Linking a performance management system and competencies: Qualitative research

Flapper, Fortuin and Stook (1996) offered a systematic method for designing a consistent performance management system to be used in practice with the focus on the relations between the performance indicators (PIs). In their view, a consistent performance management system (PMS) meant a system that covered all aspects of performance that are relevant to the existence of an organisation as a whole. The system should equip the management with a quick insight into the performance of their organisation’s tasks and the extent of the implementation of organisational objectives. The method consists of three main steps: (1) defining performance indicators, (2) defining relations between performance indicators, and (3) setting target values or ranges of values for performance indicators. Ferreira and Otley (2009) described the structure and operation of performance management systems (PMSs) in more holistically. In general, literature uses three important terms: (1) management control system, (2) performance measurement system (PMeS) and (3) performance management system (PMS). From one point of view, the type of system is irrelevant because performance indicators can be found in each one. In their research, Závadský and Hiadlovský (2014) focused on performance indicators and especially their attributes that need to be defined.

From another perspective, PMS is an excellence model that includes requirements for measurement and evaluation of performance efficiency. Several models of the kind are available. Based on the Malcolm Baldridge Award, Evans, Ford, Masterson and Hertz (2012) explored ways to further improve and achieve higher levels of performance. Abdullah, Hamid, Mustafa, Husain, Idris, Suradi and Ismail (2012) offered organisations a conceptual framework for the development of a value-based total performance excellence model (VBTPEM). In the model, the core values of an organisation are used as a strategic component use to achieve total performance excellence. It integrates the intangible parts of performance measurement that have become pivotal for many organisations. The study by Doeleman, Have and Ahaus (2012) focused on the moderating role that leadership plays in the relationship between management control as part of total quality management (TQM) and business excellence aimed at targeted change. The study also indicated that transformational leadership had the most influence on the relationship between the construct of management control and purposive change. In the context of transformational leadership, organisations can be strengthened by implementing a management control system used in combination with a thorough management communication approach. Wang (2012) presented a literature review indicating the lack of an appropriate framework for the assessment of organisational performance (OP) during a crisis. He identified key OP indicators and developed a multidimensional framework for the evaluation of OP during crises. Alfaro-Saiz, Carot-Sierra, Rodriguez-Rodriguez and Jabaloyes-Vivas (2011) described the ways to use information resulting from the application of the EFQM excellence model to analyse perceptions of the organisation held by its members based on their business vision. Heras-Saizarbitoria, Marimon and Casadesús (2012) presented an empirical study focused on the relationships between categories of the EFQM model. Lis and Szczepańska-Woszczyna (2015) linked the organisational performance with the necessity to create individual, long-lasting relationships between the company and the customer. Performance is viewed differently, yet neither of the views on PMS served the starting point of research by Závadský and Hiadlovský (2014), which rather dealt with the homogeneity of any of these performance systems with PIs as their basic element.

In the literature, terms competence, competency, ability, responsibility and performance can be encountered on a daily basis. It can be argued that these terms are often placed within a more empirical rather than a theoretical framework. With the evolvement of scientific disciplines, including business management, various performance management systems (i.e. Performance Management, Business Performance Management, and Corporate Performance Management), and Human Resources Management, new knowledge has been acquired, contributing to new and convoluted interpretations and understandings of the terms. As some of these definitions are still used interchangeably, extensive and, in many cases, chaotic debates continue on the actual meaning and composition of these new notions.

Various authors (Draganidis & Mentzas, 2006; Vakola, Soderquist & Prastacos, 2007; Vazirani, 2010) consider “competence” and “ability” as interchangeable terms. Throughout an employment relationship, an employee executes certain tasks that are beneficial for his/her employer. His/her employment includes specific tasks, duties, authorities and responsibilities. Simultaneously, an employee has to socially mature in terms of his/her practical skills and determination.

Armstrong (2007) referred to competence as an expert’s ability and competency expressed in certain anticipated behaviour, or a type of behaviour, which is necessary to reach expected goals through teamwork, communication, team leadership and decision-making. Bober (2008) assumed that competence could be literally translated as power or authority. Power is closely linked to responsibility for a specific performance. Vazirani (2010) characterised competence as the minimum standard of work performance, and competency as a description of how to reach certain performance standards for businesses.

