Evaluating Lean Performance by Using Financial Accounting Metrics

Abstract

Despite anecdotal evidence of the financial implications and well documented benefits of lean implementation, little empirical research has been conducted. There are some recent evidence that leanness leads to improved firm performance, however evaluating lean performance by using financial accounting metrics is still an under-researched topic. This study takes a meta-analytic approach to collect and analyze empirically grounded research focusing on the relationship between lean and financial perfromance. We have reviewed literature from 1992 to 2022 including 34 studies analyzing firm’s performance in various industries. We find that there is positive correlation between lean and financial performance based on 56 unique key performance indicators analyzed. The study also determined that there are certain n accounting metrics such as return on assets, return on investment and inventory turnover that are capable of measuring lean performance under certain circumstances.
Keywords: Lean, Leanness, Finacial accounting, Finance, Performance measurement
Jel Code: G30

Introduction

The history of Lean is inseparable from Japanese automobile industry. The Toyota Production System date back to the 1930s and was developed after the end of World War II. This system in essence shifted the focus of the manufacturing engineer from individual machines to the rapid and efficient production of high quality and low cost products. The whole philosophy is based on the continuous elimination of waste (non-value added processes) while optimizing quality and information management (Dekier, 2012). It should also not be ignored that nowadays, psychological well-being is also a major issue in the functioning of companies (see, e.g. Mehmood, 2024), but it is beyond the scope of this paper to include this aspect.
Countless manufacturing firms have accommodated to global challenges by becoming more technologically advanced. In line with the lean princiles they chagned their focus to value-added products and started to continously upgrading the skills of their work force. Over the last three decades, there have been increasing numbers of lean implementations all over the world. Despite the many success stories, COVID-19 pandemic accelerated preexisting issues in the supply chain management and this drew attention of many executives to revisit their approach to lean.

As lean continues to spread to every industry resulting potential improvements in operational performance, there is a growing need to understand lean performance from financial reporting perspective as well. Given this, this study aims to collect existing research on the relationship between lean and financial performance and conclude if it is possible to evaluate lean performance by using financial accounting metrics.

Literature Review

The relationship between lean production and firm performance have been studied since the 1980s when U.S. companies first started implementing lean practices (Young and Selto, 1991). Studies from the 1990s have suggested that lean adoption not only improves operational performance, but financial performance. However, the results of these empirical studies can be somewhat controversial as they are mostly based on simplyified models that do not necessary consider the industry-specific factors. Moreover, most of these studies do not consider distortings effects caused by endogeneity either (Huson and Nanda, 1995).

In order to get a better understanding of existing epirical results we have collected the most significant studites from 1992 to 2022. In research studies authors used not only different financial accounting KPIs to measure lean performance but heterogeneous samples and different methodologies too. Table 1 summarizes the results of analyzed studies in chronological order by date of publication highlighting the main samples and metrics used.

Methods

In this research, we conduct a comprehensive meta-analysis on existing empirical evidances regarding the relationship of financial accounting measures and lean performance. With detailed literature review and KPI classification we attempt to identify and collect the most significant measures to be considered. The collection of studies was performed from September to November 2023. The date of publications covered a comprehensive 30-year timeframe from 1992 to 2022. The key scholarly sources included Elsevier, ScienceDirect, ResearchGate and JSTOR.

Numerous studies have found when lean is being adopted some key financial measures indicate response. For example, ROA (Return on Assets) proved to be a good indicator to measure inventory stickiness that is considered to be a fundamental pillar of JIT inventory system (Kroes and Manikas 2018). Some studies aregue that lean performance can be measured by fundamental financial metrics as there are too many external factor involved and some of them include the effects of financial leverage as well (Klingenberg, Timberlake, Geurts, & Brown, 2013). Hence, it is hypothesized that:

Hypothesis 1 – Lean implementation has effect on financial performance.
Hypothesis 2 – Lean performance can be measured by using financial accouting measures.

Summarizing the findings based on Table 1 we conclude that 56 different KPIs were applied in 34 studies. Some of these metrics can be considered as synonyms for one another or at least closley related (e.g. ROS vs. operating margin) but we do not modify or re-classify the metrics since even tiny differences in the interpretation can affect the outcome of the analysis. As first step we divided metrics into two main groups. First group consists of simple metrics where simple means the metrics are not derived from a division or other complex calculations (e.g. ratios and growth rates). Secont group consists of complex metrcs where complex means the metrics are results of a division or other complex calculations. After grouping the data by complexity we conclude that approximately one-third of metrics are simple metrics (18 out of 56) and two-third are complex metrics (38 out of 56). The complexity of individual metrics are summarized in Table 2.

