The Supporting Force of Analytics: How Business Analytics is used to measure and manage Organizational Performance

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The Supporting Force of Analytics: How Business

Analytics is used to measure and manage Organizational

Performance

Yonne Boelen - S2725878 y.m.boelen@student.rug.nl Supervisor: Dr. A. Bellisario

Word Count: 12.681 (excl. References, Appendices) 20-01-2019

Master Thesis

MSc Management Accounting and Control Faculty of Economics and Business

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Abstract

Empirical evidence on how Business Analytics (BA) is used to measure and manage organizational performance is missing. Although it shows great potential in enhancing the effectiveness of the Performance Measurement System (PMS), since traditional systems are not able to respond to the fast-changing business environment and Big Data revolution, few organizations are able to extract value from BA. Understanding how BA can be operationalized to bring substantial value to performance management can support organizations in the implementation. An in-depth single case study was conducted in the Postal industry to investigate this phenomenon and provide practical lessons for the future. Data analysis included 18 in-depth interviews, 4 meeting observations and there was active involvement during a 5-month internship. This paper concludes that BA enables the creation of new insights for performance drivers, creation of external performance awareness, effective control of the business and evidence-based reviewing. However, organizations should not see BA as a replacement. It offers a valuable supporting role, but there is still high emphasis on intuition and organizations should strive for a strong balance of human judgement and analytics.

Keywords: Business Analytics, Performance Measurement, Performance Management, Big Data,

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1. Introduction

We are living in an era of digitalization and a growing availability and importance of data. Organizations that want to respond to the fast-changing and dynamic business environment are undergoing digital transformations aimed at mining and exploiting data in order to gain value (Ylijoki & Porras, 2016). Over the past decades, Business Analytics (BA) showed great potential in organizational performance improvement (Klatt, Schläfke & Möller, 2011; Ramanathan, Philpott, Duan & Cao, 2017; Aydiner, Tatoglu, Bayraktar, Zaim & Delen, 2019). BA refers to the application of analytical techniques and methods on business data to gain improved insights on operations and make fact-based decisions (Davenport & Harris, 2007; Chae, Yang, Olson & Sheu, 2013).

BA potentials triggered examination in multiple fields, including performance measurement and management. Performance Measurement Systems (PMSs) are acknowledged as critical for the effective and efficient management of any business (Melnyk, Bitici, Platts, Tobias & Andersen, 2014), support decision-makers with relevant information (Schläfke, Silvi & Möller, 2013) and provide a starting point for improving operational performance (Radnor & Barnes, 2007). As the well-known quote of David Garvin follows: ‘’If you can’t measure it, you can’t manage it’’ (1993), expressing the importance of a sophisticated Performance Measurement System. Generally, PMSs are developed from an assumption of a stable environment, but the current business dynamics requires a more resilient system than ever before (Nudurupati, Tebboune & Hardman, 2016). Traditional PMSs are recognized as inappropriate and the extraction of value from the Big Data revolution appeared to be challenging and often outside the traditional domain of PMS (Schläfke et al., 2013).

BA offers potential in solving some of the implications faced by traditional PMS and possibly enhancing the overall performance measurement process (McAfee & Brynjolffson, 2012; Warren, Moffitt & Byrnes, 2015). BA is able to deliver data-driven evidence for decision-making, make stronger predictive analysis from an operational perspective and take quick actions on performance (McAfee & Brynjolffson, 2012; Davenport & Harris, 2017). Furthermore, the analytical tools are able to uncover complex patterns and relationships (Klatt et al., 2011) and increased visibility of organizational operations and related performance results can be established (Fosso Wamba et al., 2015).

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research question will be answered: How is BA used to measure and manage Organizational

Performance?

To answer the research question, an in-depth case study research in a growing BU of a Dutch postal company has been conducted. A rich understanding was gathered through data triangulation; interviews, observations and archival data, and there was active involvement by means of a five-month internship. The purpose of the study is to provide empirical evidence and examples of how BA is used in PMS and to provide useful lessons for the future. In brief, the findings of this study show that BA is used to support, not replace, experience and intuition with data for the design of performance indicators, create awareness of performance for (external) stakeholders, establish effective control of the business and a move towards evidence-based reviewing.

