Inventory accuracy as a capability: building maturity and customer value

Foreword: How to Reduce Inventory Inaccuracy

Retailers make substantial investments in forecasting and replenishment systems; nevertheless, our research consistently indicates that over sixty percent of inventory records contain inaccuracies. This underscores the principle: inaccurate data yields unreliable outcomes.

While effective forecasting and replenishment are essential for maintaining well-stocked shelves, it might be assumed that all retail organisations would actively reduce inventory record inaccuracy. However, this research reveals that only select retailers have implemented comprehensive measures—including processes, incentives, technological solutions, and a top-down culture—to improve and sustain inventory record accuracy across their operations.

Furthermore, among companies that prioritise inventory record accuracy, there is a clear recognition of its critical link to achieving customer satisfaction.

This report presents practical tools and best practices designed to help retailers assess their current standing within a new maturity model for inventory record accuracy and evaluate how closely their business aligns with a framework that connects these efforts to customer satisfaction.

In today’s evolving retail environment—where consumers and third-party platforms increasingly demand real-time inventory transparency—the necessity of accurate inventory records has never been greater. To prevent lost sales and diminished productivity, it is imperative to adopt a unified, enterprise-wide approach to addressing this challenge.

We would like to thank Professors Glock, Rekik and Syntetos for carrying out this research and to the retailers who helped contribute to the thinking and the findings presented in this report.

As with all the research undertaken on behalf of ECR Retail Loss, it would not be possible without the active support and involvement of the retail community and the many employees who generously give their time to participate in the most meaningful of ways. We thank you all for taking the time to share your thoughts and experiences – by working together we can Sell More and Lose Less!

Finally, I encourage you to not only read and share this report but also to read the accompanying reports that highlight the sales benefit of improved inventory record accuracy, and the different ways that retailers can define inventory record accuracy. Together, these reports can act as a road map to organisations as they seek to tackle the inventory record inaccuracy problem and unlock the lost sales potential and grow customer satisfaction.
Further details of all ECR Retail Loss research can be found at: ecrloss.com.

John Fonteijn
Chair of the ECR Retail Loss Group

Executive Summary

Academic research and practical experience suggest that reliable inventory information is foundational to modern retailing. And there is a shared understanding amongst different functions in most organisations that inventory record accuracy is more than a technical issue; it is an enabler of increased sales and customer satisfaction and one of the most important drivers of e-commerce success. Yet, organisational practices vary considerably, and such variation raises two interesting questions: i) what constitutes maturity when it comes to inventory record accuracy, and ii) how investments in dealing with inventory record inaccuracies (IRI) may eventually translate to operational and customer-facing benefits?

In this report we unpack both issues, and with the support of the retail community we put forward two practical frameworks to assist retailers in evaluating where they currently stand, and to guide their progression towards zero IRI and high customer satisfaction. The first is the IRI maturity model that consists of several pertinent dimensions against which organisations can measure themselves and identify opportunities for improvement and reduce inventory record inaccuracy. The second is the IRI pyramid of customer satisfaction, which illustrates how improvements in inventory record accuracy can drive customer-facing benefits – showing why IRI should not be seen as a “back-office hygiene” topic, but as one of the most powerful levers for winning and retaining customers. Both frameworks should be useful for any organisation working towards zero IRI and wishing to embed that journey in their decision-making routines and performance culture.

This is the first report to treat inventory record accuracy as a capability, and we are proud to have worked closely with the retail community to jointly drive forward the agenda in IRI research and practice. The findings reported here are the outcome of 25 detailed interviews with retail practitioners and experts across the globe. The purpose of the interviews was two-fold. First, to understand what metrics are being used towards IRI measurement, and second, to understand how IRI practices are embedded into wider organisational practices and structures. The former part, i.e. the inventory record inaccuracy metrics , is separately published in a companion report that is freely available to download in the ECR website. The latter constitutes the focus of this report.

We firmly believe that the journey towards zero IRI is one of the most important ones in modern retail operations and we hope this report will make obvious the fact that IRI deserves a central place in retail strategy. Retailers who succeed will not be the ones who simply “measure better”, but those who build the organisational conditions for consistent and proactive accuracy management, and those who recognise that in this ever changing retail landscape, accurate inventory records are now a more important driver of customer value than ever before.

For loss prevention teams looking for a starting point, our pillar explainer on inventory record accuracy covers the broader business case, the original sales lift research, and a five-step action plan for getting started.

The same academic team also runs inventory record accuracy training where the three Professors look at practical implications of their research. The 2026 IRI Training course in Cardiff on 9 and 10 December covers the drivers of stock record inaccuracies, how to articulate the business case for improvement, countermeasures to enhance accuracy, and how to use research insights in practice. It is designed for loss prevention, supply chain and operations leaders and uses interactive exercises and gamification alongside academic instruction.

Introduction

Inventory record accuracy is more than a technical issue – it is a capability that shapes a retailer’s ability to deliver on its core promises to customers. From ensuring product availability and operational efficiency to enabling seamless omnichannel experiences, reliable inventory information is foundational to modern retailing. Yet, this capability is not built overnight. It develops over time through a combination of technological investments, organisational routines, and cultural commitment to data reliability.

The importance of accurate inventory records becomes evident when considering their role across retail operations. At a basic level, inventory records inform replenishment decisions – triggering orders when stock falls below defined thresholds (e.g., [1]). But their influence extends far beyond logistics. In today’s omnichannel and e-commerce environments, inventory records also power product availability information shown to customers, support order fulfilment from stores, and determine the success of click-and-collect and home delivery services. Inaccurate inventory records, therefore, can result not only in operational inefficiencies but also in lost sales, customer frustration, and reputational damage [2].

