hiring an innovative workforce: a necessary yet uniquely challenging endeavor

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Hiring an innovative workforce: A necessary yet uniquely challenging endeavor Samuel T. Hunter a, , Liliya Cushenbery a , Tamara Friedrich b a Pennsylvania State University, United States b Savannah State University, United States article info abstract To increase innovative performance in work settings, most scholars agree that organizations need both an environment that is supportive of creativity as well as employees with high levels of creative potential. Substantial research effort has been aimed at understanding work contexts that facilitate creative thinking, yet less is known regarding how to most effectively recruit and hire creative talent. To fill this knowledge gap and guide future research efforts, we discuss the KSAOs most predictive of creative potential as well as the means and methods for assessing this potential. In addition, we explore the challenges to quantifying successful innovation, proposing that creative achievement represents a unique and specialized form of organizational perfor- mance. Supplementing this discussion we provide recommendations for obtaining high-quality, substantive criterion data. We conclude with a brief discussion on recruitment and long- term selection strategies for innovation. © 2012 Elsevier Inc. All rights reserved. Keywords: Innovation Selection Creativity Hiring Interactionist perspective 1. Introduction The first step in winning the future is encouraging American innovation. None of us can predict with certainty what the next big industry will be or where the new jobs will come from. Thirty years ago, we couldn't know that something called the Internet would lead to an economic revolution. What we can do what America does better than anyone else is spark the creativity and imagination of our people. We're the nation that put cars in driveways and computers in offices; the na- tion of Edison and the Wright brothers; of Google and Facebook. In America, innovation doesn't just change our lives. It is how we make our living.President Barack Obama The quote above, delivered by President Obama in his 2011 State of the Union address is just one of many recent calls to arms by politicians and business leaders alike for innovation to be placed at the top of our collective to-do list. Despite the recent in- crease in the pace of the need for innovationdrum beat in public discourse, organizations have been placing an increased pre- mium on innovation for many years. This trend is not surprising given that innovation, defined by most creativity scholars as the successful implementation of ideas that are both novel and useful (Amabile, 1983; Mumford & Gustafson, 1988), provides a com- petitive advantage to those businesses that are able to consistently generate and implement new products and processes (Dess & Pickens, 2000; Janssen, van de Vliert, & West, 2004; Kao, 2007). In fact, a 2011 survey of 1000 business executives from 12 coun- tries commissioned by General Electric and conducted independently by StrategyOne underscores the pressing need for organi- zations to invest in innovation. A remarkable majority of the senior executives surveyed (over 88% in each instance) believed that Human Resource Management Review 22 (2012) 303322 Corresponding author at: Pennsylvania State University, 111 Moore Building, State College, PA 16802, United States. Tel.: +1 814 865 0107. E-mail address: [email protected] (S.T. Hunter). 1053-4822/$ see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.hrmr.2012.01.001 Contents lists available at SciVerse ScienceDirect Human Resource Management Review journal homepage: www.elsevier.com/locate/humres

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Hiring an innovative workforce: A necessary yet uniquelychallenging endeavor

Samuel T. Hunter a,⁎, Liliya Cushenbery a, Tamara Friedrich b

a Pennsylvania State University, United Statesb Savannah State University, United States

a r t i c l e i n f o a b s t r a c t

To increase innovative performance in work settings, most scholars agree that organizationsneed both an environment that is supportive of creativity as well as employees with high levelsof creative potential. Substantial research effort has been aimed at understanding work contextsthat facilitate creative thinking, yet less is known regarding how to most effectively recruit andhire creative talent. To fill this knowledge gap and guide future research efforts, we discuss theKSAOs most predictive of creative potential as well as the means and methods for assessing thispotential. In addition, we explore the challenges to quantifying successful innovation, proposingthat creative achievement represents a unique and specialized form of organizational perfor-mance. Supplementing this discussion we provide recommendations for obtaining high-quality,substantive criterion data. We conclude with a brief discussion on recruitment and long-term selection strategies for innovation.

© 2012 Elsevier Inc. All rights reserved.

Keywords:InnovationSelectionCreativityHiringInteractionist perspective

1. Introduction

“The first step in winning the future is encouraging American innovation. None of us can predict with certainty what thenext big industry will be or where the new jobs will come from. Thirty years ago, we couldn't know that something calledthe Internet would lead to an economic revolution. What we can do –what America does better than anyone else – is sparkthe creativity and imagination of our people. We're the nation that put cars in driveways and computers in offices; the na-tion of Edison and the Wright brothers; of Google and Facebook. In America, innovation doesn't just change our lives. It ishow we make our living.” President Barack Obama

The quote above, delivered by President Obama in his 2011 State of the Union address is just one of many recent calls to armsby politicians and business leaders alike for innovation to be placed at the top of our collective to-do list. Despite the recent in-crease in the pace of the “need for innovation” drum beat in public discourse, organizations have been placing an increased pre-mium on innovation for many years. This trend is not surprising given that innovation, defined by most creativity scholars as thesuccessful implementation of ideas that are both novel and useful (Amabile, 1983; Mumford & Gustafson, 1988), provides a com-petitive advantage to those businesses that are able to consistently generate and implement new products and processes (Dess &Pickens, 2000; Janssen, van de Vliert, & West, 2004; Kao, 2007). In fact, a 2011 survey of 1000 business executives from 12 coun-tries commissioned by General Electric and conducted independently by StrategyOne underscores the pressing need for organi-zations to invest in innovation. A remarkable majority of the senior executives surveyed (over 88% in each instance) believed that

Human Resource Management Review 22 (2012) 303–322

⁎ Corresponding author at: Pennsylvania State University, 111 Moore Building, State College, PA 16802, United States. Tel.: +1 814 865 0107.E-mail address: [email protected] (S.T. Hunter).

1053-4822/$ – see front matter © 2012 Elsevier Inc. All rights reserved.doi:10.1016/j.hrmr.2012.01.001

Contents lists available at SciVerse ScienceDirect

Human Resource Management Review

j ourna l homepage: www.e lsev ie r .com/ locate /humres

innovation was critical to creating a more competitive economy, developing green initiatives, and, most important in the presenteconomy, creating new jobs (GE Global Innovation Barometer, 2011). Additionally, a recent employment survey conducted by theNational Science Foundation found that companies that conducted or provided funding for research and development relatedwork had over 7% of their workforce devoted specifically to R&D activities (Moris & Kannankutty, 2010).

With innovation emerging as a key priority for a significant portion of the workforce, it becomes imperative that organizationsbe adequately prepared to recruit, select, and retain individuals capable of undertaking the difficult work of innovation. More gen-erally, the growing emphasis on enhancing innovation has led to the emergence of a fundamental and persistent question: Howdo organizations most effectively develop and pursue a strategy for creative performance? The bulk of the research on creativethinking and innovation suggests that the answer will be found via the interactionist model of innovation, where creative perfor-mance is theorized to emerge from the interplay between the context and the individual (Amabile, 1996; Mumford & Gustafson,1988; Oldham & Cummings, 1996; Woodman, Sawyer, & Griffin, 1993; Woodman, Schoenfeldt & Reynolds, 1989). While organi-zations continue to make strides in demonstrating their prioritization of innovation and in promoting environments that supportit, the other component of the interactionist perspective is often more difficult to implement — the human resources practicesthat aim to build a creative workforce.

The research on innovation follows a similar pattern as the applied discussion above. For instance, a rich body of research hasemerged about work environments that support and enhance innovation (e.g., Amabile, 1983, 1988, 1996; Andrews & Farris,1972; Ekvall, 1996; Knapp, 1963; Woodman et al., 1993). In fact, a recent meta-analysis on creative climate revealed that therewere over 45 differing taxonomies used to classify creative context (Hunter et al., 2007). However, less research effort hasbeen aimed at understanding how to best supply the talent for innovative endeavors. Given that employee creative potentialstands as a necessary pre-condition for innovation in organizations (Mumford, 2000), there appears to be a sizable knowledgegap in how to most effectively pursue and execute a strategy for innovation. In an effort to fill this gap, three primary issuesare addressed in the present effort. First, we outline the building blocks of any successful HR practice — the key knowledge, skills,abilities, and “other” (KSAO) attributes most predictive of creativity and innovation. In this discussion, we offer some guidance asto which KSAOs may be most useful for predicting innovative outcomes. Supplementing this discussion we consider other criticalelements of the Human Resources process, including differing selection and assessment approaches that may be used in capturingcreative and innovative potential, means for acquiring criterion data necessary for performance appraisals and associated chal-lenges in assessing creative performance, recommendations on effective recruitment of creative talent, and long-term selectionstrategies for building and sustaining an innovative workforce.

2. Selecting for innovation: identifying a predictor set

Creative performance is a complex, dynamic, multi-faceted phenomenon (Barron & Harrington, 1981; Mumford & Gustafson,1988). Not surprisingly, then, the qualities necessary for generating and implementing novel ideas are equally complex, dynamic,and multi-faceted. Although much remains to be learned about individual characteristics necessary for innovation, research fromorganizational, cognitive, social, and developmental psychology has provided us with a reasonable jumping off point to thinkabout the qualities most likely to be useful in a selection context. Consistent with most approaches to hiring, we present theknowledge, skills, abilities, and “other” (KSAO) characteristics predictive of creative performance.

