Evolutionary paths of performance measurement and management system: the longitudinal case study of a leading SME

Abstract

Purpose

The literature highlights the relevance of performance measurement and management system in small and medium enterprises (SMEs) to face the current competitive environment. However, a number of studies investigate how performance measurement and management system is effective for evolving and how contingency factors could influence this change. Newer experiences are sporadic and rarely investigated by researchers and practitioners. The purpose of this study is to identify the feasible evolutionary path of performance measurement and management system in leading SMEs to respond to current business challenges. Furthermore, it aims to contribute to the understanding of the role of key contingency factors influencing this evolution.

Design/methodology/approach

A longitudinal case study, based on retrospective and real-time investigations, is performed to investigate the primary evolutions of the performance measurement and management system and its key determinants.

Findings

The findings highlight two evolution paths, increasing the maturity of performance measurement. The first path highlights a strong command and control of performance management; the second path shows a democratic and participative of performance management. Moreover, management information system, organizational culture and management style are highlighted as key contingency factors in the change of performance management.

Originality/value

The authors contribute to knowledge in performance measurement field, showing how the efforts for developing performance measurement and management system in a leading SME could determine two different evolutionary paths. Furthermore, the paper describes the increasing role of organizational culture, management style and management information system in performance management evolution, as well as the relevance of online chats and social media in performance management activities.

Citation

Sardi, A., Sorano, E., Ferraris, A. and Garengo, P. (2020), "Evolutionary paths of performance measurement and management system: the longitudinal case study of a leading SME", Measuring Business Excellence, Vol. 24 No. 4, pp. 495-510. https://doi.org/10.1108/MBE-01-2020-0016

Introduction

The adoption of performance measurement and management system (PMMS) is recognized essential in all organizations (Bititci et al., 2012; Franco-Santos et al., 2012; Piscitelli and Mancini, 2018). It is defined as a holistic, balanced and dynamic system able to support the decision-making process through a set of performance measurement activities, e.g. gathering, elaborating and analysing performance (Neely et al., 2001), as well as performance management activities, e.g. communicating, learning and improving performance (Sardi et al., 2018; Smith and Bititci, 2017; Willis et al., 2018). It provides feedback to employees on the outcome of actions reflecting the procedures used to implement business strategy, as well as the information needed for strategy validation (Bititci, 2015; Bititci et al., 1997; Goshu and Kitaw, 2017; Ittner and Larcker, 2003). The balance between performance measurement and performance management should result from efficient systems (Nudurupati et al., 2016; Smith and Bititci, 2017).

Recent literature agrees to the successful implementation of holistic, integrated and balanced performance measurement and management in large companies. The same cannot be said for small and medium manufacturing enterprises (SMEs) where several constraints obstruct performance measurement and management (Ates et al., 2013; Bititci et al., 2012; Garengo, 2009; Garengo and Sharma, 2014; Moujib et al., 2017). For instance, SMEs highlight lack of availability of human capital, managerial skills, reactive approach and capital resources (Garengo et al., 2005; Hudson et al., 2001). Staff are primarily involved in technical and operational processes, in which they excel rather than intangible asset development. Therefore, SMEs have difficulty with performance measurement and management activities (Sardi et al., 2020). Few of them use performance measurement and management system to drive improvement of organizational performance, which in turn is not very prominent in the literature (Bianchi et al., 2015; Bititci, 2015; Garengo and Biazzo, 2012). Scholars underline that the insufficient empirical and theoretical studies on how performance measurement and management systems are not enough in SMEs and the poor understanding of what organizational factors influence these systems (Bourne et al., 2013; Garengo and Bititci, 2007; Garengo and Sharma, 2014; Jardioui et al., 2019; Taylor and Taylor, 2014).

Adopting a longitudinal methodology, this paper aims to identify how the performance measurement and management system evolves in a leading SME. Consequently, it focused on the study of the organizational conditions in which the PMMS is implemented. In particular, it investigated the impact of the contingency factors on PMMS. Contingency factors are recognized by the literature as key elements that affect the implementation and the use of PMMS. Among the main factors are organization corporate governance structure, business model, management information system (Garengo and Biazzo, 2013; Garengo and Bititci, 2007; Otley, 2016), organizational culture and management style (Bititci et al., 2006; Garengo and Bititci, 2007; Jardioui et al., 2019), but few longitudinal empirical studies support the understanding of how these factors influence the PMMS evolution. To contribute to the above research gaps, the paper answers to the following research questions:

RQ1.

