Energy Trade Settings

Designing a settings console that control machine learning algorithm


Software: Energy asset bidding software driven by a machine learning algorithm

Software forecasts market prices

Users: Energy asset managers, energy traders (think stock markets)

User Behavior: Traders weren’t using the price bids generated by the software


  • Customer (who was beta-testing) stated the lack of control over the algorithm as a core issue in the RFP

  • One of this team’s OKRs was entry into the California market and this was the first client


"We built them an autonomous aircraft but without controls for the pilot"

My task: Design a trade settings page that allows users to schedule setting changes, and adjust the bidding algorithm according to risks, resources, etc.


Existing Resources?

Existing page of a “sister” product created by another Designer Design impact: starting with hand sketches vs high fidelity prototypes

Starting out with hand sketches

What are the settings?

Sessions with Data Scientists and internal trading experts to understand how settings influence the algorithm Design impact: virtual knobs vs entry fields vs other methods

Technical Constraints

Sessions with Developers to understand when and how user submissions impact forecasting Design impact: creating a time/date picker that clearly indicates what ”asap” vs “schedule”

Editing console has a specific date/time picker

Design Review

Presentation and walkthroughs with Product Manager, Backend, Frontend, Data Science to kick start development

Mapping out the entire process flow during design review

Results & Next Steps


Traders had enough control to use the generated bids

Next Steps

  • Partner with Platform Analytics to further understand users and iterate on design

  • A/B testing of placement of components and settings knobs

  • Consider scalability issues such as: archive log of setting changes, adding filters to types of settings, consider grouping settings in tabs