futurecasting: how the rise of big social data api is set to transform the business of corporate...

7/28/2019 Futurecasting: How the rise of Big Social Data API is set to Transform the Business of Corporate Recruiting

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Copyright2013. Korn/Ferry International/Futurestep, Inc. All rights reserved. Talent with impact

ContentsForeword by Gerry Crispin

Introduction by Neil Griths

The future of candidate insight

Converging trends, emerging capabilities

Big Datas impact on talent acquisition

The strengths and weaknesses of CRM today

Futurecasting what might it look like in practice?

First things rst: building a t-for-purpose CRM

Toward Futurecasting at Informatica

Creating the Talent Knowledge Library

Drilling down at Informatica and democratizing talent acquisition

Big Social Data: the engine of Futurecasting methodology

Trust in Registry: the implications of Futurecasting for theemployer brand

Seven things organizations should do right now to implementa Futurecasting methodology

About the author

References

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There was a time, not so long ago, whenrecruiting was very much simpler. You hadan approved opening and you lled it.The technology tools at your disposalincluded a phone, a rolodex, a notebookand a paper spreadsheet. Every recruitingoce had a secretary to help arrange theinterview schedule. And quality candidateswere plentiful.

Sourcing meant calling people on thatrolodex, plus searching through other keysources the resumes of applicants whodpreviously made it to the nalist stage,your own private library of Whos Whodirectories, as well as professional journalswhose authors could be targets.

Getting the word out meant calling anadvertising agency before Thursday,the deadline for most Sunday classiedsection display ads. The biggest chokepoint was getting the envelopes openedand the resumes sorted by job.

A recruiting strategy meant knowing howlong you would try to do all this on yourown before calling in the third-party cavalry.Data conversations in those days werelimited to selection and assessment

decisions. The rest was simple arithmeticrelated to scale, relevant costs and little else.

How many openings did we have?How many candidates? How many werequalied? How many hires were madein how much time? Where did we spendmoney? What was the most ecient useof our time in the assembly line, one-size-ts-all world we lived in? Cost per hire wasabout the only thing possible to manipulate any other data collection would havesimply taken up more time and moneythan could be justied.

Times have certainly changed. Today, thereare multiple layers of technologies, tools,partners and services embedded in ourrecruiting processes many of them

automated, operating in real time and,unfortunately, lacking any human oversightto ensure they continue to work in alignmentwith the businesses they serve.

At the same time, the universe of potentialapplicants is increasingly knowable. In fact,billions of people are instantly identiable globally years in advance of the momentwe might need them. We may soon be ableto access enough information to predict withhigh condence how successful theydbe in our workforce, without ever havingspoken to them. Some claim this is alreadya possibility.

There are other factors at play. One of themost important is the fact that the pool ofcandidates capable of driving businessperformance forward has diminished.

In the US, for example, for every 100,000students entering the 9th grade in 2013,only 68,000 will graduate from high school in2016. Only 40,000 of them will enter collegethat same year and in 2021 ve yearslater fewer than 17,000 will graduatewith a college degree. 800 of these collegegraduates will be engineers, but in that grouponly 125 will be mechanical engineers. 15 of

the mechanical engineers will be women andfewer than ve of those women will remainworking in the profession by 2026.

Even today, if you have an opening fora mechanical engineer with three to veyears of experience in high-speed packagingdesign (and an SLA to ensure the slate isdiverse), you know the competition is erceand getting more so. Someday soon yourcompanys survival may very well dependon being able to compete by a) getting toknow those ve women even before theyhave three to ve years experience or

b) changing the conversion rates notedabove to produce more high school graduates,college graduates and engineers.

So the future we are facing is very dierent tothe past I described earlier. While recruitingas a profession is becoming ever-more complexand sophisticated, there is growing intensityof competition for quality candidates toll pivotal positions. The real challenge and indeed the real opportunity is learninghow to unlock the huge potential of theunprecedented levels of data we have accessto today. This whitepaper is a step inthat direction.

Gerry CrispinCareerXroads

Foreword

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Nobody knows for certain what the futureholds. But to me, it seems a sure thing that thecoming years will see the rise of what we callFuturecasting: the ability to interrogate bigdata generated by the increasingly socialdigital world, and to begin basing hiringstrategies and tactics on the new insightsthat are created.

The potential, especially for the biggest globalbrands, is truly immense. There are literallybillions of future applicants who could beidentied, targeted and engaged yearsbefore their talents are even needed. In fact,the data already exists to do this.

However, few organizations have dedicatedthe time and resource to intelligently andeectively mine that data, because it is notyet considered an essential agenda item forsenior professionals in talent acquisition.But when the industry wakes up to theuntapped potential, that situation is sureto change. And once it does, the key to usingdata to identify trends and patterns willbe ensuring that the sources are reliable,and the techniques used are rst-class.

At Futurestep, weve spent the past fourteenmonths building a decision support tool

known as Foresight to tackle the convergenceof big data and operational efficiencies.Foresight takes data from multiple systemsbeing used across the talent acquisitionlifecycle and presents information in a clear,concise display engine. From a single system,clients can now aggregate data into a logicalformat for easy decision-making.

Suddenly, by viewing the data in theForesight dashboard, HR professionalscan see key decision metrics emerging and they can use that to determine howtheir organization and investments intalent acquisition are performing.

