Key Characteristics of Effective and Ineffective Developmental Interactions

Key Characteristics of Effective and Ineffective Developmental Interactions Erik R. Eddy, Caroline P. D Abate, Scott I. Tannenbaum, Susan Givens-Skeaton, Greg Robinson Ongoing learning may be one of the few sustainable competitive advantages for organizations. Historically, research efforts and organizational resources have been primarily directed toward understanding and enhancing learning in formal settings, as in classroom training. Yet most learning at work occurs through more informal means. This research sought to enhance our understanding of informal learning by studying effective and ineffective developmental interactions between two individuals. Capturing stories and using a participant-guided qualitative coding process, the research explored factors that had an impact on the effectiveness of developmental interactions and whether those factors worked differently depending on the topic of the interaction (career advice, work-life support, or job or task guidance). Results suggest that several personal and relationship factors influenced developmental interaction effectiveness, but communication factors had no impact. Furthermore, with just a few exceptions, these same factors were important across all three topics explored in this research. The success of any organization relies in great part on the talent of the people comprising that organization. Many leaders recognize that in order to compete effectively, they must take actions that ensure the ongoing learning and development of their employees. Historically, most organizational resources directed toward employee development have been allocated to formal, structured learning experiences such as classroom training and, more recently, computer-based training (Tannenbaum, 2002). Yet research has shown that formal training accounts for less than 10 percent of employee learning (Tannenbaum, 1997). Increasingly, companies recognize that their employees will and should acquire HUMAN RESOURCE DEVELOPMENT QUARTERLY, vol. 17, no. 1, Spring 2006 Wiley Periodicals, Inc. Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/hrdq.1161 59

60 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson much of their expertise through interactions with others. These can be planned interactions such as mentoring programs or coaching assignments or more naturally occurring interactions with other people such as informal advice giving. The human resource development field recognizes the importance of employee development. The field has a rich, productive history of examining the crucial factors involved in successful employee development through structured programs (Goldstein, 1993; Salas & Cannon-Bowers, 2000) and more recently through planned interactions such as mentoring. Overall, however, our understanding of structured learning is far greater than our understanding of more informal learning. Since informal learning accounts for a greater share of learning in organizations than formal learning, this study focuses on a prominent informal learning opportunity that we term developmental interactions. Developmental interactions refer to interactions between two individuals with the intent of enhancing personal development or growth. They may address a variety of personal or professional topics, such as career advice, work-life support, and job or task guidance and involve individuals we refer to as advisers and advisees who respectively give and receive developmental advice. Developmental interactions are not limited to the traditional model of one mentor who guides and sponsors a lower-level protégé (D Abate, Eddy, & Tannenbaum, 2003; Douglas & McCauley, 1999; Higgins, 2000; Higgins & Kram, 2001). Several researchers have demonstrated the potential benefits of effective one-on-one developmental interactions, while others have warned about the potential risks associated with poorly handled interactions (Eby, McManus, Simon, & Russell, 2000; Scandura, 1998). Because developmental interactions have the potential to enhance or hinder both personal growth (for example, increased knowledge, career advancement) and organizational goals (for example, enhanced performance, increased employee retention), the goal of the research examined here was to understand these interactions better. The primary purpose of this study therefore was to identify the factors that differentiate effective and ineffective developmental interactions. In this regard, the study seeks to advance our knowledge in several ways. First, it explores three broad categories of factors (personal, relationship, and communication) hypothesized to differentiate effective and ineffective developmental interactions. Prior research has examined some of these factors in mentoring relationships, but this study extends that research by examining a broader range of developmental interactions beyond mentoring. Second, although experts have proposed the importance of many personal factors (such as gender and age), relationship factors (such as voluntary participation in the relationship), and communication factors (such as mode of communication) on developmental interactions, to our knowledge, little research exists to confirm these assertions. Our research empirically tests some of these assertions. Third, this research contributes to the literature by taking a different data-gathering

