Data-Driven Decisions - Why Simple is Often Better

Information and knowledge are the new coins dictating business organizations’ operations today. Today, companies have more information in their hands than they can handle – and that is a strength – but a strength that, at times, can become a strength. Often, when faced with mountains of data, analysts and decision-makers fall into a common trap: it goes a little overboard and makes things much more complicated than they need to be when it comes to analysis. While we strive for more data and complex infographics, sometimes, ones and zeros are the key to getting the job done. Here is why choosing retention of data complexity deliberately results in better clarity for analysis and improved decision-making.

Man pointing to a laptop

Simplicity Reveals the Signal in the Noise

Imagine a chart with numbers, bars, and pie slices in every rainbow color. It is very colorful, but what should the viewers glean from it? A lot of the time, however, the most explicit messages are obscured by much noise. A low-complexity data display assists in filtering out the main components of ‘the signal’ from ‘the noise.’ Simple and uncluttered charts and graphs focusing on critical metrics help those interested immediately identify trends, anomalies, and actionable data. Often, a simple line graph or one issue number can convey more than a set of beautifully designed customer-facing dashboards.

Collaboration

Accessible Insights for Better Collaboration

Not everyone is a data analyst, nor should they have to be. When data analysis becomes overly complex, it risks alienating the people who need to use it — your colleagues, leaders, or clients. When decisions and judgments are restricted or challenged with a twist, they threaten to reach those they aim to achieve: your colleagues, leaders, and clients. This accessibility means that those who approach the document might easily understand what is presented to them regardless of their nearness or outright disconnection from computer science. It gives individuals an opportunity to contribute, giving solutions in more depth and leading to better solutions that language barriers have not missed. The approach differs from sharply learning the content of visualization and trying to understand what it says, but instead encourages teams to sit down and start a conversation around the practical consequences of what they are seeing and how they may want to address these in the future.

Complex Does Not Mean Accurate

A common misconception is that more sophisticated analysis automatically yields more accurate results. Complexity appears to be compounded by new layers of errors and assumptions. For instance, complex statistical models can produce accurate numbers, but they can be woefully unclear, and as such, decisions made from them are made from misinterpreted figures. Simplicity also ensures that nobody misunderstands anything, enhancing the probability of users taking action.

Data Visualization

Simple Visuals Drive Action

Data is valuable, but only if it leads to action. Line charts depicting a sales trend or pie charts representing demographic sales must be the simplest way to inform decision-makers so they can easily understand what is happening and, most importantly, what must be done. It is as simple as that; indeed, they offer lucidity, timeliness, and purpose that detailed models may easily overshadow. The fewer barriers such insights present, the better the created picture, and decisions can be made quicker. Indeed, if an analysis is performed, it implies that a particular action will follow, so where is this action?

Focus on What Matters

While fancy tools and detailed analytics have their place, remember that data analysis aims not to create impressive charts or dazzling presentations. That may be true, but it is to discover information that leads to decisions being made. I urge you to strip it down and concentrate on what is necessary to provide actual value to your data.

So, the next time you dive into data, ask yourself:  Am I using complicated language, or am I using plain language to ensure the donor gets my message? Whether you are an analyst, a manager, or a business owner, the formula should be “Keep It Simple.”