Figure 1 illustrates how inventory record inaccuracy (IRI) may lead to delayed replenishment decisions and “hidden” stockouts that are not visible in the system.

Figure 1. Impact of IRI on replenishment timing and hidden stockouts 1

Unfortunately, IRI remains a persistent and widespread problem. Prior research shows that inventory records are often wrong [2, 3]. Discrepancies may arise in either direction – with the system showing more or less than what is available. Figure 2 reports a typical distribution of IRI in the grocery sector, showing that only about 35% of inventory records are correct (IRI = 0), while the remaining observations form substantial tails that reflect frequent large over- and understatements of stock.

1 Figure 1 illustrates the operation of a typical re-order point order quantity inventory control system, commonly employed in the retail sector. When the system inventory drops to the reorder point, this automatically triggers a replenishment order which is received after the lead time. If the physical inventory is different (less in this case) than the system inventory, the replenishment order is not placed when it should, leading eventually to a stockout.

Figure 2: Empirical distribution of IRI in grocery retailing

The causes of IRI are numerous and well-documented, ranging from theft, damage, and returns mishandling to system limitations and process failures [2, 4]. The consequences have also been repeatedly discussed: negative discrepancies can lead to stockouts and missed sales, while positive discrepancies may cause unnecessary replenishment and excess stock [3]. In both cases, the retailer’s ability to operate efficiently and meet customer expectations is compromised – with potentially serious financial consequences [2, 3, 5].

Evidence from prior research commissioned by ECR, and delivered by the authors of this report, illustrates the commercial importance of addressing IRI. A field experiment comparing test stores undergoing stock audits with control stores revealed sales uplifts of 4% to 11% following the correction of inaccurate records [3, 6]. These results underscore the tangible business impact of improving inventory record accuracy – not just in theory, but in day-to-day retail operations.

Beyond lost sales, IRI can undermine staff productivity and lead to unnecessary operational costs. Store associates may spend time searching for items that are not in stock or troubleshooting system discrepancies instead of serving customers or executing merchandising plans. At scale, these inefficiencies can erode margins and constrain organisational agility [3]. Moreover, inaccurate stock records introduce risks into financial reporting, planning, and performance management – especially in sectors with tight margins, high inventory volumes, or complex assortments.

Given these wide-ranging implications, the retail sector increasingly recognises that improving inventory record accuracy is not just about fixing individual errors – it requires building and embedding the right capabilities. However, this is not a uniform journey. Some retailers are just beginning to systematically measure and manage IRI, while others have embedded it into performance dashboards, cross-functional routines, and strategic initiatives. This variation raises important questions: How mature are current approaches to inventory record accuracy? What constitutes more advanced practices? And how does investment in IRI management translate into operational and customer-facing benefits?

To address these questions, we conducted a qualitative interview study with a diverse set of professionals across the retail industry. Details on the study design and sampling can be found in Appendix A. Our aim was to move beyond the mechanics of IRI measurement and investigate how inventory record accuracy is understood, managed, and developed as an organisational capability. We explored not only what metrics companies use, but also how they embed IRI practices into broader operational routines, reporting structures, and customer value propositions. The former part, i.e. the metrics used, has already appeared in a companion report we have published, and which is freely available to download in the ECR website. The latter constitutes the focus of this report.

Based on the empirical insights gathered, this report introduces two practical frameworks to support retailers in this process. The first is the IRI maturity model², which outlines how retail organisations can develop increasingly sophisticated practices for managing inventory record accuracy – from ad hoc interventions to integrated, proactive systems. The second is the IRI pyramid of customer satisfaction, which illustrates how improvements in inventory record accuracy can drive customer-facing benefits, including better availability, smoother operations, and greater trust in omnichannel experiences. While these frameworks are conceptually distinct, they are closely related: building maturity in IRI practices is a key enabler of delivering superior customer outcomes.

The purpose of this report is threefold. First, it aims to provide a structured overview of how retailers can assess and advance their maturity in managing inventory record accuracy. Second, it shows how improvements in IRI management can support broader strategic goals, particularly in enhancing customer satisfaction and operational performance. Finally, it offers practical guidance – grounded in real-world experiences – to help retail professionals embed inventory record accuracy into their organisational processes, decision-making routines, and performance culture.

By connecting the operational problem of IRI with the strategic goals of customer satisfaction and competitive agility, this report offers a new perspective on how IRI should be managed in practice. Rather than treating it as a back-office concern, we argue that IRI deserves a central place in retail strategy – as a key capability that underpins both day-to-day execution and long-term success.

“We have a new error metric. We did a massive deep dive exercise to really understand what things are impacting our accuracy completely across the chain. And we identified about 20 different reasons why you could have IRI. And we’ve aimed to tackle the biggest ones.”

2 Please note that the terms “model” and “framework” are used interchangeably for the purposes of this report when referring to the maturity construct.

The IRI maturity framework: How to reduce inventory record inaccuracy

IRI is not just a technical error to be corrected at the shelf – it is a systemic challenge rooted in how retail organisations are structured, governed, and managed. It cuts across functions such as supply chain, IT, operations, and store management, involving both technological systems and human behaviours. Whether a retailer can effectively detect, understand, and respond to IRI depends not only on the tools they use, but also on their internal processes, role clarity, accountability structures, and cultural norms. In other words, IRI is as much an organisational maturity issue as it is an operational one.