Of course, HR professionals are not datascientists, and theres no reason to imaginethey will be in the years to come either.Thats why the expertise of thought leaderslike Dave Mendoza will prove to be vitalfor the talent industry. Here at Futurestep,weve been working with Dave to scope outthe possibilities and practicalities of usingmultiple technologies to predict where tofocus talent acquisition activities.

Whether through dened and future-proofedCustomer Relationship Management platforms(CRMs for short), social media data,or Applicant Tracking Systems, the holygrail is to be able to use these technologiesto predict where the best and most relevanttalent will be found.

A key part of that is ensuring that data ishigh-quality and sustainable. The Futurecastingconcept is the result of exploratory work seekingto dene the best ways of applying big data

principles to the talent acquisition process.Were excited to be working with thoughtleaders like Dave Mendoza to help shapeand dene what comes next.

By working with industry specialists and ourcolleagues across Korn/Ferry Internationaland the Korn/Ferry Institute, our intent is toensure we continue to stay ahead of the curve,embrace the most relevant trends and helpclients to use technology and innovationto their best advantage.

Neil GrithsGlobal Practice Leader,Talent Communications& Employer Brand

Futurestep

Introduction

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Todays business world faces more datapoints than even before. But these have novalue unless we can use them to make betterdecisions. Just imagine if we could transformall the cluttered, valueless data that existsand use it to make sourcing functions moreeective, to dramatically improve workforceplanning, and to increase the strategic valueof competitive intelligence. That is what theidea of Futurecasting, as a methodology,oers organizations.

A number of recent trends have convergedto reveal Futurecasting as a high-potential

concept. On one hand, in an increasinglyknowledge-based economy, the globalizationof corporations yields an urgent need forever-better talent acquisition; CEOs leadingsome of the worlds largest companies oftenspeak of this need. On the other hand,powerful new tools are at our disposal most notably social media platforms,integrated systems, and cloud storageof information. These enhance our abilityto make use of ubiquitous Big Data.

The future of candidate insight

For instance, having longitudinal data(an always-on dynamic record) is nowpossible thanks to these tools. In fact,a large majority of people in the developedworld cannot escape their own longitudinaldata. After all, who among us has not leftsome digital record of our interests andachievements on sites such as LinkedIn orFacebook? Recruiters are now theoreticallyable not only to tap into these data streams,but also to manipulate the data to meetspecific needs. It simply comes downto process, albeit a process that needs totackle the complexities inherent in any

Big Data initiative.

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Converging trends, emerging capabilities

Futurecasting is a concept thats built on anumber of key trends and developments ofrecent years. Understanding Futurecastingspotential and application is impossiblewithout rst understanding the trajectoriesof each of these trends.

Big Data: a collection of data sets solarge and complex that it becomes dicultto process using hands-on databasemanagement tools. Unlocking Big Data canbring huge benets, as has been shown ina number of other elds. Today, for instance,techniques to interpret Big Data help us tospot business trends, measure the quality

of research and combat crime.Social: for billions of people, the rise ofsocial networking has transformed the waythey conduct their personal and professionallives. LinkedIn, Facebook, MySpace, Viadeo,Xing and Twitter are among the best knownchannels, but far from the only ones. And thesector is moving at a phenomenal pace. Only10 years ago, Facebook was a site calledFacemash with just 450 visitors.

Put Big Data and Social together, and you get

Big Social Data: every interaction withsocial media creates data points and these,

over time, oer the potential to knowindividuals and groups within society infar greater detail than is currently possible.The marketing and research opportunitiesof Big Social Data have only just begunto be explored. But the impact on talentacquisition looks certain to be just asdramatic as the impact on the wider worldof sales and marketing.

The following glossary of terms will helpreaders further understand the remainingcontents of this whitepaper:

CRM I:Customer Relationship ManagementAs a way of gaining insight into customerbehaviors and buying patterns, sales andmarketing departments used CRM platformsrst. Data generated could provide valuableguidance on how warm or cold a sales leadwas. These platforms are now adapting toBig Data and Big Social Data, providing newopportunities for marketers and salespeople.

CRM II:Candidate Relationship ManagementThe rst CRM tools used in recruitment weresimply repurposed Customer RelationshipManagement platforms. But soon, CandidateRelationship Management systems weredeveloped not only capturing information,but also enabling regular communicationwith the right individuals.

Note: through the rest of this paper,the acronym of CRM refers, in mostinstances, to CRM II.

Advanced Programming Interface (API)This is a tool which allows dierent digitalplatforms to share dynamic data. For example,an API would be needed to extract informationfrom a site like Facebook and then feed it intoother applications, such as a companysown database.

Social network aggregation platformsThese enable users to share their activitiesfrom destinations such as LinkedIn, Facebook,Twitter and other social platforms. Users canalso integrate their blog posts and commentsin the aggregation platform. Everything isshown in real time to other members whosubscribe to a particular community, whicheliminates the need to jump from one socialmedia network to another.

FuturecastingA next-generation approach to CandidateRelationship Management that harnessesBig Social Data to create a level of insightnever before possible.

