This page gives descriptions and links to our extensive library of Tellusant Quick Reads—mostly two-pagers on important management topics relating to our expertise.
Effective data unification is key to corporate performance and represnts a significant profit and growth potential. However, most firms do not realize this and delegate these efforts, if any exist, to low-level employees.
The Democratic Republic of the Congo (DRC) may be the world’s second most difficult country to analyze (after North Korea). This Quick Read shows that every country’s economic conditions can be quantified at the subnational level.
Tellusant covers China with income distribution and other metrics at a detailed level. China’s 1st level subdivisions are the 31 provinces and equivalent units. However, the average province has a population of 45 million people. Too many for good analyses and insights. We therefore work at the 2nd level subdivisions with 343 entities.
Who do we compete with? We use the Pepsi brand to expand the definition from the obvious to the sublime. We divide the reasoning into a qualitative example and a mathematical theory.
Nothing is forever, not even giant companies. It is well known that companies grow, plateau, and fade or disappear. In the short term, the Fortune top 10 US companies in 2022 saw seven new entrants and seven exits compared to 2012. This is not unique to the tech era. Churn is the norm decade after decade.
The middle class is often talked about but seldom well defined. Before we embark on an exposé on trends, we therefore define socioeconomic levels—what we call the ‘Income Level Standard’. We then show trends.
Why are subnational data valuable? Research shows that around ⅓ of corporate profitability is determined by the quality of subnational adjustments.
Here is advice for current and future business analysts at large corporations or consulting firms. Your most important goal is to add value. This means thinking long and hard about whether you copy, tabulate or analyze information. Only analysis truly adds value.
Companies are often described as decision factories. Based on the academic literature and extensive interviews, we created this decision-making framework that can be used to organize the strategic management process, and more.
How do we evaluate whether a company is successful? There are many frameworks but let us draw attention to our chairman’s Harvard Business School professor William Fruhan’s markers of success, from his brilliant book ‘Financial Strategy’.
Ernst Engel, a German economist and statistician, published what is now known as the Engel curve in 1857. He found that as household’s income increased, the share of the income spent on food decreased.
How does demand for a category or industry change with disposable income and how do you go from analysis to strategic implications? We use global beer demand to illustrate.
DuPont analysis is one of the most fundamental concepts in financial theory. Here is a new take using what we call DuPont curves.
TelluBase is the underlying macro database that feeds into our products. It covers 218 countries, 2,600 cities, and 2,500 subdivisions (states, provinces, etc.).
How can we estimate future exchange rates (XR) for strategic purposes (3-10 years out)? The answer is that a random walk model does the best job. Understanding the logic of future XR may seem difficult, but it is not. We tend to make it difficult though.
Creating a forecast is only one part of prediction. We illustrate with an example of how a country’s market for a category will evolve.
We often work with beverages companies, covering categories from bottled water to wine. A fundamental metric to understand when analyzing market growth is how much water the human body needs.
Cities typically grow faster than their countries in emerging markets, and the middle class (and above) grows even faster. We took the ten largest cities in Latin America to illustrate the point.
How will the global middle class evolve over the next 20 years. At a torrid pace, but with different regions leading the way.
How to supercharge growth is an eternal issue for CEOs, especially in mature industries like FMCG. Here are the fundamentals The Quick Read is based on our academic research.
Tellusant’s first official Roaring Forty list is out. It ranks the largest U.S. companies by value added—economists’ preferred way to measure size. Alphabet rose to the top in 2023, overtaking Apple.
Why is market share important? This Quick Read presents compelling answers to this question based on research by Bhattacharya et al.
Household income is the most important driver of demand for almost all categories globally. It is so overwhelmingly important that other demand drivers seemingly pale in comparison. However, this is only partially true. Path diagrams explain why.
It is bad practice to evaluate consumer goods markets based on gross domestic product (GDP) per capita. Why should GDP have anything to do with consumer demand?
Tellusant applies Tanis Furst’s food choice framework when trying to understand consumer behavior. We use it to design consumer surveys, to specify statistical analysis, and to have informed discussions.
Why are companies profitable? It is a fundamental question and yet few executives have good answers. There are verily four sources of corporate profits.
What should large companies do when experiencing a performance crisis? The answers are situational, but we have some general observations based on a simple framework.
Strategic forecasting is a new field in management. The strategic forecast makes 5–10-year predictions on demand, consumer groups, and other factors critical to strategic plans.
How are TelluBase data used? We highlight six examples in this Quick Read. They cover a wide range of industries and applications.
In the evening of Wednesday, April 2, 2025, the White House announced global tariffs. This is an event analysis that quantifies impact on GDP growth.
How should we look at country risk? We present the risk of nations based on a quantitative analysis. We divide risk into financial and market (demand) components. Looking at risk this way gives a strict definition to what is meant by risk. It is in line with Frank Knight’s observation: Risk is a knowable probability distribution.
Surprisingly, marketing spend is not a widely tracked metric. As part of building a model for the cost of forecasting errors, we needed this, R&D spend, and capex. Therefore, data were collected for large U.S. companies, one by one.