6/26/20161 Using McKinsey’s 7S Model to Empirically Examine Organizational Effectiveness among the NBA Teams IABPAD Conference Annual Meeting 2015 Orlando, Florida Bryant C. Mitchell, PhD Associate Professor University of Maryland Eastern Shore

6/26/20162 Introduction Explanation of Hypotheses Data Analysis and Conclusions Future Research and Significant Findings

6/26/20163 This study investigates three broad questions: 1.Is it possible to empirically validate the McKinsey 7 S Model? 2. If so, do strategy, skills, and staff explain significant differences in performance at the operational level of service firms? 3. Of these three key variables which has the greatest impact on performance among the service firms examined?

6/26/20164 Style Skills Shared Values Structure Strategy Staff Systems McKinsey 7S Model

6/26/20165 Some research has been conducted regarding how human resources create a competitive advantage in manufacturing firms (Youndt, Snell, Dean, & Lepak, 1996) The term service strategy is defined as a specific operating strategy for a service unit (Thompson & Strickland, 1999) Some service strategies are implemented by creating complex patterns of coordination between the service employees and other resources involved in the service delivery (Grant, 1991)

6/26/20166 The coordination of available resources provide unique capabilities and a potential source of competitive advantage (Cappelli and Singh, 1992). But, it is difficult to measure the level of coordination achieved and consequently the degree of service implementation. Some services have high levels of process structure complexity similar to manufacturing (Gupta & Loneal, 1998), which makes measurement difficult.

6/26/20167 Introduction Explanation of Hypotheses Data Analysis and Conclusions Future Research and Significant Findings

6/26/20168 Basic Research Model Strategy Performance Staff Our model proposes that staff, skills, and strategy have a direct effect on a firm’s operating performance. Staff H1 H2 H3

6/26/20169 Specifically, the study examines the operating performance of NBA Teams using archival data for 22 teams from 1979 to Sports data has been used by other management researchers to explore different portions of management theory. For example, NBA data was used to examine ‘tacit knowledge’ (Berman, Down, & Hill, 2002). And, NCAA basketball data has been used to study strategy (Wright, Smart & McMahan, 1995).

6/26/ Research Hypotheses Hypotheses Methodology H1: Staff has a positive, direct effect on operating performance. H2: Operating strategy has a positive, direct effect on operating performance. H3: Organizational skills have a positive, direct effect on operating performance. Common factor analysis and hierarchical regression. Hierarchical regression statistical methodologies. Common factor analysis and hierarchical regression.. Three hypotheses were developed to answer the two research questions.

6/26/ Unit of Analysis and Data Unit of analysis Data type and source Key NBA productivity data Operating strategy level Longitudinal NBA data ( ) Data SymbolData Description FGM FTM OFF DEF AST PF DSQ STLS TO BLKS Field goals/minute Free throws/minute Offensive. rebounds/minute Defensive. rebounds/minute Assists/minute Personal fouls/minute Disqualifications/minute Steals/minute Turnovers/minute Blocked shots/minute Variable Type Variable Description Ten NBA personnel productivity measures were used to develop the staff and strategy variables.

6/26/ Only data from teams in existence for 25 years or more was used. Current NBA Franchises Atlanta Hawks Boston Celtics Charlotte Hornets Chicago Bulls Cleveland Cavaliers Dallas Mavericks Denver Nuggets Detroit Pistons Golden State Warriors Houston Rockets Indiana Pacers Los Angeles Clippers Los Angeles Lakers Miami Heat Milwaukee Bucks Minnesota Timberwolves Orlando Magic New Jersey Nets New York Knicks Philadelphia 76ers Phoenix Suns Portland Trailblazers Sacramento Kings Seattle Supersonics Toronto Raptors Vancouver Grizzlies Utah Jazz Washington Wizards Selected NBA Franchises Atlanta Hawks Boston Celtics Chicago Bulls Cleveland Cavaliers Dallas Mavericks Denver Nuggets Detroit Pistons Golden State Warriors Houston Rockets Indiana Pacers Los Angeles Clippers Los Angeles Lakers Milwaukee Bucks New Jersey Nets New York Knicks Philadelphia 76ers Phoenix Suns Portland Trailblazers Sacramento Kings Seattle Supersonics Utah Jazz Washington Wizards Non-selected Franchises Charlotte Hornets Miami Heat Minnesota Timberwolves Orlando Magic Toronto Raptors Vancouver Grizzlies Yes No

6/26/ The detailed model identifies the 3 hypotheses and their respective areas of influence. Time-in-Game H3 Time-in-Game H3 Team Wins/Losses Players’ Productivity Players’ Productivity H2 H1 Detailed Research Model Team Productivity Team Productivity H3

6/26/ Several key issues had to be to addressed before conducting the hypothesis testing phase of the study. Manager’s utilize different approaches for each key personnel function in order to exploit each person’s unique capabilities. Assessment of operating strategy is based on time utilization patterns of key personnel functions (I.e. center, point guard, small forward, power forward, off guard and bench) would not be possible using composite productivity approach. IssueSolutionRationale 1. Should staff productivity be developed on a composite or on a position-by- position basis? Staff productivity was developed on a position- by-position basis.

