Stephen Herko

Intelligent Business Growth

My role

  • Lead UX Designer
  • Product strategy
  • Research


  • 14 Engineers
  • 4 UX designers
  • 3 Product owners
  • 8 Data scientists


To create an innovative application that will help our finance team create more accurate forecasts for the business. By incorporating cutting-edge AI and machine learning technologies, the application will streamline the forecasting process and provide valuable insights that will help the team make more informed decisions. Our goal is to empower the finance team to work more efficiently and effectively, and to contribute to the overall success of our business.


13 months


We will explore the process of designing an application for the finance team that leverages AI and machine learning to assist with creating a new forecast for the business. The goal of this application is to streamline the forecasting process and help the finance team make more accurate predictions about the future of the business. Our main objectives are to improve efficiency, accuracy and user satisfaction. All data reflected in the designs are purely for visual purposes. They are not reflective of the company's data.


The finance team at a large retail company spends a significant amount of time creating forecasts for the business. This process involves analyzing historical data, identifying trends and patterns, and making predictions about the future. The team currently uses Excel spreadsheets and other manual processes to complete this task, which is time-consuming and prone to errors. The company is interested in introducing AI and machine learning to this process to improve efficiency and accuracy.

Identifying gaps and unknowns

During the early stages of this UX case study, I facilitated a workshop with the stakeholders to determine viable use cases for the application we were developing. The goal of this workshop was to identify the most critical and impactful use cases that we could start tackling in the first phase of the project.

Vigilance in the Face of Change: Covering Gaps in the Project

After a thorough discussion, our perspective shifted as well as our business and user goals. I have come to realize that in the real world, things do not always go according to plan. While having processes and plans in place is beneficial, it is important to remain agile and adaptable as business needs can change due to leadership changes or shifts in the economy. Accepting this reality has made me a stronger designer as I now know what to expect and how to better plan and strategize. It's important to stay vigilant and provide coverages to gaps as the team and project shifts.


As part of my role, I lead the team towards a clear vision for the application we were developing. This was a critical step in ensuring that everyone on the team was aligned and working towards the same goals, especially since we had many stakeholders with different ideas and perspectives.

Research and strategy

We conducted research to understand the needs and pain points of the finance team. We conducted interviews with finance professionals to understand their workflow, pain points, and goals. We found that the finance team struggles with the time-consuming process of manually creating forecasts. They also expressed frustration with the complexity of the data and the difficulty of identifying relevant trends and patterns. They expressed a desire for an application that would streamline the process and provide more accurate predictions.

4 Day Design Thinking Workshop

Speaking our user's language

It was essential to understand the language and nomenclature used by our target users. This list of nomenclature was placed in confluence as a living document, and shared with the entire team. This understanding gave us motivation to use the same terminology in the interface design, which enhances the user's experience and ensures that they can easily understand the interface's functions. If we were to use different words or phrases than those familiar to your users, it can lead to confusion and frustration, which ultimately decreases the user's trust in your product.

Understanding Data Science

Although I have worked with some data scientists in the past, for this project, I wanted to delve deeper into their world and gain a better understanding of what it takes to produce the results they do. To that end, I enrolled in an introductory data science course to better comprehend their contributions and expertise.

Design and Staying Lean

Before creating wireframes, our priority was to maintain a lean approach to move quickly. We tested the proposed journey with our users, gauging their responses and noting down their likes and dislikes. Based on this feedback, we moved on to creating wireframes.

One thing was clear: the team and I needed to design an application that leverages AI and machine learning to assist the finance team in creating forecasts. The system should identify relevant trends and patterns in the data and provide recommendations for forecasting based on historical data.

Weekly design touchbases

Hosting weekly ritual meetings with the design team is an effective way to ensure everyone is aligned and on track with their responsibilities. During these meetings, we discuss the work that needs to be completed for the week, and establish a clear plan for when we will review designs and provide feedback. This helps us to prioritize our tasks and ensure that we are all working towards the same goals. By discussing any roadblocks or challenges we are facing, we are able to collaborate and come up with solutions together. Additionally, we use these meetings to identify any resources or support we may need to successfully complete our tasks, and ensure that we have the necessary tools and information to do so.

Creating stories and use cases

Our product managers fufilled this duty for the most part, but every once I needed to cover some gaps and pitch in. I wrote stories in JIRA from time to time and ensure our sprints were closed before starting the next one.

The application has a simple and intuitive interface, with features such as data visualization and interactive charts. The user can easily upload historical data into the application and view the predicted future trends based on the data. The application also provides recommendations for adjusting the forecast based on changing market conditions or other factors that may affect the business.


We conducted usability testing with the finance team to ensure that the application meets their needs and expectations. The feedback was overwhelmingly positive, with users reporting that the application streamlined their workflow and saved them significant time in creating forecasts. The team also reported that the application's recommendations were helpful in making more accurate predictions about the future of the business.

Outcomes and metrics

As part of our effort to tie our outcomes to our user goals, we also led an effort to define trackable metrics that we would use to measure the success of our finance team application. We wanted to ensure that we were not only delivering a tool that met the user's needs and goals but also providing measurable value to the business.

To achieve this, we worked closely with the finance team to define a set of key performance indicators (KPIs) that were directly tied to our user goals. These KPIs were focused on metrics such as user engagement, satisfaction, and productivity, which were critical to the success of the finance team application.


In this UX case study, we designed an application for the finance team that leverages AI and machine learning to assist in creating forecasts for the business. The application streamlined the forecasting process and helped the finance team make more accurate predictions about the future of the business. The application was well-received by the finance team and met their needs and expectations. This project demonstrates the value of UX design in creating applications that meet the needs of users while achieving business goals.