Key Characteristics of Effective and Ineffective Developmental Interactions 61 approach: capturing stories in a way that avoids sensitizing participants to the research questions and following up with structured interviews to quantify their responses. A secondary purpose of this study was to explore the importance of these personal, relationship, and communication factors across three common topics of developmental interactions: career advice, work-life support, and job or task guidance. We explored whether various factors are more or less important depending on the topic of conversation. This portion of the study was exploratory in nature. Developmental Interaction Effectiveness In recent years, scholars have expanded the conceptual framework of developmental interactions to include multiple forms of employee development. This extended literature has recognized that there are multiple forms of development as sources of social support, such as mentoring and coaching; multiple topics of the developmental interactions that can occur, such as career advice and work-life support; and numerous factors that may contribute to development (Higgins, 2000; Higgins & Kram, 2001; Higgins & Thomas, 2001). Two conceptual models have emerged that pertain to the research examined in this article. One is the conceptual framework that expands our understanding of what is provided by developers or advisers. It takes us beyond the functions of mentoring, such as career and psychosocial functions, as established by Kram (1985) to recognize that other functions may also be served. In essence, developmental interactions can provide advice on one s career, provide support for work-life balance issues, and offer guidance for a specific job or task. Eby (1997) provided a typology of alternative forms of mentoring to delineate two of these topics. Breaking developmental activities into career-related and job-related skill development, her model suggests that organizations can use alternative forms of mentoring to provide career and job development. Although her model does not take into account the support for work-life issues that is often described in the mentoring literature as psychosocial support, she does recognize that struggling with family issues can be one area where a mentor can provide assistance (p. 137). Two other authors provide a foundation for the inclusion of work-life support as a topic of development. Higgins (2000) suggests that social support is necessary for coping with work-life stress, and McManus and Russell s nomological network of constructs (1997) related to mentoring suggests that social support can have an effect on experienced stress. The contributions of these theorists create a need to examine how developmental interactions can offer support, guidance, or advice on three topics: career, work-life, and job and task. Also grounding the research examined here is a conceptual framework suggesting that various factors can affect the success of developmental

62 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson interactions. We have labeled these factors the personal, relationship, and communication factors. Specific research findings are detailed below, but it is first important to explore the theoretical rationale for these groupings of variables. Higgins and Kram (2001), for example, offer a framework of factors contributing to developmental networks. They suggest that work environment factors such as workforce composition, technology availability, e-mail use, industry, and task; individual factors such as personality, demographics, perceived need for development, and past experiences with development; and moderating factors such as interaction style, position or power of the person giving development, orientation toward development, and emotional competence can impact development. Burke and McKeen (1997) also suggest that personal, situational, and process factors can affect mentoring, and Eby s typology (1997) points to a number of factors that can be important to mentoring and development, including protégé and mentor characteristics, types of protégés who engage in job- or career-related development, and organizational conditions. These prior studies highlight the importance of understanding how various factors affect mentoring and developmental interactions and provide insight into how best to cluster potential factors. Potential Factors That Influence Developmental Interaction Effectiveness. Prior theory and research suggest that personal, relationship, and communication factors may contribute to the effectiveness of developmental interactions. Although there are many ways to conceptualize interaction effectiveness (for example, achieving organizational or adviser goals), our research uses one of the more common conceptualizations of effectiveness: advisee perceptions of interaction value (Kram, 1986). Therefore, an interaction is deemed effective when the advisee perceives that it was useful, valuable, and satisfied a need. A summary of the factors examined in our research is set out in Table 1. A review of the literature suggests that gender, age, and other personal factors are important in maintaining successful developmental interactions (Burke & McKeen, 1997; Gray, 1988; Kalbfleisch & Davies, 1993; McDougall & Beattie, 1997; Murray, 1991; Noe, 1988; Ragins, 1997). For example, one could argue that individuals may be better able to relate to advisers who are more similar to themselves and thus may gain more from working with a coach or mentor of similar gender or ethnicity. However, research findings in this area have been mixed. For instance, research on goal setting finds that age was not related to performance (Ivancevich & McMahon, 1977; Latham & Marshall, 1982) while mentoring researchers find that age is a weak predictor of amount of mentoring provided (Dreher & Ash, 1990). Similar mixed results are found in exploring race (Blake-Beard, 2001) and gender (Whitaker, 2000). Other researchers suggest that demographic variables are not as important as the structural position that individuals hold within the organization (McGuire, 1999). We examine the premise that adviser-advisee similarity influences interaction effectiveness by testing the following hypotheses:

Key Characteristics of Effective and Ineffective Developmental Interactions 63 Table 1. Potential Factors Bearing on Developmental Interaction Effectiveness Personal factors Demographics Adviser style Adviser focus Adviser expertise Relationship factors Initiation of relationship Choice in participation Frequency and duration Time known Source of relationship Communication factors Location Primary mode Ethnicity, gender, and age of the participants The manner in which the adviser gives advice either directive or encouraging self-discovery Whose needs and interests the adviser is focused on: his or her own, the advisee s, or the organization s The adviser s expertise in the area needing development Who initiates the interaction Whether participation in the interaction is voluntary How often the participants meet and how much time they spend together How long the adviser and advisee have known each other Whether the adviser is an organizational superior, family friend, peer, or professional colleague Whether the interaction takes place face-to-face or at a distance The medium used for the developmental interaction (telephone, e-mail, or face-to-face conversation) HYPOTHESIS 1a. Similarity of advisee and adviser age will be positively related to interaction effectiveness. HYPOTHESIS 1b. Similarity of advisee and adviser gender will be positively related to interaction effectiveness. HYPOTHESIS 1c. Similarity of advisee and adviser race will be positively related to interaction effectiveness. With regard to other personal factors such as adviser style, focus, and expertise, research from the leadership literature suggests that in coaching relationships, encouraging self-discovery may be more beneficial than being directive (Yukl, 1994). Research on training suggests that making the training relevant to the individual s needs, interests, and ambitions (analogous to focusing on the advisee s needs) should enhance the likelihood of success (Yukl, 1994). Our study empirically examines the potential relationship between adviser characteristics and the effectiveness of developmental interactions. Specifically, we propose the following hypotheses regarding adviser characteristics:

