Let’s hear it for Microsoft Excel: the spreadsheet just celebrated its 30th birthday. For a computer program, that’s some impressive longevity, and a testament to its influence.

For decades, the wealth management industry has relied on it — and it’s still used to manually manage the vast majority of the $120 trillion in global personal wealth. But, speaking from a design perspective, Excel is purpose-agnostic: the platform doesn’t care if you use it to plan your retirement or make a grocery list.

With the rise of beautiful, intuitive applications for everything from ridesharing to on-demand food delivery, consumers’ expectations around design have risen too, and this includes how their wealth is managed and explained to them. With an expected increase in digital evolution in 2017 for wealth management, what comes next?

First, let’s explore some of the key limitations of Excel.

For one, Excel’s data entry process is agnostic to what data is being entered. In other words, the spreadsheet doesn’t have a way of knowing whether the information you’re entering in its cells, rows and columns is financial data or the result for your weekly fantasy football league. And it doesn’t really care.

Excel’s uniform, clunky grid system can be difficult to decipher, too. For numerically-inclined wealth managers that have been trained on the program for their entire careers, this might not be a big deal.

But for those end clients — the investors and asset owners they serve — Excel’s drab, featureless UI can prolong and complicate conversations about money rather than simplifying them. This is particularly true for larger data sets, where it's easy for things to get lost in the noise.

Excel is purpose-agnostic: the platform doesn’t care if you use it to plan your retirement or make a grocery list.
Excel is purpose-agnostic: the platform doesn’t care if you use it to plan your retirement or make a grocery list.

It’s time designers helped Wall Street catch up and finally meet expectations — but in wealth management, we have two different main types of target audiences: the wealth managers, and their clients.

For UX designers right now, it’s always tempting to take inspiration from brands like Apple, which prioritize intuitiveness above all else, and whose interfaces just work, 'the way they are supposed to,' within a predefined range of functions.

Designing for wealth management, however, is a little different. Wealth managers will use any product as a tool for communicating complex financial data to their clients in simple terms.

Our design team at Addepar has determined that we need to leave some of the intuition to those who understand that complexity best, and in the context specific to their clients. We intentionally refrain from over-simplifying our product, because the wealth managers themselves are the ones providing the services, and what we might assume is intuitive, they consider limiting.

We learned a few key lessons in designing a product that resolves Excel’s ambiguities without compromising on the functionality and complexity a wealth manager would expect.

When you’re designing a technology platform that handles data, think of your data set as a package in the mail, and your UX as the delivery method for the package.

The size of the data set plays a crucial role in how you define the UX: you need to know whether you’re delivering the data in a bookbag or a UHaul truck, or, as is the case with financial data, some combination of the two — and you won’t know ahead of time. The problem with Excel is that it does a serviceable job at handling either, but is not well suited to displaying interactions between the two.

For example, if you’re a wealth management professional, you may be responsible for as little as one portfolio, or as many as 500 portfolios. Your tech platform needs to be able to elegantly accommodate either of those possibilities, and everything in between, through interfaces that are easy and intuitive to navigate.

On top of that, you’ll need those portfolios to be sortable and searchable in the order that makes sense for your unique practice — for some, this might mean alphabetical, for others this might mean chronological, and for still others this might mean enabling the ability to pin certain items in a list out of order.

(Our pro-tip for this: we’ve utilized the EmberJS framework, which enables us to build a single component (link) that we can utilize throughout our application, for any and every unbounded data list.)

Working with clients’ portfolios, wealth managers often need to look up information about a specific financial instrument out of a list of thousands, or visualize just a few investment positions to get a sense of their relationship to a broader long-term strategy.

To make all options available on command to the user without making them all visible, or the data within them all loaded into the platform simultaneously (essential for preserving performance on a cloud platform), this requires some clever UX design.

Our solution to this: a tabular architecture that allows users to self-determine how they’d like to visualize their own data. What we call "groupings" allow users to set what the table’s rows represent, while what we call "columns" allow users to see the data they’d like to see on a row by row basis.

With robust filtering, users can filter not just a particular list of data or items, but the entire universe of data that they are currently examining, visualizing, or reporting upon.

Perhaps the biggest ambiguity we’ve sought to resolve is the use of color in visually displaying financial information. In Excel, colors for pie charts, bar graphs and so on are generated arbitrarily, have an inherently “noisy” quality to them (red, yellow, green, blue, etc.) and have no inherent relationship to the context of the data being presented.

A primary design goal of any post-Excel financial tool should be to reduce this noise and maximize the signal, whether that is through the use of clean typography, whitespacing, or the progressive revelation of information on an as-needed basis. We want to bring greater transparency to finance — so we explicitly reserve color for showing distinct subsets of data.

We don’t do this for the adviser’s benefit — as a rule, they’re adept with numbers and are able to distinguish the most important information from a spreadsheet alone. It’s their end clients that often do not always share that same fluency for understanding numbers, but for whom maximum transparency is the most crucial.

Ultimately, there are often a finite number of statistics that the end client is most interested in total net worth, for example — and making those numbers readily apparent rather than burying them in 8-point font or obscuring them in rainbow-colored charts is the design ambiguity we’re most focused on solving for.

This approach, which allows some of the ambiguity to be defined by the user on the back-end, translates to flexibility and ease-of-use on the front end — and allows wealth managers to preserve that crucial element of the human touch.