Decision-making in information technology investments using synthetic control group analysis

Purpose The paper aims to adopt the synthetic control group (SCG) method for the IT-driven performance analysis and validate this tool focusing on three IT solutions: Customer Relationship Management (CRM), Human Resource Management (HRM) and the internet of Things (IoT). Design/methodology/approach Based on the literature review, this paper examines the strengths and weaknesses of various research designs employed in studies investigating IT-driven performance and presents a detailed procedure for implementing SCG research design. Drawing from a dataset of manufacturing companies from one of the Easter-European markets from 2000 to 2021, the study constructs counterfactual conditions to assess the performance effects of CRM, HRM and IoT. Findings The SCG method leverages historical data and sophisticated statistical techniques to establish causal relationships between specific IT adoptions and firm performance. The empirical findings demonstrate the effectiveness of SCG in yielding reliable results across three experiments involving CRM, HRM and IoT. Practical implications The SCG method has high potential as it can deliver evidence-based decision-making for IT implementation. Before resource-intensive investment in IT is initiated, a company can find similar cases and look for evidence that they were effective for other firms in the past. Originality/value This study contributes to the field of technology management by introducing a new tool for evidence-based decision-making in IT. By surpassing traditional approaches, the study offers a more comprehensive and reliable evaluation, providing accurate insights into the true impact of IT on overall organizational performance.