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2. Theoretical Framework

The theoretical background will explain the main concepts of this study. The first section will

introduce Performance Management Systems (PMS) aimed at beneficially managing performance and responding to the changing business environment. Secondly, the concept of Business Analytics (BA) will be introduced and its potential benefits of integrating it in PMS. These potentials will be assisted by organizational challenges and will lead to a proposed research question.

2.1 Performance Measurement Systems

It has been long recognised that a prerequisite for achieving high performance standards is efficiently measuring and managing organizational performance (Cocca & Alberti, 2009). A Performance Measurement System (PMS) is an overarching system that is concerned with defining, controlling and managing the achievement of outcomes as well as means used to achieve these outcomes at an

organizational level (Ferreira & Otley, 2009; Broadbent & Laughlin 2009). It encompasses analyzing differences between actual outcomes and desired outcomes, critically reviewing and understanding these differences and taking actions when necessary (Melnyk et al., 2014). A PMS is composed of a balanced set of performance measures, that identify deviations from expected results and quantify the efficiency and effectiveness of past actions (Lebas, 1995; Neely, Gregory & Platts, 2005; Mello, Leite & Martins, 2014). Performance measurement and management processes are not distinct, but feed and comfort one another and therefore should be viewed as complementary (Lebas, 1995; Cocca & Alberti, 2009). PMS can provide valuable information for managerial decision-making and in turn actions to be taken (Mello et al., 2014). Thereby, PMS is recognized as a way to monitor, improve and continuously adapt to a changing external environment (Cocca & Alberti, 2009; Domingues, Reis & Macario, 2015).

Over the last three decades, organizations have invested in their performance measurement systems to a great extent, because they acknowledged the power of a sophisticated PMS in supporting internal and external communication of results, strategic decision-making processes, strategy

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alignment, controllability, timeliness, technical validity and they should be interrelated by using cause-and-effect relationships (Franco-Santos et al., 2012). Detailed exchange and integration of knowledge is required and involving operational employees in the design of performance indicators can help in building more valid and credible representations of organizational performance (Wouters & Roijmans, 2011; Groen, Wouters & Wilderom, 2017). Regarding the use of PMS, it can be both diagnostically and interactive. Diagnostic use refers to the traditional mechanistic approach of monitoring, assessing and rewarding achievement on key areas, whereas interactive use is more feedforward and encourages organizational learning and the development of new ideas and strategies. Jointly using the two

approaches can support the achievement of all the benefits of performance measurement, however evidence on the right balance lacks (Henri, 2006; Ferreira & Otley, 2009). Finding the right balance is important, because information flows are fundamental to both uses and required to adequately monitor performance and support learning (Ferreira & Otley, 2009). Thereby, acquiring, storing, analyzing and disseminating information to decision-makers is one of the most important characteristics of PMS (Mello et al., 2014).

Literature is quite extensive on recommendations of a well-designed and used PMS in order to effectively and efficiently measure and manage performance, but guidance on customization and adaption to the business context remains scarce (Cocca & Alberti, 2009). Previous studies offered relatively simple frameworks, which led to organizations adopting a narrow and superficial PM system (Neely et al., 2000). The challenge for organizations is to build a resilient PMS that reflects strategy in volatile environments (Melnyk et al., 2014). In order for a PMS to be effective, it needs to be dynamic and performance indicators should be continuously updated to maintain its relevance (Cocca & Alberti, 2009; Braz, Scavarda & Martins, 2011). Few organizations appear to have the capabilities and the processes in place for evaluating and modifying their PMS. Consequently, the ability of continuous strategy alignment remains challenging for almost every organization (Kennerley & Neely, 2002). There is a realisation that the traditional PM systems are inappropriate for

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Raguseo, 2019). Organizations have to deal with different volumes and varieties of data and sophisticated and analytical tools are needed to gain new insights in performance from this data (Nudurupati et al., 2016). However, this showed to sometimes lie outside of the traditional domain of PMSs (Schläfke et al., 2013). To conclude, three major challenges are identified regarding traditional PMS; continuous strategy alignment, identification of cause-and-effect relationships and extracting benefits from the Big Data revolution.