Separating simple and complex metrics are crucial since financial metrics are used to track, compare and assess performance, and financial analysis is mostly performed by tracking changes in ratios and rates instead of measuring absolute quantities such as gross profit or total cost given that they do not necessarily imply that firm’s operations, management and control systems are efficient (Ghalayini and Noble 1996, Rákos et al. 2022). Hence, we take this same consideration into account when it comes to measuring leanness.

As a next step, we analyzed the ungrouped frequency distribution of KPIs. After excluding the least frequently used ones (frequency >= 3) we are left with 13 key metrics summarized in Fig. 1. Roughly one-third of the 13 most commonly used financial metrics are simple metrics (5 out of 13) and two-third are complex metrics (8 out of 13). If we have a closer look at the metrics, we can conclude that the they can be organized into the main types of financial accounting KPI categories. As per the commonly followed accounting rules and standards for financial reporting (Dékán T-né Orbán, 2013) we created the following groups:

– Profit measures
– Profitability ratios
– Efficiency ratios
– Capital Market ratios

In the first group we identify profit, net profit, sales, net sales and cost. From financial standpoint these might be the most essential indicators but from research standpoint these are be the most problematic ones. The first problem comes from the fact that some of the related studies do not even specify what they exaclty mean by profit or sales. In case of the net profit and net sales it is clearly declared but in the rest of the cases it is not and this can potentially lead to further data quality problems and false or at least questionable conclusions. We can highlight the same issue with cost since this is not a clearly defined metric either. As per the principles of cost accounting the exact type of the cost must be clarified otherwise the measurement principle is not met and we consequently fail to measure leanness in this regard. It is worth emphasizing that profit measures listed are all simple metrics thus they require careful consideration of interpretations to be able to measure leanness.

The second group consists of profitability ratios (Szekeres and Orbán, 2019). Here we list ROA (Return on Assets), ROS (Return on Sales), ROI (Return on Investment) and profit margin. Profitability ratios are KPIs that provide insight into how efficiently a business can generate profits. Except for sales these were the most freuently used measures in the stutides analyzed therefore, they could potentially be the most appropriate metrics for analyzing relationship between lean and financial perfomance. Furthermore, seeing these indicators, it is hard to miss the overlap with DuPont analysis. ROE (Return on Equit) was considered only once in studies analyzed with no consistent relationship regarding lean perfomance, however vast majority of the components of DuPont model are listed in this group with consistent relationship in relateion to lean perfomance. Given that DuPont analysis is a useful tool of financial statement analysis we can assume that KPIs listed in this group can form a strong basis for measuring lean performance (Soliman 2008).

In the third group we list two efficiency ratios: ITO (Inventory Turnover) and ATO (Asset Turnover). ITO is the measurement of the number of times a firm’s inventory is sold throughout a given period of time (most commonly a year). This metric was frequently applied in the studies (frequency = 6) and we can assume based on the lean principles that there is a strong relationship between inventory level (consequently ITO too) and JIT inventory system. In 4 out of 6 studies ITO showed significant response to JIT and lean adoption. Therefore the assumption is empirically verified. Compared to ITO, ATO measures the value of a firm’s net sales in relation to the value of its average total assets. In case of ATO 2 out of 3 studies showed consistent relationship between JIT and lean adoption. Based on these evidences there is considerable certainty that ITO and ATO are good indicators for measuring leanness.

In the fourth group we identify EPS (Earnings Per Share) and market share. These measures are somewhat special since they combine both Capital Market and profitability attributes. EPS indicates the profitability of a company on a per-share basis while market share is the percentage of an industry’s sales that a particular company owns. The empirical evidence suggest that EPS and market share are responsive to lean adoption. It is worth emphasizing that these metrics are less relevant in terms of financial accounting perspective however they can provide insight into how efficiently a firm can utilize lean.