Before turning to a discussion of the specific KSAOs theorized to predict innovation, it would appear useful to briefly discusswhat roles, from a conceptual standpoint, KSAOs play in driving innovative output. Recall that innovation represents the instan-tiation of creative ideas with those ideas having their initial generative roots in creative employees. Put another way, creative po-tential is a necessary precondition for innovative output — a relationship depicted in Fig. 1. Two points are particularlynoteworthy with regard to the conceptual model presented. First, creative potential is not comprised of a single construct, mea-sure, or scale. Rather, it is the aggregate of KSAOs that represent whether an individual possesses creative potential. Certainlysome aspects are weighted more heavily in this prediction – a point addressed later in our discussion – yet we must bear inmind that creativity is a complex phenomenon, driven by multiple attributes and qualities. The second point worthy of note isthat creative potential stands only as a necessary but not sufficient condition for innovative output. Consistent with interactionistperspectives (Woodman et al., 1993), creative potential will lead to innovative output under conditions supportive of creativethinking. Thus, while the present effort focuses on the initial drivers of innovative output (i.e., creative talent), organizations seek-ing to enhance creative performance must also consider the role of context in appropriately maximizing their creative talent (seeMumford & Hunter, 2005; Shalley & Gilson, 2004 for a discussion). With this conceptual framework in mind, we turn our atten-tion to a discussion on the KSAOs comprising creative potential. We begin with the building blocks of creative thinking:knowledge.

2.1. Knowledge

2.1.1. Domain specific expertiseOne of the core components of creative idea generation is information (Ericsson & Charness, 1994; Weisburg, 1999). That is,

creative idea generation may be viewed as the combination of two or more concepts that were previously viewed as unrelated. Tocombine (at least) two concepts, however, an individual must have cognitive access to such concepts (Hunter et al., 2008). Suchaccess is contingent upon a well-organized mental framework — a framework most aptly described as expertise (Weisburg,

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1999). With respect to creative performance, specifically, it is most useful to consider two types of knowledge: domain-specificand broad-based.

A sizable body of literature demonstrates the key role that domain-specific expertise plays in creative success (e.g., Chi,Bassock, Lewis, Reitman, & Glaser, 1989; Hershey, Walsh, Read, & Chulef, 1990; Reeves & Weisberg, 1994). In a study of technicalexpertise availability, for example, Dewar and Dutton (1986) found correlations around .40 between availability and adoption ofradical innovation. Additionally, a study by Vincent, Decker, and Mumford (2002) demonstrated that domain expertise of leaderswas positively related to both their performance in generating ideas (r=.47), and developing plans to implement them (r=.54).Simonton (2000) had similar findings in evaluating the careers of 59 classical composers. He found that domain relevant experi-ence (e.g., years actively working in composition, number of compositions produced) was predictive of their creative achieve-ments. A more illustrative example is the domain specific knowledge of Bill Gates and Steve Jobs, early guiding leaders ofinnovation giants Microsoft and Apple, respectively. Although each found themselves in largely decision-making roles later intheir careers, much of their early innovative success was brought about via strong technical knowledge (Manes & Andrews,1994; Young & Simon, 2005).

2.1.2. Broad knowledge baseAlthough it is intuitively clear that high levels of domain-specific knowledge (i.e., expertise) are necessary for innovation, it

also appears useful for individuals to have broader forms of knowledge as well (Mumford, 2000). Einstein, for example, was clear-ly an expert in theoretical physics but also had a keen external interest in music. In fact, Einstein suggested that his musical in-terests outside of his field helped facilitate remote connections leading to some of his most impactful theoretical work (Clark,1971). It is often said that creative individuals must have both breadth and depth to successfully innovate (Hansen & Nohiria,2004; Hansen & Oetinger, 2001). A mantra at innovative organizations such as IDEO is the need for “t-shaped” people, or em-ployees with both deep (the leg of the “t”) and wide (the arms of the “t”) interests and access to knowledge (Estrin, 2009;Kelley & Littman, 2001). The reason for emphasizing both breadth and depth is fairly straightforward. While domain expertiseis a necessary component for idea quality, broader, connective expertise is necessary to tie previously unrelated concepts togeth-er. These broader interests, moreover, may also help in facilitating connections with team members who have their own form ofdomain-specific expertise. In a study along these lines, Heinze and Bauer (2007) compared two groups of equally productive (interms of publications) scientists, where one group was classified as more creative based on awards and peer-based recognitionreceived. The authors found that while the scientists' number of publications was a significant predictor of creativity, being

Fig. 1. Interactionist model of innovative achievement.

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multidisciplinary (publishing regularly in journals of different domains) and acting as a broker between otherwise unassociatedcolleagues made creative accomplishment even more likely. In this case, creative scientists are those that not only have broad ex-pertise but are able to connect a network of disparate colleagues.

An illustrative example of how breadth of knowledge can positively influence creativity can be found in the early work ofNASA's engineers and astronauts on space walks. Prior to the efforts of project Mercury in the early 1960s, humans had notmoved in zero gravity — a challenge compounded by the cumbersome space suits worn by astronauts. Simply put, most early at-tempts went poorly. When Buzz Aldrin was tasked with preparing for his space walk, engineers finally realized a viable environ-ment for weightless training: under water. Buzz was an avid diver and had expertise in the subtle movement used to navigatethrough a viscous medium like water. His skills in this other domain (diving) led to the most successful space walk at thattime and, more importantly, revolutionized how astronaut training was performed. Thus, in addition to evaluating potential can-didates on their experiences within the domain directly related to the needed innovation, it may be beneficial to hire individualsthat have experience in a variety of other domains.

2.2. Skills

2.2.1. Domain specific skillsConsistent with the earlier discussion on expertise, it will be critical for employees to possess the domain-relevant skills nec-

essary to operate within their job (Amabile, 1996; Amabile, Hennessey, & Grossman, 1986). For instance, car designers must beable to effectively operate automobile design software, video game developers must be familiar with 3-D modeling software,and sculptors must be able to use their chisels, rasps, and hammers effectively before they are able to conceptualize new waysof doing their work. Such skill sets are highly job-specific but nonetheless stand as key predictors of creative performance. Forinstance, Ericsson and Lehmann (1999) suggest that experts such as chess masters, expert typists, and musicians can improvisemore quickly because of their acquired domain-specific skills. It should be noted that, despite intuitive and theoretical support(Amabile, 1996; Baer, 1998), there is little research that directly demonstrates a link between domain-relevant skills and creativ-ity (Oldham, 2003). In fact, there is some debate as to whether creativity should be considered a domain-specific endeavor (Baer,1998), or whether there are general creative skills that can be applied across domains (Plucker, 1998). Whether domain-specificskills do directly influence creativity or not, there appear to be some more common creativity skills for which we have clearer ev-idence of a relationship with creative performance.

2.2.2. Creative processing skillsStage or process models of creativity have come to dominate our way of thinking about creativity and depict creative perfor-

mance as a series of connected, dynamic, iterative activities (Amabile, 1996; Dewey, 1910; Wallas, 1926). The eight-stage model,for example, is comprised of early creative processes such as opportunity identification and information gathering, mid-stage pro-cesses such as conceptual combination and idea generation, and later-stage processes such as evaluation and monitoring(Mumford et al., 1991). It stands to reason that skills associated with each process will prove valuable to creative performance.Given that these creative process skills are at the core of creative problem-solving, and ultimately innovation, and that eachskill plays a somewhat different role in the innovative process, it is important to consider each one individually. Due to its com-prehensiveness relative to other process models of creativity (e.g., Finke, Ward & Smith, 1992; Wallas, 1926), we will useMumford et al.'s (1991) eight stage model of how individuals engage in problem solving as a framework for creative processskills.

There are several advantages for looking at skills that are specific to particular stages of creativity. First, given the complexityof the innovative process, from identifying a problem to the implementation of the idea, it is unreasonable to assume that a single“creativity skill” would predict success across every step of the process. Second, when making a selection decision, an organiza-tion may have a specific need for someone that can, for instance, see opportunities for innovation, generate ideas, or be the personevaluating highly creative proposals. Finally, it is not necessarily the case that individuals will be skilled at all aspects of the cre-ative process. Thus, a general creativity assessment may fail to identify someone that is highly skilled at only a certain componentof creativity that would ultimately be valuable to the innovative effort. Instead, hiring managers should assess the phase of thecreative process in which their organization is weakest and focus on hiring someone for this role.

In the eight stage model, there are three general phases — early processes (problem identification, information gathering),mid-stage processes (concept selection, concept combination, idea generation), and late processes (idea evaluation, implementa-tion planning, monitoring). There is some support for measuring creative skills associated with each phase of Mumford's eightstage model. In a study evaluating the effect of process skills on the quality and originality of ultimate problem solutions, Mum-ford and colleagues (Mumford et al., 1997) developed measures of the early and mid-stage creative process skills. The model sug-gests that the first stage of the creative process is identifying the problem. The authors measured problem identification anddefinition skills by administering a variation of a situational judgment test in which participants were given an ill-defined prob-lem and asked to choose from a list of alternative ways to define the problem where some were of higher quality and originalitythan others. Performance on the problem definition task was correlated with both problem solution quality (r=.37) and original-ity (r=.31). Individuals skilled in identifying unique ways of viewing a problem hold great value for organizations looking foropportunities to innovate.

In the same study, the authors measured the second process step, information search and encoding, by presenting participantswith an assortment of information including some that was central to the problem and some that was irrelevant. Proficiency was

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assessed by time spent on relevant information versus irrelevant information. Higher performance on this measure of informationencoding was correlated with both the quality (r=.47) and originality (r=.39) of the ultimate problem solution. Given the oftenoverabundance of available information, skill in weeding the wheat from the chaff would prove valuable not only in making bet-ter informed creative decisions, but may also help reduce the significant amount of time it takes to go through the innovativeprocess.