64 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson HYPOTHESIS 2a. Perceptions of adviser expertise will be positively related to developmental interaction effectiveness. HYPOTHESIS 2b. An adviser focus on advisee needs (rather than organizational needs or the adviser s own needs) will be positively related to developmental interaction effectiveness. HYPOTHESIS 2c. An adviser who encourages self-discovery will be positively related to developmental interaction effectiveness. The effectiveness of a developmental interaction may also be influenced by the nature of the relationship between the adviser and advisee. Table 1 suggests that whether the advisee can choose to participate, who initiates the interactions, the frequency and duration of the interactions, the time the participants have known each other, and the source of the relationship (for example, supervisor-subordinate) may influence interaction effectiveness. For instance, research suggests that individuals who persist in their efforts are more likely to reach their goals (Locke & Latham, 1990). This study attempts to confirm the potential value of more frequent, ongoing interactions and the potential benefits of nonhierarchical sources of advice (Ensher & Murphy, 1997; Geiger-DuMond & Boyle, 1995). We also provide an empirical look at the often stated, but rarely tested, advantages of voluntary or self-initiated participation in developmental interactions (Gaskill, 1993; Murray, 1991) over mandated interactions. In addition, we provide an exploration of whether there are added benefits of developmental discussions among people who have known each other for an extended time (Chao, Walz, & Gardner, 1992). Specifically, we propose the following hypotheses regarding the relationship between adviser and advisee: HYPOTHESIS 3a. Self-initiated or mutually initiated developmental interactions will be perceived as more effective than interactions initiated by a third party. HYPOTHESIS 3b. Voluntary developmental interactions will be perceived as more effective than mandatory developmental interactions. HYPOTHESIS 3c. The length of time that an adviser and advisee have known each other will be positively related to developmental interaction effectiveness. HYPOTHESIS 3d. Frequency and duration of developmental interactions will be positively related to developmental interaction effectiveness. HYPOTHESIS 3e. The source of the relationship ( for example, peer, family friend) will be an important factor in determining developmental interaction effectiveness. E-mail, company intranets, text messaging, videoconferencing, and other advancements in technology have enhanced the ability to communicate at a distance. Individuals regularly interact with members of their organization or

Key Characteristics of Effective and Ineffective Developmental Interactions 65 other organizations in a different office, state, or even country. These technological advancements have allowed a new form of advising to develop termed distance advising. As shown in Table 1, the relative location of the adviser and the communication mode are two factors that may bear on the success of developmental interactions (Rutter, 1987; Sullivan, 1995). Prior research findings suggest that interactions conducted face-to-face may be more effective than those conducted at a distance, particularly for work-life discussions (Gallupe, Bastianutti, & Cooper, 1991). This study considers the effects of advanced technology on developmental experience by examining whether the effectiveness of interactions is related to the location of participants (same or distance) or their primary communication mode (for example, telephone or e-mail) for the three developmental topics. Specifically, we suggest the following hypothesis regarding communication: Hypothesis 4. Face-to-face developmental interactions will be perceived as more effective than developmental interactions that occur at a distance. Common Topics of Developmental Interactions. A secondary purpose of this research was to explore whether the importance of the factors described in the hypotheses varies by topic of discussion. People may engage in developmental interactions for several reasons. A developmental interaction may focus on the topic of career development (Scandura, 1997), psychosocial or work-life support (Seibert, 1999), or job or task development (Gaskill, 1993). No a priori hypotheses are presented because this portion of the research is exploratory in nature. Career advice can cover a broad range of issues. For example, an advisee may seek guidance from an adviser regarding which assignments to take to reach a certain level within the organization, the best way to progress along a specific career path, or the key people to network with to advance his or her career. Sponsorship, exposure, and visibility are all career-related functions that an adviser can provide in the interests of improving the advisee s opportunities to advance within the organization, enhancing job satisfaction, and improving organizational commitment (Kram, 1985; Noe, 1988; Ragins, 1997; Scandura, 1997; Scandura & Schriesheim, 1994). Work-life support also covers a range of issues. Coping with stress or job pressure, balancing work and family demands, preparing for or adjusting to a new geographical location, coping with a difficult boss or colleague, or simply providing encouragement or friendship are all examples of this topic of advice. Psychosocial support in the form of acceptance, confirmation, counseling, and friendship enhances a sense of competence and can clarify a sense of identity for the advisee (Kram, 1986). These forms of support are also positively related to job satisfaction, self-esteem, career expectations, and organizational commitment (Scandura, 1997; Seibert, 1999).

