Sproute

Home Screen
Person Profile
Project Profile
Case View - Next Best Peer Reviewers
Case View- Timeline
Case View - Employee Sentiment
Org Chart
Metrics Dashboard
Search
Person List
Project List

Inspiration

As a company grows in size, the demands of the workforce increase as well. Having more employees makes it more difficult to engage with each individual in your organization and meet their needs appropriately. This challenge is magnified when you consider the added complexity of a fully remote workforce brought on by COVID-19. How do we ensure employees are growing and taking on the right roles within the organization? How do we ensure our employees are happy and will stay at the organization long-term?

We built Sproute to answer these questions. Employees are the single most important investment an organization can make, and no two employees are exactly alike. Knowing how to invest in each individual is the key to fostering growth, improving morale, and cultivating a good corporate culture. Sproute gives us a way to track employee skills, identify what is important to them, and provide tailored recommendations to each individual to empower them to achieve their goals.

What it does

Employee Growth
Tracking employee growth and cultivating a positive work environment is at the heart of Sproute. Centered around the Performance Review case, Sproute tracks all peer and individual feedback collected for an employee, and provides tailored recommendations based on these inputs to advise them on how to advance their career. From the start, Sproute makes it easy to get an accurate review of an employee by using Pega decisioning strategies to provide system generated recommendations of who the most logical primary reviewer and peer reviewers should be. The Next Best Primary Reviewer and Next Best Peer Reviewer decision strategies take into account where the employee falls in the organization hierarchy, who has worked closely with the employee, who has a similar skillset as the employee, and historical review information.

Contextual Advice
Once reviewers are selected, each one is assigned a feedback child case to provide an evaluation of their peer. This feedback is analyzed with Pega natural language processing (NLP) and entity extraction to identify and recommend new skills and interests the reviewee has obtained. These selections are automatically added to their user profile to track the Reviewee’s growth and skillset which can be used to make informed staffing decisions by matching employees to projects. Additional decision strategies are executed during the Promotion stage. Sproute’s Next Best Job Title and Next Best Compensation advisor recommend a wage increase and a new job title for the employee based on their yearly contributions. This insight helps to eliminate implicit bias and ensure everyone is on a level playing field. These promotion and salary increase recommendations are based solely on employee performance, contribution, and merit.

Team Morale
Reviewees are then presented with Next Best Actions they should take to advance their career. This step gives employees tangible steps they can take to move towards the goals they laid out for themselves in their self assessment subcase. These Actions are identified by the system through the use of NLP and text analyzers. Finally, at the end of the review, Pega sentiment analysis is run on the consolidated feedback of the Performance Review to gauge how the review went overall and to help leadership determine if any follow up-actions are needed to keep the employee happy. Understanding employee morale is vital to maintaining a healthy workforce. Low sentiment scores serve as flags for leadership to analyze how they can help. Sproute helps identify and mitigate an issue before it becomes a bigger problem.

Corporate Culture
Another benefit of Sproute is the ability to improve communication and ensure employees are kept up to date on staffing changes and each other’s skill sets. If someone is interested in learning about a specific topic, they can search their coworkers’ profiles to find who is an expert at that subject and connect with them. Having this information at their fingertips allows employees to take advantage of the diverse skills of the workforce and quickly conquer new challenges. Powered by Elasticsearch, users can find relevant information across People, Projects, and Performance Reviews at lightning fast speed. Users can also track their own skills on their profile and record project achievements throughout their career. Current and historical project information is available through the Project profile page, including team members, roles, and prominent features that make each Project unique. The org chart provides a simple, easy to understand visualization that makes it easy to see where all employees are staffed at a glance and help plan for new work in the pipeline. A functional dashboard provides leadership visibility into actions that need immediate attention as well as a breakdown of the active projects and performance reviews in progress.

How we built it

App Studio
Sproute has a custom front-end that was developed in React using a combination of Semantic UI React and Material-UI components. However, the application business logic is entirely driven by Pega through the Digital Experience (DX) API. We started by determining the 3 pillars defined by the Pega Express methodology. We identified our Microjourneys, Personas & Channels, and our Data model. We then configured the workflow and the majority of the views in the application using Pega App Studio’s simple drag and drop interface. Once the high level workflow was defined, we created our data model and added personas and channels to each stage in our workflow.

DX & Custom APIs
Our React code transforms the raw data and layout information sent from the DX APIs into a sleek, stylish interface. The non-workflow interfaces such as the Dashboard, Org Chart, and My Work page are all populated using a combination of the DX V1 data endpoint and the V2 data views endpoint. We built custom APIs in Pega to support manipulating data on the Project and Employee profile pages, such as adding new Capabilities, Interests, or Features and adding a Person to a project. Leveraging the powerful technology included in the OOTB Pega platform while being able to use the flexibility of the React framework allowed us to provide an optimal user experience.
custom api

Prediction Studio
Pega Decisioning played a huge part in our development. We leveraged Pega’s Prediction Studio to build and configure entity and keyword text extraction models. These models were used in tandem with Pega’s OOTB NLP and Text Analyzer rules to extract and analyze topics on Peer Feedback and Self Assessment cases to recommend Next Best Skills (Capabilities & Interests) and Next Best Actions. We also used OOTB Pega NLP and sentiment analysis on the information provided during the review to identify employee sentiment.
prediction studio

Next Best Decisioning Strategies
We built data flows to execute decision strategies recommending Next Best Primary Reviewer, Next Best Peer Reviewers, Next Best Job Title, and Next Best Compensation. These strategies make suggestions based on factors such as previous feedback, similar capabilities, seniority, and project work.
decisioning

Elasticsearch
We configured a search page using Pega’s native elasticsearch integration. Users are able to search for Performance Reviews, Persons, or Projects in a fraction of a second. We enhanced this search to provide a fuzzy search capability which can be toggled on or off.
search

What we learned

This was our first time using many of the Pega Decisioning components outside of a training environment. We were eager to find a real world application to plug these components into and put them to work in a meaningful way. Configuring data flows, decisioning strategies, NLP, text extraction, and sentiment analysis using Pega OOTB methods were new to our entire team. We also learned how to interact with a subset of the V2 DX APIs. Additionally, this was our first time configuring fuzzy search in a Pega environment. We are thrilled with what we were able to accomplish in six short weeks!

What's next for Sproute

Post hackathon, we plan to use Sproute in our organization to track employee growth and conduct performance reviews. To get Sproute production ready, we will focus on implementing role based access control (RBAC) and attribute based access control (ABAC) policies along with database encryption to secure our data and keep sensitive information confidential. We also plan to enhance the Performance Review workflow to produce recommended mitigation actions based on the sentiment analysis extracted at the end of the review. We want to know if an employee is unhappy and the best actions leadership should take to improve their work experience. Improving search to handle more complex queries is something we also plan to tackle. We want Sproute to not only be a tool to track employee growth, but also for employees to connect with each other and leverage one another’s skills. Being able to search by capability will allow coworkers to know who to ask for help when they are struggling with a certain technical area. Finally, we plan to convert more of our DX API calls to use V2 once Pega Platform 8.6 is released to keep up with the latest technology.