To support retail professionals in assessing and improving their readiness to manage IRI, we have developed an IRI maturity model. This framework outlines key organisational dimensions that influence IRI-related performance and provides a structured way to think about progress and improvement. The higher a retailer “scores” across these dimensions, the more mature their approach to managing IRI is likely to be – and the better they can control discrepancies, improve availability, and satisfy customer expectations.

The maturity model was derived inductively from qualitative data gathered during interviews with retail professionals. By analysing recurring themes and patterns across these conversations, we identified a set of critical dimensions that consistently differentiated more advanced IRI practices from less developed ones. Each dimension captures a specific aspect of how retailers manage – or fail to manage – inventory record accuracy issues. Further methodological detail is provided in Appendix A.

The IRI maturity model presents a structured overview of eleven dimensions that, taken together, shape an organisation’s ability to detect, understand, and reduce IRI. Each dimension can be assessed along a spectrum from low to high maturity. For presentation purposes, we currently use a binary classification (low vs. high), but this can be expanded into a more granular scoring model in the future. The full model is summarised in Table 1. To further illustrate the differences in maturity levels, we have included selected quotes from the interviews in Appendix B.

Table 1. The IRI maturity framework

Below, we describe each of the eleven maturity dimensions and explain what characterises low and high maturity in each case. For each, we emphasise what good looks like – and what retailers risk when this area is neglected.

Problem Awareness refers to the degree to which an organisation recognises IRI as a meaningful and impactful issue. Retailers with low maturity in this area tend to downplay or overlook the problem entirely, often viewing stock record inaccuracies as a minor operational inconvenience rather than a strategic concern. In contrast, high-maturity organisations understand the full impact of IRI on availability, customer satisfaction, and profitability. They treat inventory record accuracy as a key operational challenge that requires continuous attention and action.

“We do not measure the stock accuracy, because measuring stock accuracy is very expensive.”

IRI Measures captures the breadth and quality of the metrics a retailer uses to monitor stock record accuracy. At low maturity, retailers may have no formal metrics or only rely on basic, inconsistent figures that fail to capture the size or nature of discrepancies. Highly mature organisations implement multiple, well-thought-out metrics that address different aspects of IRI. These are used systematically and support data-driven decision-making at all levels of the business. For more information on IRI metrics and their advantages and drawbacks please refer to our companion report available for free in the ECR website.

Structured Process describes the presence of formal procedures for identifying, analysing, and correcting IRI. In low-maturity organisations, such processes are either non-existent or highly fragmented, often depending on individual initiative. Retailers with high maturity have clearly documented and standardised processes that are applied consistently across departments and stores. These processes are regularly reviewed and improved to adapt to operational needs.

Clear Responsibility refers to whether accountability for managing IRI is clearly assigned within the organisation. When maturity is low, no one owns the problem – making it difficult to drive progress or sustain improvements. In high-maturity settings, specific teams or roles are tasked with overseeing inventory record accuracy. Accountability mechanisms ensure that issues are addressed, and success is recognised.

“Nobody is responsible. Everybody can identify and directly correct IRI. But this is no one‘s direct responsibility. It is very hard to attribute the problem to an underlying cause, and therefore no one can be deemed responsible for the problem.”

Accuracy Culture refers to the underlying attitudes and behaviours that shape how people approach accuracy. In a low-maturity culture, there may be little value placed on getting inventory records right, and problems are more likely to be blamed on others or ignored. High-maturity cultures, by contrast, promote clear and shared responsibility, transparency, and a commitment to continuous improvement. Accuracy is viewed as a collective goal, not just a technical detail.

Cross-Departmental Collaboration reflects the extent to which different parts of the organisation work together to manage IRI. Retailers with low maturity often operate in silos, with little communication or coordination between departments such as logistics, operations, and merchandising. High-maturity retailers actively promote collaboration, with cross-functional teams working jointly to identify and resolve root causes and implement improvements.

Organisational Alignment assesses how well internal structures and supply chain relationships support efforts to maintain accurate records. In low-maturity organisations, poor alignment between departments or unclear inventory responsibilities can undermine even well-intentioned efforts. High-maturity organisations ensure that responsibilities are clearly distributed, supply chain stages are synchronised, and the entire system is designed to support inventory record accuracy from end to end.

Top Management Commitment signals how seriously senior leaders take the issue of IRI. In low-maturity organisations, top management is disengaged – IRI is rarely discussed in leadership meetings and receives little investment or oversight. Where maturity is high, executives are visibly committed to improving inventory record accuracy. They monitor performance, champion improvement efforts, and ensure that IRI is treated as a business-critical issue.

“There is no report at the moment to the CEO or CFO because there aren’t any hard numbers to link the accuracy to lost sales. ”

Feedback Mechanisms refer to whether the organisation has established processes for learning from discrepancies and adapting over time. When maturity is low, there may be no way to track patterns or share lessons learned, and the same mistakes can repeat indefinitely. High-maturity organisations implement strong feedback loops, using discrepancy data to identify trends, inform training, and guide corrective actions. This enables continuous learning and performance improvement.

Technological Capability looks at the tools and systems used to support IRI management. Low-maturity organisations often rely on manual processes or outdated technology, which limits both visibility and responsiveness. In contrast, high-maturity retailers invest in advanced systems that provide real-time insights, automate alerts, and support root cause analysis. Technology is integrated into daily workflows and enhances the organisation’s ability to prevent and correct errors.

Incentive Systems reflect whether employees and teams are motivated to prioritise inventory record accuracy. In low-maturity organisations, there are typically no rewards or recognition tied to IRI-related performance, and other KPIs (such as speed or sales) take precedence. High-maturity retailers link incentives to accuracy outcomes, rewarding teams that maintain high data quality and reinforcing the behaviours needed to sustain those results.

