DDS Guide: How it works
Below are the key concepts used within the DDS™ Framework.
An Overview of Data Driven Scrum (DDS)
A Process Framework to improve data science team collaboration and communication
Flow of work: DDS teams brainstorm possible questions to answer (or experiments to perform), prioritize which questions to answer, identify what data to use, and then collectively interpret the results of the work to answer the question and prioritize future work.
Iterations: Each iteration includes the work to create an artifact that answers the question (ex. a model), the work to observe that artifact (ex. how the model performs on test data) and the team’s analysis of those observations. Each iteration is focused on creating a Minimum Viable Product (MVP) or Minimum Viable Iteration (MVI).
Iterations Facilitate Agility: Each iteration enables teams to quickly answer a question (validate or reject a lean hypothesis). Learning from the current iterations helps prioritize future iterations.
Iteration Duration: Each iteration is short (~1 week), but are capability-based (not time-boxed calendar events). Hence, an iteration completes when the work required to answer the question has finished (i.e., not a specific date).
Product Increments: A high level goal for the team to achieve in a fixed amount of time (ex. 3 months) using multiple iterations. Increments help teams prioritize iterations within the increment and set expectations with clients.
Roles: The Product Owner (“voice of the client”) defines product increments, brainstorms and prioritizes the Product Backlog Items (which are potential questions or hypotheses to answer). The Process Expert ensures that the team is effectively using DDS properly (ex. meetings, tools). The Data Science Team Members (ex. Data Scientists, Software Engineers) work to create artifacts (ex. models) to answer the questions / experiments.
Prioritization: The team explores potential backlog items (questions to answer) by providing high level estimates of: (1) the value of the work, (2) the amount of work (team effort), and (3) the probability of success of that work. This information is used to prioritize and select the question to be answered (i.e., what to do during the iteration).
Meetings: There are regular meetings (ex. weekly), facilitated by the DDS Process Expert, to plan iterations, to review iteration results (to learn for future iterations). There is also a meeting to reflect on how to improve a team’s process (ex. monthly) and a daily meeting (ex. 15 minutes) to understand potential roadblocks in the iteration.
For more information on DDS, go to: www.datascience-pm.com/data-driven-scrum