Workday Account Payable Intelligent Work Queue - LUPING YEH

The Challenge - Delivery design solutions that depend on multiple development teams with limited resources and time capacity.
The Outcome - Create an intelligent work queue that facilitate the payment matching workflow automation and efficiency.
The Impact - Informed the product roadmap and save 30% time on invoice processing cycle.
My Role - Lead designer & researcher

Overview
Account Payable Intelligent Work Queue is a Machine Learning enhancement incorporated OCR capability to Workday's Payment application that can automatically match incoming payments to invoices or purchase orders. For Enterprise Financial Customers who handle large volumes of payments, this feature saves time, requires little or no configuration, and has significantly greater coverage since it can identify patterns and does not rely on exact matches.

Problem Statement
For many organizations, the process of supplier invoice capturing, routing and keying in to Workday is very manual. The workflow of invoice processing depends on sending documents to the correct department or individual at the right time avoids potential delays, thus enabling accounts payable to disburse remittances promptly and saving the business money. The AP Processor needs a way to minimize the processing time because there is too much manual works for handling high volume invoices and the AP department is not getting bigger.

The Process
During the project kickoff, I aligned with the Product Manager to understand where we stand today with the current product, shared knowledge about the hypothesis and identified the knowns and unknowns, then we determined the project plan moving forward collectively.

1. Explore the problem space through user interview
I started the research plan and conducted a series of interview to understand user’s payment matching workflow and get insights what improvements can be made upon current existing transactional functionality. There were total 10 user interviews from 5 different customers in remote and on-site sessions.

2. Define user needs, journey and opportunity
After the user interviews, I created the Persona and outlined primary Job-To-Be-Done to address user needs. I also worked closely with Product Manager to synthesize what we learned from user interviews via journey mapping exercise and identified pain points, opportunities and focus areas. The journey map also helped the team to evaluate where the initial hypothesis stood. The biggest insight was that user felt struggling to connect with different touch points and complete their tasks all in one place, which make the AP team hard to track the performance and improve the productivity. That was a great opportunity for Workday to improve and close the gap.

3. Design ideations and iterations
During the design process, I organized a design thinking workshop with Application and Machine Learning teams. We focused on ideating possible solutions and sketching user experiences. Collectively, there were many concepts and design themes generated for further iterations.

REFLECTION
This feature has been released in the early Q1 of 2019 for few partnered customers to adopt and it helps save 30% time on invoice processing cycle. With the alignment from research insight and journey map, I have successfully establish the vision for the product and the team will continue improving the product agilely in the following releases to meet the aspirational experience.