TY - GEN
T1 - Analyzing the flow of knowledge with sociometric badges
AU - Fischbach, Kai
AU - Gloor, Peter A.
AU - Lassenius, Casper
AU - Olguin, Daniel Olguin
AU - Pentland, Alex
AU - Putzke, Johannes
AU - Schoder, Detlef
PY - 2010
Y1 - 2010
N2 - This paper presents a collection of "best practices" for the use of "Sociometric Badges" that support automatic collection of face-to-face interaction between workers within an organization. The practices presented aim to improve data quality over legacy methods allowing insights into the processes and structures of an enterprise's de-facto communication networks. Our approach uses dynamic Social Network Analysis (dSNA) to make it easier for executives to analyze and manage communications networks. The practical applicability of the approach was evaluated by case studies conducted in three different organizations: (1) the marketing department of a medium sized bank in Germany, (2) the post-anesthesia care unit at a large US hospital, (3) teams of software developers in a Nordic European country. For the analysis, we tracked, amongst others, all personal interactions between the knowledge workers in a department or team using sociometric badges worn by each employee for the duration of the case studies. We analyzed this sociometric data as well as emails and instant messages exchanged between the employees and compared it with performance data of individuals and teams. The paper highlights 16 key lessons learnt during these studies. The first nine lessons focus on overcoming the employee's privacy concerns to set up the necessary technology infrastructure, and the final seven provide general findings for efficient management of knowledge workers based upon the results of the case studies.
AB - This paper presents a collection of "best practices" for the use of "Sociometric Badges" that support automatic collection of face-to-face interaction between workers within an organization. The practices presented aim to improve data quality over legacy methods allowing insights into the processes and structures of an enterprise's de-facto communication networks. Our approach uses dynamic Social Network Analysis (dSNA) to make it easier for executives to analyze and manage communications networks. The practical applicability of the approach was evaluated by case studies conducted in three different organizations: (1) the marketing department of a medium sized bank in Germany, (2) the post-anesthesia care unit at a large US hospital, (3) teams of software developers in a Nordic European country. For the analysis, we tracked, amongst others, all personal interactions between the knowledge workers in a department or team using sociometric badges worn by each employee for the duration of the case studies. We analyzed this sociometric data as well as emails and instant messages exchanged between the employees and compared it with performance data of individuals and teams. The paper highlights 16 key lessons learnt during these studies. The first nine lessons focus on overcoming the employee's privacy concerns to set up the necessary technology infrastructure, and the final seven provide general findings for efficient management of knowledge workers based upon the results of the case studies.
KW - knowledge flow optimization
KW - social network analysis
KW - sociometric badges
UR - http://www.scopus.com/inward/record.url?scp=77954971135&partnerID=8YFLogxK
U2 - 10.1016/j.sbspro.2010.04.048
DO - 10.1016/j.sbspro.2010.04.048
M3 - Conference contribution
AN - SCOPUS:77954971135
T3 - Procedia Social and Behavioral Sciences
SP - 6389
EP - 6397
BT - 1ST COLLABORATIVE INNOVATION NETWORKS CONFERENCE - COINS2009
ER -