66 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson Job- or task-specific advice includes issues such as receiving guidance, instruction, or advice on how to perform a specific task on the job or how to perform a task more effectively. Interestingly, job and task support (sometimes referred to as transfer of expertise) has received little empirical attention. However, a factor analysis by Steinberg and Foley (1999) identified task support as important in mentoring relationships. Specifically, career development, psychosocial support, and job coaching were found to be the three functions that account for 95 percent of mentoring behaviors (Steinberg & Foley, 1999). Our research examined these three common developmental topics and explored the factors associated with their effectiveness. Method Data was gathered using a structured interview technique. The following sections provide more detailed information on the study design, data gathering procedures, participants, and measures. Design and Procedure. Structured interviews were used to capture stories of effective and ineffective career, work-life, and job- and task-related developmental interactions, employing a 2 (effectiveness) 3 (topic) factorial design. The within-subjects factor was effectiveness (effective and ineffective interactions), and the between-subjects factor was topic of interaction (career advice, work-life support, job or task guidance). Four trained interviewers conducted interviews with eighty-one participants either by telephone or face-to-face. Each participant was asked to describe two developmental experiences one effective and one ineffective for one of the three topics of career advice, work-life support, or job or task guidance. The order of request was counterbalanced, such that half the interviewees were first asked about effective interactions. Participants were asked to identify two specific developmental interactions (one they perceive as effective, the other as ineffective). They were given as much time as they required to identify these experiences and were asked to state who each interaction was with and to note when they were ready to discuss both interactions. They were then asked to tell a story about each experience to the interviewer. The story provided preliminary information about the developmental interactions prior to exploring the details of each experience. By asking participants to describe both stories in their own words before probing about specific research factors, we avoided sensitizing respondents to the factors being studied. Data Preparation. Data were prepared by using qualitative and quantitative data-gathering techniques in an integrative manner. The interviewer took notes while the interviewee told his or her story about each developmental interaction. Then the interviewer followed up using a structured interview protocol to review the story with the participant. The interview contained several forced-choice and scaled items that quantified information (the key personal,

Key Characteristics of Effective and Ineffective Developmental Interactions 67 relationship, and communication factors) from the story (see the appendix for a sample protocol). For any factors that were clearly described during the story, the interviewer confirmed the coding with the participant to ensure his or her understanding was consistent with the interviewee s perception of the interaction. For example, if during the story a participant said, This interaction was with a supervisor who I currently work with, the interviewer would confirm the coding: So you mentioned that the person in this story was your direct supervisor. If the interviewee did not provide specific information about a factor, the interviewer asked the participant a direct question to gather the information; for example, the interviewer would ask, How long had you interacted with this person prior to the interaction you described? The open-ended portion of the interview allowed the participant to provide an unfiltered, unsensitized description of the interaction. The structured portion of the interview helped avoid a potential concern with qualitative data collection where during the coding process the interviewer attempts to infer, perhaps inaccurately, what the participant meant. The transition from qualitative information to quantitative data was built directly into the data collection process. As a result, we refer to this method of gathering and preparing data as a participant-guided qualitative coding process. The initial protocol was pilot-tested with ten interviewees to identify unclear or ambiguous items. Pilot data also highlighted a number of issues that had been overlooked in the initial protocol. For instance, phrasing of questions was clarified, and more appropriate response alternatives were added. The protocol was revised to ameliorate these ambiguities. Because we wanted to ensure the effectiveness of this unique data-gathering process, a second pilot test with ten different interviewees was conducted. This second test verified the appropriateness and clarity of the final interview protocol. Participants and Measures. Using the structured interview protocol items set out in Table 2, we collected data from eighty-one individuals across both effective and ineffective types of interactions for a total of 162 response sets. The target population consisted of individuals who had experienced effective and ineffective developmental interactions. Because organization culture can often influence perceptions of interaction effectiveness, we decided not to collect data from a single organization. Rather, a purposive (Stone, 1978) and referral (Welch, 1975) sample of eighty-one individuals provided information on both effective and ineffective developmental interactions. Individuals came from various backgrounds, worked in a variety of industries, and were limited to no particular age group, gender, or geographical location. This allowed us to study developmental interactions from diverse perspectives of people in various walks of life. The final sample consisted of eighty-one working-age adults; 38 percent were male. Thirty-two percent were between twenty and twenty-nine years old, 46 percent were between thirty and thirty-nine years old, 5 percent were between forty and forty-nine years old, 7 percent were between fifty and fifty-nine years old, and 10 percent were over

