🚀 My Impact

Key business impacts include:

• Long-term Forecaster, Scheduler and Capacity-Planning Infrastructure and functionality.

MVP:

• New Concept validated: Improved forecasting through the Continuous Forecast concept.

• Enhanced visibility and understanding of the the main view, with the Continuous, and Published forecasts.

• "What if" scenario creation and modifiable comparisons.

• Main view improvements: rearrangement controls, chart visibility, and data visualization.

• UI reskin of main components of the list and main view in line with the Spark Design System.

Background

Established in 1990, Genesys is a U.S. software company specialising in customer experience and call centre technology for mid-sized and large businesses. Applied Works has collaborated with Genesys for nearly eight years. This project involves partnering with the Workforce Management (WFM) team to develop and implement a novel concept, "Continuous Forecast," from scratch (0-1) on its existing platform. Leveraging AI and machine learning, this concept simulates potential future scenarios, enabling users to assess the impact of variable changes on call centre forecasts and offering valuable insights for proactive planning.

The Challenge

Forecasters, Schedulers and Capacity planners of the call Centres didn’t have a platform to make more accurate predictions. Genesys and Applied Works aimed to solidify a vision for implementing a Forecasting, Scheduling (and Capacity Planning) experience into Genesys Cloud over the next few years. This process included delivering a MVP in the short term while building out the vision in the long-term.

Role

Senior Freelance Product Designer.

Alongside the Design Lead and the Genesys Project Manager, We led the new concept validation, MVP, and long-term vision from scratch.

• Product Designer

• User Experience (UX) Designer

• User Interface (UI) Designer

• Visual Designer

Deliverables

These are all the deliverables:

• UX strategy

• Analysis of the current platform

• Interviews

• User Personas

• Competitor analysis

• Workshop User stories/MVP

• Infrastructure blueprint

• Iterative prototypes

• Concept Validation Usability test

• Audit the current forecast section

• New data visualisation

• Creation of the components of the Design System

• Documentation

Tools

Figma, Chat GPT, Miro, Jira, Excel, pen and paper.

Final UI

Overall, the layout and the main UI endpoints are more aligned with the Spark Design System, and there is a improvement of the main view and the chart data visualisation.

#UX Strategy

The Design lead and I worked closely with key Genesys stakeholders to understand the Vision, Business, and User Goals. Genesys emphasised the User Goals for the next six months since they had already done some research. We crafted a more precise plan by establishing a UX strategy for the Continuous Forecast concept validation project. We mapped out a tactical and strategic vision for the next six months to two years through an exercise with Genesys. The Lead designer and I outlined all the actions to achieve the goals in the UX Roadmap mapping workshop. Nevertheless, the project's complexity may modify the plan as we navigate uncertainties with this innovative concept.

We focused on the next 6 months…

✅ Empathise

• UI mapping: Firstly, I started to map out the main UI part of the Forecast section.

• Initial Questions: Secondly, I asked some basic but necessary questions to understand the basics and new concept definitions.

• Forecast User Flow: Understanding how a forecaster Creates a forecast was essential to grasp how he behaves with the platform.

• Interviews: We interviewed 7 participants, a Mix of Genesys and non-Genesys customers, Forecasters, Planners, Performance Managers, and Schedulers from different industries: Finance, IT, Utilities, Education Management, Design, and Healthcare.

• User Personas: From all the information gathered in the Interviews and some data that Genesys had from previous years, We identified some patterns, so, We created the UX personas

• Miro assist AI : Although Miro hadn't implemented "Miro assist" AI at that time, I leave an example of how the clustering by tag and Summarise feature could help speed up the process.

• Competitor Analysis: Our main Competitor was Amazon Connect, so Genesys wanted to focus only on this competitor. I went through it in detail to break down the main functionalities…

✅ Define

User: Forecaster ( Phase 1). That said, We need to plan and take into account Schedulers and Cap. Planners too.

Needs: Creation of the forecast from the continuous forecast, having a view of the Continuous Forecast stream of data along the published forecast and “Scenarios”, what-if scenarios and the ability to modify them.