“We do not have a bonus system that specifically looks at IRI, our bonus structure is based on sales and profit.”

To support retailers in improving their IRI maturity along the dimensions of the IRI maturity framework, Table 2 introduces some indicative best practices implemented in mature retail organizations that participated in our interviews.

Table 2. Some best practices for improving IRI maturity

The customer satisfaction pyramid

IRI not only affects internal operations and KPIs – it also has direct consequences for customer experience. To help retailers understand this broader impact, we developed a conceptual framework that links IRI to customer satisfaction. This framework is structured as a seven-tiered pyramid that we call the IRI Pyramid of Customer Satisfaction (see Figure 3).

The pyramid illustrates how organisations move from basic awareness of IRI toward delivering better availability and, ultimately, improved customer satisfaction. It shows that tackling IRI is not just about stock audits or system fixes – it’s about building the knowledge, measurement practices, and processes that allow retailers to deliver on their customer promise.

The IRI pyramid was derived inductively from the same set of interviews with retail professionals that informed the IRI maturity model. During our analysis, a clear progression emerged in how different retailers spoke about IRI – starting with foundational awareness and culminating in customer-centric outcomes. The pyramid captures this journey in a structured, easy-to-communicate format. 

Figure 3. IRI pyramid of customer satisfaction

The pyramid consists of seven tiers / levels, each separately discussed below. Retailers may be at different stages in this journey – and progress is not always linear – but each level represents a prerequisite and necessary step towards leveraging inventory record accuracy and moving “upward” to customer satisfaction.

1. 1. Problem Awareness At the base of the pyramid lies simple recognition: retailers must first become aware that IRI exists and recognise that it matters. Organisations at this stage begin to realise that inaccuracies in their stock records are not just a minor nuisance – they have real implications for operations, planning, and service quality. Without this awareness, no meaningful action can follow.
   2. Understanding Root Causes Once aware of the problem, retailers begin exploring why IRI occurs. This includes identifying and analysing root causes such as human error, scanning mistakes, process breakdowns, theft, or system limitations. Retailers who skip this stage risk treating symptoms instead of addressing the underlying drivers of inaccuracy.
   3. Revisiting Stock Management Processes As understanding deepens, attention shifts to the way stock is managed. Retailers at this level start questioning whether their current processes and systems are fit for purpose. They may not yet have introduced new tools or workflows, but they recognise that more proactive and flexible inventory management is needed to control inaccuracies effectively.
   4. Inaccuracy Metrics and Measurement Having recognised the limits of existing processes, retailers next begin to define how they measure IRI. They move beyond simple stock count comparisons and start developing more nuanced metrics – tailored to their business needs and rolled up at appropriate levels (e.g., product categories, stores, or regions). This stage marks a shift from anecdotal knowledge to structured, data-informed understanding.
   5. Implications-Oriented Measurement At this level, retailers begin to connect measurement to impact. It’s no longer just about how inaccurate the stock records are, but what the consequences are. This means tracking how IRI affects availability, cost, shrink, waste, and missed sales. Retailers who reach this level have the foundation to make informed decisions and start building strategies that address both cause and effect.
   6. On-Shelf Availability With a robust understanding of causes and consequences, retailers begin to act – and one of the first visible outcomes is improved availability. At this point, the organisation begins to prioritise inventory record accuracy as a way to reduce out-of-stocks and avoid overstocking. Even if full benefits haven’t been realised yet, the link between stock record accuracy and availability becomes operationally visible and strategically important.
   7. Customer Satisfaction At the top of the pyramid lies the ultimate goal: consistently meeting customer expectations through better inventory record accuracy. Retailers at this stage understand that getting stock right is not only about efficiency – it’s about trust, loyalty, and delivering a seamless customer experience. IRI is now seen not just as a technical challenge, but as a direct driver of customer satisfaction and brand success.The IRI Pyramid of customer satisfaction offers a powerful narrative for explaining why IRI matters – not just to inventory teams, but across the organisation. In Section 4, we explain how this framework can be used in practice to guide internal alignment, drive change, and strengthen customer-focused strategies.

Action steps

4.1 How to use the IRI maturity framework in practice

The IRI maturity framework is more than a conceptual tool – it is designed to support practical action. Retail professionals can use it to reflect on their current capabilities, identify areas for improvement, and guide targeted interventions that strengthen their organisation’s ability to manage inventory record inaccuracy. In the following, we outline four main ways the framework can be applied in a retail setting:

1. Self-assessment: where do we stand? The first step in using the framework is to conduct a structured self-assessment. This can be done at the store level, across departments, or for the entire organisation. For each of the eleven dimensions, teams can evaluate their current practices and classify them as either closer to low maturity or high maturity – or place themselves somewhere in the middle. A simple workshop format can work well: gather a small group of relevant stakeholders (e.g., operations, inventory control, loss prevention, IT) and walk through the dimensions together. Use the framework as a discussion guide. Encourage honest reflection: What are we doing well? Where are the gaps? Where do different parts of the business disagree? To support this process, organisations can create a scoring sheet or radar chart to visualise their position across all dimensions. This helps build a shared understanding of strengths and weaknesses./li>
   • Prioritisation and action planning: what should we work on next? Once a self-assessment is complete, the framework can be used to prioritise improvement efforts. Most retailers will find that they are strong in some areas but weaker in others. Rather than trying to improve everything at once, focus on the dimensions that:
   • Represent the biggest risks or pain points (e.g., no clear responsibility, no reliable metrics).
   • Have quick wins (e.g., introducing a feedback loop or clarifying ownership).
   • Show major differences in ratings across functions (e.g., store teams rate a dimension low while senior leaders rate it high); such divergence highlights misalignment worth exploring.
   • Enable progress in other areas (e.g., gaining top management commitment can unlock funding for process improvements or technology investments).