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Futurecasting 7

Big Datas impact on talent acquisition

For much of 2012 there was talk of justwhat Big Data is, how it would aect talentacquisition and talent management, and howto work with the constant and much larger owof data that will soon have an impact on thisindustry. Big Data, according to most majoranalysts, may change everything about whatwe do and why we do it.

Juxtapose these attempts to make sense ofBig Data with the actions of more and morecompanies, who today are looking to replacelegacy systems, often a rst step in capturingthe insights of Big Data in their talentacquisition processes. As Josh Bersin noted

in a recent report, every evolution leading tothis point started with reporting and a coreunderstanding, then moved on to predictiveanalysis. Thats how it happened in consumermarketings now prolic use of Big Data,and that is very likely how it will happen in HR.

Simultaneously, the ongoing discussionabout Candidate Relationship Managementand Applicant Tracking Systems began tomerge with a concurrent conversation aroundsocial recruiting. And against this backdrop,many talent acquisition professionals havequestioned the value of adding extra socialdata to the disorganized and often redundant

data already in our cluttered databases;

the eect could be overwhelming, after all.Rarely, however, do companies refuse totap into the deep well of candidate data(or consumer data, for that matter).The benets of having all this candidatedata are abundantly clear, yet the data itselfhas little value unless something can beachieved with it. The question is whetheror not talent acquisition professionals canglean insight from their data in a way thatturns the recruiting function around fortheir organizations.

As things stand, most companies are only clearabout how to accumulate data, not how to keep

it, use it and interpret it. Despite increasingfunctionality within CRM suites and pluginswithin ATSs, the talent acquisition functionstill struggles to keep candidate data dynamicand current in a constantly changing work-scape, even with the promise of social to dojust that. Talent acquisition has certainlymade recent strides in the reporting part ofthe data equation, but there is not yet a realunderstanding of how to prepare for Big Data particularly the protocols that shouldsurround the accumulation of data andthe storage and use of data, as well asthe relational nature of social data and

the interpretation and predictive analysisof you guessed it, data.


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Futurecasting 8

The good news is that CRM suites are primedto manage the onslaught of data and makesense of it with enhancements andmodications, of course. An eective CRMcan aggregate and sort through data to tell anorganization where its talent audience spendstime and in what ways and not just the hiresthat lasted and became internal stars, but theones who resigned after three months as well.Done correctly, there is the potential for:

Consider the alternative. If a companys talentmanagement team isnt keeping track of wherethe organizations employees and applicantscome from, and if it isnt keeping that recordalive with information about how they fared,its doing the organization a disservice and

at some point, catching up will become nearlyimpossible because the hurdles are too greatto surmount practically.

With todays social records, the data isthere to keep track of the next job in the line.That kind of information, along with company-specic job titles, can assist workforceplanning in a big way. Big Data analyseshold great potential to answer criticalquestions whose answers have practicalapplications for talent acquisition specialists:

What universities and trade schoolsdo competitors invest resources in?

What are the most common,identiable patterns that reect

sources of hire among key competitors? Who do they hire from, and are there

commonalities in job title descriptions? What product verticals align most

appropriately to corporate oerings,and are the skillsets involved consistent?

How do competitors establish quotasto measure performance?

What are key indicators of recognitionand awards among key businessfunctions such as R&D and sales?

What is the average length of timeidentied to progress from a graduateintern to a software architect or

management role? How do all the above questions factorinto internal organizational bestpractices, and has the organizationcreated a platform as a depository toarchive these critical data inputs?Is the Talent Knowledge Libraryavailable at an enterprise level,and is the data accessible in real-time?

How do all the above compare to theorganizations own, internal talentacquisition functions in determiningsource of hire, and how can thatknowledge translate into actionable

improvements in time-to-ll andcost-per-hire?

forecasting to become Futurecasting reporting to become auto-analysis

useless information to becomeessential information

time-consuming activity to becomeecient

jumbled data to become decision-supporting analysis


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Futurecasting 9

The strengths and weaknesses of CRM today

How people use CRM in their sourcing andrecruiting is a crucial part of the process.In fact, many of the potential cons can beeliminated or exacerbated based on the waya person interacts with the software itself.

Big Data is often misunderstood, especially bythose within talent acquisition. While graduallyinuencing discussions within the talentacquisition industry, the common agreement isthat it will aect us, but many are not sure how.Used to wrangling large and unwieldyspreadsheets and juggling SQL databasesthat would make other departments cringe,talent acquisition professionals think they

can handle Big Data when and as it comes.But there is a reason that there has been amassive uptick in calls for data scientistsand a spike in requisitions for psychologiststo interpret this data. With Big Data, the inuxof data is erce and only will become more so.Organizations need and many currently lack an adequately evolved system, comprisingtechnology and human skillsets and processes,to make sense of all the data and developwisdom from the interpretation of it.

BIG DATA, BY DEFINITION

Big Data is a collection of data setsso large and complex that it becomesdicult to process using on-handdatabase management tools. Big Dataallows correlations to be found to makeall sorts of reliable, important, actionablejudgments about dierent things.If Big Data can be used to do all that,then workforce planning, recruitingand sourcing should be a cinch. In fact,Big Data is already being touted as a realweapon in the war for talent, ostensibly

able to:

identify business trends determine quality of research

(or sourcing) develop competitive intelligence discover or determine real-time

career progression illuminate hiring trends target geographic shifts of a

talent audience (local, regional,national, global)

But the denition remains and haunts us:

a collection of data sets so largeand complex that it becomesdicult to process using on-handdatabase management tools.


