Financelens (Master Thesis) Project

As a part of Master Thesis at UCL, this project was a part of the Microsoft Project where researchers are exploring the behavior of people across using multiple device interactions with cross device user interfaces, decision making, information flow & efficient sense making.

Individual Project

Stages

Abstract

In-depth interviews were conducted with 13 different participants with various financial backgrounds, to understand how they interact with multiple devices at their workspace and explore issues, their information flow, configuration spaces and sharing of information across devices as well as with their department.

The findings present that the workforce follow simple interaction patterns while performing their tasks on more than two devices i.e. either in parallel, simultaneous or without a logical flow and have one device which is a primary and other device a secondary.

Data transfer and sharing is mostly carried out within a dedicated server or on company's own platform. Lastly, information sharing and workflow is heavily focused on interacting with teammates, supervisors, clients or bosses in majority of the scenarios.

Data Collection

Semi-structured informal interviews were conducted with each of the recruited participants, each lasting around 30-45 minutes. About eight (8) of the participants were interviewed over Skype/telephone as they were located at in a different country or their workspaces were inaccessible to carry out an interview in-situ. However, three (3) of the total participants agreed to be interviewed at their workspace and two (2) of the total agreed to be interviewed outside their workspace but in person.

For the participants that were interviewed over Skype and outside their workspace, they were asked to submit pictures of their workspace or to describe their settings of different devices that they use. The were also asked to share their background information prior to the start of their interviews.

This was helpful especially in understanding their level of know-how and experiences with handling a specific device, software or hardware for their roles. For example, Bloomberg Terminal, Murex: a trading software.

An online questionnaire was sent to the participants prior to their interviews along with consent forms and information sheets. The purpose of this questionnaire was to understand how many devices are being used by the participants at their workspace. Later the same was used to probe deep in the interview related to a specific device or technology.

The research explored the answers to these three questions:

• How exactly are the current multi-device/display setups used for financial computing/analytics?
• What strategies exist to arrange devices and information spaces?
• How is information transferred between devices? This section aims to give out the certain aspects of the study conducted, information about the participants, the method used to collect data and analyze data.

Data Analysis

Based on the research questions to answer through this research, the analysis technique used was a mix of top-bottom approach and bottom-top approach. Key categories like Data transfer and sharing, Device Settings/Ecologies, Information flows were the main focuses here and the others came from the analysis of interesting facts and insights from the interviews. Thematic coding was used because this is one of the most widely used Grounded theory approaches.

This approach led me to form “thematizing meanings” from the data gathered. Because this method is flexible and gives a freedom to concentrate on key elements and analyze that specific area of interview data, it also takes enormous period of time coding longer interviews.

Reading through the data, I made notes. After the first stage of note taking was completed, the researcher moved to the generating general codes for the analysis. Codes and themes which were related data or experiences were gathered in the this stage.

Further categorizing these codes into more relatable themes was the next step and finally defining names and creating relationships between these themes was the final step. These were the three-layer analysis that was carried out with the qualitative data from all the interviews.

Discussions

One of the findings showed that, there is a primary-secondary device pattern usage and settings from the data flow diagrams and task-activity matrix that is prepared. Most of the participants use one computer as their primary go to device and the other as helping device.

The other finding states about how workforce in the finance domain usually use online method to share and transfer data within their colleagues and departments. They use a dedicated server which is either company owned or a separate platform like Microsoft SharePoint or Live Link.

Conclusion

Using several multiple devices in modern workspaces is a norm. There is a need to better understand people in the finance industry to design better user experience that helps them in their future working styles. This research conducted 13 in depth semi structured interviews specifically from the financial domain to explore and investigate insights about this industry.

The research to quite an extent tried to investigate and explore the answers to the research questions. For the first question, yes there is a strong behavior of using devices in serial and parallel patterns coming out from the primary data. The devices are also setup on the basis of one’s roles and activities but follow primary-secondary pattern when choosing the go to device.

For the second question to answer, Information space is generally split across interacting with people from the office majority of the time. And to answer the third question about how data sharing works in these environment is mostly through a dedicated centralized server or emails. Occasionally, USBs are used but needs to be encrypted.

User research, Qualitative Studies, Observations, Fianance, Expert interviews

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