68 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson Table 2. Personal, Relationship, and Communication Factors Measures Factor Personal factors Relative gender Relative age Relative ethnicity Adviser style Adviser focus Adviser expertise Question Presented and Response Alternatives What is the relative gender of adviser and advisee? Alternatives were same as mine, different from mine, and do not know. What is the relative age of adviser and advisee? Alternatives were younger than me, about the same as me, and older than me. What is the relative ethnicity of adviser and advisee? Alternatives were same as me, different from me, and do not know. What was the style of the advice giver while you discussed this particular issue? Alternatives were mostly directive, mostly encouraged self-discovery, and a mix of directive and encouraging. Respondents were asked to rank-order whose needs and interests were the adviser s focus. Alternatives were, mine, theirs, and the organization s. What was the expertise level of the advice giver in the area you needed help? Alternatives were little or no expertise, some, extensive, and do not know. Relationship factors Initiation of relationship Choice in participation Frequency Duration Source of relationship Time known Communication factors Location Primary mode Who initiated the conversation? Alternatives were self-initiated, initiated by advice giver, third-party initiated, and mutually initiated. How did you choose to participate? Alternatives were voluntary, voluntary but strongly encouraged, and required/mandatory. How many times did you interact with this advice giver to discuss this particular issue? Alternatives were one time, two to four times, and five or more times. How long did this advice giver serve as a source of advice for this particular issue? Alternatives were less than one month, one to six months, six months to one year, and more than one year. Who was this advice giver in this experience? Alternatives were supervisor, subordinate, friend/family, professional colleague, teammate at work, peer at work, and senior in my organization but no reporting relationship. How long did you interact with this person before discussing this particular issue? Alternatives were initiated with interaction, less than six months, six months to one year, and over one year. Where was the advice giver most often located when you discussed this particular issue? Alternatives were same location and at a distance. How did you most often communicate about this particular issue? Alternatives were face-to-face, phone, e-mail, and other.

Key Characteristics of Effective and Ineffective Developmental Interactions 69 the age of sixty. Most of the participants were Caucasian, with 17 percent from other ethnicities. Most participants worked in common career fields such as education, health care, journalism, law, finance, marketing, retail, and the public sector. More than twenty-four industries were represented in the sample. Results MANOVA was used to assess over effects and control for experiment error. ANOVA was used to interpret the results further. There were no meaningful differences in the pattern of results between the ANOVA and MANOVA analyses. Results from the within-subjects ANOVAs are presented. Effectiveness of interaction (effective versus ineffective) served as the within-subjects factor, and topic of interaction (career advice, work-life support, or job or task guidance) served as a between-subjects factor in the ANOVAs. Whenever a main effect for topic was discovered, post hoc comparisons using a modified Bonferroni technique were conducted. The dependent variable in each ANOVA was one of the personal, relationship, or communication-related factors. The following sections summarize results for each hypothesis and discuss the implications of these results. Test of Hypotheses. Table 3 presents the ANOVA results for the personal factors. A significant main effect for effectiveness was exhibited for adviser style (F 19.82, p.01). Post hoc analysis revealed that effective interactions were typified by an adviser style that promoted self-discovery more than one that was highly directive. The adviser s focus was also significantly related to effectiveness. Advisers in effective interactions were more likely to focus on the advisee s needs (F 92.09, p.01) and less likely to focus on the adviser s needs (F 59.25; p.01). There was no effect for focus on the organization s needs. Advisers in effective interactions were viewed as possessing greater expertise about the issue (F 44.68; p.01). These findings support hypotheses 2a, 2b, and 2c. Interestingly, no significant results for effectiveness were exhibited for any of the gender, age, or ethnicity variables (hypotheses 1a, 1b, and 1c). Table 4 contains the ANOVA results for the relationship factors. No main effects for effectiveness were exhibited for self-initiated or adviser-initiated interactions. However, a main effect did emerge for third party initiated (F 3.00, p.10) and mutually initiated (F 4.92, p.05) interactions. Post hoc analysis revealed that effective interactions were more likely to be mutually initiated and less likely to be initiated by third parties, partially supporting hypothesis 3a. Choice was significantly related to effectiveness (F 10.94, p.01), such that ineffective interactions were rated more mandatory than were effective interactions, supporting hypothesis 3b. Effective developmental experiences were based on more frequent interactions (F 15.61; p.01) that occurred over a longer duration (F 3.71; p.10). However, the length of time the advisee had known the adviser was not significantly related to