How could PMMS evolve in a leading SME to face the new competitive environment? How do contingency factors influence this evolution?

Firstly, we reviewed the existing literature to identify a framework supporting the study of performance measurement and management system maturity. Secondly, we defined the research methodology adopted. Thirdly, we present and discuss the findings. Finally, we addressed the main practical and theoretical contributions, future opportunities and research limitations.

Literature background

From the mid-1980s, scholars and practitioners developed several performance measurement and management models, thus adopting a holistic approach highlighting the significant relevance of tangible and intangible assets (Pimenta, 2017) – see for instance the Balanced Scorecard (Kaplan and Norton, 1992, 1996) and the Performance Prism (Neely et al., 2001; Neely and Adams, 2001). These new models challenged traditional performance models based on control of financial and economic measures (Franco-Santos et al., 2012; Kaplan, 2012; Kaplan and Norton, 2004, 2005; Nudurupati et al., 2016). Their main purpose was to shift focus from control to learning and support the decision-making process (Bititci et al., 2012; Bourne et al., 2013; Jääskeläinen and Laihonen, 2013; Nudurupati et al., 2016; Sardi and Sorano, 2019).

Though highlighting important results in large companies, this approach could not be extended to SMEs because these have specific attributes not shared by large companies, especially in manufacturing, such as lack of financial resources, high reliance on few customers and lack of a clear organizational structure (Ates et al., 2013; Bititci et al., 2012; Cannavacciuolo et al., 2015; Garengo, 2009; Garengo et al., 2005; Garengo and Sharma, 2014). As stated by Garengo et al. (2005), these specific attributes can prevent the implementation and use of PMMS. Staff are mainly involved in technical and operational processes, in which they excel rather than intangible asset development. However, the maturity of an SME affects the success of PMMS and quality management systems (Sousa and Aspinwall, 2010).

Consequently, SMEs have difficulty with PMM. Performance measurement often involves inadequate awareness of the causal relationship of measures, few managerial skills and insufficient performance reviews as against balanced metrics, regular and short interval control (Bititci, 2015; Smith and Bititci, 2017). Performance management implies work specialization, job standardization and internal competition as against appreciation of employees’ differences, willingness to share new ideas and encourage autonomy and self-management (Bititci, 2015; Smith and Bititci, 2017).

Despite the significant progress made in terms of knowledge in performance measurement and management model improvement, scholars and practitioners still highlight problems impeding the effective adoption of PMMSs by SMEs (Bititci et al., 2012). Research papers currently available point to the fact that few SMEs adopt an advanced PMMS (Garengo and Bititci, 2007; Hudson Smith and Smith, 2007). The efforts made to identify an effective approach to meet the needs of these companies are too sporadic considering the existing competitive and challenging environment (Bititci et al., 2013; Garengo and Biazzo, 2012), although recent researches offer new insights. For instance, some researchers describe new low-cost PMMS using information that is easily available to owner-managers, showing that SME performance can be managed using a simple system built around the firm’s financial statements (Moujib et al., 2017).

To demonstrate that the context within which the use of PMM is changing, Bititci et al. (2012) identified eight global trends affecting PMM, i.e. collaborative organizations, knowledge work, networks, turbulent operating environment, culture, servitization, open innovation, global sustainability and information technologies. They also explained numerous gaps and specific challenges for PMM within a holistic systems-based framework.

