Question

a. Please relate the "Storytelling with Data" principles on color, font, and overall visual design to financial model design. Please post thoughts on presentation and communication styles, whether text or graphics are more effective, and for which audiences this might be true.

Note: please consider:

- Which colors might be appropriate/inappropriate to use in corporate finance model building.
- How the principles translate into building models in Excel or Word for financial reporting purposes.

Please read the Visual and Statistical Thinking and explain what Edward Tufte means by these concluding words:

b. Visual representations of evidence should be governed by principles of reasoning about quantitative evidence. For information displays, design reasoning must correspond to scientific reasoning. Clear and precise seeing becomes as one with clear and precise thinking."

c. Please provide your understanding of 5 rules of data visualization

Your responses must be original and based on your own words.

Answer 1

a) Charts and Graphs (Graphics) are More effective than texts as they Make the financial analysis readable, easy to follow and provide great data represntation. When an analyst uses charts, it is necessary to be aware of what good charts and bad charts look like and how to avoid the latter when telling a story with data.

Charts and Graphs (Graphics) are often included in the financial model’s output, which is essential for the key decision-makers in aThese decision-makers comprise executives and managers who usually won’t have enough time to synthesize and interpret data on their own to make sound business decisions. Therefore, it is the job of the analyst to enhance the decision-making process and help guide the executives and managers to create value for the company.

Audiences and Data Presentation

Internal Audience

An internal audience can either be the executives of the company or any employee who works in that company.

For executives, the purpose of communicating a data-filled presentation is to give an update about a certain business activity such as a project or an initiative. Another important purpose is to facilitate decision-making on managing the company’s operations, growing its core business, acquiring new markets and customers, investing in R&D, and other considerations. Knowing the relevant data and information beforehand will guide the decision-makers in making the right choices that will best position the company toward more success.

External Audience

An external audience can either be the company’s existing clients, where there are projects in progress, or new clients that the company wants to build a relationship with and win new business from. The other external audience is the general public, such as the company’s external shareholders and prospective investors of the company.

Graphic presentation Mosts fit to the internal audience for easy decision making

Colours used in financial Modeling

Blue – best used for inputs that make up historicals, assumptions, and drivers

Black – this color should be used for calculations and references on the same schedule or sheet

Green – references from another schedule or sheet should be exemplified in green

Red – red represents caution and, as such, should be used as a warning to another user or to link to another model

Dark Red – a deep, dark red is appropriate for a formula linking to databases like Capital IQ

Principles and practices in building financial model

1. Clarify the business problem and intended goal

• What problem is this financial model designed to solve?
• Who are the end users?
• What are users supposed to do with this model?

2. Try to keep the model as simple as possible

• What is the minimum number of inputs and outputs required to build a useful model?
• Remember that the more assumptions a model has, the more complex it becomes.

3. Plan your model structure

• Plan how the inputs, processing, and outputs will be laid out.
• Try to keep all your inputs in one place, as much as possible, in order to have a quick overview of all inputs and their impacts on the model.

4. Protect data integrity

• Utilize Excel tools to protect data integrity, including “data validation” and “conditional formatting.”
• (This limits other users ability to accidentally “break” the model).

5. Use test or dummy data

• Ensure that the model is completely functional and works as expected.
• Stress test it by putting in scenarios that should cause the model to run of out cash, grow at a flat rate (no changes), or that create other scenarios that are easy to sense check.

c) 5 Rules of data Visualisation

1) Make sure your data answers a question

Ask yourself what you want to know about your data. Then try to think of what people reading your graphs or charts will be looking for. The more specific you are, the better. Decide whether you prefer to explore and highlight the best (biggest, highest) or the worst (smallest, lowest) elements, compare specific data points, or maybe examine a trend over time.

2) Describe your data precisely

Explain the data to people to help them understand it. It’s easier when your chart is presented in an article or book, surrounded by text. But when it stands on its own—as an infographic, report, or presented on a dashboard within an app people use, you need to make sure each of your data points and the relationship between them are completely clear.

3) Use visual hierarchy

Visual hierarchy is the way you organize your visual elements, which also implies how important each of them is. It’s the order in which we perceive things, and it’ll help people make sense of your data and follow the story you want to tell. Flat and uninspired graphics that lack flow make it harder for people to make sense of your data.

4) Highlight what's important

This follows from your visual hierarchy. Highlighting can guide your readers through the data and draw their attention to the most significant parts of your graphic.

Make the data you want to focus on stand out from the rest. Here are some ways to do that:

• use bolder, brighter colors (but don’t go overboard),
• lighten or soften other elements to push them to the background,
• use thicker lines,
• draw borders,
• introduce eye-catching elements.

To keep your data clear, make sure the extra elements you introduce don’t conflict with your visual hierarchy.

5) Make your data readable

All of the points above essentially lead to this one. Because, just as text needs to be readable, so does data and visual information.