Table 3. Results of ANOVA for Personal Factors F-Values Main Effect Cell Means a Effectiveness Topic Main Effect: Main Effect: Effectiveness Topic Interaction Effective Ineffective Career Job or Task Work-Life Relative Gender b.52.78.52.65.61.67.67.56 Relative Age of Adviser.84 1.11 1.95 2.57 2.64 2.67 2.48 2.67 Relative Ethnicity b 1.59 2.30.40.86.82.93.74.85 Adviser Style 19.82*** (.21).25 1.03 2.31a 1.66a 2.02 2.02 1.92 Adviser Focus Advisee s needs 92.09*** (.55) 3.95* (.10) 1.12 1.38a 2.40a 1.73b 2.10b 1.83 Adviser s needs 59.25*** (.47).63 1.16 2.54a 1.61a 2.14 2.09 2.00 Organization s needs.31 1.39.15 1.94 1.87 2.05 1.75 1.92 Expertise of Adviser 44.68*** (.37) 1.29.72 2.64a 1.97a 2.23 2.44 2.25 Note: Numbers in parentheses are effect sizes (eta 2 ). Means for adviser focus are average rank-ordered (1 highest, 3 lowest). a Letters indicate that two means in that row are statistically significantly different from each other. b Dummy coded variable: different 0, same 1. * p.10; ** p.05; *** p.01.

Table 4. Results of ANOVA for Relationship Factors F-Values Main Effect Cell Means a Effectiveness Topic Main Effect: Main Effect: Effectiveness Topic Interaction Effective Ineffective Career Job or Task Work-Life Initiator of Interaction Self-initiated b 2.12 8.35*** (.18).13.54.44.59a.26ab.63b Third party b 3.00* (.04) 6.70*** (.15).00.06c.14c.01a.22ab.01b Adviser initiated.20 2.87* (.07).30.84.82.89.72.87 Mutually initiated b 4.92** (.06) 10.55*** (.21).10.64c.49c.67a.32ab.72b Choice (Mandatory 10.94*** (.12) 25.56*** (.40) 3.01* (.07) 2.47c 2.16c 2.54a 1.69ab 2.72b or Voluntary) c Frequency of 15.61*** (.17).91.11 2.35a 1.95a 2.09 2.28 2.07 Interactions Duration of Interaction 3.71* (.05).07 1.33 2.08a 1.80a 1.89 1.98 1.94 Source of Relationship Direct supervisor 4.10** (.05) 2.43* (.06) 2.16.41a.55a.44.61.39 Family or friend 1.12 3.65** (.09).49.18.13.17.03a.24a outside organization Professional colleague.09.60 (.02).09.09.08.12.07.06 outside organization Peer or teammate at work 1.93.97 (.02) 2.21.17.11.10.20.13 Superior, no reporting.07 1.30 (.03) 3.39** (.08).14.15.17.07.19 relationship Time Adviser Known.16 9.81*** (.20) 1.02 3.07 3.01 3.32a 2.48ab 3.33b Note: Numbers in parentheses are effect sizes (eta 2 ). a Letters indicate two means in that row are statistically significantly different from each other. b Dummy coded as 0 No, 1 Yes. c Mandatory 1; voluntary but strongly encouraged 2; voluntary 3. * p.10; ** p.05; *** p.01.

72 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson effectiveness. Ineffective interactions were more likely when a direct supervisor was involved (F 4.10; p.05). Therefore, hypotheses 3d and 3e were supported, but hypothesis 3c was not. Table 5 contains the results of the ANOVAs for the communication factors. As shown in Table 5, the data failed to provide evidence to support hypothesis 4. Neither location nor method of communication was significantly associated with the effectiveness of the interaction. These findings suggest that in effective interactions, advisers focused on advisee needs and were more likely to have encouraged self-discovery and less likely to use a controlling, directive approach. Effective interactions were also most often voluntary and based on more frequent interactions over a longer period of time. Furthermore, an effective interaction was more likely to involve a knowledgeable adviser and less likely to be conducted by a direct supervisor. Interestingly, the length of time that the adviser and advisee knew each other was not significantly related to effectiveness, nor was demographic similarity. Collectively this suggests that advisees should seek the most knowledgeable advisers and not default to their supervisor, the people they know best, or the people most like themselves. Effective interactions are also typified by more frequent interactions that occur over a longer period of time. In fairness, it is unclear whether greater contact makes interactions more effective or whether more effective interactions encourage ongoing contact. In any case, the results suggest that advisers and advisees should not expect that isolated, one-time interactions will resolve all developmental needs. Additional Analyses. The exploratory portion of our research examined whether the importance of personal, relationship, and communication factors varied across the topic of interaction. Personal factors associated with topics of developmental interactions are presented in Table 3. A main effect for topic was exhibited for focus on advisee needs (F 3.95; p.10). Developmental interactions that addressed job and task issues were less likely to focus on the advisee s needs than those that addressed career-related issues. All other personal factors were not significantly related to the topic of the interaction. As shown in Table 4, several relationship variables exhibited main effects for topic. Job- and task-related interactions were less likely than either careeror work-life-related discussions to be self-initiated (F 8.35; p.01), mutually initiated (F 10.55; p.01), or voluntary (F 25.56; p.01) and more likely to be third party initiated (F 6.70; p.01). Job or task interactions were also more likely to be conducted by an adviser who was known for a shorter length of time (F 9.81; p.01). Friends and family members were more likely to provide work-life advice than job or task advice (F 3.65; p.05). A main effect for topic was also exhibited for direct supervisor interactions, but post hoc analyses did not reveal any statistically significant differences. Finally, as shown in Table 5, neither location nor method of communication was significantly associated with the topic of the interaction.