In addition to these early stage processes, two mid-stage processes were also measured. Skill at category selection wasassessed by providing participants with a problem scenario and a list of general concepts that may or may not be relevant tothe task. Those who demonstrated greater skill in selecting relevant concepts were more likely to have problem solutions ofhigher quality (r=.29) and originality (r=.39). Additionally, those who were better able to create new categories to define aset of disparate items that were exemplars from different categories (e.g., furniture and sporting equipment) also had problemsolutions that were of higher quality (r=.29) and originality (r=.40). A very clear example of the benefits of combining previ-ously unrelated categories into a new concept can be seen in Apple's iPhone. By combining a mobile web browser, intuitive inter-face, and a telephone, Apple created a new standard for media-rich phones.

Once individuals have defined a problem, chosen relevant concepts and combined them in unique ways, they then engage inidea generation, or ideation. Ideation is often what individuals think of when they think of creativity — an individual or groupcoming up with a list of as many solutions as possible. For this, many divergent thinking measures would suffice to assess the flu-ency of an individual's creative capacity. However, individuals who are skilled in generating creative ideas do not just generatelarge quantities of ideas, they generate many quality ideas across a breadth of categories. In testing the effectiveness of trainingtheir process model of creativity, Basadur, Runco, and Vega (2000) measured ideational and evaluative skills. To assess Ideational(generative) skills, they measured managers' skill in both generating many ideas (the quantity) and ideas that were novel (thequality of their ideas) in responding to four different management problems. They found that improving managers' skill in idea-tional fluency (quantity) was positively related to ideational quality or originality, and this, in turn, was positively related to skillin evaluating creativity ideas — the next of the eight process skills.

Often in discussions of creativity, the emphasis is on the generation of the idea; however, great importance lies in the evalu-ation and refinement of creative ideas before they are implemented (Lonergan, Scott & Mumford, 2004). It has been demonstrat-ed in studies, such as Blair and Mumford's (2007) study on idea evaluation, that the evaluation of highly unique ideas is a difficultundertaking and individuals are prone to prefer more familiar ideas. In the Basadur, Runco and Vega (2000) study mentioned ear-lier, evaluative skill was measured by asking participants to rate their own ideas for originality, and their evaluative skill was de-termined by the amount of both original and unoriginal ideas that were correctly identified. In the Blair and Mumford (2007)study, participants were given ideas to choose between with varying attributes related to originality.

The final two creative process skills, idea implementation and monitoring, are late in the innovation process, following eval-uation. When it comes to implementing an idea and ensuring that it is carried out effectively, there are other relevant skills be-sides creative process skills, such as communication skills and teamwork skills. However, those deal with implementationplanning beyond the individual creative person. Individuals working through the creative process should have the foresight tothink through the implementation of their idea and how they will ensure it can be evaluated and improved. Vincent, Deckerand Mumford (2002) had leaders prepare responses to questions regarding how they would implement their new idea andhow they would ensure that the idea was carried out as they wanted. They found that the quality of their implementation andmonitoring plans was positively related to their ultimate performance.

While there is evidence for the importance of different skills to different phases of creative thought, there is research that fo-cuses on general “creativity skills”. However, there are two notes of caution for evaluating creativity skills more generally. First,given the evidence for different steps within the innovative process, a general creativity skill measure may not provide a usefulassessment for how well the individual may perform in different steps. Additionally, different processes may be more criticalin different fields of work. A recent study by Mumford, Antes, Caughron, Connelly, and Beeler (2010) found that individuals work-ing in different domains demonstrated different levels of skill across the eight processes. They proposed this was a result of thefield in which they worked and the skills that were required. Second, some of this research uses measures that are based on a nar-row definition of creative problem-solving, particularly focusing on the generation of ideas. Thus, using such measures would notbe a useful predictor of other critical elements of the creative process such as evaluating and refining of ideas.

2.3. Abilities

2.3.1. IntelligenceMuch of the early work on creativity centered on the debate between the distinctiveness of creative ability from general cog-

nitive ability (Runco, 2007; Sternberg & O'Hara, 1999). Initial efforts revolved around a series of studies revealing a strong corre-lation between intelligence and creativity, with initial conclusions suggesting the two constructs were fundamentally similar andshould not be viewed as unique (Getzels & Jackson, 1962). In response to these early findings, Wallach and colleagues (Wallach &Kogan, 1965; Wallach & Wing, 1969) conducted follow-up studies and demonstrated that in the appropriate environment, crea-tive ability was, in fact, distinct from more general cognitive ability — a view that is currently held by most creativity scholars(Runco, 2007).

Although there is general agreement that creative ability and intelligence warrant independent consideration, few denythat a relationship exists between the two. More precisely, current debates on creativity and intelligence center on the natureof this relationship rather than the fundamental existence of one (Sternberg & O'Hara, 1999). Debates regarding this

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relationship will certainly continue, but the emerging popular view has been termed the threshold theory (Guilford &Christensen, 1973; Runco, 2007; Runco & Albert, 1990), where intelligence is theorized to be related to creativity but onlyup to a point. Beyond minimal or threshold levels, intelligence has little bearing on creativity and instead other factors suchas divergent thinking ability account for the variability in creative performance. This is not to suggest that intelligence is unre-lated to creative achievement. Indeed, a meta-analysis by Kim (2008) found significant relationships with IQ and several mea-sures of creative achievement. Thus, congruent with threshold theory, we can conclude that intelligence is a necessary but notsufficient precursor to innovation. In a selection context, then, intelligence may prove useful as an initial, but not final, predic-tor in a multi-hurdle selection system. Instead, other predictors may prove more valuable; namely, those abilities associatedwith divergent thought.

2.3.2. Divergent thinkingGuilford's call to arms on behalf of creativity research in his 1950 American Psychological Association (APA) presidential ad-

dress led many scholars to explore the topic of creativity with greater rigor and focus. His own work on creativity often centeredon cognition, and he was one of the first scholars to make a distinction between convergent thinking (identifying the single cor-rect answer) and divergent thinking (identifying one of many possible solutions). Guilford and his colleagues' early efforts(Christensen, Merrifield, & Guilford, 1953; Guilford, 1956) contended that there are multiple types of creative abilities includingfluency, flexibility, and elaboration, among many others. Current thinking on these constructs is that they represent a higherorder latent variable, broadly termed divergent thinking ability (Hovecar, 1981; Runco, 2007). These early efforts have been fur-ther expounded by several other scholars (Getzels & Jackson, 1962; Mednick & Mednick, 1967), most notably Torrance and col-leagues (Cramond, 1994; Torrance, 1969, 1972, 1979, 2002a, 2002b) who, similar to Guilford, developed a collection of divergentthinking measures.

Although there is substantial variability in the types of divergent thinking measures used, at least two meta-analyses suggestthat they are predictive of creative achievement — more predictive, in fact, than assessments of general cognitive ability (Kim,2006, 2008; Plucker, 1999; Vincent, Decker, & Mumford, 2002). Perhaps most impressive is that these measures have beenshown to be predictive longitudinally at 7 years (Torrance, 1962, 1972), 12 years (Torrance, 1972), 22 years (Torrance, 1980,1981) and even 40 years (Torrance, 2002a, 2002b). Data from these studies have also been re-analyzed by other scholars suchas Yamada and Tam (1996) and Plucker (1999), resulting in similar conclusions. Divergent thinking as a predictor is not withoutits critics, however (Simonton, 2003). Most notable are the criticisms levied against scoring procedures (Sawyer, 2006; Weisberg,2006). Fortunately, work aimed at improving procedures (Silva, 2008), and by-proxy reliability and validity, looks promising andwith such improvements it appears that divergent thinking will prove to be a viable, albeit not sole, predictor of creative and in-novative achievement.

2.3.3. Associational abilityEarly work by Mednick and colleagues (Mednick, 1962; Mednick & Mednick, 1967) proposed that associational ability is an

important predictor of creative achievement. Simplifying somewhat, the associational perspective holds that the most originalideas are derived from the furthest associations between two concepts. Individuals who can make these remote associationsmore readily are therefore theorized to be more creative. Although these propositions make intuitive sense, a number of issueshamper the utility of associational ability as a predictive variable in a selection context. First, although highly remote associationsmay be novel they are also typically less useful. That is, highly remote associations often lack a practical application. Not surpris-ingly then, work by MacKinnon (1962) and Gough (1976) found that moderate, rather than high, levels of remoteness were mostpredictive of creativity. Second, there is some debate as to what constitutes an idea being more or less remote. Perkins (1983), forexample, argued that associations are only remote if they are derived from clearly differing domains — a stance contended bysome scholars who suggest that an idea must only be remote relative to an individual's personal knowledge base (Poze, 1983).Third, the results of associative tests have produced only modest predictive findings with respect to creative performance(Mendelsohn, 1976; Mumford & Gustafson, 1988; Sobel, 1978). Fourth and finally, although we must be careful not to confuseconstructs and measurement it is worth noting that the most common tools used to assess remote associative ability have provedto be rather weak psychometrically. In particular, scales such as the Remote Associative Test (RAT) lack discriminant validity fromother tests of convergent ability and verbal ability (Runco, 2007). On the whole, then, associative ability may not prove to be asubstantial contributor to predicting innovative performance in a selection context.

