Empowers with Reasons behind Numbers
This Data Science-powered report presents a forward-looking analysis of the latest company financial results and explains the drivers behind sales and profits at global, segment, product and geography levels. Each important element is visualized and helps in forming a comprehensible understanding of ongoing company processes. The report also contains a high-quality printable dashboard which enables grasping the “whats” and “whys” within a minute. It can be used to support important decisions, to win an executive argument, in a presentation or in strategic analysis.
Additionally, the report includes next-quarter forecasts derived from current company drivers and economic environment and contains expectations for the upcoming six to twelve-month period (when applicable). This knowledge helps not only to be perfectly informed but also continuously expands the circle of competence on companies, products, industries and geographies.
Public companies continually release materials such as earnings reports, industry and investor presentations or management discussions. Taken as they are, earnings reports divulge very little valuable information which is often kept scarce by the companies themselves on purpose.
The publisher's analysis brings meaning to earnings reports by providing the reasons behind reported numbers. The report answers questions such as: “Why net sales decreased 8.99%?“ or “Why EMEA revenue decreased 7.39%?”
It’s those answers that reveal the processes called drivers that are shaping a company’s future. Being aware of them gives the ability to act preemptively on events that will become known to the public months later.
Using this knowledge, the publisher starts assessing the direction and magnitude of each driver and predicts with a high level of confidence the company’s future performance. Their technology helps to selectively reduce the large volume of data into those nodes of information that carry real value and can empower personal knowledge in an efficient manner.
As an investor, business leader, adviser or money manager this will greatly reduce the margin of error when taking action against the upcoming risks that surround us.
Table of Contents
1. Introduction
2. Coca-Cola Q2 2020 Earnings Retrospection
3. Coca-Cola Q3 2020 Earnings Analysis
3.1. Net Sales
3.2. Operating Income
3.3. Net Income
3.4. Operating and Net Margins
3.5. Cash Flows
3.6. Beverage Categories Volumes
3.6.1. Sparkling Soft Drinks
3.6.2. Juice, Dairy & Plant-based Beverages
3.6.3. Water & Sports
3.6.4. Tea & Coffee
3.7. Geographic Segments
3.7.1. EMEA
3.7.2. Latin America
3.7.3. North America
3.7.4. Asia Pacific
3.8. Global Ventures Segment
3.9. Bottling Investments Segment
4. Forecast
5. Appendix: Dashboard
Executive Summary
Coca-Cola underwent significant changes in the past several years in an attempt not only to diversify from sparkling soft drinks (SSD) but also to find high-growth potential verticals. The company’s efforts led to the $4.9 billion acquisition of the UK-based Costa Coffee which became the primary factor behind Coca-Cola’s positive results in 2019 with net operating revenues rising 8.65% for the full year.
The publisher found out that Coca-Cola’s structural profile has changed significantly and the company’s reliance on its away-from-home business was growing. According to their assessment, the companies tend to underestimate the levels of uncertainty inherent to the travel, tourism and similar businesses which are very hard to balance. In addition, Costa’s growth contributed substantially for this shift with the tendency to have an even bigger impact in the future.
From the publisher’s perspective, one thing COVID brought is to reveal the underlying risk structure of The Coca-Cola Co. Nonetheless, their analysis identifies a lot of substance in Coke’s traditional defensive strength and according to them the company’s management is showing remarkable agility into leveraging it in the current harsh environment.
Companies Mentioned
- Coca-Cola
- Costa Coffee
Methodology
The publisher employs advanced Data Science methods such as probabilistic inference and algorithmic reasoning to establish causal relations between outcomes such as company sales and profits, and the hidden processes that drive them. Furthermore, their methodology uses stochastic processes analysis to model and predict company performance in a period of three months ahead and formulate high-probability expectations for the next six to twelve month intervals.
The publisher relies strongly on analyzing inherently uncertain streams of information and all analytical output represents the highest confidence results of a specific study with two or more such results presented in the report whenever they discovered that several factors had similar impact on a target variable.
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