In the last six years, competence has been defined as the social and individual maturity of an entity (Porvazník, 2007; Vazirani, 2010). Competences are understood as a set of behaviours or internal qualities of individuals executing their responsibilities. In many cases, the authors refer to it as the internal characteristics of an individual and his/her motivation to undertake necessary efforts. It is assumed by the authors of this article that these preconditions are understood as an ability rather than competence.

It is necessary to proceed to a detailed and unambiguous definition of the issue under the current analysis. According to Minárová, a work position is defined by “duties to be executed and powers we need for proper execution and responsibility for using such powers when carrying out a specific duty which can be referred to as a competence” (Minárová, 2014, p. 49). However, a work position is limited by “personal requirements of a candidate occupying a specific work position, i.e. general and expert knowledge, practical and applied abilities, social and personal maturity, which are all referred to as abilities” (Minárová, 2014, p. 49). According to Porvazník (2007, p. 24), this term “clarifies what duties, powers and responsibilities an individual or a group of people (a team or an organisation, an institution or an authority) should have.” Competence is understood as all the duties, powers and responsibilities related to a particular work position regardless of who will be in charge of a specific competence. From this point of view, competences form a comprehensive strategy to facilitate the peak employee and organisational performance (Kalyani, 2016; Vazirani, 2010).

Seková et al. (2013) and Manohar (2017) defined competency as an ability to execute duties and powers (authorities) effectively and to take responsibility for one’s actions. They perceived the word competency as preparability of the management subjects — shareholders, managers and employees — to manage and govern their work, or the work of others to create real added value as the main key to success. The linkage of competences to performance management is that competences indicate what the employee can do or has the ability to do and the performance management system indicates what the employee does. Vakola, Soderquist and Prastacos (2007) added that competences, in contrast to competencies, could be delegated and competency can only be acquired through knowledge and experience.

As mentioned above, it may be assumed that an employee’s competency includes his/her abilities and competences. Being able to carry out one’s duties and being engaged are the main characteristics of one’s ability including the following key assets (or personal characteristics): general and expert (professional) knowledge (1), practical and applied abilities (2), social and personal maturity (3), and self-motivation (4).

Competence relates to certain conditions that have to be respected to execute certain work duties. Therefore, competence consists of duty (1), power or authority (2) and responsibility (3). Excellent performance is achieved by the assignment of work duties, powers and responsibilities to employees that have mixed abilities, knowledge, practical skills, social and personal maturity and self-motivation. Appropriate design of roles and responsibility sets are the key to a successful performance management system.

As all the phases of performance measures include a human factor, professional, practical and social requirements have to be determined for those businesses which have an obligation or are entitled to and liable for a measurement process and business performance evaluation (Moore, Cheng & Dainty, 2002). The ambiguous and vague definition of competences demonstrable by staff members responsible for measuring and evaluating their company’s performance process may result in incoherences and disorganisation. Examples of staff members responsible for measuring and evaluating their company’s performance are shareholders, top managers, company auditors, junior managers, members of t the controlling department etc. An employee to whom a competence for measurement process and performance evaluation has been delegated, is solely responsible for the quality of the performance management process (Wagner, 2009).

The predetermined arrangement of competences is a general and key feature of a competence model. According to Vazirani (2010), the majority of competence models include 10 to 12 competences to be classified into various categories. A competence model can be regarded as one of the subsystems of business process management as it creates a relation between activities and their implementors (Sanchez & Levine, 2009; Manohar, 2017). A competence model is a simplified system of business management, including such elements as business activities or human resources. A competence model can identify real responsibility for the performance of a fundamental management level. In summary, a business competence model aims to define the responsibilities and powers of specific work positions for the execution and implementation of particular activities (Závadský, 2012). Various problems can be solved, and direct consequences can be drawn by active engagement of employees in explicitly defined responsibilities and their acceptance (Wagner, 2009; Verle et al., 2014; Olšovská, Mura & Švec, 2016). When a company creates its system, it is necessary to tailor it according to certain parameters, such as the size of the company, the production programme, company culture and ways of doing business (Tuček & Dlabač, 2013).

The Z-MESOT framework represents a managerial and systematic approach to measuring and evaluating performance. It is mainly used when assessing the degree of consistency within measurement systems and performance evaluations. The managerial and systematic approach is based on the determination of the attributes particular to specific indicators used for the measurement and evaluation of business performance. Consistency is usually defined as an agreement or compatibility, especially uniformity among the parts of a complex matter. Ensuring consistency within any system is a guarantee for long-term balance (Závadský et al., 2016). The tool, for which consistency of the performance measurement and evaluation systems is identified, is often referred to as the matrix Z-MESOT, as shown in Tab. 1.