To explain these new trends, scholars are studying PMMS as a system of systems (Bourne et al., 2018) and as an interplay between performance measurement process (i.e. what to measure) and performance management process (i.e. how the measures are used to manage organizations’ performance, Bititci et al., 2012; Melnyk et al., 2014). Recently, Smith and Bititci (2017) developed a framework to show the interplay between performance measurement and performance management defined as two separate but interdependent organizational control processes (Otley, 2012; Smith and Bititci, 2017). This theoretical framework bases on the different maturity of two processes named performance measurement and performance management. Performance measurement maturity highlights characteristics such as the balance of target setting, interval control and the time of performance reviews (Speckbacher et al., 2003); whereas the maturity of performance management process depends by industrial democracy, the degree of autonomy and job enrichment. This framework was recently upgraded with the new characteristics shown in Figure 1 (Sardi et al., 2018). In terms of performance measurement dimension, this upgrade highlighted the growing use of technological tools (e.g. social media and enterprise social networking) to increase a real-time data collection, analysis and reports; self-control of activity reports and the major use of key performance indicators. Considering the performance management dimension, the increasing use of these tools shows the growing relevance of continuous feedback, relationships, discussions and an inclination at a self-performance measurement (Sardi et al., 2018). The effective balance of the performance’s dimensions supports the design, the implementation and the use of a PMMS (Bititci, 2015) encouraging people to discuss performance (Otley, 2012; Smith and Bititci, 2017). This theoretical framework gave a robust basis for research, especially to describe the evolutionary path of the interplay between performance measurement and management (Smith and Bititci, 2017).

Adopting a contingency approach, Garengo and Bititci, (2007) showed the relationship between contingency factors and performance measurement, and they highlighted the role of organizational governance structure, business model (Afuah and Tucci, 2003), management information system (Garengo and Biazzo, 2013; Mithas et al., 2011; Sardi et al., 2018; Sørensen et al., 2010), organizational culture and management style (Bititci et al., 2006; Jardioui et al., 2019; Schein, 1996) (Table 1). They also showed that advanced information practices and behaviours impact people engagement, a necessary condition for the effective its implementation and adoption in SMEs (Garengo and Bititci, 2007).

Methodology

The case study methodology is more than simply researching a single individual or situation (Baxter and Jack, 2010; Yin, 2018). It favours the exploration and explication of complex situations and it allows the researcher to describe a phenomenon within its context (Baxter and Jack, 2010; Easterby-Smith et al., 2002; Eisenhardt and Graebner, 2007).

We adopted the longitudinal case study based on retrospective (from 2004 to 2016) and real-time investigations (from 2017 to 2019) of a leading SME and selected as a suitable method for an in-depth understanding of little-explored managerial activities (Garengo and Biazzo, 2013; Yin, 2018). The main stages of the longitudinal case study are as follows:

• case study selection;

• data collection; and

• data analysis.

Case study selection

To select a leading manufacturing SME, we adopted the two criteria suggested and used by Kirby (2005) and Richard et al. (2009) and Bititci et al. (2012). These two criteria were to be the best performer in its business sector according to some economic and financial indexes (Kirby, 2005; Richard et al., 2009; Bititci et al., 2013) and to match the emerging performance measurement and management trend as shown in recent literature (Bititci et al., 2012). AA, to preserve anonymity, was a leading SME operating in Italy:

• AA was globally the best performer in its sector. It had a significant increase in turnover (+480%), number of employees (+173%) and ROE (+231%) from 2004 to 2019.

• AA matched the performance measurement and management trend stated by Bititci et al. (2012). A preliminary interview with the Company Director revealed that the Company exhibited all the emerging trends suggested by the literature as shown in the below list:

Emerging performance measurement and management trends:

Emerging trends

1. Collaboration and networks – PMMS includes relationships and trust between stakeholders:

   • AA collaborates with customers, suppliers and other business partners. AA believes that internal and external relationships are essential to improve employees’ skills, knowledge and products. To foster relationships, the company has set up a laboratory that hosts international students and designers to promote creativity, friendliness and knowledge exchange. It also proposes an online blog for continuous discussion of how to improve furniture.

2. Multicultural environment – PMMS includes diversity management:

   • AA thrives to develop innovative initiatives to introduce new products and new ideas. An example is “The Apartment” initiative, comprising a temporary shop that embodies the continued insight of AA in the idea of redefining and re-inventing spaces for selling and uniting stakeholders.

3. CSR and sustainability – PMMS includes quality measures of social performance:

   • Corporate social responsibility is a crucial point for the Company. Headquarters premises are made of wood and glass, thus providing a peaceful environment for staff. AA promotes cultural initiatives, e.g. open days to show the features of its business, and has an environmentally friendly approach in the design and manufacture of its products, thus monitoring the impact of products on the environment.