Results

Based on the studies analyzed and assumption considered we summarize the results in Table 3. Our results suggest that profit measures were highly relevant for measuring leanness since 19 out of 19 studies showed positive correlation. Relationship between (net) profit and lean implementation was first documented by Bhasin (2008) by setting up DMP model for lean and later concluded positive correlation (r=0,6) in manufacturing firms in 2011. This was later supported by Agus and Hajinoor (2012) in Malaysian non-food manufacturing industries and by Alhuraish, Robledo, & Kobi (2016) in French manufacturing firms. Relationship between cost and lean implementation was first analyzed by Inman and Mehra (1992) with positive correlation (r=0,6952) in US manufacturing firms that was later confirmed by Callen, Fader, & Krinsky (2000) in Canadian manufacturing firms and also supported by Alhuraish, Robledo, & Kobi (2016) in French manufacturing firms. Despite being highly relevant for financial accounting profit measures are not ideal due to their low complexity but still they are worth considering.

Profitability ratios proved to be ideal choices to measure leanness as complexity, lean measurement and financial accounting relevance are high. Callen Callen, Fader, & Krinsky (2000) concluded positive correlation (r=0,5850) between profit margin and lean implementation in Canadian manufacturing firms and this was later supported by Cumbo, Kline, & Bumgardner (2006) and Ray, Zuo, Michael, & Wiedenbeck (2006) in US wood products manufacturing industry. Continuing with the most researched metric, ROA was first analyzed by Balakrishnan, Linsmeier, & Venkatachalam (1996) and Biggart (1997) in different industries with no significant response (r= 0,07) to lean adoption but this was later rejected in 12 studies – except for Klingenberg, Timberlake, Geurts, & Brown (2013) – where authors have found positive correlation between ROA and lean performance. Similar conclusions can be highlighted in case of ROI where first Inman and Mehra (1992) found positive response to lean that was later confirmed by Ray, Zuo, Michael, & Wiedenbeck (2006) and Cannon (2008) in different instustries and only rejected by Jayaram, Vickery, & Droge (2008) in US supplier firms (r =-0,542).

Similarly to profitability ratios, efficiency ratios are also highly relevant for lean measurement and financial accounting. Kinney and Wempe (2002) and Boyd, Kronk, & Boyd (2006) concluded positive correlation (r=0,896) between ATO and lean implementation in different instudtries and it was only rejected by Klingenberg, Timberlake, Geurts, & Brown (2013) in automotive supplier firms. ITO was first documented by Huson and Nanda (1995) concluding positive correlation (r=0,7258) to lean implementation in manufacturing firms. Except for Balakrishnan, Linsmeier, & Venkatachalam (1996) and Klingenberg, Timberlake, Geurts, & Brown (2013) the positive relationship was confirmed by 3 further studies in different US industries.
Capital Market ratios are high complexity KPIs and may provide relevant information regarding firm’s lean performance but these are the least researched metrics and most importatnly they have low relavance to financial accounting that make them a less ideal choice. Huson and Nanda (1995) concluded positive correlation (r=0,229) between EPS and lean adoption that was supported by Bhasin (2008). Market share was first analyzed by Agus and Hajinoor (2012) ending up with positive correlataion (r=0,408) that was also confirmd by Fullerton, Kennedy, & Widener (2014) and Swarnakar, Singh, & Tiwari (2021) in manufacturing industries.

Conclusions

Hypothesis 1 is supported, indicating that there is positive correlation observed in 29 of out 34 studies (85,29%) between lean adoption and financial performance while in the rest of the 5 studies the relationhip is not or only partially justifiable.
Hypothesis 2 is supported, indicating that there are certain financial accounting metrics such as ROA, ROI and ITO that are capable of measuring lean performance under certain circumstances.

Our present study possesses some shortcomings that open avenues for further research. Some of the studies analyzed took a very direct approach in measuring leanness and may have not considered external factors and effects of endogeneity. Furthermore, it is interesting to consider the limitions of financial ratios in general since these metrics have been around for decades but still they require careful data preparation and analysis when it comes to measuring financial performance (Faello 2015).

This study is only the beginning of a work with potential future development. Overall, results suggest that lean is associated with improved financial performance that can be measured by using financial accounting metrics however it is still suggested to donduct deeper analysis on the measures collected. Considering the outcomes it is aslo suggested to build a general and structured mathematical model that would be albe to measure and assess firm’s lean performance relying on the relevant financial metrics indentifed in this study.

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Attila Bányai PhD student
at Hungarian University of Agriculture and Life Sciences, Assistant Vice President at Citibank Europe plc Hungarian Branch Office