The parameters for measuring the functionality of a system are represented by so-called Performance Indicators (PI). Every Performance Indicator is used to research the functionality of a partial structure or the whole business process. Defining a consistency rate is the basis of systematic characteristics. A proposal for the attributes of performance measurement and evaluation should be in line with a systematic approach to its management. A consistent basis for a performance management system is a model comprising the Z-MESOT matrix. This matrix contains 21 attributes for testing the consistency of a performance management system. From the methodological point of view, it is necessary to differentiate between the attributes by particular patterns even though all the attributes end up being integrated into only one indicator. The Z-MESOT matrix contains 21 performance indicators divided into four groups (F1–F5 — formal attributes, T1–T5 — attributes of the indicator’s target value, I1–I6 indicator’s measurement, E1–E5 — indicator’s evaluation) (Závadská & Korenková, 2017).

This paper presents the analysis of attributes related to responsibility as a fundamental part of competences listed in the Z-MESOT matrix (Tab. 1) necessary for managers as well as other employees. Regardless of the method of performance measurement and evaluation, every business entity has to execute these activities as part of their business. Závadský and Kovaľova (2011, p. 4) assumed that the “implementation of specific activities is always delegated to an individual employee or managers in charge of the outcomes of business processes as well as its stability.” The Z-MESOT method supports a systematic approach towards the performance measurement and evaluation considering a competency-based approach. Z-MESOT is interlinked with a competence approach when it comes to those attributes defining responsibility in the business performance measurement and evaluation. The Z-MESOT matrix includes four basic attributes defining responsibility: the responsibility for defining an indicator — attribute F5 (1), the responsibility for defining a target value — attribute T1 (2), the responsibility for performance measurement — attribute I1 (3), and the responsibility for performance evaluation — attribute E1 (4).

Attribute F5 from the Z-MESOT matrix is the first important responsibility attribute. Indicators are usually defined by process owners, level managers or even first-level management. It is highly important to define the responsibility for determining its target value T1. When defining an indicator, it is often recommended to determine its target value as well. It is fundamental to appoint an employee in charge (I1) who will be responsible for monitoring the values at the right periodicity (or at the right time) and the right place. In many cases, the responsibility for an indicator’s evaluation (E1) is often connected with the responsibility for defining a target value, i.e. when a manager is supervising his/her own indicators. The responsibility for evaluation is also linked to operative performance evaluation. This is performed by company managers or top management (Závadský, 2005; Závadský & Hiadlovský, 2014).

The businesses were classified according to the type of production as KPIs were implemented differently in businesses focusing on custom manufacturing in comparison to those who focus on mass production or a combination of these two types. One large and two medium-sized businesses specialised in custom manufacturing accounted for 25% of analysed businesses. The majority of the businesses, i.e. four large companies and three medium-sized companies, specialised in mass production, which accounts for 58.33%. Two of the larger businesses were considered to be a combination of mass production and custom manufacturing as they focused on customer needs. These companies accounted for 16.67%.

As all of the proposed indicators were tightly linked to the attributes of responsibilities in large businesses (through process owners, as defined by the business information systems), they differed considerably in medium-sized enterprises, as mentioned below in the analysis of particular KPI attributes.

The first KPI was defined by all the large and medium-sized businesses as a key performance indicator. In large businesses, the Logistics Director (the owner of logistics processes) is responsible for defining the indicator and its target value to minimalise, or at least maintain it, in case it is determined by a customer as well as for performance evaluation. Large businesses stated that they were trying to eliminate human failures, which could result in inaccurate KPI measurements or mistakes in performance indicator measurement and evaluation. They assumed that attribute I5 was defined by a specific ERP system which was implemented and used in large businesses. It could, therefore, be assumed that in large businesses, the same person, i.e. the process owner, was responsible for defining the indicator as well as its target value and measurements. However, the same fact could not be applied to medium-sized enterprises. In this instance, it was the Operations Manager who was responsible for defining KPI 1, i.e. for increasing the percentage of customer orders that arrived on time and were tailored to customer requirements. A target value in medium-sized enterprises was determined by the Operations Manager in cooperation with the Logistics Supervisor, whereas in two out of five businesses analysed, it is only a Logistics Supervisor who acted without any cooperation with the Operations Manager. Logistics engineers were in charge of KPI 1 measurements as they collect all the necessary data to be further evaluated, either by a Logistics Supervisor or an Operations Manager.