2.3.4. Analogical abilitySeveral scholars have suggested that an employees' ability to engage in analogical thinking will predict creative performance

(e.g., Dreistadt, 1968; Gordon, 1966; Harrington, 1981; Welling, 2007). Analogical thinking ability is generally viewed as an indi-vidual's ability to recognize similarities between a previous problem and a current one, in turn using solutions from the former tosolve the latter. Examples of analogical reasoning as a tool for innovation include the classic illustration of the steam engine de-riving from a screaming tea kettle — although this direct lineage is debated by some scholars (Runco, 2007). A more recent ap-plication of analogical evidence may be found in the field of biomimicry (Benyus, 2002), where phenomena found in natureare used as guides for solving emerging design problems. Observation of a Gecko's feet, for example, led to the development ofa super-adhesive surgical tape (Geim et al., 2003). One of the earliest, and perhaps most lucrative, examples of biomimicry isthe development of Velcro which was invented by a Swiss engineer who noticed the exceptional gripping power of burrs caughtin his dog's hair after a long walk.

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There is little denying the intuitive appeal of analogical and metaphorical ability in predicting creative performance, yet a coupleof points should be borne in mind with respect to its use in a selection context. First, making the cognitive connections used in an-alogical reasoning is contingent upon a well-organized knowledge structure for both the original problem and the current problem(Kolodner, 1983; Schank, 1990; 1999). These well-organized knowledge structures may prove analogous (no pun intended) toknowledge structures known as schematic knowledge (Hunter et al., 2007; Phye, 1990; Sakamoto & Love, 2004; Wisniewski,1996). Not surprisingly, given its similarity to analogical thinking, schematic knowledge has proven useful to creative performancein several studies (Baughman & Mumford, 1995; Hunter et al., 2007). Schematic knowledge, moreover, is often derived from signif-icant experience — that is, experience cognitively organized in a useful way (i.e., organized by schema). Thus, schematic knowledgeand analogical ability may prove to be highly correlated with traditional views of expertise. In this way, assessing expertise and an-alogical ability (or schematic knowledge) may be somewhat redundant in predicting novel idea generation.

One way that analogical ability can be particularly viable in creative performance, however, is in later stages of innovation.Note that creativity is defined as the generation of novel and useful ideas while innovation, in turn, is defined as the successfulimplementation of those ideas (Amabile, 1983). Although creativity is largely an individual and group effort, implementing prod-ucts or processes requires a number of organizational resources and capabilities (Klein, Conn, & Sorra, 2001). Accordingly, projectteams with a creative idea must convince organizational decision makers of the potential value of their idea. The use of analogiesmay prove particularly useful in taking a novel concept and making it “familiar”, thereby reducing the negative bias often asso-ciated with new ideas (Lonergan, Scott, & Mumford, 2004; Mumford, Blair, Dailey, Leritz & Osborn, 2006). Thus, on the whole, an-alogical ability may prove somewhat useful in creative idea generation but will likely serve a larger predictive role in later stagesof innovation. However, while there is much anecdotal evidence and theory that supports the premise that analogical abilitywould be useful for innovation (Welling, 2007), there is little research that directly assesses analogical ability and creativeperformance.

2.4. The “O” in KSAO — qualities such as personality traits and individual dispositions

2.4.1. DispositionsThe study of creativity is replete with investigations of the relationship between personality and innovation (see Barron &

Harrington, 1981; Dellas & Gaier, 1970; Eysenck, 1995; Freeman, Butcher, & Christie, 1971; Gilchrist, 1972; Mumford &Gustafson, 1988). Given this sizable body of literature, it would prove unwieldy to discuss each of these studies in turn here. In-stead, we will begin by discussing several summary efforts, noting specific studies when applicable. Perhaps the most notablesummary effort is the work by Feist (1998) whose meta-analysis provides an excellent synopsis of the relationships between var-ious dispositions and innovation. Overall, this work and others like it (e.g., Ma, 2009) suggest that personality appears to exertsizable, albeit complex, effects on creative achievement.

Helping to make sense of these complex relationships, Feist (1998) provides a useful framework for grouping dispositions intobroad social, cognitive, and motivation categories. Feist observed that social traits such as arrogance, hostility, self-confidence,need for autonomy, and introversion were significantly associated with innovative performance — a general pattern consistentwith other reviews (Barron & Harrington, 1981; Feist, 1999). Key cognitive traits significantly related to creative performance,in contrast, include less caustic qualities such as openness to experience and flexibility. Openness to experience has beenshown to be a particularly consistent and non-trivial determinant of innovative performance across many studies (Barron &Harrington, 1981; McCrae, 1987). Finally, motivational traits such as drive and ambition were found to demonstrate sizable ef-fects in predicting innovation as well.

2.4.2. MotivationMost researchers would agree with the basic contention that performance is a function of ability and motivation (Campbell &

Pritchard, 1976; Chan, 2010). Notably, creative performance is theorized to result from high levels of intrinsic as opposed to ex-trinsic motivation (Amabile, 1985; Amabile & Mueller, 2008). The rationale for this relationship is fairly straightforward — crea-tivity represents a collection of processes that often lack templates or exact plans of action for accomplishment. When thischallenge is coupled with increased numbers of mistakes and frequent failure, frustration will inevitably arise (Berkun, 2007).Thus, having a passion for the task (i.e., intrinsic motivation) will help address the inherent difficulties associated with generating,revising and implementing novel products and processes.

Motivation has been conceptualized in a number of ways including state oriented conceptualizations to more stable, trait-likeperspectives (Chan, 2010). It seems reasonable to suggest that state motivation will be derived largely from context (Amabile,1996) while more stable motivation qualities will prove most useful in hiring creative talent. Potential predictors might includenearly personality-like individual differences discussed earlier such as need for achievement (McClelland 1962, 1985) or morecreativity specific interest oriented variables such as work-preference (Amabile, Hill, Hennessey, & Tighe, 1994; Holland, 1985).Although these approaches to conceptualizing intrinsic motivation vary somewhat, the underlying message here is clear — passionfor creative work is an important predictor of creative performance and should be considered in the selection context.

3. Measurement tools, techniques, and methods for assessing innovative potential

It would prove unwieldy to discuss specific measurement approaches and methods for each of the unique KSAOs discussedabove, yet it is useful to broadly consider differing methods and their applicability to identifying creative potential. Using a

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framework put forth by Hough and Dilchert (2010), we will discuss the applicability of self-report, other-report, biodata, inter-views, situational judgment tests, and assessment centers in the measurement of creative potential.

3.1. Self report

The use of self-report as a means to gather predictor data is likely to be very useful for assessing more stable creativity-oriented KSAOs such as personality and motivation (Hough & Dilchert, 2010). In fact, the self-report method is popular andtends to produce reasonably high reliability coefficients for scales that have been appropriately developed and validated(Hough & Oswald, 2000; Spector, 1984). Moreover, there have been well-developed scales that are specific to creativity assess-ment providing some indication of the applicability of self-report to assessing elements of creative potential. Amabile's (1994)Work Preference Inventory, for example, has proven to be both reliable and valid as a measure of intrinsic motivation for creativetasks. Similarly, McCrae's (1987) work on the NEO-PI (Costa &McCrae, 1992), a measure of the big five personality traits, has beenfound to be robust psychometrically and dimensions such as openness to experience have demonstrated sizable and reliable re-lationships with creative performance. In short, to assess stable individual differences, self-report scales are generally cost-effective and relatively easy to administer, providing reasonable reliability and validity estimates if developed with acceptablelevels of care and rigor.

Where self-reports may prove less useful, however, are in global (i.e., broad) assessments of perceived creative ability. In arecent study of students, for example, Kaufman, Evans, and Baer (2010) found that self-report ratings of creative ability wereminimally (or sometimes not at all) predictive of creative performance as assessed by expert judges. It appears that self-reports of creativity may be capturing a form of efficacy or self-assurance rather than creative ability. Although constructssuch as confidence have shown to be useful for creative achievement in some contexts (Feist, 1998), the nature of self-reportassessment currently used in this manner precludes clarity as to what is actually being captured thereby limiting our recom-mendation for using self-reported creative ability in a selection context.

3.2. Other-reports

The use of other-reports, such as peer and supervisor ratings of creative potential, may be viable options for general assess-ment of creativity-oriented KSAOs. As will be discussed later in the manuscript, however, there are a number of potential biasesthat emerge when using peers and supervisor assessments of creative potential as well as creative performance. Supervisors, forexample, may simply not be witness to many forms of creative activity thereby limiting the accuracy and utility of assessment.Peers, while having access to such behaviors, may be influenced by biases such as “halo” or “horns” effects (Bowman, 1999).Moreover, peer reports of creative potential that use broad phrasing such as “how creative is this person” may be susceptibleto a number of implicit biases that rely on stereotypes of creative achievement (Mumford, 2000). In contrast, other-reportsthat focus on the occurrence of specific behaviors, characteristics, skills, or attributes may be useful in providing valid assessmentsof creative potential. It will be paramount, however, to specify what is to be assessed and to operationalize predictors in the mostconcrete means possible.

3.3. Biodata

The utility of biographical data, or biodata, is predicated on the principle that prior behavior significantly predicts futurebehavior (Guthrie, 1944). As an assessment method, biodata may be viewed as a specialized form of self-report and can varyin format and scoring, contingent upon the needs and approach of the assessor. For example, biodata questions aimed at asses-sing leadership potential may ask the candidate to describe their leadership history qualitatively or present the candidate with aseries of options and ask them to choose the response that best captures their work experience. These responses are then scoredeither empirically by assessing patterns among candidates or via rational scaling where a-priori predictions are made about pre-dictor and criterion relationships. Biodata has been shown, not surprisingly, to overlap with interest and personality inventoriesyet typically offers incremental predictive ability over and above these tools. From a validity and reliability standpoint, biodatahas proven to be both highly reliable (Chaney & Owens, 1964) and valid, with criterion-related coefficients rivaling even thoseof cognitive ability for several performance outcomes (Mumford & Stokes, 1991).