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Futurecasting 10

Database tools such as the beloved CRMsystem are eective in elds identifying whatexists, but fail miserably in reverse-engineeringthe process by incorporating elds that searchfor what does not exist within records.For instance records that do nothave:

The limitations of todaysout-of-the-box CRMTherein resides the inability to deal with theBig Data wave using existing, o-the-shelfCRM systems. If only elds that have text entryare searchable, then that renders incompleterecords unsearchable. For each of the lines

listed above, data that is not there will limit thesearchable capability inherent within records.And what about the revolution that is currentlyunderway within talent acquisition? As hasbeen noted for the last ve years by socialrecruiting vendor Jobvite, more companies arejumping onto the social recruiting bandwagon,with as many as 92% of companies usingsocial recruiting as part of their talentacquisition process. So how do CRMs(both process and software) deal with thisadvent? Not well many company recordshave lagged in the default inclusion of criticalcompetitive intelligence elds. Source of Hire,

for example, is a category of form elds,not simply a single transaction as generallyconsidered.

Key variables are signicant and worthaddressing in the talent mapping processcoinciding with key business intelligencebeing factored into a robust CRM:

While the list may seem long, consider this.If 92% of companies are using social to recruit,many of them already have access to thatinformation, and instead of being able to createa rich and dynamic database within their CRM(one that would be eminently searchable),in many cases, these companies are shovingthose URLs wherever they can nd them,in a neglected notes section or using tagsas a way to search for records. Often, thisprocess results in duplicates, multiplespellings and acronyms and general search

confusion; a muddying of the data waters.Again, this shows that in our most-usedsystems (CRM is arguably second only to theATS in the talent acquisition function), talentacquisition professionals have yet to adapt tothe inux of social data, much less preparefor the Big Data that is coming.

Top schools: are there specicuniversities generating certain typesof candidates?

Prior employers: are thereattributable patterns of both immediateand former competitor companiesfeeding your talent pipelines and hires?

Post employers: which competitors,

within an industry niche or skill setcategory, do employees likely migrateto and why?

Online social real estate of acompetitors ecosystem: is it variedand are there established bestpractices inherently observable withinany given competitors onlinepresence (corporate blogs, onlinedeveloper communities, careers page,LinkedIn corporate careers page,Facebook careers, career-orientedTwitter accounts, webinars/podcasts,newsletter email updates?)

mobile or work or home phone numbers a social media specic URL (linkedinID,

Linkedin Recruiter, Facebook, Twitter, etc.) an attachment pdf or Word doc resume an employer listing a job title

a city or state or country a linked job/pipeline ID notations a source ID


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Futurecasting 12

Futurecasting what might it look like in practice?

Building a CRM as a solution for talentacquisition is about having access to key talentdata that can transform the record into a prolethat has an extended period of shelf life andcan be measured. Companies adept at datamining will use a knowledge-discoveryframework to predict whats next and increasethe viability of their competitive intelligenceand talent acquisition functions. Across theenterprise, organizations that recognize andcapitalize on the opportunity Futurecasting

oers experience several benets: moredetailed demographic models, product alignedto new hires skillsets, shorter time-to-ll ata lower cost. The resulting, greater in-housereliability of new hires to carry out the needsof the organization inevitably speeds theproduct development and sales cycles,which then enjoy greater prot margins.

The old waysLets look at the old way of doing things.This would get in the way of building anagile CRM to get at and make sense of thereal-time data that would enable organizations

themselves to become equally agile in theiracquisition of talent. Imagine, for instance,a report consisting of over 250 companies todemonstrate a clients competitive landscapefor talent. Ten dierent sources are reviewed tocalibrate for accuracy. All the aforementionedis conducted manually in a spreadsheet.Given factors of time, mergers andacquisitions, and the business cycle itself,the business intelligence report becomesdated material upon submission. Access tothe document limits the ability to distributeits data to provoke discussion and unearthbest practices. Above all other considerations,

the product is static. Any revisions to updatecritical information are based on initiativeand conducted manually, by hand.

The future is now: o-the-shelftechnologies can create a newparadigm todayThe future will not be like this. Aided byFuturecasting, the next generation oftalent acquisition solutions will give socialaggregators center stage. Developers APIswill make manual row-by-column edits athing of the past and transform data intoa dynamic, evolving stream of information always in real-time and providing the basis

upon which to make sensible, objectivedecisions drawing on data immediately atthe disposal of recruiters and sourcers.

SaaS and mixed-and-matchedreal-time data making it possibleSome readers might recognize that this isa description of the practical progressionof Software as a Service (SaaS) to achieveits promise on behalf of talent acquisition.Consensus is now building behind cloud-based, distributable platforms that areaccessible across multiple corporate functions,to meet the demands of a globally oriented

talent acquisition organization. What ismissing among todays vendors oeringsof SaaS platforms is the convergence ofo-the-shelf technology to include an allof the above capability within one platform.