Manufacturing Cycle Time (hereinafter — KPI 2) was defined by all the analysed large and medium-sized enterprises as a key performance indicator. In large businesses, the attributes of responsibility (F5, T1, E1) were connected with owners of specific processes, to which the indicator belonged. Based on structured interviews, it was found that in four businesses, this indicator was measured and evaluated by the logistics department headed by the Logistics Director, while three businesses had this incorporated in the main production process supervised by their Manufacturing Director. In medium-sized enterprises, this role was delegated to the Operations Managers to reduce the amount of time taken to produce a product and ship it to customers. The indicator’s target value was usually determined in cooperation with the Operations Manager and the Production Supervisor. In medium-sized enterprises, such responsibilities were usually delegated to lower management, i.e. the Production Supervisor, which depended on the measured values (recording downtime or time that is needed for retyping manufacturing facilities) in cooperation with production operators. Operations Managers were fully responsible for the evaluation of the indicator in all of the analysed businesses.

KPI 3, i.e. the Capacity Utilisation Rate, was also considered to be a key performance indicator. In all the large businesses we analysed, the owner of the main production process, namely the Manufacturing Director, was in charge of defining the indicator, its target value as well as its evaluation. The Director would also focus on maximising the indicator’s value to increase the total utilised manufacturing output capacity. In all of the analyses medium-sized businesses, the Operations Manager was responsible for the four attributes of the KPI 3 indicator. In other words, it is possible to talk about the explicit definition of all the responsibility attributes.

Based on the structured interviews, the indicator OEE – KPI 4 was regarded as a key feature only by seven of the mass production businesses. In contrast, this indicator was not considered crucial by custom manufacturing businesses as their production facilities were quite heterogeneous or not identically used (depending on the type of production, to meet customer requirements). As a result, the OEE indicator did not always belong among key performance indicators. For mass production businesses, however, this indicator was one of the most fundamental features. As far as responsibility attributes in large businesses are concerned, three custom manufacturing businesses did evaluate partially the attribute but did not define it explicitly. In the remaining four businesses, the Manufacturing Director was responsible for defining the indicator; while in large businesses, Managers or Chiefs of Departments dealt with the evaluation of the OEE indicator. Two medium-sized enterprises did not have responsibility attributes explicitly defined for the indicator. The remaining three businesses considered the Operations Manager to be responsible for the definition and evaluation of the indicator. The structured interviews showed that specific responsibility attributes were delegated to different employees and, therefore, these were not strictly defined. The target value was not determined only by the Operations Manager, but also by Maintenance or Improvement Supervisors. Besides Maintenance and Improvement Supervisors, there was also the Quality Manager, but only through his/her formal job description. Indicator values were measured by production operators managed by the Production Supervisor. In two of the businesses, it was the Operations Manager who was responsible for measuring the OEE indicator, and one medium-sized respondent indicated a Maintenance and Improvement Supervisor. An inaccurate delegation of responsibility may result in incorrect approaches to its measurement and evaluation. When duties, authorities and responsibilities are not properly defined, this may give rise to numerous arguments among staff on different management levels and eventually lead to a drop in performance of the whole business.

The Inventory Turnover indicator, referred to as KPI 5, was considered a key performance indicator. In large businesses, responsibility attributes of the Z-MESOT matrix were clearly defined by the owners of the processes, i.e. Logistics Directors. In medium-sized enterprises there was the Operations Manager responsible for defining the Inventory Turns indicator and the Logistics Supervisor who was in charge of determining the indicator’s target value as well as its evaluation. The Operations Manager would then evaluate the two processes. There were various people responsible for measuring the Inventory Turns indicator, e.g. Logistics Engineers who managed Logistics Supervisors followed by Production Supervisors and Assembly Coordinators in three cases. However, two of the businesses did not define the I5 attribute. This might be an indicator of inconsistency in defining responsibility attributes of the measurement and performance evaluation systems.