6/26/ Hierarchical regression was used to examine the differences between an Staff only model, Staff-Strategy Model, and Staff-Strategy-Skills model. IssueSolutionRationale 2. How to reduce the 10 NBA statistics for each position to a single produc- tivity measure? A common factor analysis technique was used to develop position-by- position factors that were used to weight each of the 10 NBA Statistics. Approach is a statistically valid way to reduce several variables into independent factors. The factor values could then be used as weights to re- duce the 10 NBA statistics into a single productivity value. 3. What technique should be used to analyze the impact of the team’s operating strategy and skills? Hierarchical regression techniques enabled me to examine incremental differences.

6/26/ IssueSolutionRationale 4. What is the best way to measure the contribution of the bench (on a composite or positional basis)? The bench variable was measured on a composite basis. Bench players tend to be generalist. For example, the typical guard is expected to perform either a point guard or a off guard role depending on what particular skill is needed at that time. Versatility is the key attribute of most good bench players. Bench players tend to be less stable, in that they are more frequently traded and cut.

6/26/ IssueSolutionRationale 5. What is the best cut off point for using factor score values? All values of smaller than 0.01 treated as zeroes. Based on discussion with my co-authors. The cut-off value to use is an arbitrary decision. 6. How many ways should the data be disaggregated to examine the impact of the strategy variable on performance? Disaggregated data was examined by: 1)conference 2)decade 3)winners and losers Many people believe that teams in the Western and Eastern conferences have developed very different playing styles. Many people believe that the style of play has changed dramatically in the last 10 years. Many people believe that winners and losers have distinctive playing styles.

6/26/ IssueSolutionRationale 7. Should actual wins or the RPI be used as the dependent variable in the regression model? Actual wins were used as the dependent variable. Power ratings are meant to be predictive models. Earliest power rating only dates back to only Power ratings have two principal uses in sports: 1. handicapping for gambling, 2. and ranking NCAA tournament selections. Neither of these two uses is helpful to effective management of NBA franchises.

6/26/ Introduction Explanation of Hypotheses Data Analysis and Conclusions Future Research and Significant Findings

6/26/ All positional variables, except the off guard were significant at a p value of a The dependent variable in each model is the number of wins per team per year. Regressors are the composite performance potential score for the indicated positions as described in earlier. b N = 440, df = 433

6/26/ The addition of strategy significantly improves model predictability. a The dependent variable in each model is the number of wins per team per year. Regressors are the composite performance potential score for the indicated positions as described in earlier. b N = 440, df = 432

6/26/ The addition of two of the four skills significantly improves model predictability. a The dependent variable in each model is the number of wins per team per year. Regressors are the composite performance potential score for the indicated positions as described in earlier. b N = 440, df = 428

6/26/ The Implications of these results are: The Staff Only model supports Hypothesis 1. The Strategy-Staff model supports Hypothesis 2. The Strategy-Staff-Skills model supports Hypothesis 3. While individual talent is important, strategy is by far the most dominant determinant of performance. The addition of skills to the model results in each of individual positional variables becoming less critical to performance (i.e. there coefficients are smaller).

6/26/ This study provides evidence in support of all 3 hypotheses HypothesisResultsManagerial Implications H1: Staff has a positive, direct Hypothesis supportedRecruiting, training, and the development of effect operating performance.key employees is critical to achieving high levels of firm performance. H2: The direct effect of staff Hypothesis supportedStrategy does matter. For example, in the on performance is moderated by case of the NBA, simply playing the most the operating strategy. capable players all the time does not work. Coaches must develop effective strategies for managing their critical resources. In addition, the overuse of key personnel can have a detrimental impact on firm firm performance H3: The direct effect of staff Hypothesis supportedOperating level managers’ do have more and strategy on performance is than one strategic path to choose from. As a Moderated by skills.result, managers’ must build distinctive organizational-wide skills as oppose to just recruiting and training individual staff. HypothesisResultsManagerial Implications H1: Staff has a positive, direct Hypothesis supportedRecruiting, training, and the development of effect operating performance.key employees is critical to achieving high levels of firm performance. H2: The direct effect of staff Hypothesis supportedStrategy does matter. For example, in the on performance is moderated by case of the NBA, simply playing the most the operating strategy. capable players all the time does not work. Coaches must develop effective strategies for managing their critical resources. In addition, the overuse of key personnel can have a detrimental impact on firm firm performance H3: The direct effect of staff Hypothesis supportedOperating level managers’ do have more and strategy on performance is than one strategic path to choose from. As a Moderated by skills.result, managers’ must build distinctive organizational-wide skills as oppose to just recruiting and training individual staff.

6/26/ Lessons for the Service Industry First, strategy does matter.  Deployment of key staff personnel. Second, over-utilization of key staff personnel may have a negative impact on operating performance.  increased injuries to key personnel (NBA)  employee burnout  key employees leaving to work at rival or competitive firms. Third, development and maintenance of employee productivity data for service firms is potentially as critical to managerial effectiveness as it has proven to be in manufacturing. Four, leading firms not only develop key staff personal, but they seek to develop distinctive organization-wide skills as a basis for sustainable competitive advantage. For example, 3M has instituted policies that not only support individual staff members innovation but they have enabled 3M to develop organization-wide capabilities that many of its competitors have yet to replicate.

6/26/ Introduction Explanation of Hypotheses Data Analysis and Conclusions Future Research and Significant Findings

6/26/ Further research is needed to investigate other possible factors that influence the number of wins. (i.e. the remaining 4 S’s in McKinsey’s 7S Organizational Model) Investigate whether or not strategic time periods exist and determining their impact on operating performance. Investigating whether time phased or work flow strategy development systems are used as in the case of manufacturing firm’s order review release functions.