With respect to innovation specifically, there is a sizable literature suggesting that biodata is particularly adept at predictingcreative performance (Albright & Glennon, 1961; Kuhlberg & Owens, 1960; McDermid, 1965). A biographical inventory devel-oped for NASA scientists, for example, was used to assess the creative potential of pharmacists with results revealing that biodatascores were correlated with creative performance around .40 (Tucker, Cline, & Schmitt, 1967). Moreover, as part of a selectionsystem, biodata measures are highly flexible and can be developed to capture a range of KSAOs related to innovation. Finally,given that creative performance in early life is predictive of later life creativity (Torrance, 1981) the basic foundation of biodataappears quite sound in assessing creative potential.

A form of biographical data that is unique to creative performance is the portfolio, a tool often used in creative jobs to dem-onstrate achievement and competence in prior innovative activities. Although portfolios can vary substantially by individualand across jobs, they typically consist of multiple samples of an individual's prior projects. This may be a series of writing samplesby an author, a collection of lesson plans developed by a teacher, or a series of designs compiled by a graphic designer. An assessorcan examine these projects and make a judgment about the candidate's creative potential that is clearly grounded in previous

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experience. In addition, portfolios allow assessors to compare the candidate's style to that of current employees to see if they addsomething unique to their creative team. Given the intuitive appeal of portfolios as a means to demonstrate proficiency in a va-riety of skill-sets, many educational institutions are requiring students to develop “ePortfolios” to exhibit the capabilities theypossess (Norton-Meier, 2003; Wright, Knight, & Pomerleau, 1999). Although little work has been done on the use of portfoliosto assess creative potential in a hiring context, specifically, they represent an interesting, and possibly viable, biodata-like methodof creativity-oriented KSAO assessment given greater validation evidence.

3.4. Interview

Interviews are the most commonly used selection method and are often standard practice in organizational hiring decisions(Hough & Dilchert, 2010; Moscoso, 2000; Ryan, Mc Farland, Baron & Page, 1999). The aim of most interviews – either explicitlyor implicitly – is to assess a candidate's disposition or personality (Huffcutt, Conway, Roth, & Stone, 2001). Despite this goal, itis frequently unclear what is actually being measured in an interview, particularly in unstructured interviews. Interviewers' as-sessments of personality, for example, have been found to be more highly correlated with cognitive ability than the personalitytrait interviewers are trying to assess. More central to the discussion on creativity, there is evidence to suggest that more visibletraits such as extraversion are easier to assess than less visible traits such as openness to experience (Hough & Dilchert, 2010).Similarly, creative potential and many of the creativity KSAOs discussed earlier can be difficult to observe in a typical question-and-answer interview format. Thus, interviews may not be the most reliable and valid method for assessing creative potential.There may be some constructs, however, that lend themselves to assessment via structured interview. For instance, Morgeson,Reider and Campion (2005) identified characteristics that are essential for teamwork and developed and validated structured in-terview questions to assess those characteristics.

3.5. Situational judgment tests

Situational judgment tests (SJTs) provide candidates with a scenario or situation and ask them to provide a response indicat-ing how they would or should behave in that setting. Scenarios are often presented in paper and pencil format, although there hasbeen significant growth in web-based and video-based methods (Weekley & Ployhart, 2005). Candidate responses are thenscored according to predefined procedures and criteria (Chan & Schmitt, 2002). As a selection method, SJTs may be used to assessa variety of predictor types (e.g., personality), and are often tailored for specific jobs such as firefighter or police officer. Some re-searchers have suggested that SJTs are not a method per se, but rather a broad test of knowledge comprised of multiple dimen-sions (Weekley & Ployhart, 2005). Meta-analyses suggest that SJTs are correlated with task performance at around .30 correctedfor sampling error unreliability (McDaniel, Hartman, Whetzel, & Grubb, 2007). With respect to reliability, Hough and Dilchert(2010) lament that coefficients are rarely presented in the literature and it is unclear, overall, how reliable SJTs are.

Despite some degree of intuitive appeal, little is known about how well constructs measured via SJTs would predict creativepotential, specifically. It seems reasonable to suggest, given their moderate success in assessing personality traits in various do-mains, validity would translate to similar traits in a creative context. SJTs can also be viewed as a form of knowledge assessment(Weekley & Ployhart, 2005) and thus may prove viable in assessing knowledge about working on creative projects. In fact, theambiguous nature of the scenarios used in SJTs provides a reasonably fertile ground to elicit novel, original, and new responsesfrom selection candidates.

The challenge, it would seem, lies in developing scoring criteria. That is, highly novel responses from candidates may not fitpredetermined scoring protocols and, almost by definition, would not have been anticipated by scoring key developers. However,a recent study by Mumford et al. (2010) developed situational judgment tests for each of the eight creative process steps to mea-sure differences in skill across domains. These domains included biological science, health science, and social science. Participantswere given domain-based scenarios and response options that varied in quality and originality. Taken a step further, it wouldprove challenging to develop standardized scoring procedures for assessing global creative potential. Instead, reliability maybest be derived from multiple assessors. This argument provides a natural segue into discussing our final method of quantifyingcreative potential: assessment centers.

3.6. Simulations and assessment centers

Of the methods discussed, simulations and assessment centers (ACs) may prove to be one of the most reliable and valid – albeitcostly – means of identifying creative potential. Simulation based approaches to selection vary somewhat by the jobs they aredesigned to assess, yet they are typically characterized by placing a candidate into a variety of scenarios where they are askedto respond and behave as if they were working in an organization. While participating in the simulation tasks, candidates areobserved by trained assessors who provide evaluations using pre-determined dimensions (Motowidlo, Dunnette & Carter,1990). Although they can be costly given the level of time and rigor necessary to develop exercises, role-plays, and in-baskettasks, as well as to train raters and obtain appropriate simulation space, assessment centers have proven to be one of themost predictive and reliable methods used in selection (Arthur, Day, McNelly, & Adams, 2003; Gaugler, Rosenthal, Thornton,& Bentson, 1987; Sackett, 1987).

Notably, there has been some research on creative problem-solving in assessment centers suggesting that ACs are useful forassessing creativity and innovation, specifically. A recent meta-analysis on ACs and criterion related validity, for example,

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revealed that problem-solving produced the largest validity coefficient of the dimensions examined (Arthur et al., 2003). Theoperationalization of problem solving in the meta-analysis, moreover, was congruent with the creative process model, emphasiz-ing the importance of recognizing opportunities, gathering appropriate information and generating novel ideas. In addition,problem-solving consistently accounted for incremental variance above other AC dimension such as planning, communication,and drive. Consequently, it appears that creative potential may be accurately assessed in an AC and simulation context andthat doing so could result in sizable relationships with performance.

We suggest that ACs and simulations are adept at assessing creative potential for at least three primary reasons. First, assess-ment centers allow for ambiguous, ill-defined scenarios to be presented to candidates. A necessary precursor to witnessing acandidate produce creative output is that the candidate, simply put, has the opportunity to do so. Many paper-and-pencil mea-surement tools such as self-reports of personality provide candidates with a series of multiple choice responses or ask them toprovide levels of agreement on finite rating scales. These tools are inherently confining and may only reliably capture a smallnumber of the qualities necessary for creative performance. In contrast, ACs possess nearly infinite flexibility with respectto designing tasks and scenarios that allow for the emergence of creative responses. Second, ACs typically use raters or judgesto assess candidates on predictor dimensions. Work on quantifying creative achievement has often relied heavily on raters,demonstrating quite readily that trained or expert judges can consistently and reliably rate the creativity of an idea or product(Amabile, 1992). It stands to reason, then, that trained raters in an AC context will be able to reliably assess creative potentialin its various forms. Third and finally, the simulation-oriented nature of ACs allow for social interaction via group or role-playing exercises. In other words, ACs allow assessors to observe how candidates interact with others when engaging in cre-ative processes. Although many components of creativity require individual-level idea generation, successful implementationof ideas will necessarily require interactions with peers, subordinates, and supervisors. ACs permit simulation designers toreasonably depict the complex social interactions that characterize creativity and innovation. Thus, we suggest that assess-ment centers may be the best method of evaluating candidates' creative potential.

3.7. Summary and KSAO rankings

Although our proposed model depicts creative potential as a latent construct comprised of multiple attributes, it is clearthat some qualities aremore or less predictive of creative output. Thus, considering the practical constraints of time, money, and gen-eral business resources, organizationswill likely have tomake prioritizations as towhich qualities to assess in their selection systems.Fortunately, research by scholars such as Ma (2009) offer some guidance as to which predictors might initially be emphasized in aselection context. For example, Ma's (2009) meta-analysis of over 111 creativity studies found that early stage creative processingskills produced a larger effect size (d=.93) than general cognitive ability (d=.31). Using results such as these as guidelines, arough rank order of KSAOs is presented in Table 1. The table also includes a set of recommended assessment methods as well asthe corresponding stages of the innovation process for which these KSAOs are most effective.

4. Creativity as a unique performance criterion

Measuring, choosing, and assessing predictors of creative achievement are not the only challenges faced by organizationsaiming to hire creative employees. The measurement and assessment of creative and innovative performance also presents anumber of challenges. Specifically, in contrast to many traditional forms of organizational performance, we suggest that creative

Table 1KSAO rankings by criticality, methods for assessment, and stages of innovation best predicted by KSAO attributes.

