Use of A/B testing to determine the target state of a business process as part of organizational digital and business transformation

Abstract

   Objectives. The problem of correctly defining the target state of business processes, which determines whether the results align with a company’s strategic priorities, is key in the digital and business transformation of organizations. Current goal-setting practices, which rely primarily on expert assessments and stakeholder requirements, are characterized by methodological limitations, which include excessive subjectivity and insufficient validation of hypotheses. This work sets out to substantiate and develop an integrated approach to defining the target state of business processes that combines strategic goal-setting tools and verification methods to improve the validity of the proposed changes.    Methods. The study is based on a critical analysis of existing approaches to goal setting in transformation projects. To overcome the identified limitations, a synthesis of two methodological tools is proposed: the use of the objectives and key results (OKR) system to decompose long-term strategic priorities into measurable indicators of the target process state combined with A/B testing tools to experimentally test hypotheses about which changes in key results lead to the achievement of a strategic goal.    Results. The integration of OKRs and A/B testing is shown to create a closed-loop change management system. OKRs provide strategic navigation to ensure that the target state is consistent with the company’s mission. A/B testing, in turn, adds an empirical basis for goal setting, allowing for the confirmation or refutation of hypotheses about the impact of process changes on desired business outcomes based on data rather than intuition. By improving the adaptability of the process to environmental changes, this approach reduces the risk of implementing ineffective project solutions.    Conclusions. The proposed approach bridges the gap between abstract strategic goals and operational changes to improve methodological rigor in goal-setting through a synthesis of planning and experimental testing. Research prospects lie in scaling the approach to complex process architectures and interpreting A/B test results to adjust OKRs.