   For each targeted dimension, teams can define practical next steps. For example:

   • If structured process is weak, identify one high-impact IRI-related workflow and document it with clear roles and checkpoints.
   • If technological capability is low, assess current tools and identify low-cost upgrades or better uses of existing systems.
   • If incentive systems are missing, explore how performance on IRI-related KPIs could be integrated into store manager reviews or team bonuses.

    

   • Monitoring and improvement: are we making progress? The maturity framework is also a helpful tool for tracking improvement over time. After implementing changes, teams can revisit the same dimensions in three, six, or twelve months and assess whether maturity has improved. By integrating the framework into regular performance reviews, internal audits, or operational planning cycles, retailers can build a habit of continuous improvement. Over time, this helps embed IRI management more deeply into the organisation and align it with broader goals around availability, efficiency, and customer satisfaction.
   • Peer benchmarking and knowledge sharing. While the current version of the framework uses a binary maturity scale (low vs. high), it can be extended into a scoring system for benchmarking purposes. Retailers operating across multiple regions or brands can use the model to compare maturity levels between business units. Similarly, it can serve as a basis for structured conversations within retail networks, allowing peers to learn from each other’s approaches to IRI. Figure 4 illustrates the outcome of a benchmarking exercise conducted during one of the ECR meetings in 2025.

    

    

   

   Figure 4: Use of the IRI maturity framework for benchmarking purposes among retailers

    

   By applying the IRI maturity framework in these ways, retail organisations can move from reactive problem-solving to a more strategic and proactive approach to inventory record accuracy. The goal is not to achieve perfection in every dimension overnight – but to build awareness, define direction, and take concrete steps toward more mature and effective IRI management.

   4.2 How to use the IRI pyramid of customer satisfaction in practice

   The IRI pyramid of customer satisfaction can be a powerful tool for helping retail professionals frame the strategic importance of inventory record accuracy, build organisational awareness, and align cross-functional teams around a shared vision. Unlike the maturity model, which is diagnostic and operational, the pyramid is explanatory and motivational – it tells the story of how improving inventory record accuracy can ultimately enhance customer satisfaction and loyalty.

   Here are three ways the pyramid can be used effectively in retail settings:

   1. 1. Create shared understanding across teams. The pyramid is particularly useful as a communication and alignment tool. Because it illustrates a logical, step-by-step progression from IRI awareness to customer outcomes, it helps teams in different functions – such as store operations, merchandising, supply chain, and IT – see how their work fits into a broader journey.

   Retailers can use the pyramid in team briefings, onboarding materials, or internal workshops to:

   1. 1. • Explain why IRI matters beyond operational metrics.
         • Show how different teams contribute to improving availability and customer satisfaction.
         • Encourage shared responsibility and a common language around IRI.

   This framing is especially helpful in breaking down silos and shifting mindsets from short-term fixes to long-term capability building.

   1. 1. 1. Position inventory record accuracy as a customer experience enabler. In many organisations, customer satisfaction is seen as the domain of service, marketing, or customer relationship management teams. The pyramid helps bridge the gap between back-end operations and front-end experience by showing how accurate stock records are a foundational enabler of availability – and thus of meeting customer expectations.

   This perspective can help:

   1. 1. 1. • Build a stronger case for investment in IRI initiatives (e.g., audits, new technology, better processes and business models).
            • Reframe internal conversations from “fixing errors” to “supporting our promise to customers”.
            • Elevate the topic of inventory record accuracy in customer strategy discussions.

   If your organisation uses customer satisfaction ratings or availability KPIs, the pyramid can help explain why some of those results may be lagging – and what upstream changes are needed.

   1. 1. 1. 1. Use the pyramid to shape strategic roadmaps. While the maturity model supports capability assessment and operational planning, the pyramid can guide narrative-driven strategy building. For example, if your goal is to improve availability by X%, you can use the pyramid to identify the foundational gaps that need to be addressed first – such as inconsistent measurement or limited awareness of root causes.

   Rather than repeating the same planning steps outlined for the maturity model, we recommend using the two frameworks in tandem:

   1. 1. 1. 1. • Start with the maturity model to identify what capabilities are missing.
               • Use the pyramid to explain why those capabilities matter – and how they connect to customer-facing outcomes.

   By using both together, you can build both strategic clarity and executional focus.

   In summary, the IRI customer satisfaction pyramid provides a compelling narrative that connects inventory record accuracy to customer value. Use it to engage stakeholders, shape strategy conversations, and drive alignment between teams that may not always see themselves as part of the IRI conversation – but ultimately have a key role to play.

   Conclusion

   

   Inventory record inaccuracy (IRI) is no longer a peripheral concern—managing IRI is a strategic capability that underpins modern retail performance. This report has demonstrated that IRI affects not only operational efficiency but also customer satisfaction, financial outcomes, and brand reputation. Retailers who treat IRI as a core capability rather than a technical fix are better positioned to thrive in increasingly complex and competitive environments.

   The IRI maturity framework introduced in this report offers a structured lens through which organisations can assess their current practices and chart a path toward improvement. By evaluating themselves across eleven key dimensions—from problem awareness and technological capability to cross-functional collaboration and incentive systems—retailers can identify specific areas for development and build a roadmap for progress. This framework is not prescriptive; rather, it is a flexible tool that can be adapted to different organisational contexts and strategic priorities.

