USER-CENTERED DESIGN: increasing the value of data

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    USER-CENTERED DESIGN: increasing the value of data

    User Experience (UX) design has been used in many industries to display information in a way that is easy to consume and interpret. From desktop software to iPhone applications, UX design has become a baseline requirement for consumer products. In recent years, there has been a need for UX design in the business sector as well. The rapidly increasing volume of data firms are facing today is contributing to reduced efficiencies in everyday workflow, increased costs and limited employee potential. In this article, Parry Ruparelia, Jennifer Evans and Matt Hopgood discuss how firms in the capital and commodity markets are now leveraging UX design to address these problems and meet business objectives.

    Twenty years ago, analysts had limited access to data. They relied heavily on human intelligence and printed material. Today, the number of information sources has exploded. Analysts can choose from seemingly limitless amounts of data—from market prices to supply and demand information, Twitter-based sentiment analysis, emails, spreadsheets, newsfeeds and geospatial mappings. For the past two decades, organizations across all industries have made great strides in creating robust infrastructures to process this growing amount of data. Most firms addressed it from a transaction perspective, focusing on processing the information instead of enabling users to get the best insight from the data.

    With the projected amount of data growing, understanding large, complex data sets and using them to make more intelligent and informed choices is more important than ever. To be successful, firms will need to layer new functionality on top of their powerful infrastructures that enables users to effectively ingest and analyze greater amounts of information—and with better results.


    Successfully managing large amounts of data is a daunting task, especially when the majority of it is unstructured. Data without structure is meaningless. It is not until data is paired with a logical context and timely relevance that it gains significant value. The problems surrounding today’s tidal wave of information extend beyond its sheer volume to include maintaining user confidence and making data usable and easy to access.

    Volume of Data
    The amount of data in existence is immense. Not only is the volume of data growing rapidly, the number of databases, means to access information, corresponding connections to other data sets and decisions that need to be made based on data are too. Finding and identifying the most relevant piece of information as users move across the transaction life cycle is becoming more difficult. Instead of dealing with data one piece at a time, analysts now need to consider the entire information landscape. For instance, new regulatory reporting mandates require a more holistic view of data. Specifically, CFTC transaction reporting requires up to hundreds of data fields per transaction.

    Confidence in Data
    Data is everywhere, making it difficult to determine which piece of data is most relevant to the problem at hand. When data is jammed together from different systems, it is more difficult to gauge the cleanliness or timely relevance of a given data set. As a result, confidence in the information is eroding. Each data set’s respective sources, taxonomies and underlying assumptions can be easily overlooked. With clean and accurate data, analysts can be confident that their information is the best reflection of the problem at hand.

    Visibility of Data
    Large volumes of data, combined with the complex ways in which it is stored, make locating desired information a considerable challenge. Most of today’s systems are designed to run on unsophisticated single screens. As the volume of information continues to grow, today’s systems will need to scale too. UX artifacts that relay information hierarchy and priority, such as mental models and wireframes, can be designed to illustrate current data and project it to a larger scale, both for analysis and future work.

    Data to Support Decision Making
    Analysts rely heavily on data to journey through the workflow process. Understanding where the information comes from and its place in the data hierarchy allows an analyst to be confident in his or her decisions. Traditionally, systems have been built on the incorrect assumption that all data is of equal importance. Analysts cannot harness the potential that data holds if the systems they use do not convey a sense of hierarchy.

    Natural Interactions with Data
    To keep up with increasing volumes, firms ask employees to manually sift through data, opening it up to human errors and miscommunications. Oftentimes, firms have created specific processes for weeding through large volumes of information. These interactions with data become forced and artificial. User-centered design helps employees to “see” what is important to them without having to follow a process—enabling them to have more natural interactions with data.


    To most effectively leverage data to create information and therefore enable better decision making, users must interact with it in a natural way. UX design is the practice of incorporating how users access, interpret and relate to data into the overall design of a particular system or piece of software. Adding UX techniques, such as data visualization and user journey optimization, to established data systems helps create a much more natural search and analyze process. A more natural process creates scalability, enabling users to view, filter and consume greater amounts of information in less time.

    The potential impact of UX within the commodity markets is enormous. UX helps firms uncover key decision factors from piles of unstructured data. If a firm is interested in pipeline optimization, for example, visualization techniques can help compare possible operating regions, monitor key geophysical data and predict compressor station fuel costs. Additionally, user interfaces can be built over navigation APIs to track natural gas movement. Using visualization tools, UX teams can create interactive maps that provide insight into fuel consumption and emission rates on the global energy supply. By enabling users to view data in a visual way, firms can help ease the effects of overwhelming data volume and empower users to make better decisions.