Emancipating data-sharingwith open sourceIn keeping with an open-source philosophy,if the talent acquisition industry communicatesa demand for all its vendors to establishrelations to collaborate on the notion ofdata-as-a-service, the potential is limitlesswhere data warehousing across industries

develops proprietary relationships with socialplatforms. Automated convergence is theprinciple outcome of harvesting once disparateand multiple developer APIs form a commonplatform from which to exchange andcommunicate information.


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Futurecasting 13

The net result is compelling. Talent acquisitionprofessionals will nd themselves able to nelytune and refresh data to more eciently targetcandidates and build high-functioning talentpipelines. In this scenario, the only limitation

is imagination, really. Above all the talentacquisition industry should demand easeof use, free from premium costs, in the abilityto customize data elds to congure key data.Smart vendors will embrace these demands.Their obligation is to oer their clientele inHR and talent acquisition tools that are easilycongured and customized to specic needs;these tools must be usable and searchable.Talent leaders should feel free to suggestany data categories that would enhancea platforms capabilities, because too often afew simple tweaks are all that is necessaryto nd the right talent.

To illustrate, a next-generation SaaSbased, open-source platform could easilybe congured to key data outlets:

Dow Jones & NASDAQ: real-time marketdata triggering RSS feeds to alertcompetitors to likely layos

Hoovers: contact information,competitive reports, and the abilityto develop targeted executive listings

LinkedIn: identifying competitorsproducts and services to add relevanceto search keywords, to the more criticalbusiness intelligence aspects (whereemployees came from, as well as topskills and expertise by function)

Why is all this important? Automationand convergence of data oer thefollowing capabilities

accurately forecast which candidatewill stay and for how long

determine real-time career progression create talent pipelines that assess

cultural t long before the applicationprocess

nurture candidates and studentsyears before they apply

identify business market trends,mergers and acquisitions and alignproduct with them

bolster the candidate experience byautomating relationship-buildingcommunications and establishingalerts to ensure prospects are notiedof developments regularly, in a timelyfashion


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Futurecasting 14

First things rst: building a t-for-purpose CRM

CRMs have a pivotal role in makingFuturecasting a reality for organizations.Yet any CRM system is only as good as thedata it includes. The most common problemswith the data are caused by human factors.While these are certainly frustrating toencounter, they are usually the easiest to x.Human factors as dened here are usuallyworkow-related, process-related oradministrative in nature.

Workow issues generally stem from alack of specic plans for what each user ofthe CRM creates, when they create it and how

it gets stored in the system. Protocol issuescan often be xed by creating a standardplan and procedure that each member of theglobal talent acquisition team must follow.For example, forward-thinking clients areproactively preparing for an API that makesit simple to integrate social data into theirCRM systems. Because those elds are alreadylled with data from Twitter, LinkedIn andFacebook, they can be hooked up when thetechnology is available. This is a much betterprotocol than wasting hours going backthrough every record to nd potential socialdata for that prole.

Process issues are often caused by a lack oftraining or a disorganized approach to usingthe CRM. Best practice involves rst settingthe protocols and then providing educationto ensure everyone is following the correctprocess. An example of this is segmentinglists when the prole is initially placed sothat the system doesnt become cluttered andfrustrating to navigate. Building an audiencelter at the source is much simpler than tryingto segment later. A CRM implementationmust be operated from a talent perspective.Its crucial to have criteria to determinewhether a source of information is CRM-eligible and aligned to a particular pipeline.

In any inventory system, you have to prioritizeand establish the source channel to fully useeach source to its true potential. In the buildingof a CRM, to ensure a fail-safe process, youmust cross-reference various data sourcesas inventories for reference. Then, to expandthe CRMs capabilities and navigation,you identify additional channels you wishlater to integrate.

Administrative issuesfeed into both ofthese. When you lack a dedicated qualityassurance process or administrative function(even on a consultative or contract basis),

you lose quality and freshness of data.You should also establish a universal templatesystem as part of the administrative function;this must be suitable across geographicregions and business organizations. As wellas standardizing the nomenclature, this alsoprescribes a minimum viable data format foreach record. Lack of customizable data eldsand, worse still, the existence of empty ones they all obstruct the capabilities of lters andsearch results; they limit the modern CRMspotential to produce actionable information.Common missing elds include those formobile phone numbers, social media-specicURLs and job titles. Limiting the parametersfor how both to lter and segment datainevitably leads to false exclusions orinclusions in a CRMs search results.


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Futurecasting 15

Data is at the heart of so many conversationstoday, but its not the data: Its the access to theright data at the right time by the right person.Its about being able to put your nger on apiece of data that helps make a businessdecision or to nd that pink squirrel withpurple polka dots in our world. The work Davehas done to embed the key nuggets of datainto our CRM is the game changer for us.Previously, we had no repository that wouldallow for unstructured data to be housed andretrieved. With Daves practical approach todata capture and retrieval, we now have acentral databank of very specic competitiveintelligence that has the ability to withstand

time with its social and mobile aspects builtin for future proong. Brad Cook, Global VicePresident Talent Acquisition Informatica

Futurecasting is not about where candidates(recruiters leads) are now; it concerns asystem-wide, strategic eort to harvest andcombine dynamic and static data regardingprospects, to enable a talent pool to besearchable for years as it feeds o multipledata points, ensuring its own relevance.Illustrating this is my work with Informatica,drawing on the concept of passive pipelining which is to say, creating a pipeline that a talentacquisition team can source from, at any time,to identify source-of-hire information amongimmediate and prior employees.