   Complementing the maturity framework, the IRI Pyramid of Customer Satisfaction provides a compelling narrative for why inventory record accuracy matters. It connects the dots between internal processes and external outcomes, showing how foundational improvements in awareness, measurement, and process design can ultimately lead to better availability and enhanced customer experiences. This pyramid reinforces the idea that IRI is not just a back-office issue—it is a customer-facing imperative.

   Together, these frameworks offer a dual perspective: one focused on organisational capability, the other on customer value. They are grounded in real-world insights from retail professionals and designed to be actionable. By using these tools, retailers can move beyond reactive fixes and toward proactive, systemic management of inventory record accuracy. This shift is essential for building resilience, agility, and trust in today’s retail landscape.

   Importantly, the journey toward zero IRI is not a one-time project—it is an ongoing commitment. It requires sustained leadership attention, cross-functional collaboration, and a culture that values data integrity. Retailers must embed IRI into their performance dashboards, operational routines, and strategic conversations. Only then can they unlock the full benefits of accurate inventory records, from reduced shrink and improved margins to stronger customer loyalty and competitive differentiation.

   As retail continues to evolve—driven by digital transformation, omnichannel expectations, and rising customer demands—the importance of inventory record accuracy will only grow. This report provides a foundation for that journey, but the work must continue. We encourage retailers to use the insights and tools presented here to reflect, act, and lead. The future of retail belongs to those who can deliver on their promises—and that starts with getting inventory records right.

   Ultimately, IRI is not just about counting stock. It is about building trust—with customers, with systems, and within organisations. It is about creating the conditions for excellence in execution and experience. And it is about recognising that in the age of data-driven retail, accuracy is not optional—it is essential.

   Appendix A: Methodology

   This appendix outlines the methodology used to derive the results presented in this report. Given the limited research available on how retailers manage inventory record inaccuracies, this report draws on insights from a qualitative interview study conducted with retail professionals. The primary aim of the study was to explore how retailers perceive and address IRI and to develop a deeper understanding of the metrics and practices they use.

   To capture a wide range of perspectives, the study employed semi-structured interviews. This approach allowed the researchers to guide the conversation with predetermined, open-ended questions while also enabling flexibility to explore new topics introduced by the interviewees [7, 8]. Interviewees were recruited through multiple channels. First, a sequence of posts to those on the Efficient Consumer Response (ECR) Retail Loss mailing list invited retail professionals working in areas such as loss prevention, inventory control, or inventory auditing to participate in the study. Second, the researchers directly contacted individuals from their professional networks. This dual recruitment strategy helped ensure a diverse pool of participants, reflecting variations in retail segments (e.g., grocery, fashion), business models (e.g., brick-and-mortar, online), geographical location, and seniority and job description of the interviewees (making sure in all cases that interviewees did possess the knowledge and information we were after).

   In selecting participants for the study, the researchers followed the principle of ‘maximum variation’ and the ‘replication logic’ [9, 10]. Maximum variation ensured that participants represented a broad range of organisational contexts likely to influence how IRI is measured and addressed. The replication logic allowed the researchers to include similar cases to verify whether observations made at one retailer were consistent across others. The sample size was determined using the concept of ‘saturation’, where additional interviews were conducted until it became unlikely that new insights would emerge [11]. Saturation was reached after 25 interviews in our case, which included participants from a variety of roles and retail contexts. Table 3 provides an overview of the interviews conducted during the study.

   Table 3: Overview of the interviewees participating in the study

   Role of the Informant	Retail Sector	Location
   Retired Retail Expert	N/A	North America
   Head of Global Store Operations	Grocery	Europe
   Commercial Manager Loss Prevention	Household hardware	Oceania
   Head of Stock Operations	Grocery	Europe
   Performance Manager	Grocery	Europe
   Product Director	Online Grocery	Europe
   Supply Chain Developer	Fashion	Europe
   Team Manager Stock Movement	Grocery	Europe
   Internal Audit Manager	Grocery	Europe
   Accuracy and loss business partner	Fashion	Europe
   Project Manager Group Operations	Fashion	Europe
   Team leader central supply function	Grocery	Europe
   Head of Retail Operations	Pharmaceutical	Europe
   RFID and Analytics Manager	Fashion	Europe
   Retail Strategy Leader	Grocery	North America
   Process Lead	Online Grocery	Europe
   Senior Director Retail Operations	Grocery	North America
   Stock Optimisation and Retail Audit Manager	Household hardware	Europe
   Solution Analyst Supply Chain	Grocery	Europe
   Lead Analytics Manager	Grocery	Europe
   National Director of Hypermarket Format	Grocery	Europe
   Program Manager	Grocery	Oceania
   Manager Loss and Fraud Prevention	Grocery	Europe
   Head of Front Store Operations and Innovation Team	Pharmaceutical	North America
   Replenishment Director	Grocery	Europe

   All interviews were conducted online using a video conferencing platform. Each session lasted between 20 and 70 minutes and was attended by two researchers from our team. With the consent of the informants, the interviews were audio- and video-recorded and subsequently transcribed using Sonix.ai. This process allowed the researchers to capture detailed responses and ensure the accuracy of the data for subsequent analysis. Following best practices in qualitative research ([11, 12]), transcription and analysis commenced while the interview study was ongoing. This iterative approach allowed findings from earlier interviews to inform the questions and areas of focus in later sessions.

   The transcripts were analysed using a qualitative coding process based on the Grounded Theory approach (see [13] for an example). This method involves developing theoretical insights directly from the data rather than testing pre-existing hypotheses. Specifically, the analysis followed the conventional content analysis method described by [14]. Key thoughts were identified through repeated rounds of coding, and emerging categories were used to group related codes into clusters. Two researchers independently coded the transcripts and resolved any differences in interpretation through discussion, ensuring consistency and rigor in the analysis process.