4. Innovation and knowledge-based work – PMMS covers innovation and knowledge base:

   • Innovation and knowledge are distinctive features of all functions. For instance, AA communicates with customers through social media and interactive showrooms. Living showrooms enable people to learn about furniture design.

Data collection

We collected the data using a retrospective approach (twelve years) and real-time investigation. From 2004 to 2016, we gathered data through interviews, historical information and documents, whereas from 2017 to 2019, data were collected from three sources: interviews, documents and observations. Because of these three sources of evidence, we collected documents, information and reports to understand their actual PMMS. As required by Yin (2018), the information was collected as follows:

• Interviews– No. 24 semi-structured interviews with middle-senior managers.

• Documents– No. 165 documents with the main performance measures.

• Observations– No. 120 full-job-days subdivided between all functions.

We recorded and printed all the available data on digital and paper supports. The data were entered on predefined forms to facilitate summarizing and comparison.

Data analysis

Scholars suggest the analysis of data collected during qualitative studies through within-case and cross-case analysis (Eisenhardt, 1989; Garengo and Bititci, 2007; Miles and Huberman, 1984; Yin, 2018). According to these scholars, we analysed data in two ways:.

1. Within-case study:

   The within-case study focuses the researchers’ attention on the search for explanations and causality within the case study (Eisenhardt and Graebner, 2007; Yin, 2018); it aims to understand the case and identifying emerging models (Eisenhardt, 1989; Miles and Huberman, 1984). The within-case analysis is conducted through an accurate description of the cases that highlights the relationships between the factors investigated (Yin, 2018).

   To understand the enterprise context, we summarized the main company information (e.g. turnover and number of employees) and the main features of their performance measurement and management (Table 2).

2. Cross-analysis:

   The cross-case analysis supports the generation of models deriving from the case study (Yin, 2018). It is essential to increase internal validity and the ability to generalize research results. Eisenhardt (1989) argues that subjects have a limited analytical ability because they have access to a limited amount of data, are excessively influenced by other individuals and sometimes ignoring basic statistical properties or inadvertently neglecting evidence that does not confirm the expected results (Eisenhardt, 1989; Miles and Huberman, 1984).

   To develop the cross-analysis, we used Smith and Bititci’s (2017) theoretical framework because it is one of the best conceptualized in performance measurement literature and it considers the current turbulent operating environment in which a company acts today, one of the key elements on the design, implementation and adoption of PMMS (Bititci et al., 2012). Its adoption supports the develop of the cross-analysis (Table 4) and the identification of the evolutionary path of the performance measurement and management in SME (Figure 3).

   To carry out the cross-analysis, we first assessed the two processes by the scoring dimensions of the main PMM characteristics in 2004, according to the historical documents and interviews with the senior managers. Consequently, we assessed the characteristics of two processes in 2019, according to the documents and interviews with various functions as shown in Figure 2. We evaluated the PMM characteristics to score their maturity (Garengo, 2009; Smith and Bititci, 2017). Range of evaluation scale was 0 to 5, i.e.:

• 0 = PMMS does not show the characteristic; and

• 5 = PMMS shows fully the characteristic.

To graphically compare the data collected, we described the evolutionary path of PMMS through the theoretical framework suggested to Smith and Bititci (2017).

We analysed two contingency factors proposed to Garengo and Bititci (2007), i.e. organizational culture and management style and management information system. Corporate governance structure and business model were not investigated as they did not change during 15 years.

To evaluate these factors, we assessed data collected through interviews using the frameworks shown in Figure 4. To investigate organizational culture and management style, we used the framework proposed to Bititci et al. (2006) because it has already shown its validity in previous studies (Garengo and Bititci, 2007; Garengo and Sharma, 2014; Jardioui et al., 2019). It allowed studying the relationship between performance measurement, organizational culture and management styles through categorization of culture with corresponding management styles (Hofstede, 1980).

To study management information system, we adopted Garengo and Bititci’s (2007) framework, which was based on technology, management practices and human behaviours dimensions. The technical aspects were assessed according to investment on information technology (IT). To evaluate management practices and employees’ behaviours concerning the information system, we gathered the main practices adopted and employees’ perceptions of the use of technology through interviews and observations.