OverviewInformatica reviewed its database anddetermined that Jobs2Web, the companysSEO product, would benefit from thedynamic environment of my CRM platform.The rst step in data migration was a directimport of the corporate talent organizationsentire database originating from the talentcommunity population. In addition, a live-feed

was created to integrate the ow of new talentcommunity registrants in real-time, within theCRM platform.

Through this implementation, Informaticawas able not only to review source-of-talentchannels within one platform, but alsomerge talent community members withexisting lead generation for a more completeprole record, and all in real-time. As a result,Informatica transcended out-of-the-box CRMto congure form elds and other CRMfunctionalities that enhanced the recruitersexperience and capabilities. In the creationof this approach, the standard for passivepipeline to yield data deliverables had tomeet the following criteria:

1) Data must be usable and searchable.

The data should be easy to lter by dataequal to, containing, or not equal to keycriteria, and custom elds specic tosocial platform hyperlinks to accuratelyidentify missing data, as well as datamissing as a subcomponent.

2) Extraction and leveraging of data mustbe easy to ensure a tool that is at oncepowerful, intuitive and requires minimaltraining. The solution would be used bya diverse community of recruiters, only ahandful of whom had an appreciation ofdata science.

3) Data must be capable of being migrated

from multiple lead-generation channels spreadsheets, job boards, online resumes,talent communities, social proles, etc. in order to optimize removal of duplicatesand track metrics of source-of-hire moreaccurately and consistently.

4) Data must be categorized, tagged andmapped to talent for ease of segmentation.A successful conguration can allow forsegment creations in a matter of seconds,and these can be complex such as theability to splice a talent pool by proleswith a LinkedIn URL.

Toward Futurecasting at Informatica


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Futurecasting 16

The Talent Knowledge Library (TKL) isa simple proposition: providing a secure,cloud-based depository for businessintelligence that is actionable for recruitmentneeds, where data is fed by various onlineAPIs to ensure real-time relevance. A TKL isaccessible throughout the talent acquisitionenterprise and standardized for promptplug-and-play in order to produce automatedsearch queries. In practice, this is afunctionality that makes Futurecastingpossible. Aligning social data and businessintelligence provides greater context to howcompetitors skills, job titles, and productscompare to those of your own organization.

Migrating data from various databases withinone platform, strengthened by a multitudeof developer APIs:

documents an organizational processescreates a depository of data inputs

comprising the organizations competitivetalent landscape, allowing for greatercomparative analysis

identies critical source-of-hire informationto benchmark patterns among prioremployers of interviewees, oers made,and hires

develops nomenclature be it key skillsets,

industry terms of art, or product relevance

In todays CRM, too often search stringsare accessed and utilized by precisely oneperson, the sourcer. The sourcing stringswithin current platforms are often uniqueto the user, which makes standard protocoldicult to adopt. A TKL would dramaticallyenhance the ability to provide missing context.It would promote recruitment eciency indistinguishing among applicants, and oereective standardization to sourcing teamsaspiring to develop more accurate leads with automated and standardized macros

of search string, plugged and played,to be equivalent in accuracy to those createdby their most advanced researchers withinthe organization.

Via a TKL, the talent organization has a meansto archive the successes of its best recruiters,at a tactical level, and the means to distributethe learning as data that can be distributedthroughout its global operations, to the benetof critical hiring verticals. A TKL would recordteam member usage of all vendor-suppliedtools within one instance, creating real-timereports to gauge relevance and eectiveness asan investment within the hiring cycle. It wouldallow for successful behaviors and methodsto be tracked within a source-of-hire report,and provide the means to be reproduced foreach business organizations hiring vertical.

A TKL is an extension of the Futurecastingmethodology: it fosters the use of severaldata points to help talent acquisitionprofessionals establish patterns and makeobjective decisions. Data becomes relevantfor both immediate and long-term decision-making processes. The data a TKL utilizeswould have longevity beyond the combinedintellectual contributions of any one teammember in one day, but for that day andall days thereafter. The TKL would createa searchable and usable library of talentknowledge that is virtually immuneto intellectual property loss, turnover

or transition slowdowns and processbreakdowns, all because the data livesin the cloud and is constantly current.Accessible to all in the talent acquisitionorganization, the TKL must be, by denition,both distributable and searchable bystandard keywords, job titles and more.A proper TKL would have a system thatallows anyone to pull up folders of searchstrings based on common search terms.

