Enterprise IT users switch between a multitude of programs and devices on a daily basis. Inconsistencies between user interfaces can slow enterprise users’ productivity, as those users may enter the same information repeatedly or need to figure out what format to enter data (e.g. specifying an employee might be done with an employee number, a name, or an e-mail address). On the application development side, code for user interfaces may be written over and over again. One approach to solving these problems is to create a common User Experience (UX) framework that would facilitate discussion and the production of shareable interface templates and code. Intel IT took the challenge to do just that, with the goals of increasing employee productivity by at least 25% and achieving 100% adoption. To create that unified enterprise UX frame work, Big Data approaches were critical, as described in this white paper from IT@Intel.
To understand the requirements for the enterprise UX, two sources of data are available, but both have unique problems. Traditional UX research methods like surveys, narratives, or observations, typically are unstructured and often do not have statistical significance. Usage data from logs have large volumes, and user privacy is at risk. Unstructured data, varied data, and voluminous data are a perfect fit for Big Data techniques. We used de-identification (aka anonymization) to hide the personal information of users. De-identification techniques were combined with Big Data to create a Cloudera Hadoop based analysis platform shown to the right.
Using that analysis platform, Intel IT’s UX team created a single framework standard for all enterprise solutions. 60% of Intel IT’s staff can take advantage of it. Data from this platform was also used to select and implement a new internal social platform. The analysis platform has also been used to analyze other aspects of user behavior, which we are planning to write about in a future IT@Intel white paper.
In addition to the white paper, more detail on the development of the UX framework can be found in the following papers:
- McCreary, F., A. McEwan, D. Schloss, and M. Gomez. “Envisioning a New Future for the Enterprise with a Big Data Experience Framework.” New Perspectives in Information Systems and Technologies, Volume 1. Springer International Publishing, 2014. 199–209.
- McCreary, F., M. Gómez, D. Schloss, and D. Ali. “Charting a New Course for the Workplace with an Experience Framework.” HCI in Business: First International Conference, HCIB 2014, held as part of HCI International 2014, Heraklion, Crete, Greece, June 22–27, 2014. Proceedings. Springer International Publishing, 2014.
Regarding our use of de-identification/anonymization, we talked about our early explorations in this white paper, and a more detailed analysis of the challenges of using de-identification in an enterprise setting our detailed in this conference paper: