Integrate SAP's predictive services into Analytics Cloud by offering a Key Influencer Analysis to help break down influencers in large datasets.
Analytics Cloud had built out two of the three strategic pillars with analytics and planning capabilities. This work was the first step towards offering predictive services.
Decision makers are frustrated with the amount of data at their fingertips. Often, decisions are made by a gut feeling.
Alex can perform light analytics to help make key decisions during his business day. He's looking for help in crunching large amounts of data, but can't do it on his own.
The Guided Machine Discovery's core is a Key Influencer Analysis, which required a deep dive to understand the processes.
My team included myself, another Interaction Designer, Data Scientist, Development Manager & Development team. This project also required regular collaborated with teams in Dublin and Paris.
The full design scope was not feasible for the first release, therefore, this design was developed and released in two phases.
Project success was achieved by designing with stakeholders instead of to stakeholders.
Working iteratively provided the best possible designs. Each design carried pros and cons, which were reviewed to decide how to move forward. This project benefited from an amazing team who enjoyed participating in the design process.
• I love designing systems, both for my projects, but also for my own project management.
• Including key stakeholders throughout the entire process helps guarantee the product’s success.
• In most cases an agreement can be made on how designs can be de-scoped for release, but there are times when you can’t give in if you feel the UX is being compromised.
This was the first predictive feature designed for BusinessObjects Cloud. The process involved gaining an understanding of the predictive process, breaking down both applications, and deciding how the features would integrate.
• Predictive needed to be more prominent within the application.
• The Guided machine Discovery is an automated analysis that runs on an entire dataset. Because of this, the feature should be placed within the Data space.
• Customers found it difficult to find and access the data space.
Our user works with data every day. Having a clear understanding of how to navigate to and from the data space is imperative for a successful product
I am a life-long learner, and each project I take on drives my personal growth. Large and complex problems like this one continue to offer me a great deal of personal satisfaction and growth.
This project allowed me to think freely about the beginning-to-end workflow of our predictive users. I was able to create a design strategy which worked with the persona, technical requirements and scope limitation but also addressed the inherent risks. The design process generated a simple design to the customer, which was then validated during user testing. Through the process, I was able to defend my UX when needed while working with an amazing and collaborative team.
"A question is sometimes better than an answer." Charles Ives
Success to me means realizing that I am a member of a larger team. Including stakeholders in the iterative design process helped shape an efficient and successful product.
I enjoy designing systems for my projects as well as my process. I enjoy thinking in terms of macro and micro when designing projects.
I enjoy working in the predictive space. I'm excited about where we are heading with machine learning, natural language processing, and artificial intelligence. I will take any opportunity to continue learning in this area.
It is necessary to break large projects into achievable phases. There are times where you must defend user experience, and there are other times when an alternative is easily found.
To minimize confusion for the user, the analysis is revealed in stages. Blank states and hover states were used to reinforce this information hierarchy and allowed the user to consume the data.
Revealing the key influencers first in the top left of the analysis established this bar chart as primary data. Each new chart appearing to the right of this chart is driven by the previous.