Findings

The enterprise in question was a furniture SME operating in Italy. It was set up at the end of the nineteenth century as a family-run business, unchanged in the last 15 years. AA has about 400 stores located in major cities including London, Paris and Barcelona, and is the best performer in its field, exhibiting the performance measurement and management system trend as per Bititci et al. (2012). It collaborates with an active network of customers, suppliers and universities. The Research & Development (R&D) department has international students participating in research projects to create new products and services and promotes other initiatives with continuous interactions in a multicultural environment.

The within-case study shows how the PMM approach has developed (Table 2) from initial collection, analysis and reporting information without specific measurement methodology, frequency or purpose, thus merely highlighting financial and economic indicators. In 2009, the first PMMS was implemented because of several managerial projects. Although not yet covering all departments, the method and frequency of data collection were adequate to meet financial, sale and production requirements. In 2013, the PMMS was improved by implementing sophisticated information systems. However, some departments still collected and analysed data using other tools. Employees often autonomously collated and processed data using managerial software, Excel spreadsheets and paper sheets. To move on, AA employed new staff for data integration in a management information system, which facilitated collection, processing and circulation of data in support of the decision-making process.

All company processes were controlled using financial and production indicators, sales turnover and marketing data. Interviews yielded 165 performance parameters such as production list per month (Operation Department), calls per month (IT Department), email campaign per week/month (Marketing Department) and market analysis per year (Sale Department). Parameters were compared to those of previous year or specific periods.

Parameters were placed on the internal managerial platform using automated procedures to be accessed by all management functions and selected staff. They were circulated as daily or weekly reports via email on the intranet or software. Some were printed and posted on department boards to facilitate circulation. This visual approach enabled all employees concerned to see the reports, especially benefiting senior staff with limited technological fluency. Reports were often shared on an internal platform and social media, e.g. Facebook and WhatsApp. Results were discussed during one-to-one meetings (formally) and private group chat (informally). In meetings, all management functions discussed operational aspects such as project management and marketing campaigns. At the end of the presentations, the management set out activities to achieve the targets for the period, e.g. week and month.

To analyse the evolution of PMM characteristics over the years, we carried out a cross-analysis. Figure 2 shows the job position of interviewer and the assessment of the different PMM characteristics if the paper will be print in black and white we should write light grey. The yellow cells show averagely the PMM characteristic as listed in Figure 1. In turn, the blue cells show insufficiently the performance management characteristic. This cross-analysis identified the two different approaches below:

1. the first approach, namely “Maturity and Control Path”, based on the characteristics of performance measurement and less frequently on the characteristics of performance management; and

2. the second approach, namely by “Maturity and Democratic Path”, based on the characteristics of PMM.

Both approaches were based on performance measurement activities for real-time data collection, analysis and reporting, each employee self-monitoring own activities through the use of parameters (key performance indicators), with new management software and technological tools such as Facebook and WhatsApp playing a key role. In turn, these aids permit continuous feedback, suggestions and support, facilitate knowledge sharing and discussion and promote self-management of knowledge, skills and open-project proposals on specific topics. They also support explorative organizational learning and encourage connective networks and bonding among stakeholders.

To show PMMS paths through cross-case analysis between 2004 and 2019, we calculated the average score for 2004 and 2019. We graphically compared case studies by the evolutionary paths of PMM (Figure 3).

Finally, we carried out a contingency factor analysis (Figure 4).

Management information system

AA introduced company management software several years ago. It invested in IT to obtain an advanced management information system that supported the development of performance measurement and management system based on a large data amount to answer strategic and operative needs. This progressively increased the maturity of its performance measurement inclusing real-time data collection, analysis and reporting with each employee being able to self-monitor own activities. This management information system was based on formal practices and consuetudinary behaviours.

In recent years, part of the company started the use of informal performance management sources like social media, WhatsApp and other freeware, cross-platform messaging and voice over internet protocol. This informal management information system encouraged participative and democratic performance management permitting continuous feedback, suggestions and support; it facilitates knowledge sharing and discussion, and self-management of knowledge, skills and competences and proposals of open projects on specific topics. This management information system was based on informal practices and consuetudinary usual behaviours.

Organizational culture and management style

AA used an authoritative management style and power culture as a starting point. The authoritative management style favoured the initial implementation of a PMMS in the company. After the implementation, the use was split up in two different approaches.