Table 5. Results of ANOVA for Communication Factors F-Values Main Effect Cell Means Effectiveness Topic Main Effect: Main Effect: Effectiveness Topic Interaction Effective Ineffective Career Job or Task Work-Life Location (same or other).06 2.29.40 1.17 1.16 1.26 1.09 1.15 Primary Mode Face-to-face.18 2.21.63.81.84.74.90.83 E-mail.18.81.79.04.03.06.02.02 Telephone.18.81.79.96.98.94.98.98 * p.10; ** p.05; *** p.01.

74 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson As shown in Tables 3 and 5, no significant interaction effects were exhibited for any of the personal or communication factors. However, Table 4 demonstrates evidence of significant interaction effects for some of the relationship factors. An interaction effect was found for choice (F 3.01; p.10), suggesting that choice may be most influential in determining the effectiveness of job or task discussions, which tend to be more mandatory than either career or work-life discussions. Although sometimes the adviser must be quick and directive, we speculate that in some cases, advisers should be able to approach the advisee in such a way that it conveys that the conversation is mutually initiated. For example, asking an employee who is struggling on a project, Would you like to discuss the project? can convey a different message from, I want you to come to my office to discuss the project. An interaction effect was also exhibited for superiors to whom the advisee does not report (F 3.39; p.05). A post hoc analysis of cell means suggests that effective developmental conversations with this type of leader were more likely to be for job or task issues, and ineffective developmental interactions were more likely to be about work-life issues. These findings suggest that job- and task-related discussions exhibited a different set of characteristics than did work-life or career-related discussions. Job- and task-related discussions were less likely to be self-initiated or mutually initiated and more likely to be third party initiated. These discussions were also more likely to be considered mandatory. Interestingly, many of the characteristics commonly found in job or task interactions were also found in less effective interactions, highlighting the difficulty of conducting an effective job- or task-related discussion. With the exception of the choice interaction and one related to superiors in the organization, we found no differences in what makes a developmental interaction about one topic more effective than an interaction about another topic. For the most part, it appears that a common set of factors is related to the effectiveness of developmental interactions, regardless of the purpose of the interaction. Discussion This study examined a common and important yet understudied phenomenon we call developmental interactions. It helped clarify our understanding about which factors differentiate effective from ineffective interactions. The results confirmed some generally accepted assumptions and provided a few less intuitive findings. For example, the study confirmed the importance of the perceived expertise of the adviser, the value of multiple interactions, and the benefit of focusing on the advisee s rather than the adviser s needs. Somewhat more surprising were the findings that time known and adviser-advisee similarity were unrelated to effectiveness, that job and task interactions

Key Characteristics of Effective and Ineffective Developmental Interactions 75 possessed the most challenging characteristics, that supervisor interactions were often less effective, and that focusing on the organization s needs along with the advisee s needs was not detrimental. The results of this study appear to be readily interpretable and lead to several recommendations for advisers, advisees, and organizations to enhance developmental interactions. The study also has implications for HRD research. Implications for Practice. The findings from this study provide several clear ideas about how individuals and organizations can increase the likelihood that their developmental interactions will be effective. We can begin with advice for advisers. Given the magnitude of the effect for selfdiscovery, advisers should encourage advisee self-discovery rather than being highly directive. One interviewee noted, He asked me questions about my experiences and got to know me. He didn t give me the answer. Another interviewee noted that it was critical to make sure to let the advisee know that the decision is theirs. Others shared negative reactions to overly directive advisers. As one interviewee put it, the adviser told me what to do and completely missed what I needed.... I ignored his advice out of frustration. As a general guideline, advisers should start with the goal of self-discovery, using a directive approach only if self-discovery is not working or safety or other urgency requires immediate direction. Furthermore, when possible, the adviser should frame the developmental interaction to be voluntary and mutually initiated; for example, asking, Would you like to discuss the new task you ve been working on? will appear more voluntary than, You need to meet with me to discuss the new task. Naturally some developmental interactions should be mandatory. Advisers should recognize that these may be more challenging and prepare accordingly. As a result, mandatory developmental interactions may be particularly important times to encourage self-discovery. Advisers should convey that they are focused on the learner s needs and not their own needs. Interestingly, our research suggests that advisees will find it acceptable for the adviser to represent the organization s needs along with the advisee s needs. However, the interaction is less likely to be effective if the learner perceives that the interaction is primarily about the adviser s needs. One interviewee related a time when her adviser inquired how I would feel and how I would deal with being overburdened with work. He didn t appear to be biased. He approached it like he was looking for what was best for me. This focus on advisee needs can enhance the probability that advice will be accepted. Finally, given the findings about frequency and duration, advisers should try to be accessible for multiple conversations over time rather than expecting a one-time fix. Whenever possible, advisers should follow up with advisees to assess progress, allow them to share any self-discoveries, and assess if they have additional questions or need further advice.