Creating the Talent Knowledge Library


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Futurecasting 17

At Informatica, I established CRM templateforms outlining competitor nomenclature;top producers awards and recognitions, naturallanguage terminologies, alignment by product,and pre-set sourcing strings. By developinga process that resulted in archiving the historyof Informaticas talent organizationsknowledge base, team members elevatedtheir understanding of nuances between terms.By inputting product relevance, matchingcompetitive titles, skill keywords and identiedcompetitors, Informaticas talent acquisition

specialists increased the data relevance ofsearch results to import into the CRM in therst place. Exemplifying the by-product of aTKL in practice, Informaticas team addressednatural language as an indicator of performanceand reviewed data patterns in both curriculavitae and social proles that would correctlyidentify a talent prospect being recognizedfor one or more of the several awards andrecognitions provided by their employers.For example:

(Competitor X OR Competitor XY)Product + Performance Indicator +

Skill/Expertise = Hire

Over *% of quota in * Achieved *% of FY* plan *+ Quota of $.*.million (percent | %) exceed Quota FY Achieved *% of Annual Quota (Top 10% | Top ten percent |

top 10 percent) year over year sales quota attainment

By elevating their level of uency interminologies relevant to targeted leads

among the competitor pool, Informaticasrecruiters and sourcers were able to equipthemselves with a formula-driven aptitudefor more precise hires. The impact of thiswas immediately seen in standard successbenchmarks within talent acquisition suchas time-to-ll and cost-per-hire, becauserecruiting was just plain easier. By havingclear and standardized data elds, the newapproach made recruiters work quickerand less prone to error.

During the course of the implementation,specically in conguring customized eldsto cleanly inputted data and emphasizingsocial data as a module for each work record,we came to a critical realization: conventional,traditional work contact information,previously the holy grail of a CRM record,is no longer a sucient or viable option toensure longitudinal history for a candidate.Instead, by ensuring that each record has acomplete record of hyperlinked LinkedIn ID,Twitter URL and other social links

all updated in near real-time Informaticanow creates dynamic proles out ofstagnant proles to ensure that relevant,accurate contact data is available and recordmaintenance performed at each phaseof sourcing, through recruitment.

In other words, the CRM has a new lifespanthat underscores the concept of Futurecasting,an industry game-changer. Record maintenance,or data quality process, is one of themost important parts of the Futurecastingmethodology. The maintenance of records,alongside the customization of a CRM, is

the cornerstone of new projects Im workingon. Viable data with a dramatically extendedshelf life is no longer as easily susceptibleto drastic market shifts and attrition thatcould negatively impact the searchabilityof passive candidates.

Drilling down at Informatica and DemocratizingTalent Acquisition


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Futurecasting 18

Simply stated, Futurecasting is aboutmanaging the life span of your talentaudience as a proactive pipeline tomorrowand thereafter. Building CRM as a solutionis about gaining access to key talent datathat transforms the record into a prole andensures relevance over an extended periodof shelf life, something that can be measured.In developing its methodology and fulllifecycle of implementation, one can clearlysee that it provides incredible value.

Companies end up investing in data thatis strategic and durable. Corporate talentorganizations prosper not simply by comparingthe quantity of data records, but by nurturingdata to become composite proles and bycreating access to data across social platformsthrough a detailed methodology, whichunderpins relevance. Today the technologiesfor all of this are readily available, if not yetfully converged, and companies who haveaccess to their data and identify practicesand learn from it are investing in their ownenduring intellectual property to hire the bestin a more proactive manner than ever deemedpossible. Big Social Data is the fuel. With it,a Futurecasting methodology has:

Big Social Data: the engine of Futurecasting methodology

One lead and one record withinone place and linked to all pipelineand job ID reqs, resulting in massivecost savings by ending sourcing-related multi-billing for duplicatelead records.

All leads vetted already by therecruiters and sourcers who generatedthe data over several years allrecords merged and updated forshelf-life extension through now-perfunctory social media elds.

Recruiters and sourcers can come

and go, because offorever data.This essentially secures theintellectual property of the datawithout the need to rely on individualsand their consistency to track it.

Whenever feasible, automation asthe common denominator.Organizations can now see to itthat candidates are re-engaged atappropriate time periods. RSS feedsnow alert team members globally ofsudden market developmentsadversely aecting key competitors.Macro functionality standardizes

the expertise level of search stringsapplied in identifying and creatingpipelines.


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Trust in Registry:the implications of Futurecasting for the employer brand

Notably and naturally, Futurecastinghas implications for the talent acquisitionprofessionals relationship with the targetedtalent. Organizations that establish a Trustin Registry help themselves in navigatingthrough the coming changes.

A term coined by Gerry Crispin, author of thiswhitepapers foreword, a Trust in Registrypresents a mutual advantage for talentacquisition specialists and candidates.Candidates today are records, but with the

philosophy of Futurecasting and progressionof technology, records are becoming proles:the sum of many records, all consolidated.We are moving to a stage when anyone activein social networks will have what amountsto a digital wallet comprising their social datalinks, etc. Knowing that companies store thisdata, candidates can gain access to it for easeof mobility. As we approach ubiquity in theavailability of Big Social Data, a Trust inRegistry will equal the sum of social dataand the mutual trust in the transactionsbetween job seekers and career providersor potential employers. Cloud-based, it will

be a service utility.

By designing and sharing a disclosure withtheir targeted talent, organizations assure thesepopulations that theyre not building merelya database (a sterile, faceless talent pool),but instead trust management relationships.These trust management relationships speedcommunication and enable talent acquisitionorganizations to track longitudinal datasuccessfully. At its core, this is a transformationof dynamics surrounding the employer brand.

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Without a blueprint or initial guidance,the organization that would otherwiseembark on a plan to implement Futurecasting a methodology possible to employ right now might give up altogether for want of simplerst steps. This whitepaper aims to helpsuch organizations jump-start the process.What follows, therefore, are seven stepsthat are recommended for any organizationlooking to take advantage of theFuturecasting methodology.