The first was based on an achievement culture and a consultative management style. The development of an achievement culture favoured people engagement. They worked hard to achieve goals and better the company as a whole. The company had highly motivated people who need little to no supervision but of sharing. This SME had ethical value but not too many rules and procedures because they may interfere with the accomplishment of work. The leadership style was based on humility and the ability to communicate equally to anyone, especially between colleagues from the same department/office.

The second was based on support culture and a democratic management style. It encouraged explorative organizational learning and facilitated connective networks and bonding among stakeholders, often including informal activities based on the use of social technologies. This style of leadership favoured a strong moral reinforcement that led to product and process innovation. People often talked to each other of company performance in formal and informal meetings. This dialogue made it possible to improve listening and communication of company performance.

Discussion

The results of this research identified two evolution paths with a net increase in the maturity of performance measurement. The first path, namely, maturity and control path, highlights a strong command of performance management, whereas the second path, namely, maturity and democratic path, highlights participative performance management. They also encourage the use of performance measurement parameters and facilitate self-monitoring of activity reports, but differ from performance management activities. The maturity and control path applies to performance activities based on formal support without changes to sharing, commenting and posting of main information, rarely allowing self-management of information. The maturity and democratic path is the favourite among the new generations of employees. Management is increasingly breaking new ground, thus opting for completely different use and perception of information technologies. Different skills, competencies, preferences and interaction processes are emerging, with continuous feedback and widespread use of social media and nano-technology. In turn, wireless sensor networks, cloud computing, embedded systems and mobile internet are supporting the development of computer systems able to continuously interact with the physical system in which they operate. New technologies are changing how enterprises perceive and manage their assets (Nudurupati et al., 2016) because products and services are enhanced with digital capabilities that increase their value. In this scenario, PMMS relies on continuous feedback, open communication and knowledge sharing, helping interaction of employees from different teams, departments and enterprises. Social media and chats now enable employees to dialogue with peers about performance, as stated in the literature (Bititci, 2015), thereby changing business communication, both internal and external. This revolutionary tool and the new topics arising from it, which gives researchers opportunities for future studies on performance management, although the performance measurement literature does not carry much investigation on the relationship between PMM and the new social technologies.

The maturity and democratic path answers to the recent literature, which defines PMMS such as a holistic, balanced and dynamic system able to support the decision-making process through a set of performance measurement activities and performance management activities (Smith and Bititci, 2017; Willis et al., 2018). However, the balance between performance measurement and performance management, which should give a basis of an efficient system, it was still rarely identified especially in SME (Bourne et al., 2018; Smith and Bititci, 2017).

To understand the contingency factors of the implementation and use PMMS, the study emphasized the key role played by management information system and organizational culture and management style for the development of a maturity and democratic path. Firstly, high IT investment and informal practices and behaviours on management information system strongly impact on the improvement of performance management. Secondly, the study highlights the impact organizational culture and management style on the different development of PMM. An achievement culture and a consultative management style favoured the development of a maturity and control path, while a support culture and participative management style favoured a maturity and democratic path.

As highlighted by the institutional theory, the resilient and deeper aspects of social structure are recognized as authoritative guidelines for social behaviour perspective (Di Maggio and Powell, 1991; Scott, 2001). Institutions are described as social structures that have attained a high degree of resilience. The company investigated showed the same company governance structure since the 1900s. AA was a traditional family; the company capital is held by a small group of shareholders belonging to the same family; the board of directors play a “service role”, while the decision-making regarding strategy and management is of the owners. Although different components explain how organizations create, diffuse and adapt over space and time, the institutions are stable but are subject to change processes (Scott, 2001, 2004; Di Maggio and Powell, 1991). As specified to Burns and Scapens (2000), the relationship between actions and institutions highlights the importance of organizational routines and institutions in shaping the processes of management accounting change (Burns and Scapens, 2000). As seen by the findings of this research, the issue of PMMS implementation and evolution in the logic of management accounting changed in the company. The results agree with the institutional theory and Burns and Scapens (2000)’s study.

