Branch: Scheduling For the Hourly Employee

This case study’s focus was to evaluate Branch, a scheduling app for the hourly employee. Taking the clients presented opportunity and creating some recommendations around features, current and potential.

The current page is a broad overview of the project and the methods used. Due to intellectual property rights certain information can not be explicitly divulged in this case study.

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Branch Full Case Study

Identified Goals

Client Goal

Branch’s goal for the study was to evaluate current and potential expansion features.

Users Goal

Hourly employees want to find ways to track schedule, swap shifts, receive pay advances, and network with their peers and coworkers.

Limitations

Proposed features and recommendations should not exceed a set amount of development points.

Process

Analyzing and comparing similar products and companies in a Competitive Audit, I compiled a list of what features were offered and where there were gaps in the feature sets.

I created a User Journey Map to showcase Branch’s current feature offering and identified areas of opportunity for Branch’s future growth.

Working with a Branch developer, i designed a set of features that were assigned scoping scores to determine the length of time each feature would take to complete.

I conducted a Kano Analysis to determine users interest around the feature sets.

I then put together a plan and report for how Branch could go about implementing those selected features within the timeframe given. This report showcased the features using high-fidelity annotated wireframes.

Following the report I created an interactive prototype of one feature using Axure to show the client how that particular feature might function to users.

Kano Analysis Results Distribution Graph

Takeaways From This Case Study

Working with the Kano Analysis I really saw the value of the statistics in helping to determine value of feature sets. when the list of features are extensive it can be useful to compile a specific set to fit within the reality of development.

Also within the Kano Analysis it was fascinating to see the features that users found unnecessary or not useful. It directed the feature set in a way that was not anticipated when the set was created. It also highlighted the potential for expansion and future growth by showing areas that current users may not desire but additional users might have value for those features.

Working with the Kano Analysis I realized that even the actions of choosing very specific answers can tell a lot about the why underneath what users do and even more so what they say. It allowed me to target specific areas of the features that would be useful and fit them within the structure of the limitations.