Best Practices for Innovating 0-to-1 Products Within Large Enterprise Organizations

( Vol-12,Issue-4,July - August 2026 )

Author(s): Nitin Garg

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Page No: 054-061
DOI: 10.22161/ijaems.124.6

Keywords:

0-to-1 innovation, enterprise product management, market expansion platform, data-driven mapping tool, opportunity selection, site prioritization, experimentation, innovation governance, decision systems, de-novo growth.

Abstract:

This article examines how large enterprise organizations can reliably create 0-to-1 products under structural constraints such as multi-layer governance, legacy operating models, and uncertainty in market selection. The study focuses on one specific contribution developed by the author: a data-driven mapping tool embedded in a market expansion platform for de-novo growth and acquisition screening. The novelty of the article lies in combining research on opportunity framing, experimentation discipline, governance design, and innovation structures with an applied product case in which multi-source market data were converted into a visual decision system for location prioritization. The aim is to identify enterprise practices that increase the probability of launching a first viable product while preserving strategic alignment and decision quality. The material base combines recent peer-reviewed literature with an analytical reconstruction of the product work on a mapping platform that integrated reimbursement signals, patient-segmentation data, media-efficiency indicators, and market restrictions into a unified scoring logic. Methods include comparative analysis, analytical synthesis, and conceptual modeling. The results show that enterprise 0-to-1 success improves when opportunity selection is treated as a productized decision system rather than a one-time strategic exercise. The article is relevant for product leaders designing internal decision platforms, growth tools, and other data-intensive products inside large organizations.

Received: 29 Jun 2026; Received in revised form: 25 Jul 2026; Accepted: 31 Jul 2026; Available online: 06 Aug 2026

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