Microsoft Excel, which remains the universal charting application within the investment banking industry, has held a virtual monopoly over the finance world for the last twenty years. It is an amazing piece of software and unique in its tremendous scope. Whereas most applications serve one specific purpose, Excel offers something for every possible user, from the casual spreadsheet modeler to the professional computer scientist. For the advanced user, Excel‘s charting platform provides unlimited possibilities for data visualization customization.
But Excel’s charting flexibility comes at a cost. It requires a hands-on approach requiring users to build charts from the ground up. Some templates and user-defined styles are available, but the rich feature set of Excel’s charting framework precludes the easy use of these for all but the most standardized and static content items. Therefore, even minimal formatting of the simplest of charts requires at least some manual processing time to both create and update content. For investment bankers, who generate thousands of charts each year, this translates to significant time and huge costs.
Generally, investment bankers do not need (or know how to apply) the extensive flexibility provided by Excel
The vast majority of charts produced by bankers are simple bar, line, and pie chart variants which are subject to strict branding guidelines and institutional style guides. So all of the fully customizable formatting options available actually result in more processing time and more potential for inconsistencies and inefficiencies.
Pellucid’s charting platform, by contrast, can be thought of as providing a “filtered” feature set, focused on only the customizations that bankers need. Pellucid was designed by bankers, for bankers, so built into the platform is the importance of charts, and more broadly, presentations to the client coverage and pitching effort. Also considered are the tasks associated with building and updating the charts and tables that comprise a significant portion of junior banker time, which contribute to the long working hours and boring work that ultimately lead to job dissatisfaction.
Pellucid empowers its users to focus on higher-value tasks (or to just go to bed earlier) by releasing them from responsibility for the mundane tasks of charting, such as formatting chart components or keeping dynamic source data linked to the chart. Not to mention the need to select the correct visualization type and make other charting decisions (such as axis labeling, number formatting, series coloring and labeling, annotations and callouts, etc.) for which bankers typically have no formal training or expertise. Since Pellucid’s content library is pre-populated with loads of the most relevant and frequently used pitchbook content, the entire cognitive approach to turning raw data into a visual narrative is flipped. Changing from a bottom up, manual process to a top down one where users can explore and react to tangible, visual representations of the data they care about, select the appropriate graphics, and then apply data or appearance customizations for their particular situation.
Pellucid is leveraging its first-hand experience to institutionalize this knowledge across the investment banking industry
Pellucid is an evolution of the charting paradigm championed by Excel, but especially for bankers. Comparisons are therefore inevitable, and, in my view, instructive to highlight their fundamental differences. In Excel, charts are offered independent of data and classified by distinct visual attributes. For instance, users can choose between plotting their data with bar charts, line charts, pie charts, scatter charts, and so on. Pellucid, on the other hand, recognizes the difference in the value proposition (to the banks’ clients) between purely visual and stylistic choices vs. analytical approaches and moves the value proposition “upstream” by instead categorizing content by analysis type and data. For instance, some of the charting templates inside Pellucid include benchmarking charts, time series charts, and histograms, each of which has a visual variant that, if replicated in Excel, would use its “bar chart” type. Each of Pellucid’s chart “archetypes” has a universe of applicable data and metrics and a set of features that users can customize to alter the appearance of the chart or the analysis, based on the content’s purpose, sometimes in extremely distinct visual ways.
The implication of this is huge. Not only does Pellucid significantly speed up chart creation for its users by pre-processing abstract chart types into usable analyses, but it also disseminates data visualization best practices to bankers, who do not have the time to learn about charting in addition to their other responsibilities. This relates to everything, from the high-level choice of an appropriate graphic for a given data set to more nuanced concepts like concording dual axis labeling and optimizing data label placement. By embedding the knowledge and science behind visualizing data into its content Library, Pellucid is leveraging its first-hand experience to institutionalize this knowledge across the investment banking industry.
If you’re curious about the content or data available in Pellucid, email me at email@example.com to learn more.
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