Research picked up on these challenges and started to explore the potentials of Business Analytics (BA), which led to a growing consensus that BA has great potential in measuring and managing performance. BA can potentially solve the implications faced by traditional PMS and offer valuable information. The next section will discuss the concept of BA and its potential role in improving the effective application of PMS.

2.2 Bringing Business Analytics to the field of Performance Measurement Systems The connection between a sophisticated and effective PMS in order to increase organizational performance is missing, however might be improved by the use of data analytical tools (Silvi et al., 2010). There is a growing interest in Business Analytics, both in the academic as business world, and this research area can potentially provide a major boost to the domain of performance measurement systems. Some of the benefits of using BA will be discussed shortly, followed by their potential applications regarding effective PMS and the challenges from an organizational perspective will also be touched upon. Finally, a research question will be proposed to contribute existing knowledge.

Business Analytics refers to the application of multiple data-driven analytical methodologies in order to create insights to everyday issues regarding different business domains (Chae et al., 2013; Abai et al., 2015). BA can create new insights through analyzing business data and information from a diversity of sources (Davenport, 2006) and the goal of data analytical systems is to make a large amount of data available and useful to as many users as possible (IBM, 2013). The competitive organizational environment intensified the need for the masterful exploitation of data for better operational and strategic decision-making and it is argued that the organizations that achieve

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guidance on the mechanisms through which BA capabilities can lead to these organizational benefits is provided (Torres, Sidorova & Jones, 2018).

The promise of BA in facilitating performance improvement, motivated research on the usage in a large variety of domains and a growing stream of literature proceeded on the potentials of using BA for performance measurement purposes (McAfee & Brynjolfsson, 2012; Raffoni et al., 2018). As our markets are becoming more competitive and digitized, organizations will have to keep up, and early adopters of BA in PMS might establish a strong competitive advantage for themselves

(Davenport, 2006). Moreover, combining the potential of (Dig) Data analysis in BA with the strategy-shaping capability of PMS can offer significant value (Raffoni et al., 2018). Although this field of research is still in its infancy, there are some studies that provide contributions on the potentials of BA in PMS and the related organizational challenges.

2.2.1 The potentials of integrating BA in PMS

BA is able to discover causal relationships between target measures and impact factors, which enables identification of the true underlying drivers and root causes of performance (Ittner & Larcker, 2005; Klatt et al., 2011; Silvestro, 2016). Managerial decisions are often based on core assumptions about what drives performance instead of justified assumptions underlined with data from their organization (Silvestro, 2016). Due to adoption of BA into PMS, data-based knowledge on the true drivers of performance can be provided, which enables bringing this information into a complete overview of the organization (Schläfke et al., 2013; Raffoni et al., 2018). For this reason, the Key Performance

Indicators (KPIs), which are important instruments of PMS, should be based on insights from analytics to improve key decisions (Davenport, Harris & Morison, 2010). By adding refinement to decisions on performance indicators and related targets, the effectiveness of strategic PMS can be greatly improved, suggesting organizations to move away from indicators based on intuition and place more importance on the usage of analytical techniques (Ittner & Larcker, 2005). It is important to keep the focus on the largest drivers of performance, because they lead to a more effective diagnostic use of PMS and otherwise organizational capabilities will exhaust (Barton & Court, 2012; Raffoni et al., 2018).

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data analytics, questions regarding what has happened (descriptive), what will happen (predictive) and what should happen (prescriptive) can be answered (Appelbaum, Kogan, Vasarhelyi & Yan, 2017; Raffoni et al., 2018). These better predictions from an operational perspective allow organizations to take prompt actions, while managers can quickly identify trends and make predictions (Davenport & Harris, 2017).

Using analytical PMS can also contribute to the interactive use of PMS, while it enforces the collection of multiple sources of data, information sharing and related discussions across different levels of the organization (Raffoni et al., 2018). There is an opportunity nowadays to combine data and expand insights by identifying the valuable data you already have and exploring new sources of information (Barton & Court, 2012). In this regard, BA can provide enhanced visibility of

organizational operations and performance and provide new insights (McAfee & Brynjolfsson, 2012; Fosso Wamba et al., 2015).