1) Map the organizations process

Creating a fully functional CRM begins withmapping out your talent acquisition process,from rst contact with a prospective candidateto when they come aboard. If this is notsomething that youve previously worked onwithin your company, now is the time to makeit a priority. How can you know what you needfrom your system if you havent identied itwithin your process?

2) Standardize the organizations protocolThe very rst step that any organization shouldundertake toward a realizing more ecientCRM is to create a standard protocol. Initiate

a stakeholder-driven eort to establish aworkow process that applies to the entireCRM lifecycle, with each stakeholders roleclearly established and documented.For instance:

Seven things organizations should do right nowto implement a Futurecasting methodology

3) Add social dataYou might claim to be operating withinsocial recruiting. But if youre not alreadyincorporating social data into the tools you use,youre missing half the equation. While manysystems do not yet have clickable URL eldsavailable by default (such as a link to someonesLinkedIn prole), you can certainly setthem up as customized portions of yourcandidate proles.

4) Segment the organizations dataBecause its such an important part of CRM,segmenting audiences should be an ingrainedprocess for every sourcer and recruiter. A basicuser can easily create simple segmentation,and advanced users can build rules and ltersrobust enough to allow the CRM to recognizea Twitter URL vs. a LinkedIn URL, if these arecapable of being segmented. For instance, anorganization might want to, and would be ableto, split lists by those with Twitter URLs andthose with only LinkedIn URLs to then pushthese leads into groups or as followers to acorporate career site or user name. Once thedata is segmented, an API facilitates theuploading. Though not all CRMs currently

oer this feature as an o-the-shelf option,it soon will be standard. So start proactivelyadding URLs: when the CRM has thatcapability, the organization can besourcing immediately.

5) Reinforce competitive intelligenceas a workow processAdding an organizations own job titles tosearch for people within the system doesntalways make sense. In fact, unless theorganization is one of the worlds largestcompanies or a governmental entity, it makesno sense at all. Ideally, most of the proles in

the system are of passive candidates. Their jobtitles will likely look very dierent from thoseused within the company. So make sure tobuild in titles for competitor organizationsand create a more robust search string for example, x is far more useful than y to account for these discrepancies. In thesame vein, consider using notes and tags todiscover marks of distinction that competitorsroutinely give out (e.g. Presidents Circle,Chairmans Club, Catalyst Award).

What default elds do you retain vs.which customized elds need to becreated to meet your organizationalneeds?

What determines a complete recordprole vs. a record that requiresadditional revision?

What is the data quality review processby which incomplete records arereconciled?

What is the standardized model forgeo-locational, industry-specic,or in-house organizational data?What is the standardizedmodel for number-based entries suchas postal codes and telephone numbers(no dashes or numbers only)?

What is the agreed-upon terminologyfor a tagging system, list titles, and jobID vs. pipeline requisitions?

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6) De-duplicate and enforce data quality

standards to your organizations databaseThough not a short or easy process, it is onethat every company under the age of ve yearsshould do on a regular basis, at least until thetechnology does it for us.

7) Recognize the value ofintellectual propertyWith recruiting turnover and contractrecruiting a fact of life for many local andglobal organizations, companies need torealize the value of their data. Simply put,if an organization pays someone to sourcedata on a daily basis, it must make sure thatit keeps that data safe and validated byfollowing the steps listed above.

By ridding the database of duplicaterecords, the organization accomplishestwo things:

It determines where its data needs tobe standardized (see step 1).

It saves time when looking for records.

By cleaning up the database ridding itof incorrect, incomplete or old informationand replacing all that with correct, complete,new information the organizationaccomplishes another two things:

It creates URLs for proles that didnthave them before.

It lls in elds that are empty, makingthat prole fully searchable.


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Futurecasting 22

Dave Mendoza provides global talentstrategies at the executive level of Fortune500 companies and start-ups, in additionto product development and innovationconsultations to vendors in the HR andtalent space. Dave introduced the conceptof talent mapping using business intelligencemethodologies and was an early evangelistfor social recruitment. His research utilizingBig Data principles has explored the broadimplications of social data convergence,business intelligence as a service,and retaining organizational intellectual

property through the application ofa talent knowledge library.

Recognized for Strategic TA Roadmapon behalf of Informatica:

* Winner 2011 ONRECRecruiting Innovation Award

* Winner 2011 ERE RecruitingExcellence Award Best StrategicUse of Technology

* One of the rst to oversee Jobs2WebTalent Community feed & ATS integrationwith CRM launch in collaboration withclients sourcing management

* A global speaker, he has evangelizedtalent mapping in 10 countries withinthe past 12 months

[email protected]/in/ldavemendoza/

About the author


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References

Good Data Wont Guarantee Good Decisions. Harvard Business Review.Shah, Shvetank; Horne, Andrew; Capell, Jaime;. HBR.org. Retrieved 8 September 2012.

Big Data in HR: Why its here and what it means. Bersin, Josh:http://www.bersin.com/blog/post/BigData-in-HR--Why-its-here-and-what-it-means.aspx November 17, 2012.

Does Big Data Live Up To Its Hype? Lorenz, Mary.http://thehiringsite.careerbuilder.com/2012/11/15/does-big-data-live-up-to-its-hype/ November 15, 2012.

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