. analytics. to. solve.complex.supply.chain,.manufacturing,.and.customer-.centric.issues. to. enhance. revenue,. reduce. cost,. improve. asset. utilization,. and. reduce. supply.chain.risk.

A. study. by. the. Aberdeen. Group. reinforces. the. finding. that. top. per- formers.are.making.advanced.analytics.activities.a.priority.to.take.con- trol.of.manufacturing.complexity.and.supply.chain. risk..This. is.a.good. thing.since.uncertainty,.complexity,.and.risk.continue. to.grow.globally.. Research.reveals. that. the.companies. that.are.best.at. leveraging.big.data. average.a.19%.year-.over-.year. increase. in.operating.profit.as.opposed. to. only.a.9%.increase.for.all.other.companies..And.80%.of.companies.that.are. the.best.at. leveraging.big.data.have.witnessed.improvement.in.the.cycle. times.of.their.key.business.processes.over.a.one-.year.period,.as.opposed.to. 47%.for.average.companies.and.39%.for.laggard.companies.14.Increasingly,. the.ability.to.compete.successfully.as.well.as.manage.supply.chain.risk.will. rest.upon.a.company’s.ability.to.leverage.big.data.and.predictive.analytics.

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Summary of key points

•. The.Leadership.Council.of. Information.Advantage.sees.big.data.as. data.sets.that.are.growing.exponentially.and.that.are.too.large,.too.raw,. or.too.unstructured.for.analysis.using.relational.database.techniques.

•. Predictive.analytics.(PA).encompasses.a.variety.of.techniques.from. statistics,. data. mining,. and. game. theory. that. analyze. current. and. historical.facts.to.make.predictions.about.the.future.

•. IBM.has.created.a. topology.that. looks.at.big.data. in.terms.of. four. dimensions:.volume,.variety,.velocity,.and.veracity.

•. One.way.to.manage.data.uncertainty.is.through.data.fusion,.where. combining.multiple,.less-.reliable.sources.creates.a.more.accurate.and. useful.set.of.data.points..A.second.way.is.through.advanced.math- ematics.that.embrace.uncertainty.

•. World-.class. procurement. organizations. on. average. spend. less. than.30%.of.their.time.compiling.data,.compared.with.60%.for.the. bottom-.quartile.companies..World-.class.organizations.spend.more. of.their.time.analyzing.the.data.and.making.informed.decisions.

•. An.adoption.process.or.continuum.has.emerged.through.observa- tion.of.big.data.and.predictive.analytic.projects,.or.what.IBM.calls the.4-Es:.Educate,.Explore,.Engage,.and.Execute.

•. Foundational.methods.are.a.pragmatic.way.to.start.interpreting.and. analyzing. big. data,. but. the. need. for. more. advanced. visualization. techniques.increases.with.the.introduction.of.big.data.because.data- sets.are.often.too.large.for.business.or.data.analysts.to.view.

•. Consumer. packaged. goods. (CPG)/grocery,. electronics,. automotive. assembly,.and.energy.are.the.four.industries.leading.the.way.toward. leveraging.predictive.analytics.to.solve.operational.problems.

endnOteS

. 1.. McKendrick,. Joe.. “Big. Data,. Big. Issues:. The. Year. Ahead. in. Information. Management.”.2010.

. 2.. Eshkenazi,.Abe..APICS.Big.Data.Insights.and.Innovation.Report,.2012.

. 3.. Schuster,. Edmund.. “Big. Data. Is. a. Big. Reality.”. Accessed. from. http://ingehygd. blogspot.com/2012/02/big-.data-.is-.big-.reality.html.

. 4.. Lohr,. Steve,. “The. Age. of. Big. Data.”. New York Times,. accessed. from. http://www. nytimes.com/2012/02/12/Sunday-.review/.bid-.data-.impact-.in-.the-.world.html.

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220 • Supply Chain Risk Management: An Emerging Discipline

. 5.. Accessed. from. http://www.apics.org/.industry-.content-.research/.publications/.apics-. dictionary.

. 6.. All.definitions.were.retrieved.from.Google.

. 7.. IBM. Global. Business. Services. Business. Analytics. and. Optimization. Executive. Report,. “Analytics:. The. Real-.World. Use. of. Big. Data.”. in. collaboration. with. Said. Business.School.at.the.University.of.Oxford,.2012–2013.

. 8.. Fisher,.Ane..“Big.Data.Could.Generate.Millions.of.Jobs.”.Fortune,.May 21,.2013.

. 9.. Fisher,.Ane..“Big.Data.Could.Generate.Millions.of.Jobs.”.Fortune,.May 21,.2013.

. 10.. Crandall,.Richard.“The.Big.Data.Revolution.”.APICS Magazine,.March/.April,.2013.

. 11.. White,. David.. Aberdeen. Group’s. Analyst. Insight. Report,. “Software-.as-.a-Service. Helps.Deliver.Satisfied.Analytics.Users.”.May.2013.

. 12.. White,. David.. Aberdeen. Group’s. Analyst. Insight. Report,. “Software-.as-.a-Service. Helps.Deliver.Satisfied.Analytics.Users.”.May.2013.

. 13.. Coster,.Helen.“Calculus.for.Truckers.”.Forbes,.2013.

. 14.. Lock,.Michael..Aberdeen.Group’s.Embedded.Analytics.Report,.March.2013.

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