A Decision-Driven Methodology for Business Intelligence Dashboards in Start-Ups; Integrating Conservationist and Green Infrastructure into the Public Sphere of Transportation: A Critical Analysis of Wildlife Crossing Implementation in the U.S.

Many businesses rely on data-driven
metrics to inform critical decisions and drive success.
Data reporting is a common way to facilitate these
decisions so businesses may effectively achieve their
mission. However, ‘data’ can present a significant
obstacle for companies if not appropriately presentable
for stakeholders while maintaining accuracy and
reliability. The work herein describes the design of
dashboard systems that effectively display important
metrics based on user and enterprise needs for a startup.
Through utilizing user design principles and identifying
business needs, we applied the following discovery
methodology: understanding and familiarizing ourselves
with enterprise data, conducting discovery interviews
with stakeholders, and distilling interviews into key
business decision needs. From here, we determined
system objectives for each decision and metrics for each
objective. This methodology, which focuses more on the
centrality of a dashboard in supporting decisions than
many published methodologies, is applied to a specific
case, a financial technology startup that focuses on loans.
The process involved simultaneously building an
understanding of the business, discovering and
identifying business decisions, wireframing the data
reports, verifying that the data reports effectively and
accurately guide the business decisions, and realizing the
data reports in a Business Intelligence platform.
Applying this methodology to the startup revealed
several key takeaways: the importance of pivoting
quickly from paper prototypes to prototypes using the
final product software, distinctly identified decision
traceability for each dashboard element, and iteration
between stakeholder engagement, product development,
and testing.