PILOT – Organizing Time for Innovation
- Resource Type
- Research Project
- Author
- Heidi Bertels
- Topics
- Organization and Future of Work, Culture, Leading Innovation Organizations
- Associated Event
- Research Project
Initiated: Spring 2021
Completed: Fall 2023
Read the results of part 1 of their project here.
To learn more, contact Matt Dorocak.
Value proposition
Creativity time is time “during which employees choose what projects to work on and how to complete such projects” (Burkus & Oster, 2012, p. 49). Creativity is critical to organizations’ competitive advantage, but providing slack time for creativity and innovation is costly. In addition, the relationship between slack time and innovation is not straightforward. On the one hand, slack time has been linked to breakthrough innovation and experimentation as it allows organizations and individuals to allocate time to projects that may be riskier and that are not focused on short-term objectives. On the other hand, slack time has been associated with a reduction in discipline and selectiveness, leading to resource misallocation. For example, slack time can lead to individuals supporting pet projects that become difficult for the organization to abandon (Staw et al., 1981). Therefore, the decision of how to allocate time and effort for innovation programs should be considered carefully. While companies in practice experiment with different time models for creativity, there is no systematic research that documents different configurations’ pitfalls, how organizations overcome them, and the circumstances under which the different setups may be most advantageous. Therefore, this research looks at the following question: How should companies organize creativity time to maximize creative output?
Companies subscribe to different time models to stimulate creativity and innovation (Table 1). Some companies, such as Twitter and Atlassian, provide employees with structured programs to engage in creative work continuously (Baldwin, 2012b). In this setup using a continuous time model, teams of employees are provided with uninterrupted blocks of time off from their regular commitments. For example, Atlassian organizes “innovation weeks” as well as quarterly “Ship It” days where employees are challenged to create and ship an item within 24 hours (Atlassian, 2021). Other organizations, like 3M and Intuit, are known to allocate a percentage of employees’ time to work on creative projects (the famous 15% rule). Of these companies using a spread-out time model, some follow an unstructured approach, leaving it up to employees to schedule this time (e.g., Intuit (Chang, 2016)). Others follow a structured approach by providing a specific weekly timeslot to work on the creative projects (e.g., W. L. Gore (Grønning, 2016), Quicken Loans (Baldwin, 2012a), and TargetProcess (“20% Project,” 2021)). Google uses both time models consecutively, to focus on different stages of the innovation process. Time from their 20% rule supports the creation of early-stage ideas that feed into their “Area 120” initiative, where Google employees “work on 20% projects 100% of the time” (Area 120 by Google, 2021) to turn projects that began as experiments or passion projects into full-time projects. This suggests that some time programs may be better fit for the front end of innovation (Bertels et al., 2007, 2019; Koen et al., 2014a, 2014b) whereas other time programs may be more beneficial for later stages i.e. that optimal time models may vary based on purpose.
Table 1: Creativity Time Models
| Time Model | Example |
| Continuous Time Model | Twitter, Atlassian |
| Unstructured Spread-Out Time Model | Intuit |
| Structured Spread-Out Time Model | W.L. Gore, Quicken Loans, TargetProcess |
| Consecutive Time Model | Google 20% rule followed by Google Area 120 |
How slack time is organized affects important variables which influence creativity. For example, employees in the spread-out model may feel that they have more job autonomy as they are free to schedule their creative time (Brem & Utikal, 2019). This in turn affects intrinsic motivation, which is positively related to creativity (Amabile et al., 1996). Employees in the continuous time model, on the other hand, face less scheduling conflict making it easier to engage in team creative work (Agrawal et al., 2018). If we know this, then how can companies mitigate the negative effects on creativity? For example, could companies increase perceived job autonomy for employees in the spread-out model and provide a process to handle scheduling conflict for employees in the continuous time model? What kind of hybrid models may be optimal? In addition, are there differences in the effectiveness of time models for creativity focused on the early stages of the innovation process versus later stages and for online versus offline environments?
Timeline
| Winter 2021 | Literature review done; experimental setup further refined |
| Spring 2021 | Interviews with interested IRI members to gather ideas and input |
| Summer 2021 | Finalize experimental setup; contact IRI members for participation |
| Late 2021 – Winter 2022 | Data collection |
| Spring 2022 | Data analysis |
| IRI Annual Conference 2022 | Report out |
| Fall 2022 | 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 Lead
Heidi Bertels – Associate Professor of Management, Chazanoff School of Business, College of Staten Island/CUNY