KPI6, i.e. the Manufacturing Costs as a Percentage of Revenue attribute, was regarded as a key performance indicator by all of the analysed large businesses. However, medium-sized enterprises classified it only as a performance indicator despite its regular measurement and evaluation. The owner of financial business processes was fully responsible for its definition, determining its target value as well as its evaluation. In three of the large businesses, this work position was defined as the Purchase and Finance Director, while in the remaining companies he/she was referred to as the Finance Director or the Chief Financial Officer. In the case of medium-sized enterprises, there were various work positions related to responsibility attributes of the KPI 6 indicator. These were General Managers or any other representative within top management who was responsible for measuring and evaluating the given indicator. Their main goal was to focus on the reduction of total manufacturing costs. The whole process involved the Financial Controller who dealt with the finance while the Revenue and Operations Manager focused on planning, budgeting and manufacturing costs. However, the Financial Controller was considered to be fully liable for these processes in medium-sized enterprises.

Productivity in revenue per employee was often referred to as KPI 7 and classified as a financial key performance indicator by all of the analysed large enterprises. In the case of the KPI 6, all of the responsibility attributes were delegated to the Purchase and Finance Director or the Chief Financial Officer. However, in some large businesses, HR Managers and Operations Directors had some participation without being considered owners of financial processes; therefore, they were not defined in the E1 attribute. Medium-sized enterprises regarded KPI 7 as a key performance indicator, which was almost identical to KPI 6 when it came to responsibility attributes. The only difference was the HR Coordinator who was responsible for the I1 attribute related to measurement in four businesses. Their main goal was to control and improve productivity in revenue per employee.

Earnings before tax, interest, depreciation and amortisation (EBITDA), hereinafter — KPI 8, were always referred to as a key performance indicator for all of the analysed large and medium-sized enterprises. In large businesses, it was the Chief Financial Officer, as a member of top management, who was responsible for defining the indicator and its target value. However, the Chief Financial Officer did not evaluate the indicator as he/she cooperated closely with the Financial Analysts. In medium-sized enterprises, the General Manager was in charge of the duties, while the target value of EBIDTA was determined by the Financial Controller. A bookkeeper was considered fully liable for measuring KPI 7 even though its evaluation was delegated to the Bookkeeper and the Financial Controller. Close to the KPI 8 was the KPI 14, referred to as Cash Conversation Cycle (CCC), was not considered to be a key performance indicator for the majority of the businesses we analysed, but rather a key indicator for cash-flow. This indicator emphasised possible fluctuations or a discrepancy between payables and obligations. In large businesses, it was the Chief Financial Officer who was responsible for the F5, T1 and E1 attributes. In medium-sized enterprises, the responsibility attributes were identical to other analysed financial indicators (e.g. KPI 8).

KPI 9 represents one of the most modern and the most sophisticated indicators which is supposed to become a highly important and significant metric measuring business performance of human resources in the future. Kronos Corporation from the USA (American Experts at Improving the Performance of People and Business) claimed that effective labour contribution was accomplished when managers could see and manage the three OLE elements — availability, performance, and quality (similar to OEE, but applied for HR). A manufacturer can improve shop floor productivity, and therefore the level of profitability, by understanding the interdependency and trade-offs of these three factors and managing them in real time. From among the analysed businesses, only one large corporation implemented this indicator, even though it was considered a PI rather than a KPI. Due to inconsistency in performance measurement and evaluation in the case of this indicator, the attributes F5 and T1 were not strictly defined. The HR Manager and the HR Counsellor were responsible for performance measurement and evaluation. Other large and medium-sized enterprises did not measure the indicator or did not even implement it into their practice.

Customer Reject Rate or KPI 10 did not represent a key performance indicator in the analysed large businesses (% of complaints was only considered as a performance indicator) while three of the medium-sized enterprises consider this indicator as a KPI. When it comes to responsibility attributes for KPI, it was assumed that the three analysed large businesses did not explicitly define the responsibility attributes. The remaining four large businesses defined this indicator vaguely and, therefore, they had to put a lot of effort into determining responsibility. It was discovered that in large businesses, a top management representative (the CEO) or the Chief Marketing Officer was responsible for defining the indicator. Meanwhile, the Quality Director defined the indicator’s target value, the Quality Manager or the CRM Manager was in charge of measuring, and the Quality Manager was responsible for its evaluation. In the sample of analysed medium-sized businesses, this indicator was measured and evaluated by all the corporations, three of which considered it a KPI. The General Manager was responsible for its measurement and target value definition while the number of complaints was recorded and administered either by the Quality Manager or the Quality Assurance Engineer with the Quality Manager responsible for its evaluation. The Customer Satisfaction Index (KPI 13), which is related to KPI 10, was regarded as essential and fundamental only by the custom manufacturing businesses as this feature was not considered a key performance indicator in any of the analysed mass production businesses. However, all the enterprises measured and evaluated the indicator. Large and medium-sized mass-production enterprises did not explicitly define responsibility attributes as they were determined only in custom manufacturing businesses. It was the Chief Marketing Officer who was charged with responsibility attributes in large enterprises. In medium-sized enterprises, the responsibility F5 was delegated to the General Manager while responsibilities T1 and E1 were ensured by the Quality Manager with the Quality Assurance Manager in charge of measuring the indicators. There was no marketing department in the company hierarchy of medium-sized enterprises operating in the production industry.