Insights: Users are frustrated with not having the possibility to create What-if scenarios and compare them, maintaining data accuracy is an ongoing pain, and the current forecasting predictions, unfortunately, fall short of the desired accuracy level, and inconsistencies in data synchronisation across user personas.

✅ Ideate

• Epics: The Initiative is to “Build and create a Continuous forecast” encompassing the Forecasters, Schedulers and Cap. Planners. So, the epics related to this significant Initiative are the ones below. Although Phase 1 is just for the Forecaster, We need to see the impact on the Schedulers and planners.

• Q&A Epics: I had many questions about the epics, so We had several meetings with Genesys, as reflected in this Excel sheet .

• Chat GPT: Although Chat GPT was not in the market yet, this is an example of How We could automate the awful Excel sheet information and restructure it in a meaningful and thoughtful way (basically copy-paste all the content to Chat GPT) and prompt…

• We started to create the user stories from the epics, I workshoped that with Genesys, since this was long and complex.

• We workshoped too the MVP once I created the user stories.

Genesys pushed for more UX features for the MVP, although realistically, What We workshoped was more than enough since We didn’t even start to validate the concept… In parallel I started to make the blueprint/Infrastructure for long-term vision…taking into account Schedulers and Capacity Planners…

• Mapping Main Areas: I first proposed rearranging some UI elements to start the wireframes since the grouping was not intuitive enough.

• Initial Wireframes: Baseline Initial concept.

✅ Prototype

We asked Genesys to generate a real use case where We could test all the assumptions; otherwise, it would be more challenging to have a tangible impact on what We tried to achieve.

✅ Concept Validation Test

• User Testing - Concept Validation

Alongside the lead designer and the researcher, I created a plan to test the concept and validate its main aspects.

Roadmap Reassessment 

• What Applied works will deliver in this 6-month contract?

Since We spent so much time doing research, 1 Month previous to the contract deadline, Genesys and Applied Works worked on What We had to deliver since we had a budget for these six months, Genesys was keen to push for more UX features like Forecast Health, Business Drivers, Accuracy Metrics…so We gave them two options:

Pros: We’ll be delivering new, helpful features, making advancements to compete with new Amazon product, efficient use of budget, UX strengths AW.

Cons: Features will take longer to reach public release than option 2.

Pros: Faster to public release than developing new features.

Cons: Limited new features.

Genesys and Applied Works reached an agreement with Option 2, as it presented a more feasible step forward from both design and engineering standpoints.

Visuals

Upon completing iterations on the prototypes, we were prepared to initiate the development of visuals for the forecast sections and continue the iterative process. We conduct an audit of both the Forecast List View and the Forecast Main View to understand all the functionalities and identify potential changes. Due to time constraints, Applied Works allocated two additional designers to help us deliver Option 2.

Genesys had an in-house design system team that developed a Design System featuring a more modern aesthetic than the current platform. So, we started to iterate on the two main parts we needed to reskin: tabs and the Forecast Main View. Once we iterated on that, we worked and iterated on the data visualisation and how to integrate it into the main view.

• Tabs: We initiated the exploration focusing on the tabs within the main Forecast View, the taxonomy, and the structure, always considering if we could reuse a component from the 'Spark' Design System.

• Forecast Main View: We started with the Forecast Main View. We focused on the metrics panel and all the controls of the chart. And We iterated on this.

• Data Visualisation: The most important thing in this step was to iterate on the data visualisation, but above all, the integration into the Main Forecast View.

• List of sections to reskin and Documentation: We identified and started to reskin and document all the sections and areas from the Forecast section, according to the “Spark” Design System and Design Tokens. We created new components and delivered them to the Genesys design team to integrate them into the Design system. 

Lessons Learned

One of the lessons we learned is that when you start a project from scratch (0-1) and aim to validate a concept while concurrently planning for the MVP, aligning all actions and tasks within each sprint's timeframe becomes challenging. Numerous unknowns and dependencies arise, and even with a well-established UX strategy, constant reassessment becomes necessary. It’s not lineal, and sometimes you have to go back to previous stages and reassess. Given our budget constraints with Genesys, we (Applied Works) would have preferred to conduct usability and accessibility tests with real data, above all, the data visualisation part.

Previous
Previous

Priority Pass - Travel Services - Loyalty

Next
Next

UK Bands