The findings gap iterature need as expressly required by recent publications, i.e. to understand how SMEs respond to new and current business challenges and how to improve performance management in SME (Garengo and Biazzo, 2013; Mithas et al., 2011; Sardi et al., 2018; Sørensen et al., 2010). Moreover, recent literature underlined the need of holistic, integrated and balanced PMMS in SMEs (Ates et al., 2013; Bititci et al., 2012; Garengo, 2009; Garengo and Sharma, 2014). The findings connect these literature needs offering a participative and democratic approach to managerial improvement in manufacturing SMEs as required by scholars to the performance measurement field (Ates et al., 2013; Bititci et al., 2012; Garengo and Sharma, 2014). These results address the design of efficient and balanced PMMSs in SMEs based on new requirement of the digital era, i.e. engage people in conversations about performance (Bititci, 2015; Nudurupati et al., 2016; Smith and Bititci, 2017). The maturity and democratic path connects performance measurement activities and performance management activities supporting people on the decision-making process by specific feedback based on real-time data collection, analysis and reporting data (Bititci, 2015; Bititci et al., 1997; Goshu and Kitaw, 2017; Ittner and Larcker, 2003).

Conclusion

The paper shows how the efforts for developing PMMS in a leading SME could determine two different evolution paths into the same company because of the influence of management information system, organizational culture and management style.

Research implications suggest how the results can be important for policy, practice, theory and subsequent research. Through the frameworks adopted by this research, SMEs may evaluate their PMMS to understand their weaknesses and seek improvement solutions. A possible solution introduced by this research is the use of informal tools such as chats and social media in performance management activities. In this sense, SMEs should forecast strategical management of informal tools for improving performance management activities to engage people in conversation about performance.

This project offers academic and practical contributions in the form of a longitudinal, in-depth assessment of the PMMS adopted by a leading SME. The academic aspect covers the understanding of the evolutionary path of performance measurement and management in a manufacturing SME. The practical contribution offers a path, namely, maturity and democratic path, to managerial improvement in leading manufacturing SMEs. Hopefully, these results will drive the design of efficient and balanced PMMSs in SMEs. However, the main purpose of the project remains the recognition of the increasing role of chats and social media in performance management activities.

The main limitation of this study is that only one SME was investigated. However, its strength is that it permits an in-depth understanding of performance measurement and management of the best performing SME for 15 years.

The results give scope for future research opportunities, thus encouraging more case studies for exploration, testing, validation or improvement. Note that additional research is required to explain how performance measurement and especially performance management activities are evolving in SMEs. Moreover, further investigation is required on the use of innovative technology in performance management activities.

Figures

Figure 1

Framework characteristics typical of performance measurement and management

Figure 2

Cross-analysis

Figure 3

Evolutionary paths of performance measurement and management

Figure 4

Contingency factors

Table 1

Contingency factors

Factors	Definition
Management information system	It is part of the overall management system in an organization and form parts of company technology such as enterprise resource planning. It supports almost all management activities providing the identification of key performance indicators (Sørensen et al., 2010). The adoption of technology often leads organizations to focus their attention on technical aspects rather than on human aspects (Garengo and Biazzo, 2013), Mithas et al. (2011), Sardi et al. (2018). Although scholars outline the importance of analysing human behaviours concerning the information system, they do not enough investigate their impact on information systems Garengo and Bititci (2007)
Organizational culture and management style	Organizational culture is a set of values, beliefs and way of working for individuals in an organization Schein (1996). Change culture is a challenging process. So, it is considered a shared and stable factors by members of an organization for a long time Jardioui et al. (2019). Management style is a practice adopted by leaders in people engagement, information management and decision-making process Schein (1996). It is recognized as a key factor influencing organizational culture due to its impact on work sharing, decision-making time and activities control (Garengo and Bititci, 2007).

Table 2

Company history and PMMS evolution

Enterprise AA
Main information
Turnover	€29m
Employees	194
Country	Italy
Profile	Innovative brand in the field of Italian furniture design, producing home furniture
Main events
1900s	Family business in woodworking.
1950s	Launched production of bedrooms and other furniture.
1980s	Started to produce the living room furniture.
2006	Changed to joint-stock company, supplying over 400 stores and various single brands
PMMS
2006	Company reported, collected and analysed information without specific measurement method, frequency and purpose
2009	Company implemented the first PMMS, but did not cover all departments. Method and frequency of collating data based on financial, sales and production requirements. Management communicates performance data weekly
2013	Company improved PMMS through the implementation of business object and other tools