Chapter One — 1.1 Background to the Study

Over the past decade, the relationship between data-driven product decision making and time-to-market has become a subject of considerable debate among scholars and industry practitioners alike, particularly within the context of Selected Small and Medium Enterprises in Nigeria where operating conditions differ markedly from more developed markets.

Selected Small and Medium Enterprises in Nigeria presents a useful setting for examining this relationship precisely because the conditions there — structural, regulatory, and behavioural — differ from those typically assumed in the broader literature, most of which draws on evidence from more developed economies.

1.2 Statement of the Problem

Despite a growing body of literature on data-driven product decision making, there remains limited consensus on the precise nature of its relationship with time-to-market, particularly within Selected Small and Medium Enterprises in Nigeria. Many organizations continue to make decisions about data-driven product decision making without a clear, evidence-based understanding of how those decisions ultimately affect time-to-market. This gap between practice and empirical understanding is the central problem this study seeks to address.

1.3 Objectives of the Study

1. To examine the effect of Data-Driven Product Decision Making on time-to-market in Selected Small and Medium Enterprises in Nigeria.
2. To assess the extent to which data-driven product decision making influences time-to-market within the study area.
3. To identify the challenges associated with data-driven product decision making in relation to time-to-market.
4. To recommend strategies for optimizing data-driven product decision making in order to improve time-to-market.

1.4 Research Questions

1. What is the effect of data-driven product decision making on time-to-market in Selected Small and Medium Enterprises in Nigeria?
2. To what extent does data-driven product decision making influence time-to-market within the study area?
3. What challenges are associated with data-driven product decision making in relation to time-to-market?
4. What strategies can be adopted to optimize data-driven product decision making in order to improve time-to-market?

1.5 Significance of the Study

Beyond its academic contribution to the field of product management, this study has practical value for management teams within Selected Small and Medium Enterprises in Nigeria seeking to understand how data-driven product decision making translates into measurable outcomes around time-to-market. It is equally useful to students and future researchers looking for a localized empirical reference on this relationship.

1.6 Scope of the Study

In terms of scope, this MSc study confines itself to Selected Small and Medium Enterprises in Nigeria, focusing specifically on how data-driven product decision making relates to time-to-market within that setting. Findings are interpreted within these boundaries rather than as universal claims applicable to every organization or market.