Customer Feedback
Identifying and Prioritizing Data Use Cases
Translate business ideas into a portfolio of experiments ranked by value and feasibility.
The Mission at a Glance
The Company
A banking network organized into regional entities
The Context of the Project
The Data Department of a banking network wanted to identify useful use cases for its various entities. The diversity of ideas and the difficulty in estimating their return on investment required a common method for evaluating them.
The Challenge
Numerous ideas for data use cases that needed to be evaluated and prioritized based on their business value and feasibility.
Our Approach
The Process, Step by Step
Organizing the Emergence of New Uses
PALMER structured the work around strategic themes defined by the Data department.
The workshops incorporated the needs of end users as well as both business and IT perspectives. This approach helped align the proposed ideas with the operational challenges they were intended to address.
Evaluating and Prioritizing Use Cases
Use cases were evaluated based on their potential value and technical feasibility.
Attention was given to early initiatives that could be tested quickly. Prioritization was intended to help focus efforts while taking into account implementation constraints and uncertainty regarding expected benefits.
Facilitating Experiments
The initiative established a community of data scientists and facilitated regular discussions about the work being done.
The “test and learn” approach made it possible to incorporate feedback and adjust practices. Pioneering entities were involved in the process to support experimentation and the rollout of validated use cases.
Preparing the Resources for Implementation
PALMER designed and managed a request for proposals for a Big Data platform capable of supporting these use cases.
A service offering for data scientists was also formalized, including tools, services, and training. This work supported the promotion of a data-driven culture within the organization.
Work Completed
What the “
” initiative has implemented
- 01
A process of ideation, evaluation, and prioritization.
- 02
A community of data scientists and a framework for experimentation.
- 03
A request for proposals to select a Big Data platform.
- 04
A range of services and training programs for data teams.
The Firm’s Support
PALMER’s Contribution
PALMER facilitated dialogue between business units and IT to focus efforts on practical applications. Community engagement supported the sharing of best practices and adjustments resulting from experiments.
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