KSAOs rank ordered by criticalityto overall success of innovation

Method(s) recommended for assessment Stages of innovation process at which theKSAO is most likely to predict success

Creative processing skills Assessment center;situational judgment tests

Full range

Early-stage processes Assessment center;situational judgment tests

Early stages

Mid-stage processes Assessment center;situational judgment tests

Mid stages

Late-stage processes Assessment center;situational judgment tests

Later stages

Personality Self-report; other-report Contingent upon personality trait assessed,but overall most predictive at later stages

Divergent thinking ability Self-report Mid stagesExpertise Biodata; interview Full rangeDomain specific skills Assessment center Full rangeBreadth of knowledge Interview, self-report; biodata Full range with particular predictive ability

at middle stagesCognitive ability Self-report Later stagesMotivation (intrinsic) Self-report, interview; biodata Mid and later stagesAnalogical ability Self-report Later stagesAssociational knowledge Self-report Mid stages

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performance is a unique outcome that warrants special consideration in a selection context. This argument is made on four pri-mary bases: 1) lower base rate, 2) veiled nature of creative performance, 3) cognitive and social nature of creative outcomes, and4) process models of creativity. Each is discussed in greater detail below.

4.1. Lower base rate

A general rule of thumb of creative accomplishment is that approximately 1 in 10 or 1 in 20 ideas will succeed, while the restwill stand as failed attempts that never make it beyond the speculative phase (Estrin, 2009; Mumford & Hunter, 2005). Althoughnot particularly desirable, a success rate of between 5 and 10% is not wholly surprising when the nature of creativity is carefullyconsidered. Recall that innovation involves the generation of novel, useful ideas. Due to this novelty, creative ideas are inherentlydifferent from the products and processes that came before them. Put another way, original ideas have no template to guide theirdevelopment— they are, by definition, distinct from earlier approaches. Pragmatically speaking, organizations pursuing a radical-ly innovative entity often have little to go by with regard to testing, prototyping, building, evaluating, and even selling their newproduct or process. Simply put, the ambiguous nature of novel ideas simply means there will be frequent failure and misstepsalong the way (Berkun, 2007).

In addition to challenges associated with infrastructure, early creative ideas often fail simply due to lack of support (Jelinek& Schoonhoven, 1990; Meyer & Goes, 1988; Mumford & Hunter, 2005). A growing body of research suggests that decisionmakers often fail to see the value in novel ideas (Lonergan, Scott, & Mumford, 2004; Mumford, Blair, Dailey, Leritz & Osborn,2006). This may occur, in part, because individuals in a position to provide support lack a mental model with which to comparea truly new idea and, therefore, fail to see the potential of such an idea. In addition, assessing the value for new ideas is cogni-tively taxing and, given a busy schedule, decision makers may gravitate toward more predictable solutions (Bazerman, 1994;Ford, 1996). Finally, new ideas are inherently risky and in many for-profit contexts, risk is not a welcomed component of or-ganizational strategy (Adams, Day, & Dougherty, 1998). Although these explanations vary somewhat in their causal explana-tion, the central conclusion holds true: making decisions about creative ideas often means that the most original ideas willnot see the light of day.

Consideration of the above trends reveals a common theme — the successful implementation of creative ideas is a relativelyrare phenomenon. From a criterion standpoint, this represents a distinct challenge, one noted expressly by scholars who investi-gate other low base-rate organizational phenomena such as turnover and absenteeism (Hulin, 1991). If creative success is used asthe primary outcome, there are relatively few useful data points with which to distinguish potential candidates. From a statisticalstandpoint, low base-rate outcomes can also have problematic impacts on the interpretation of validity coefficients (Hulin et al.,1984; Olsson, Drasgow, & Dorans, 1982; Wiggins, 1973), further hampering hiring decisions.

4.2. Veiled nature of creative performance

In addition to low base-rate issues, creative performance is also a difficult phenomenon to witness and accurately assess.Although this is true of several types of organizational criteria (e.g., turnover intentions), careful consideration of the natureof creativity reveals the challenges uniquely bound to creative performance. To begin, it is important to bear in mind that, formany employees, putting forth highly novel ideas is a stress-producing endeavor. Many employees are fearful of feedback(Ashford, Blatt, & VandeWalle, 2003; Cleveland, Lim, & Murphy, 2007) and because creative ideas are innately different from pre-vious ideas, they can often be met with even greater levels of skepticism and criticism. Ideas deemed strange can result insimilar negative attributions to the generator of those ideas. There is also some indication, moreover, that negative attributionstend to remain more salient than positive attributions (Kasof, 1995; Rothbart & Park, 1986; Winter, 1993). Stated more directly,generators of odd ideas can appear less competent because they are not upholding the standard procedures or norms of theirorganization.

Taking this concept a bit further, it is worth noting that a common means of collecting traditional performance data is the useof supervisor ratings (Borman, Bryant & Dorio, 2010; Landy & Farr, 1980; Lent, Aurbach, & Levin, 1971). For more typical forms ofperformance, supervisor ratings are valuable given that supervisors often have an appropriate mental model for what perfor-mance should be (Becker & Klimoski, 1989; Cascio, 1998). For creative performance, however, there are no templates for whata creative idea should be; simply by definition, a creative idea is unlike other ideas generated previously. In addition to vague stan-dards for creative ideas, managers may have a difficult time rating the employee behaviors that lead to developing these products.Since creativity is inherently a cognitive process that may or may not occur during work hours, it is difficult to create explicitbehavioral exemplars of “good” creative performance to differentiate employees.

Presenting an even greater challenge is the observation that many employees may not want to share their most novel ideaswhen supervisors are near. Again, radically novel ideas can result in unwanted attributions placed on the employee, whichwould be particularly detrimental if those making the attributions were managers making decisions about future task assign-ments and promotions (Kasof, 1995). As such, trusted colleagues are often in the best position to witness the most originalideas and therefore to provide accurate assessments of creative performance. The use of trusted colleagues for performance rat-ings, however, also represents a unique challenge due to a number of potential biases that may occur (Borman, 1974; Borman,White, & Dorsey, 1995; Conway & Huffcutt, 1997; Klimoski & London, 1974). In addition, Rotundo & Sackett (2002) suggestthat when resources are limited and competition between coworkers is high, peer ratings may be artificially low. Companieswith highly competitive reward structures may not have work environments that are conducive to coworkers sharing ideas

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with each other. In competitive environments, coworkers may not be exposed to the creative ideas of their colleagues and wouldthus be poor judges of their creative potential.

4.3. Cognitive and social nature of creative performance

Physical prototypes, storyboards, script drafts, building mock-ups, and early design sketches are physical manifestations ofwhat are largely cognitive endeavors. That is, much of the early work on novel idea generation is cognitive or mental in nature— creative work simply involves thinking about and exploring ideas (Hunter, Bedell-Avers, Hunsicker, Mumford, & Ligon,2008; Mumford & Gustafson, 1988; Mumford, Hunter, & Byrne, 2009). Thus, similar to the challenges associated with the veilednature of creativity is the fact that idea generation and associated creative processes are frequently less observable activities. Thisis likely why innovative powerhouses like Google, IDEO, and Pixar are often depicted by employees residing in bean bags, playinggames, relaxing with coffee, and generally appearing, on the surface, not to be physically working (Berkun, 2007; Capodagli &Jackson, 2010; Estrin, 2009). As evidenced by the amazing innovative output of these organizations, this is clearly not the case.Rather, much of their work is cognitive, thereby making it uniquely challenging to capture in the criterion space.

Turning now to the social nature of creativity, it is important to note that when ideas have been adequately thought about andare ready to be discussed, they are typically expressed in a group setting. Stated more directly, much of today's creative work isdone in teams (Cotton, 1993; Manz & Sims, 1993; Mohrman, Cohen, & Mohrman, 1995; Morgeson, Reider, & Campion, 2005;Paulus, 2008; Pirola-Merlo & Mann, 2004); gone are the days of the lone inventor — save the exception of the rare single entre-preneur with which selection systems have little bearing. Instead, teams comprised of members with multiple forms of expertise,backgrounds, and experiences are used to engage in, oftentimes, multiple creative projects simultaneously. When these projectsmove forward, individual ownership over ideas is often lost or at least becomes a debatable issue (Stark & Perfect, 2007). Instead,the group produces an assortment of thoughts, notions, concepts, and ideas that shape the final product (Hirschberg, 1999). Froma selection standpoint, the team-based nature of creative performance represents an interesting multilevel challenge (Mumford &Hunter, 2005). Moreover, the team-based component highlights the importance of effectively working with others in the creativeprocess and underscores the criticality of considering social components in a selection system.

4.4. Creative process

As is the case with many types of performance, creative performance is multi-dimensional (Kurtzberg, 2005). Although wemight stereotypically think of idea generation as the primary creative activity of innovation, the array of research on creative pro-cesses suggests that a host of other activities are necessary for creative output. In fact, process models of creativity have a longhistory, beginning with the efforts of Dewey (1910) and driven largely by the early four stage model of Wallas (1926). More re-cent approaches, akin to the work byWallas, including those by Taylor, Austin and Sutton (1974), Finke et al. (1992) and Amabile(1996) have taken these early models and expanded them in a host of useful ways.