2.2.2 The challenges of integrating BA in PMS

It is clear that BA can provide substantial advantages to PMS, therefore the issue is not whether organizations should perform BA, but how to perform BA and extract the most insights out of the numbers (Emblemsvag, 2005). Organizations need the capabilities to integrate BA into their current infrastructures, requiring talent, money, a collaborative data strategy and analytical skills (Ylijoki & Porras, 2016; Fleckenstein & Fellows, 2018; Raffoni et al., 2018). A low number of organizations succeed in adopting analytical performance management, as they seem to struggle in extracting operational and strategic valuable insights from data (Raffoni et al., 2018). PMSs are often a combination of different accounting packages, complicating the design and use of such a system in conjunction with BA (Malmi & Brown, 2008; Nielsen, 2017).

Due to the Big Data era, organizations are often overloaded with information, which does not necessarily lead to better operational performance (Roden et al., 2017). The large amount of

unstructured data coming from all kinds of sources can be a hurdle and it is challenging to make this data trustworthy, available and understandable to all employees (Fosso Wamba et al., 2015). This is empirically grounded by Barton & Court (2012), as they showed that employees in a retail company were reluctant on using data analytical outcomes, because they did not trust it or were not capable of using it. The communication and interaction of relevant analytical output to decision-makers in a usable and understandable manner is needed, which can be supported by the use of dashboards reports and visualization systems (Bose, 2009; Chen et al., 2012).

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data-driven decision-making (McAfee & Brynjolfsson, 2012). Managers and employees should have the ability to balance judgement and analysis to make good decisions, but it is found that only 50% of senior managers and 38% of employees possess the analytical skills to fall into this group (Shah, Horne, & Capellá, 2012). Thereby, the pre-existing frame of reference of managers have a high influence on the selection of data elements and the relationships that are inferred from the data (Lycett, 2013). Employees in all levels of the organization need to be well-equipped in order to understand and extract value from data in BA tools, which can be achieved by training (Fosso Wamba et al., 2015). However, when organizations introduce a new BA tool, often a one-off training is provided to

employees that is focused on the use of the tool, instead of how decision-makers can use it to improve their judgement (Shah et al., 2012). There seems to be a need for a new role, translators, in

organizations, who communicate the information to the decision-makers and bridge disciplines (Brown, Court & McGuire, 2014; Mckinney, Yoos & Snead, 2017; Raffoni et al., 2018). These skills go beyond the skills of data analysts in the past and therefore people with this valuable skills set are extremely difficult to find (Davenport, Barth & Bean, 2012).

To cultivate decision-making based on facts and results, it has to be encouraged within the entire organization, supported by the organizational culture and integrated in a sensible manner (Klatt et al., 2011). In order to extract all benefits from BA, organizational culture and capabilities across the organization have to be aligned (Fosso Wamba et al., 2015). A challenge that arises here is the

transformation of the organizational culture and the stimulation of a sustained cultural shift, which requires the commitment, responsibility and engagement of company leadership (Brown, Court & Willmott, 2013; Mayhew, Saleh, & Williams, 2016). Frontline adoption and embracement of

analytics, including automated tools and training, can support this transformation (Brown et al., 2014). Changing the mind-set and organizational culture is also a prerequisite for attracting the right

analytical employees and ‘translators’ as mentioned above (Brown et al., 2014).

2.2.3 How to integrate BA in PMS

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al., 2014; Fosso Wamba et al., 2015). More empirical research and practical examples in different types of organizations would provide useful learnings for the future and could support organizations in adoption (Mello et al., 2014; Roden, Nucciarelli, Li & Grahamd, 2017).

Therefore, this study will contribute to existing knowledge by providing practical evidence on how BA is operationalized in a PMS context and what the organizational consequences are. The following research question will be investigated: How is BA used to measure and manage

Organizational Performance?

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3. Research Design

This section will present the design of the research, that starts with a comprehensive description of the case setting. Secondly, the data collection procedure will be described and details on the sample will be provided. Finally, the process of analyzing the data will be elaborated on.