    What does this entail?
    User-centered design processes include:

    • Contextual enquiries
    • User interviews
    • Persona data
    • Ecosystem creation
    • Application mapping
    • Wireframe development
    • Visual design
    • Data visualization


    There is a reason why few pieces of software are built today without considering user-centered design (UCD). The benefits of investing in the UCD process are monumental. A study, conducted by IT consultancy, Strategic Data Systems, found that firms that invest 11.5% of their product development budget in user-centered design see significant positive impacts on their ROI. These effects include decreased initial development costs and reduced risks of incurring extra development costs. Also, successful user-centered design has the potential to increase productivity and promotes user adoption. It can also decrease time to market by reducing the number of development cycles and shedding light on key feature sets.

    A user-centered design approach allows users to:

    • Model the decision-making thought process
    • Support user requirements by creating mental models and decision trees
    • Analyze which data best supports decision making and user tasks
    • Enable users to better manage task lists and make more informed decisions by positioning them in the modes of interaction
    • Create visual tools to filter and surface important data based on user requirements
    • Create a common interaction language


    Users interact with data in a number of ways. To accomplish the end goal of making a well-informed and confident decision, users must understand how they are going to leverage the data. Understanding what purpose each piece of data serves and how it will be leveraged can be thought of as a mode of interaction.

    Designing and visualizing data with the user in mind means focusing on the user’s current mode of interaction. Matching modes of interaction with current business functions can increase efficiency, thereby minimizing the total effort and cost for a given task. In the modes of interaction model, efficiency can be measured by calculating the percentage of the total time spent in each mode.

    Figure 1: Through Automation and UX Design, Users Spend More Time Transforming Raw Data into Insight.

    All modes are needed to effectively run an information business. However, most firms spend too much time in the beginning phases. There should be a focus to move the curve to the right (see Figure 1). By spending more time in the monitor and manage phases, employees are able to focus more on decision making as opposed to sifting through data, increasing both employee satisfaction and workflow efficiency.

    The modes of interaction include research, analyze, communicate, execute, monitor and manage.

    Research—This phase allows users to investigate the data landscape and determine which sets are most relevant to their business goals.

    • Function: A passive data gathering and discovery phase
    • Goals: Gain insight into specific business goals that are driven by tasks
    • Example: A research portal

    Analyze—Analyzing data allows users to dig deeper to filter out what is important. When looking critically at—and comparing—data, users can separate information from non-information and gain meaning.

    • Function: Highly interactive phase to filter and examine important information
    • Goals: Validate research or opinion, convince sponsors of key principles
    • Example: Application health monitoring system

    Communicate—Communication allows users to express and share views with others. This is critical to getting everyone on the same page and creating a shared view of information.

    • Function: Collaborative mode to connect teams
    • Goals: Keep others informed, integrate, share ideas, gauge feedback
    • Example: Universal inbox

    Execute—Business processes are task driven. Execution is the process of completing work and getting things done.

    • Function: Task-driven journey to completion
    • Goals: Limit distraction, focus on the most important tasks and goals
    • Example: Oil operations

    Monitor—Observation is the key to understanding. By watching various tasks and information, users gain insight into requirements and methods of completion.

    • Function: Passive experience by noticing alert and feedback mechanisms
    • Goals: Gateway into the other modes
    • Example: Gas nominations grid/Oil operations grid

    Manage—Managing provides an overview of all processes. Managing to-do lists and tasks helps users work together and ensure progress.

    • Function: Direct actions and tasks
    • Goals: Set client expectations, plan for portfolio/(trade) positions


    Copious amounts of data have caused many problems within organizations. As the sheer volume of unstructured information explodes, analysts are struggling to effectively find and process the data they need to do their jobs. UX design with a focus on data visualization can help address these problems while adding value in a variety of ways. By aligning software with how users typically manage information in their daily tasks, UX design provides a more natural way to search and analyze information. This allows analysts to more effectively and efficiently find and consume data. Analysts will find themselves equipped to make better decisions because it is easier to find and analyze the most relevant data.

    The Authors
    Parry Ruparelia

    Parry Ruparelia
    leads Sapient Global Markets’ User Experience and Visualization Practice in Houston with a particular focus on the capital and commodity markets. He has led user-centered design projects from conception to delivery for 15 years. Parry is an expert in creative leadership, facilitating stakeholder workshops, gathering and developing user requirements, providing project leadership in producing design concepts, and addressing key visualization and experience design opportunities.

    Matt Hopgood

    Matt Hopgood
    is based in London and co-leads Sapient’s Visualization practice. Matt has a background in business and digital strategy, creative and commercial leadership, web/application support, user-centered design (UCD), information architecture and content management. Recently, Matt has worked on P&L apps for energy majors, collaboration tools for market data providers, collateral management for a central bank, risk, balance sheet substantiation and mobile strategies for Investment Banks.

    Jennifer Evans

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