Using Data from Digital Traces

Bradley R. StaatsVisiting Associate Professor, The Wharton School

University of PennsylvaniaAssociate Professor, UNC Kenan-Flagler

Trace data: A sign or evidence of some past thing

http://hadoopilluminated.com/hadoop_illuminated/Big_Data.html

1. Introduction 2. Examples 3. Issues to Consider

1. Digital trace: Process data

1. Introduction 2. Examples 3. Issues to Consider

Additional Application

Capture (1 & 2)

Document Tagging

No

YesPolicy fail?

Application received &

scanned

Document Tagging

Application Capture (1 & 2)

Preliminary Information (1 & 2)

Materials received &

scanned

Automatic rejection letter

sent

Application Complete?

NoAutomatic incomplete

application letter

Yes

Credit Check (1 & 2)

Policy fail?

Automatic rejection letter

sent

Yes Automatic rejection letter

sent

NoAutomatic request for additional

materials

Application Complete?

No Automatic incomplete

application letter

Yes

Policy fail?Income Tax

(1 & 2)

NoPolicy fail?

Real Estate (1 & 2)

No

Yes Yes

Credit Approval

NoAutomatic

approval letter sent

Yes

Routed to credit expert

for negotiationMarginal

CustodianYes

No

CustodianYes

No

111 workers over 2 ½ years598,393 individual transactions

A perennial problem in industry has been that of sustaining human productivity over extended periods of time.

–Scott 1966: 4

Staats & Gino (2012). Specialization and variety in repetitive tasks: Management Science.

Specialization(Smith 1776; Taylor

1911; Skinner 1974; Boh et al. 2007; Schultz et al.

2003)

Variety(Hackman & Oldham 1976; Schilling et al.

2003; Narayanan et al. 2009)

Task Allocation Strategy?

Findings• During a day: Specialization > Varied

assignment• Across days: Varied assignment >

Specialization • Workers exhibit learning in setups

2. Digital trace: Click data

1. Introduction 2. Examples 3. Issues to Consider

2. Digital trace: Click data

1. Introduction 2. Examples 3. Issues to Consider

How does the team encourage (or discourage) individual knowledge sourcing behavior?• Knowledge repository data– Per-click data by person

• Software development project data– Project outcomes, characteristics– 487 projects

• HR system data– E.g., demographics

• Do temporal landmarks motivate aspirational behavior

Google searches for “diet” (average)

3. Digital trace: Search data

1. Introduction 2. Examples 3. Issues to Consider

Dai, Milkman & Riis (Forthcoming). The Fresh Start Effect. Management Science.

Mon Tue Wed Thu Fri Sat Sun505560657075

Day of the Week

-4 -3 -2 -1 0 1 2 3 450

55

60

65

70

75

Days Since the First Workday After a Federal Holiday

First workday after federal holidays

4. Digital trace: Tracking data

1. Introduction 2. Examples 3. Issues to Consider

Dai, Hengchen, Milkman, Katherine L., Hofmann, David A., & Staats, Bradley R. The Impact of Time at Work and Time off from Work on Rule Compliance: The Case of Hand Hygiene in Healthcare.

RFID tags monitoring hand washing compliance Personalized messagingData transfer to a central server 13,773,068 hand hygiene opportunities• Generated by 4,157 caregivers at 35 hospitals

from January 2010 to March 2013

4. Digital trace: Tracking data

1. Introduction 2. Examples 3. Issues to Consider

Dai, Hengchen, Milkman, Katherine L., Hofmann, David A., & Staats, Bradley R. The Impact of Time at Work and Time off from Work on Rule Compliance: The Case of Hand Hygiene in Healthcare.

How do job demands affect individual compliance over the course of a single shift?

• Access– Relationship building– Pipeline management

• Structure to the data• Mechanisms– Mixing other methods– Or maybe leveraging

more trace data…• Informed consent

Issues to Consider

1. Introduction 2. Examples 3. Issues to Consider

Myers, Chris, Staats, Bradley R., & Gino, Francesca. “My Bad”: The Impact of Internal Attribution and Ambiguity of Responsibility on Learning from Failure.