Expanding these models further is perhaps the most detailed model, put forth by Mumford and colleagues (e.g., Baughman &Mumford, 1995; Mumford et al., 1991, 1997, 1996). Known as the eight-stage model, creativity is theorized to begin with theidentification of a problem or opportunity, followed by gathering information used to solve the problem. Key concepts are thenchosen and narrowed and formal idea generation can begin. Once ideas are generated they can be evaluated for their appropri-ateness and utility. The process then shifts to determining how to implement an idea or solution. With the solution in place, at-tention shifts to monitoring the process where problems can be identified and fixed as needed. Although the process is presentedhere linearly, it is unlikely to occur in a linear fashion in real working environments (Finke, Ward, & Smith, 1992). Phases are oftenleapfrogged and information from each phase fed back into earlier phases. Moreover, projects do not operate independentlydown this linear path. Rather, multiple concepts, ideas, and notions are often fed into other ongoing projects comprising a broaderproject portfolio (Hunter et al., 2011; Mumford, Bedell-Avers & Hunter, 2008).

Consideration of creative process models highlights a key point: creativity is not a singular event. Rather, creative performanceis more accurately represented as a series of interrelated activities and, more pragmatically, it must be borne in mind that successacross all these activities cannot be captured at a single point in time. Thus, it will be critical for assessors to bear in mind thatcreative performance is both multi-dimensional at a given time point and that the importance and emphasis of activities willchange over time (Ghiselli, 1956).

4.5. Summary

Creative performance is best represented as a collection of interrelated processes that are challenging to both observe and as-sess given the cognitive and social nature of the tasks (Barron & Harrington, 1981; Mumford & Gustafson, 1988). Moreover, tra-ditional selection techniques such as supervisor ratings may be less useful because many processes involved in creativity requiretrust and high levels of psychological safety (West, 2002). Finally, successful creative projects are a relatively rare phenomenonand there is an inherent challenge in identifying these low-base rate outcomes (Hulin, 1991). On the whole, consideration ofthe challenges above highlight the care that must be placed in developing a selection system aimed at identifying individualswith creative potential.

Given the aforementioned idiosyncrasies of creative performance, we suggest that several approaches be taken to establishuseful criteria in a selection context. First, although a very common tool in selection, caution should be paid to the use of

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supervisor ratings for assessing creative performance. In many circumstances, supervisors simply may not witness highly originalidea generation. Granted, in organizations where psychological safety is high and supervisors have established environments inwhich subordinates feel comfortable sharing original ideas, supervisor ratings may certainly prove viable (Capodagli & Jackson,2010). In many other contexts, however, peers may prove most useful in capturing accurate creative performance ratings.

Along these lines, it will be critical that assessment of criteria clearly be gathered for validation and developmental rather thanevaluative (promotion or pay) purposes. That is, to the extent raters believe their ratings will be used to make decisions about payor promotion, biases will increase (Boswell & Boudreau, 2002; Gioia & Longenecker, 1994; Murphy & Cleveland, 1995). Such biasmay be exacerbated, moreover, because peers in the position to make the most accurate assessments (i.e., most trusted) are alsothe individuals most likely to produce biased ratings (Gioia & Longenecker, 1994; Longenecker & Gioia, 1992) underscoring theimportance of conveying developmental intent in criteria collection. Fourth, although objective outcomes such as patents or pub-lication counts are useful indicators of innovation, they fail to capture the range of processes that occur in creativity and as suchthey should not be used as the sole indicator of creative performance. This is not to deny the importance of objective indicators orsuggest that profit and sales figures are not of paramount importance for gauging innovation success. Rather, it is important tobear in mind many of these objective outcomes are largely dictated by factors outside of the individual and as such have less util-ity in an individual-based selection context. The aim, instead, should be to expand and enrich the criterion space to ensure thegreatest degree of variance in outcomes of interest.

Finally, when gathering performance data it will be critical to consider both the multidimensional and longitudinal nature ofcreative performance. More precisely, it will prove useful to assess employees on early stage creative processes such as opportu-nity recognition and later stage processes such as planning and monitoring in addition to more traditional forms of evaluatingidea generation. Assessments should also be made, moreover, at multiple points in time to maximize the likelihood of capturingthe full range of creative activity— creativity, after all, takes time (Shalley, Gilson, & Blum, 2009). Application of these approaches,in the aggregate, should provide a reasonably sound representation of creative performance.

5. Recruitment and long-term selection strategy

5.1. Recruitment

Selection decisions are only useful if there is a solid pool of high-quality candidates entering the system (Cable & Turban, 2001;Ryan & Delany, 2010). Unfortunately, as we can infer from the complex predictor set, creative job candidates may be particularlyrare (Torr, 2008). Thus, recruitment of creative employees stands as an important factor for hiring innovative talent. The keyquestion, then, is what do creative employees want and how are these qualities promoted in order to increase recruitment? Re-search on creative individuals suggests that there are at least six aspects of organizational life attractive to a creative workforce.

5.1.1. AutonomyOne of the strategies organizational decision makers can do to attract creative talent is to provide elevated levels of autonomy

on high-profile projects. This is exemplified by organizations such as 3M, Epic Games, and Google who allow their employees asignificant portion of time to work on their own projects — an approach that has proven useful both as a recruitment tactic aswell as a profitable product generator (Vise & Malseed, 2005). The basic principle of these programs can be applied to all organi-zations by allowing employees some degree of autonomy in how projects take shape. Leaders can provide structure via a generalmission while trusting their employees to find the actual path to creative success (Mumford, 2000). Managers at innovative pow-erhouse Pixar, for example, have approximately a 20:1 span of control over projects while other organizations typically have an8:1 span (Capodagli & Jackson, 2010). In short, creative employees may be especially sensitive to micromanagement by theirleaders and increased levels of autonomy are a desirable commodity for an innovative workforce.

5.1.2. Support for risk-takingA second organizational attribute attractive to creative talent is an environment supportive of risk-taking. Creative individuals

want to try new and different things and if their most original ideas are stifled before they can be adequately explored, they willsimply find another organization that allows them that level of exploration (Berkun, 2007). Along these lines, recruitment teamsshould keep in mind that creative employees often want to test their ideas quickly and should stress the opportunities for rapidexploration in their marketing materials. This is not to say they want to succeed quickly— innovative talent is keenly aware of thefrustrations inherent to innovation. Rather, these individuals want to learn, rapidly, what works and what does not. Illustratingthis concept nicely is an often used phrase at innovation powerhouse IDEO, “fail faster to succeed sooner” (Kelley & Littman,2001). Thus, organizations that embrace rapid prototyping and testing facilities will be adept at recruiting high level creativetalent.

5.1.3. Encourage diversity of expertiseInnovative individuals know that the more they become entrenched in one content area, the more they lose their ability to see

original connections across content areas. This desire for new experiences and information is nicely illustrated by Google, whooften bring in experts from largely disparate content areas simply to expose their employees to new ways of thinking (Vise &Malseed, 2005). Another example of the appeal of diversity in expertise is found in an examination of the Bell Labs in the1960s and 1970s — an organization that gave us the cell phone, laser, multiple Nobel Prizes and many other notable innovations.

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The organization succeeded, in large part, by attracting high-level talent — talent that was drawn to the wide variety of contentexpertise. As one former scientist noted, “the best thing about the old Bell Labs was that there was an expert in every subject ofinterest right down the hall” (Estrin, 2009, p. 67). Thus, organizations that embrace cross collaboration and sharing both withinand outside the organization will be attractive to creative employees.

5.1.4. Passion for the workAs noted throughout our discussion, intrinsic motivation is clearly a key predictor of creative performance (Amabile, 1985).

Not surprisingly, creative individuals want to work with others who are also passionate about their work. Simply put, creative in-dividuals are zealous about what they do and if others do not share that passion, they are likely to be annoyed at their lack of com-mitment to the project. Building this culture of innovative enthusiasm within an organization certainly takes time, but once it isestablished culture can be an attractive recruitment tool for creative talent.

5.1.5. RecognitionFinally, leaders should publically recognize creative efforts in their organization. Although the available evidence does not sug-

gest that extrinsic rewards produce effects that are as strong as those derived from intrinsic satisfaction (Amabile, 1985, Amabile& Mueller, 2008), organizations that recognize both success and failure of highly novel projects send the message that originalthinking is an acceptable approach to problem solving. In fact, rewarding innovative attempts can convey the sentiment that cre-ativity is important and valued (Mumford & Hunter, 2005; Shalley, 1995). Thus, extrinsic recognition is an important factor in fa-cilitating a climate that is attractive to individuals who want to engage in creative work.

5.1.6. RewardsOne final point that should be borne in mind is that pay is not a singular driving mechanism for attracting creative talent.

Although pay certainly matters in any hiring context, the above factors will likely play a larger role in attracting creative talent,particularly when pay scales are comparable across employment opportunities (Chalupsky, 1964; Shapiro, 1953). In fact, severalscholars have argued that an overemphasis on external rewards such as pay will hamper creativity and that, by hiring thoseemployees who are “in it for the money”, long-term creative and innovative performance will suffer (Amabile & Mueller,2008).

5.2. Long-term strategy and innovation

One of the inherent challenges to hiring for creativity is that there is some degree of “unknown” implicit to creative work. Infact, to the extent that there is a specific product or product line-up in mind, the creativity of that line-up will be minimized. Or-ganizational leaders, then, are often faced with hiring creative talent for projects that are not yet conceived. The implication hereis that a long term hiring strategy for innovation will require some degree of talent acquisition that may not be derived frommoretraditional forms of job analysis where current employees' jobs are examined to infer what a future employee might do. A focuson current job requirements will result in the hiring of employees that are proficient in those tasks — not necessarily those thatare needed in the future.