76 Eddy, D Abate, Tannenbaum, Givens-Skeaton, Robinson Advisees can also enhance the quality of their developmental interactions. For instance, advisees should seek advisers with relevant expertise and not simply someone they have known for a long time or someone with similar characteristics. Although she was a long-time friend, one interviewee notes, she really didn t understand the situation... she just agreed with whatever I said and didn t offer any new perspective. Advisees should jointly work with potential advisers to identify opportunities to discuss developmental issues. Finally, advisees should actively seek out people who can provide advice and feedback and serve as a sounding board, not relying on their supervisor as the sole source of development. Similar to the advice given to advisers, advisees should not expect a one-time fix: multiple conversations tend to lead to better results. In sum, advisees can benefit from being active, involved seekers and screeners of advisers, not defaulting to those advisers who are most convenient, not assuming their supervisor will address all their needs, and not relying on one-off interactions. Organizations too can facilitate developmental interactions. Preparing supervisors to conduct developmental interactions effectively, particularly jobor task-related interactions, can be an important step. It is important to note that while some of the advice we offered for advisers may seem like common sense, interviewees had little difficulty identifying ineffective developmental interactions. Apparently it is not safe to assume that supervisors will naturally handle developmental interactions in the recommended manner without some form of preparation. We found that job and task interactions are less likely to be voluntary, making these interactions more challenging. We also learned that developmental interactions with direct supervisors are viewed as least effective, so there are likely to be opportunities for improving their capabilities as coaches and advice givers. Training or coaching sessions should teach supervisors effective questioning methods to uncover learners needs and promote self-discovery. Based on our findings about expertise, supervisors should be taught how to identify when to bring in someone with more specialized expertise to support the learner. Implications for HRD Research. Most of the prior research on learning and development has focused on structured experiences such as training or formal mentoring programs. This study builds on that foundation. However, while we believe that it is appropriate to begin with the research on structured learning as a foundation, it is equally important to extend beyond that to examine more informal learning opportunities. Sometimes the results may be different. For example, in the training arena, some research has suggested that in a continuous learning culture, mandatory training is perceived more positively (Tannenbaum & Yukl, 1992), in part because it sends a signal that the organization considers training to be important. Yet in this study of developmental interactions, mandatory learning opportunities were perceived less

Key Characteristics of Effective and Ineffective Developmental Interactions 77 positively. Given the prevalence and importance of informal learning and the fact that some dynamics may be different than in formal learning, we encourage further research on informal learning opportunities. This study has several limitations that could be rectified in future research. First, all of our data came from advisees. We defined effectiveness from their perspective. It is quite possible that advisers would describe the same interaction in a different way. Second, all of our measures were collected through interviews, which could contribute to common method bias (Cook & Campbell, 1979). Future research should seek to collect data from additional sources, such as advisers and advisees, and use alternative methods (for example, diaries) to collect data. We examined the factors that influence the effectiveness of developmental interactions. Our focus on specific learning events provided some insights, but further insights could also be gained by examining informal learning more holistically. Gathering ongoing information about informal learning opportunities and obstacles through journaling or event sampling methods would greatly add to our knowledge of what enhances and inhibits informal learning. Future studies that use intervention strategies would also be illuminating by providing a basis for causal inference. For example, would advisers and advisees who were trained using the findings from this study demonstrate more effective developmental interactions? We found very few differences between the factors related to the effectiveness of career, job or task, and work-life developmental interactions. This suggests that the similarities may be greater than the differences, but we are not prepared to suggest that there are universal guidelines. Future research should examine some of the potential nuances between these different topics of development. Finally, we introduced a somewhat novel approach to data gathering: the participant-guided qualitative coding process. This approach has a few advantages and seemed to work well, producing highly interpretable results. We believe this could be beneficially employed in future research in other HRD areas. Conclusions Developmental interactions occur every day in virtually every organization. As revealed by the participants stories, some of these are truly developmental, while other interactions are ineffective or even detrimental. This study furthered our understanding of what differentiates effective and ineffective developmental interactions. Organizations and leaders can follow the recommendations here to help foster effective developmental interactions, whether for career-related, job- or task-related, or work-life-related issues.