   The semi-structured format of the interviews provided rich qualitative data, enabling the researchers to explore a variety of perspectives and uncover unanticipated insights. By using open-ended questions and probing follow-ups [15], the interviews encouraged participants to provide detailed explanations and share practical examples of how IRI is managed in their organisations. This approach enhanced the validity of the findings and ensured that the report reflects the complexities of IRI measurement and management in the retail sector.

   

   In addition to the interviews, we conducted a verification workshop in collaboration with ECR Retail Loss in March 2025. The session brought together 46 retail experts, many of whom had a background in loss prevention and some of whom had participated in the earlier interviews. During the workshop, preliminary findings from both the literature review and the interview study were presented and discussed in facilitated breakout groups. Participants provided feedback and contributed additional insights, which helped validate our findings and prompted minor refinements where necessary. This workshop served as a member validation exercise (cf. [16]), enhancing the credibility and practical relevance of our analysis through direct engagement with industry professionals.

   This detailed methodology underpins the report’s objectives and findings, providing a robust foundation for understanding the metrics, practices, and contexts associated with IRI. Our methodology is graphically presented in Figure 5.

   

   Figure 5. Methodology

   Appendix B: Quotes from the interviews that illustrate the IRI maturity model

   In the following, we present statements from the interviews that illustrate and support the dimensions of the maturity model.

    

    

   	Low IRI maturity	High IRI maturity
   Problem awareness	“We do not measure stock accuracy, because measuring stock accuracy is very expensive.”	“In the last 18 months, we’ve worked really hard to give ourselves an accuracy measure and understand the inaccuracies within our business… We’ve built a three-year roadmap to become industry leading in this field.”
   # and nature of IRI measures	“IRI is not officially measured at the moment because our priorities are elsewhere.” “We don’t measure it very well… it’s a very crude figure.” “We do not have established inventory records inaccuracy metrics.”	“We have a new error metric… we identified about 20 different reasons why you could have IRI.” “We look at degradation of balance on-hand, negative inventory balances, and weekly record changes.”
   Structured process (and SOPs)	“We are kind of auditing the warehouses and then find out the best way to execute each process.” “We don’t have good line of sight between inventory periods.”	“Process adherence is measured through algorithms and automated alerts.” “We use metrics to check whether stores adhere to their processes.”
   Clear responsibility	“Nobody is responsible… therefore no one can be deemed responsible for the problem.”	“Store management is responsible.” “The warehouse manager is the ultimate responsible.”
   Right culture	“If you focus only on productivity, stock accuracy and other quality KPIs will suffer.”	“We changed how accuracy was presented, moving to gross accuracy, which removed a lot of unhelpful conversations.”
   Cross-departmental collaboration	“We do have separated KPI ownership or area ownership.”	“We are big on cross-functional teams.” “Four groups meet weekly and jointly own IRI in stores.”
   Organisational alignment	“We would struggle finding SKUs for an extra stock audit as not all SKUs have fixed locations.”	“Operational metrics exist for all parts of the supply chain, from supplier to store.”
   Top management commitment	“There is no report to the CEO or CFO.” “It doesn’t get to board level.”	“This is reported at the top level.” “Stock accuracy is becoming a boardroom topic.”
   Feedback mechanisms	“There’s not really been a discussion on the cost of visualising and getting the data.”	“We use real-time sales feeds to dynamically adjust stock and availability.”
   Technological capability	“Our accuracy is now 57–58%, gaining 2–3 percentage points per year.” “Further improvement requires investment in technology.”	“We use digital safety stock.” “Guided Split automatically sequences stock into the digital stockroom.”
   Incentive systems	“There are no bonuses whatsoever.” “We don’t incent inventory accuracy.”	“IRI is used for bonuses.” “Shrink is a major part of the bonus system, especially for store managers.”

    