Consider the following illustration from Google. At a non-work function, an organizational decision maker met a group of soft-ware engineers working on voice recognition software. Although Google had no plans at the time for using voice recognition, theorganizational leader hired the engineers the next day without an explicit plan for what they would be doing. Since then, the soft-ware engineers have been significant contributors to Google's voice recognition search engine popular on many smart phones(Estrin, 2009). The point here is that innovation is not a wholly predictable endeavor and hiring for an unpredictable endeavormay require a more abstract talent acquisition approach — sometimes an organization must simply hire experts who have anovel approach and allow them to explore ideas.

Fortunately there is a balance to be struck between predictability and unpredictability in facilitating innovation. Mumford andcolleagues (Mumford et al., 2008) suggest that when planning for innovation, projects should be built around key problems thatare broadly framed and span an organization's infrastructure (Hughes, 1989). This is nicely illustrated in DuPont's success in de-veloping synthetic fibers — a decision made after carefully considering whether it would be fruitful to pursue polymer chemistry(Hounshell & Smith, 1988). The decision was made, in part, because a pursuit of the fundamental would contribute to a number ofproduct areas the organization was already invested in. The use of fundamentals, moreover, allows for projects to have commoninfrastructure and therefore utilize similar types of talent. Apple's innovative progression from iPod to iPhone to iPad is a usefulillustration— although the projects varied substantially, there was common scaffolding among products that allowed the compa-ny to scale relatively rapidly from one to the next. From a selection standpoint, this approach gives clues as to what types of talentmay fit within the broader project portfolio. In considering our Google example above, although there was no current use for thevoice recognition software engineers, the organizational decision maker certainly knew that this talent would contribute to thebroader Google project portfolio (Estrin, 2009).

Along similar lines, it will be useful for decision makers to bear in mind that several KSAOs may be improved through devel-opmental experiences and training. Creativity training, for example, has been shown to produce positive impacts on skills asso-ciated with idea generation (Rose & Lin, 1984; Scott, Leritz, & Mumford, 2004; Wang & Horng, 2002). Thus, depending on theneeds of the organization, selection approaches may focus on acquiring employees with more stable traits associated with

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creative performance, while aiming to develop more malleable skills and knowledge in those employees once they are hired. Incontrast, organizations that need creative production quickly may choose to hire employees with a proven set of KSAOs.

One final note regarding a long-term selection strategy is that it may be useful to develop differentiated, albeit coordinated,selection systems for the various creative processes necessary for innovative success (Hunter et al., 2011). That is, it may proveviable to focus hiring efforts on a subset of individuals who provide KSAOs in early stage creative processes and an additionalsub-set of individuals who provide KSAOs in later stage implementation processes. This selection strategy requires careful consid-eration of organizational goals as well as a strong commitment by organizational leaders to continually integrate efforts amongthese groups of employees. As the desire for innovative talent grows, however, this approach may increase in use and popularity.

6. Summary and concluding comments

This manuscript makes at least two primary contributions to the literature on organizational innovation and selection. First,we have highlighted the challenges inherent to capturing creative performance criteria and offered strategies for addressingthese challenges. In doing so, we believe greater progress can be made in gathering more accurate assessments of creative out-comes. A richer criterion base has significant implications for understanding and validating current predictors of innovation aswell as those yet to be developed. For scholars, this highlights an important area of study to not only develop, but refine and val-idate measures of creativity for the purpose of hiring and performance appraisal. For practitioners, this presents a point of cautionto ensure that those responsible for assessing creative performance review their assessment procedures and determine if the wayin which performance is being assessed is accurately capturing creative work.

The second primary contribution of the present effort is the consideration of KSAOs predictive of creative performance.Although other reviews exist (e.g., Barron and Harrington, 1981; Hovecar, 1981; Mumford & Gustafson, 1988) none of these effortsfocused on selection, specifically. Given the critical role hiring plays in organizational success, such a discussion appears warranted.Along these lines, this manuscript represents an updated summary of the individual factors necessary for creative performance —

a summary that is currently lacking in the selection literature. The growing interest in facilitating innovation, moreover, suggeststhat such a summary will be useful to both researchers who study innovation in work contexts and practitioners seeking to acquirecreative talent as part of their overall innovation strategy. Finally, following our discussion on KSAOs we have offered some sugges-tions regarding tools, techniques, and methods for acquiring predictor data.

6.1. Theoretical contributions

In addition to these two primary contributions, the present effort makes several theoretical contributions to the study of cre-ativity and innovation as well. First, consistent with scholars such as Mumford and Gustafson (1988) we have proposed a “crea-tive potential” conceptual framework for viewing individual-level antecedents of creative performance. As scholars have recentlysuggested, there is an overemphasis on qualities such as divergent thinking whereby such attributes can be viewed as the primarydriver of creative achievement (Runco, 2008). We have suggested that it is the aggregate of these qualities that better representscreative potential. A second theoretical contribution, congruent with scholars such as Austin and Villanova (1992), is that we haveproposed an expanded criterion space for creative performance. That is, to more fully understand why innovation occurs we sug-gest that a consideration of the range of activities will lead to a richer understanding of the processes involved in facilitating cre-ative outcomes. This will, in turn, allow us to more accurately target qualities to predict the various forms of performance therebyincreasing overall validity and predictive ability.

6.2. Limitations and future directions

Before turning to the broader conclusions of the present effort, several limitations should be noted. First, space constraints lim-ited the potential discussion of alternative KSAOs. Although an attempt was made to be as comprehensive as possible, not all pre-dictors were discussed and, as such, stands as a limitation of the manuscript. Along similar lines, although we provided the readerwith some guidance on the rank order of possible predictors, such a list stands as an early set of propositions rather than a defin-itive set of rules for choosing a predictor set. We do feel, however, that there is reasonable guidance for beginning to build a se-lection system aimed at increasing creative performance.

Perhaps most critically, it is important for the reader to bear in mind that a number of contextual moderators exist that mayinfluence the utility of the predictors discussed in this manuscript. As depicted in the model, a creative climate low in psycholog-ical safety, for example, may dictate whether thick-skinned personality traits (e.g., low on agreeableness) are required for inno-vation. In contrast, a climate or context that embraces novel thinking may require an alternative set of dispositions (George &Zhou, 2001). Work on participative and psychological safety, in particular, suggests that such environments are critical to maxi-mizing creative potential (Edmondson, 1999; Hunter et al., 2007; West, 2002). Additionally, the creative capacity of the leadermay directly impact the success of creative endeavors. For instance, a leader responsible for giving the approval on the creativework of his or her team that is not skilled in idea evaluation would underestimate the potential contribution of the original ideaand limit the potential success of the idea. Zhou (2003), for example, found that supportive supervision and the presence of cre-ative colleagues interacted with creative personality to ultimately influence creative performance. Thus, special attentionshould be paid to the broader organizational and environmental context when choosing a predictor set aimed at increasing cre-ative and innovative performance.

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6.3. Concluding comments

The aggregate of the present effort reveals a number of broader points that appear worthy of discussion. First, creative perfor-mance is an elusive construct and an attempt to apply traditional performance assessment techniques to capture it as a criterionwill prove problematic. Instead, we must be cognizant of what creativity entails and, excuse the expression, be creative in our ap-proach to gathering outcome data. This realization has a number of implications for how we approach appraising creative perfor-mance and stands as an interesting area for future research.

The present effort also reveals that creative performance is likely to be facilitated by a number of predictors ranging quitebroadly across the KSAO spectrum. As scholars we have, at times, overemphasized creative personality and divergent thinkingability as the sole predictors of creative performance. Thus, as Mumford and Gustafson (1988) concluded, creativity is indeed asyndrome and requires a broader, multivariate approach in a selection context. Moreover, as we expand our predictor set, inter-play among creative predictors also stands as an interesting and important area for future research.

Congruent with the interactionist theme, the discussion on contextual moderators reveals that caution is warranted in blindlyapplying a host of tools to predict creative performance — better known, perhaps, as the “shotgun” approach. Instead, care is nec-essary in assessing the current environment as well as the goals of the selection system. For example, an organization with a his-tory of rigidity and emphasis on cost efficiency seeking to become innovative may need to hire employees with personality traitsthat facilitate fighting against norms. In contrast, an organization that has an established record of innovation and places greatemphasis on teamwork and collaboration may choose to emphasize creativity specific skills and abilities, avoiding some of theacerbic personality traits associated with innovation in caustic environments.

Additionally, organizations must not forget the key role that recruitment plays in building the base of creative talent and en-suring variability in the selection pool. The discussion on contextual moderators reveals that context matters not only in facilitat-ing creative performance but also in attracting talent to that organization. Organizations are well served by publicizing theirapproach to innovation— particularly if their approach distinguishes themselves from other organizations competing for creativeemployees.

Finally, as much as we would like to prescribe a formula for selection, creative achievement is a messy, complex, and challeng-ing endeavor. It is not, unfortunately, akin to setting one's watch and anticipating today's creative lightning to strike. A more re-alistic approach is to establish an environment where lightning can occur by ensuring that talented individuals are interactingwith each other on a frequent basis and they have the resources around them to fully and continually pursue novel ideas. Thismay require, at times, the acquisition of talent that may not have an immediate project role but fits within the broader organiza-tional strategy and project portfolio scaffolding.

In sum, the acquisition of creative talent is an important pre-condition for creative performance. Although hiring the rightpeople is only an initial step in building an organization with innovative capacity, it is a key first step. We believe the present ef-fort will help organizational decision makers and researchers better pursue this critical endeavor.

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