PILOT - Organizing Time for Innovation

Initiated:  Spring 2020

Expected completion:  Fall 2021

Kick off webinar:  Tuesday, April 28, 12 - 1pm; Register

Value Proposition

Creativity is needed to come up with new product and business model ideas. Hence, it is critical for companies to understand when and how they should grant specific time to employees to be creative. In this study, we will look at the difference in creative output between groups who organize their creativity time differently. Creativity time is defined as time “during which employees choose what projects to work on and how to complete such projects” (Burkus and Oster, 2002, p. 49).

Employees can be given autonomy in scheduling their creativity time or not. When participants do not have autonomy to schedule creativity time, they are allocated fixed time slots to work on creative projects. In some companies, such as Twitter, employees are provided with an entire week per year to engage in creative work. Another situation arises when participants have autonomy to schedule creativity time. In this case, they are allocated a percentage of their time to work on creative projects rather than routine tasks, but the time during which they do so is not predetermined. For example, in some companies employees are allowed to work up to 15% or 20% of their time on creative projects, such as at 3M and Google.

The benefits of innovation programs are not in question in the literature, but how the time should be allotted to maximize creative performance is unclear. Therefore, our research question is:

How does scheduling autonomy affect performance on creative and routine tasks?

Approach

To answer our research question, we will follow an experimental approach combined with additional data collection using surveys.

In the experimental phase, employees will be asked to perform both a creative task and a routine task. We are open to working with IRI members on determining what the creative and routine tasks should consist of. Below we elaborate on two possibilities.

Possibility 1: Easier to score, but lower level of domain-specific creativity

  • Creative task: Participants will receive a set of 12 letters arranged in alphabetical order. The creative task is to create as many words as possible from this set of letters (Eckartz et al., 2012).
  • Creative task performance: The number of unique words generated that are in the English dictionary.
  • Routine task: Participants will solve addition calculations.
  • Routine task performance: The number of math problems solved correctly.

Possibility 2: More complicated to score, but higher level of domain-specific creativity

  • Creative task: Participants generate ideas for a company’s business model. Participants are provided with a business model canvas of an existing business and are asked to suggest new ideas to improve it.
  • Creativity task performance: Two independent raters will judge the novelty and usefulness of the ideas generated. How unique are the ideas compared to others’ ideas and how useful and plausible are they in terms of cost savings and/or revenue generation? We can also count the number of ideas and business model canvas elements in which participants have proposed new ideas.
  • Routine task: Participants will respond to emails.
  • Routine task performance: The number of emails addressed.
  • Both independent raters will be experts, recruited by the research team.
  • Experimental setup
    • One group of participants will have a fixed time schedule to work on a creative task (for example: from 10:00 am until 10:15 am) and the routine task (10:15 am until 10:30 am) whereas the other group will be asked to spend the same amount of time on the creative and routine task (i.e., 15 minutes each), but this group will have scheduling autonomy (participants will be told that they need to complete both tasks within the next half hour). We will control for the number of times participants with scheduling autonomy switched.

We will also ask participants to complete a survey to control for important individual-level variables that might affect creativity. Examples are creative self-efficacy, creative personality scale, preference for autonomy, flow, and intrinsic versus extrinsic motivation. Since this is an experiment, organizational-level control variables might not be relevant.

Timeline

Winter 2020 Literature review done; experimental setup further refined
Spring 2020 Interviews with interested IRI members to gather ideas and input
Summer 2020 Finalize experimental setup; contact IRI members for participation
Late 2020 - Winter 2021 Data collection
Spring 2021 Data analysis
IRI Annual Conference 2021 Report out
Fall 2021 RTM article submission

Anticipated Deliverables

We will aim to publish a paper in RTM. We plan to present our findings at the IRI conference, and if companies are interested, also at member companies (depending on travel funding). Finally, it would also be very interesting to follow up with case studies in member companies where there can be more regard for organizational-level variables such as size, culture, and industry, which might lead to further insights and publications in RTM.

Project Leads

Heidi Bertels - Assistant Prof. of Management, Chazanoff School of Business, College of Staten Island/CUNY

Alexander Brem - Chaired Prof. of Management, Daimler Chair of Innovation and Entrepreneurship, University of Stuttgart, Germany