The Parts Per Million indicator was seen as a key indicator by all of the analysed medium-sized and large enterprises engaged in mass production. None of the custom manufacturing businesses evaluated or measured the indicator. As this indicator relates to various types of waste, defects and failures, its main purpose is to reduce the amount of these factors within a given process, though, mainly in manufacturing. The Quality Director was responsible for specific responsibility attributes in large enterprises while cooperating with the Quality Manager in the evaluation of the indicator. In medium-sized enterprises, it was the Operations Manager who was considered to be responsible for its evaluation and determining specific steps leading to the improvement or preservation of the required quality. The target value was set by the Operations Manager in cooperation with the Quality Manager. Many other employees were responsible for measuring the indicator, e.g. Production Supervisors, Production Operators, Assembly Coordinators, Process Engineers or Quality Control Engineers as the data were collected from different company departments and summarised by the Operations Manager. In medium-sized enterprises, the data were collected in writing, which might have affected its accuracy.

KPI 12, hereinafter — the Supplier’s Quality Incoming, was not considered to be a key performance indicator (but rather an ordinary PI) by any of the large and medium-sized companies. In large businesses, it was the Purchase Director, or the Purchase and Finance Director, who was responsible for defining the indicators. The target value and its evaluation were delegated to the Quality Director as he/she would evaluate suppliers and input quality to increase the value of this particular indicator, but also to ensure the supply from a supplier at the right time, at the right place, in the right quality. In medium-sized enterprises, the General Manager was in charge of defining the indicator while its target value and evaluation is a competence of Quality Manager. The Manager dealt with integral evaluation of the measured data in cooperation with the Quality Assurance Engineer, the Assembly Coordinator or the Procurement Assistant.

The Total Recordable Health and Safety Incident Rate was the last indicator to be analysed. Some of the analysed businesses regarded this rate as a key indicator, while others did not. The large businesses outsourced this process and, therefore, there was no exact definition of the attributes F5 and T1. It was the Quality Manager or the HR Manager who was responsible for measuring the indicator, the Quality Director or the Integrated Management System Manager dealt with its evaluation. Three medium-sized enterprises did not clearly define the responsibility attributes of the KPI 15, while the remaining two businesses delegated this responsibility to the Quality Manager with the Quality Assurance Engineer being fully liable for measurements and evaluations of the KPI 15 indicator.

The structured interviews presented results of attributes from the Z-MESOT matrix related to responsibilities for the definition KPIs, the determination of target values of indicators, and the measurement and evaluation of the indicators. As a result of the research synthesis, two charts were devised, which included specific work positions in relation to certain attributes of responsibilities for every performance indicator while still respecting the criterium of the company size. The type of production seemed to be important when determining the top 5 KPIs from the proposed indicators (the indicators defined as TOP 5 KPIs in the mass production framework differed considerably from those of custom manufacturing businesses). In regard to the attributes of responsibilities, only minor differences in work positions occurred, mainly due to the company size. The main difference between large and medium-sized businesses was found in the degree and significance of process orientation. All the analysed businesses had detailed process maps at their disposal and defined owners of specific processes. These owners were responsible for “performance indicator management”, which was either evaluated by an integrated business management system (Orion) or by using licenced management systems, such as Enterprise Resource Planning (e.g. SAP, Oracle, E-Business Suite, Qlick Sense/View). The effectivity of implementation of an ERP system was generally greater in large businesses. Besides, the ERP implementation was generally considered to be more effective/efficient in large businesses. The analysed medium-sized businesses mainly used Helios Orange or Green, Microsoft Dynamics Nav, Microsoft Dynamix AX, Exact Globe or simple spreadsheet applications, such as MS Excel, to measure and evaluate their business performance indicators.