Driving a data-informed culture: organizational self-knowledge through evaluation

DeStefano, Lizanne; Miles, Tonya; Wernert, Julie; Andrews, Elisabeth

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https://hdl.handle.net/2142/120595 Copy

Description

Title

Driving a data-informed culture: organizational self-knowledge through evaluation

Author(s)

• DeStefano, Lizanne
• Miles, Tonya
• Wernert, Julie
• Andrews, Elisabeth

Issue Date

2023-09-07

Keyword(s)

• XSEDE
• NSF
• Evaluation
• Data
• Data-informed culture
• Lessons learned

Abstract

The Extreme Science and Engineering Discovery Environment (XSEDE) — the largest ever NSF-funded supercomputing initiative, spanning 19 institutions and running for 11 years — provided an unprecedented opportunity to embed external evaluation strategies over time within a large, complex, distributed virtual organization. In this article, the XSEDE evaluation team shares learnings from developing and deploying an evaluation model on which project leaders increasingly relied in their programmatic decision making. XSEDE’s embrace of evaluation as a tool for organizational self-knowledge supported the project’s success in both its services to the community and internal staff satisfaction. The Data-Informed Culture model, which we present here, encapsulates the evaluation lessons learned in XSEDE, offering a framework for incorporating these best practices in future initiatives. We describe the model’s development, implementation, and outcomes within XSEDE, including measurement and instrumentation strategies as well as approaches to obtaining buy-in from project leaders and ensuring a transparent evaluation process. We then provide suggestions on best practices for using evaluation to support a data-informed culture, and conclude with ideas for future implementation.

Type of Resource

text

Language

en

Sponsor(s)/Grant Number(s)

NSF OAC 15-48562

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