   List of references

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         2. N. DeHoratius and A. Raman, “Inventory Record Inaccuracy: An Empirical Analysis,” Management Science, vol. 54, no. 4, pp. 627-641, 2008.
         3. Y. Rekik, C. H. Glock and A. A. Syntetos, “Inventory Inaccuracy in Retailing: Does it Matter?”, ECR Retail Loss (available at: https://ecrloss.com/category/inventory-accuracy), 2019.
         4. Y. Rekik, A. A. Syntetos and C. H. Glock, “Modeling (and Learning from) Inventory Inaccuracies in E-retailing/B2B contexts,” Decision Sciences, vol. 50, no. 6, pp. 1184-1223, 2019.
         5. A. Shabani, G. Maroti, S. de Leeuw and W. Dullaert, “Inventory record inaccuracy and store-level performance,” International Journal of Production Economics, vol. 235, p. 108111, 2021.
         6. Y. Rekik, R. Oliva, A. Syntetos and C. Glock, “Inventory record inaccuracy in grocery retailing: Impact of promotions and product perishability, and targeted effect of audits”, arXiv, (available from the authors of this report upon request) 2025.
         7. E. Grosse, S. M. Dixon, W. P. Neumann and C. H. Glock, “Using qualitative interviewing to examine human factors in warehouse order picking: technical note,” International Journal of Logistics Systems and Management, vol. 23, no. 4, pp. 499-518, 2016.
         8. R. K. Yin, Case Study Research and Applications: Design and Methods, 6 ed., Los Angeles: Sage Publications, 2018.
         9. N. Anand, H. K. Gardner and T. Morris, “Knowledge-based Innovation: Emergence and Embedding of New Practice Areas in Management Consulting Firms,” Academy of Management Journal, vol. 50, no. 2, pp. 406-428, 2007.
         10. K. M. Eisenhardt and M. E. Graebner, “Theory Building from Cases: Opportunities and Challenges,” Academy of Management Journal, vol. 50, no. 1, pp. 25-32, 2007.
         11. K. M. Eisenhardt, “Building Theories from Case Study Research,” Academy of Management Review, vol. 14, no. 4, pp. 532-550, 1989.
         12. J. M. Corbin and A. Strauss, “Grounded Theory Research: Procedures, Canons, and Evaluation Criteria,” Qualitative Sociology, vol. 13, no. 1, pp. 3-21, 1990.
         13. R. N. Raghuraman, A. Upasani, A. Gonzales, J. Aviles, J. Cha and D. Srinivasan, “Manufacturing Industry Stakeholder Perspectives on Occupational Exoskeletons: Changes after a Brief Exposure to Exoskeletons,” IISE Transactions on Occupational Ergonomics and Human Factors, vol. 11, no. 3-4, pp. 71-80, 2023.
         14. H.-F. Hsieh and S. E. Shannon, “Three Approaches to Qualitative Content Analysis,” Qualitative Health Research, vol. 15, no. 9, pp. 1277-1288, 2005.
         15. K. Roulston, “Considering Quality in Qualitative Interviewing,” Qualitative Research, vol. 10, no. 2, pp. 199-228, 2010.
         16. K. Thoring, R. Mueller and P. Badke-Schaub, “Workshops as a research method: Guidelines for designing and evaluating artifacts through workshops,” Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 5036-5045, 2020.
         17. S. Goyal, B. C. Hardgrave, J. A. Aloysius and N. DeHoratius, “The effectiveness of RFID in backroom and sales floor inventory management,” International Journal of Logistics Management, vol. 27, no. 3, pp. 795-815, 2016.
         18. H. H.-C. Chuang and R. Oliva, “Inventory record inaccuracy: Causes and labor effects,” Journal of Operations Management, Vols. 39-40, pp. 63-78, 2015.
         19. R. Ishfaq and U. Raja, “Empirical evaluation of IRI mitigation strategies in retail stores,” Journal of the Operational Research Society, vol. 71, no. 12, pp. 1972-1985, 2020.
         20. The Auburn University RFID Lab, “Inventory Accuracy,” available at: https://rfid.auburn.edu, 2023.
         21. C. Glock, A. Syntetos and Y. Rekik, “On the measurement of inventory record inaccuracies”, Working paper (available from the authors of this report) 2025.

   Disclaimer

   The research for this report was supported by ECR Retail Loss. The report is intended for general information only; it is based upon a review of the available literature together with primary research undertaken with retail organisations in worldwide. Individuals or companies are advised to seek professional guidance regarding their specific needs and requirements prior to taking any actions resulting from anything contained in this report. Any such actions taken by individuals or companies are entirely at their own risk. Companies are also responsible for assuring themselves that they comply with all relevant laws and regulations, including those relating to intellectual property rights, data protection and competition laws or regulations. The images used in this document do not necessarily reflect the companies taking part in this research.

   © December 2025, all rights reserved.

   About the Authors

   Christoph H. Glock is head of the Institute of Production and Supply Chain Management at Technical University of Darmstadt, Germany. His research concentrates on the coordination of inventory replenishments and the management of physical stocks in warehouses. Prof. Glock has worked together with many companies, and decision support models and methodologies co-developed by him are today successfully used in industry to efficiently manage inventories and warehousing operations. He is a member of several professional societies and editor of three international scientific journals.

   Aris A. Syntetos is Distinguished Research Professor of Decision Science and the DSV Chair of Logistics at Cardiff Business School, Cardiff University. He researches forecasting, and uncertainty management for improving inventory and supply chain decisions. He has worked with numerous organisations worldwide and many of his inventory-forecasting algorithms feature in best-selling supply chain software packages and in-house solutions and have led to enormous economic benefits. Aris is past Director of the International Institute of Forecasters (IIF) and current Vice President of the International Society for Inventories Research (ISIR).

   Yacine Rekik is Professor of Operations & Supply Chain Management at emlyon business school, France. The principal purpose of his research is to develop models that provide qualitative and quantitative insights into the impact of inventory inaccuracies and the benefits of RFID technology on the performance of supply chains in terms of cost reduction and/or improvement of service levels. As a TOUPARGEL chaired professor, he has also developed new inventory and routing policies taking into account the ecological footprint related to the vehicle routing problem, and collaborates with the ECR Retail Loss Group.

   Acknowledgements

   The authors are grateful to all companies that participated in this research project by sharing their experience and knowledge in interviews and during workshops. They would also like to thank all other retailers who offered feedback and additional insights during the physical and online meetings of ECR Retail Loss

   To contact the authors: glock@pscm.tu-darmstadt.de; aris@cardiff.ac.uk; yrekik@em-lyon.com

   About ECR Retail Loss

   ECR Retail Loss is part of ECR Community, a voluntary and collaborative retailer-manufacturer platform with a mission to ‘fulfil consumer wishes better, faster and at less cost’. Over the last 26years, the Group has acted as an independent think tank focused on creating imaginative new ways to better manage the problems of loss and on-shelf availability across the retail industry. Championing the idea of Sell More and Lose Less, ECR Retail Loss is open for any retailer and manufacturer to join at no cost..

   For further information: ecrloss.com.

   Research commissioned by the ECR Retail Loss Group is made possible by independent research grants provided by Axon, Checkpoint Systems, NCR Voiyix, Retail Insight, RGIS and Vusion: