O que os modelos de market sizing não ensinam aos negócios? Uma análise estratégica sobre a dinâmica dos mercados e disponibilidade da demanda no contexto do setor de tecnologia

Abstract

Estimating market size is a fundamental activity for strategic decision-making, enabling firms to assess growth opportunities, resource allocation, and competitive positioning. Over time, classical models, such as the TAM, SAM, and SOM framework, have played an important role in providing a holistic view and structuring strategic thinking, standardizing growth narratives, facilitating communication with investors, and supporting comparative analyses. However, because they often adopt a more static and deterministic perspective, such models tend to reduce or overlook the dynamic fluctuations of supply–demand curves and adoption curves, potentially leading to distorted projections, analytical biases, and ultimately compromising the effectiveness of business strategies.In this context, this research aims to identify and examine contributions related to methods and models for market sizing within the B2B technology sector, seeking primarily to understand how market-addressing models translate market dynamism into reliable outcomes. To achieve this objective, the study draws on theoretical lenses from multiple fields of knowledge, including Schumpeterian Growth Theory, Disruptive Innovation, Diffusion Models, System Dynamics, Corporate Finance, Strategic Marketing, among others. The purpose is to highlight the multiplicity of factors that condition market movements and to emphasize the importance of incorporating such dynamics as a fundamental element in the success—or failure—of strategies aimed at identifying demand potential.The dissertation is composed of three articles. The first article consists of a Systematic Literature Review (SLR) combined with bibliometric analysis, covering the period from 2015 to 2025, with the objective of systematically mapping the existing scientific production on market estimation methods and the most recurrent calculation models. The study highlights the main conceptual, methodological, and empirical approaches employed by scholars who address the measurement of market opportunities across different contexts. Among the main findings, the results indicate that there is no significant volume of studies specifically focused on the B2B technology market, particularly in emerging economies, which requires researchers to draw on insights and empirical evidence from other sectors.Furthermore, the current research agenda on market sizing can be delineated into three major thematic clusters:(1) an operational stream, focused on inventory management, intermittent demand, and supply chain dynamics;(2) an analytical-technological stream, concentrating on the application of machine learning and deep learning techniques to improve accuracy, probabilistic forecasting, and dynamic market sizing; and (3) an economic-strategic stream, which connects demand estimation with topics such as platform contracting, market structure, and risk. The integration of these streams suggests a transition from a purely technical perspective toward a systemic approach, in which market sizing becomes a component of decision systems that combine predictive models, organizational structures, and the competitive environment. For business practice, the frontier of best practices lies in the combination of advanced probabilistic models with robust forecasting governance, translating predictions into strategic decisions regarding portfolio management, capacity planning, and go-to-market strategies. The value resides primarily in structuring decisions under uncertainty based on demand distributions and market scenarios. The second article presents a teaching case examining the rise and subsequent crisis of Facily, with the objective of enabling students to diagnose and differentiate the concepts of existing demand and sufficient demand, as well as to analyze the impact of operational friction, negative network effects, and shifts in the macroeconomic environment on the viability of new digital business models in emerging markets.Finally, the third article focuses on a deeper examination of the failures and limitations of traditional market sizing models. Based on elements drawn from different market-addressing models, the study develops two conceptual artifacts: the Integrated Market Estimation Framework (IMEF) and the Intertemporal Adjusted Market Model (IAMM). Both models are designed under the premise of integrating, with mathematical and statistical rigor, the influence of dynamic market factors. The central objective is to reduce 5 analytical errors and biases while providing a tool adaptable to diverse sectoral contexts and levels of analytical maturity, particularly within the B2B technology market.Despite promising initial indications, the artifact, currently at the Proof of Concept (PoC) stage, presents certain limitations. These include the need for further testing in real business operations in order to capture potential deviations, as well as the mathematical refinement of the functions used to calculate Market Size, with the aim of increasing the logical and scientific rigor of the formulas embedded in the application. These considerations outline the future research agenda for improving and scaling the artifact.