The Digital Tool Experience Trap Phenomenon
A Mixed-Methods Study on How Familiarity Bias Impacts Corporate Technology Decisions.
Abstract
Decades of behavioral science suggest these choices are systematically distorted by cognitive and social biases (e.g., status‑quo bias, sunk‑costs, confirmation bias). Although IT project risk is well documented, there is little cumulative, cross‑industry evidence on how European executives themselves experience and manage decision bias during software selection. Nor are there validated tools to diagnose and mitigate such bias at decision time. This study will fill that gap through a sequential explanatory mixed‑methods design: (Phase 1) a pan‑European survey of executives who made at least one significant software decision in the past 36 months (N=250, SMEs and large firms), and (Phase 2) semi‑structured interviews with a theoretically sampled subset (N=20).
Outcomes include (1) awareness: quantifying which biases are most prevalent, under what conditions, and how they relate to post‑decision worry/regret; and (2) intervention: development and psychometric validation of a Software Decision Bias Assessment (SDBA) that organizations can use ex ante to reduce avoidable error. The study integrates bounded rationality, dual-process, and prospect-theory accounts with organizational influences (incentives, power dynamics, regulatory context). It provides a practical, evidence-based instrument and decision checklist tailored to European contexts. Evidence of extreme tail risks in IT programs, widespread algorithm aversion, and the availability of a robust Decision Regret Scale to adapt for leadership contexts motivate the design.
Why this study
Major IT programs exhibit fat‑tail risks; one large international study reported average overruns around 27%, with a “Black Swan” subset incurring ~200% cost and ~70% schedule overruns—consistent with planning fallacy, optimism bias, and escalation of commitment. These dynamics make the quality of executive decision processes in software selection materially consequential (HBR, 2011).
Across professional domains, cognitive biases reliably shape high‑stakes judgments, including those of experienced decision‑makers. Integrative reviews document robust effects of anchoring, confirmation bias, availability, loss aversion, and overconfidence on professionals’ decisions—precisely the heuristics activated by uncertain, time‑pressured, politically charged procurement choices (Berthet, 2022).
European relevance and gap. European firms are active purchasers of advanced software (e.g., AI systems), with EU‑wide surveys showing substantial adoption and an emphasis on external sourcing—making executive selection choices frequent and consequential (European Commission, 2020). At the same time, European procurement regimes (especially public‑sector tenders) shape selection processes (Boonstra & van Offenbeek, 2018), and EU research documents forms of “home bias” in procurement markets (Hanspach, 2023). However, existing IS and procurement literatures in Europe focus on regulation, case studies, or user-level adoption rather than executive cognitive bias during cross-industry software selection; there is no validated, Europe-normed instrument to assess and mitigate such bias during decision-making.
A small but growing managerial stream proposes bias‑awareness frameworks for ERP adoption. Yet, these are not psychometrically validated across diverse European firms and languages—underscoring the need for a rigorous, applied psychology approach (Davidson et al, 2024).
The preceding analysis highlights a critical and costly paradox: while digital technology is a key driver of corporate strategy, the very decisions that acquire these tools are prone to systematic, predictable judgment errors. The "fat-tail risks" of IT programs are not merely technical or project management failures; they often stem from the cognitive biases of the experienced leaders who champion them. As documented, a significant gap occurs in understanding and mitigating these biases, specifically across Europe's diverse corporate landscape.
To address this, our research aims to translate general theory into a concrete, evidence-based understanding of this Digital Tool Experience Trap.
Phase 1: Establishing the Quantitative Baseline
The first phase of our sequential explanatory mixed-methods study directly addresses this knowledge gap through a broad quantitative survey. This questionnaire serves as the primary instrument for gathering data to map the landscape of decision-making across European firms. Its purpose is twofold:
To measure the prevalence of specific cognitive and social biases (e.g., confirmation bias, status-quo bias, escalation of commitment) in recent, high-stakes software selections.
To identify the factors——such as industry, company size, and decision-making structures—that may amplify or mitigate these biases and their link to post-decision outcomes like regret or worry.
This data forms the foundation of the study. It will enable the first robust, cross-industry profile of executive decision-making challenges in this domain and inform the development of the Software Decision Bias Assessment (SDBA) tool.
Your direct experience is essential to achieve this. We invite you to contribute your valuable perspective to this foundational phase of the research.
Are your IT investment decisions truly objective?
To survive in today’s volatile business environment, bold decisions are unavoidable. With rapid digital transformation, software choices now shape organizational futures. Yet, as our research aims to explore, many such decisions are subject to unconscious decision bias. The EBT Hub’s working group “Digital Tools for Transformation” is currently exploring how decision bias impacts IT software solutions in companies across industries and sizes in Europe.
To this end, we’ve launched a short survey as part of a professional study. Your input will help identify patterns, challenges, and best practices in software-related decision-making.
Why participate?
If your company has implemented an IT system within the past three years, investing just 10 minutes can give you access to insights from other companies’ experiences. You’ll also have the option to register for a follow-up qualitative study.
Participate now!
Let’s start: Please answer the following questions based on your company’s experience with IT system implementations in the past three years.