3.1 Case Setting

To study the research question in detail, a qualitative research approach is chosen in the form of a single-case study. Case study research enables studying behaviour in the field and focuses on understanding the dynamics presented within single settings (Eisenhardt, 1989). According to

Merchant & Van der Stede (2006), the characteristics that differentiate case study research from other forms of research, is that it involves the in-depth study of real-world phenomena and events by direct contact with the participants in the organization in order to discover why they exist. I was able to study the research question in a deeper context due to an internship of five months with active involvement in the research setting. A qualitative case study requires this close engagement and direct contact with participants, in contrary to a distanced capture (Ahrens & Chapman, 2006).

The setting of the case study is a Business Unit of a Dutch postal company, called Dutch Logistics from now on due to anonymization. The postal market is changing, due to growth in e-commerce, an aging population and technological developments, and the organization has to quickly adapt to this. Digitalization is identified as one of the market trends that is shaping the lives of their customers and has a direct impact on their strategy. Next to the traditional mail and parcel industry, the company also provides logistics services to the B2B market. The BU of interest, called Dutch Logistics BU from now on, grows by over 15% year-on-year and shows great potential.

Dutch Logistics BU is highly appropriate for studying the research question, while it enables me to analyze a company that aims to become more data-driven, by introducing BA tools, and fully capture the impact of BA on organizational performance measurement. Thereby, performance measurement is seen as an important attribute in this company, both financially as operational. A weekly report is made by the Business Controller, which presents the results on the Key Performance Indicators (KPIs) and the Net Promoter Score (NPS). Every Tuesday morning this is presented to the entire company of Dutch Logistics BU in an informal way by General Management. Especially their NPS, reviewed by approximately 1.000 customers per week, is one of their most important

benchmarks and drivers. The combination of a digitized mindset and emphasis on performance indicators makes this a very appropriate case setting.

3.2 Data Collection

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data collection are the semi-structured interviews, because they are useful to obtain descriptions by the people actually experiencing the phenomenon of interest and it offers the possibility to analyze a small sample in detail (Flick, Kardorff & Steinke, 2004; Gioia, Corley & Hamilton, 2012). A total of 18 semi-structured in-depth interviews were undertaken with 10 employees during a collection period of two months. An interview protocol with open-ended questions was composed to encourage the interviewees to talk freely, while still focusing on the main research question. This interview protocol can be found in Appendix A. Moreover, this research is interpretive in nature, so all information collected up to that point in time was reviewed and there was flexibility to ask more questions and address issues that arose from subsequent interviews. This enabled the discovery of new concepts, often described as a problematic aspect of traditional research (Gioia et al., 2012). The sample was chosen according to the purposeful sampling method, characterized by the selection of information-rich cases for investigating the research question in depth (Patton, 1990). My internship coordinator had an advising role in this, while I arranged a pilot meeting with him to gain broad insights into the phenomenon of interest in combination with the case setting to identify relevant participants. Eventually, the sample of participants was chosen on the premise of intensity sampling and maximum variation sampling. The sample consists of employees with rich examples from different backgrounds, departments and levels in the organization, such as operations, control, sales, IT and general management, in order to analyze BA in the context of broader operational performance management (Patton, 1990). All interviews were tape recorded and followed-up by email and telephone conversations for clarification when necessary. Thereby, transcripts of the interviews were sent back to the interviewees in order to assure validity and verification. Table 1 in Appendix B shows the characteristics of the interviewees with function, field, date, and time.

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3.3 Data Analysis After data collection, all the interviews were formally transcribed without changing the key words and expressions. The company observations and archival documents were examined in order to gain additional information and knowledge on the subject of interest. These findings were summarized and added as a transcription as well. Subsequently, the transcriptions were analytically coded and analyzed to potentially identify patterns. Atlas.ti was used as a software tool to perform the systematic processes of open coding, axial coding and selective coding of all findings (Wolfswinkel, Furtmueller & Wilderom, 2011). Codes where attached to quotes from the text, while staying close to the actual words and meaning of the interviewee. The analytical strategy used for coding is an inductive approach, while the codes will be derived from the data itself, according to the method of Gioia, Corley & Hamilton (2012). Their method is aimed at analyzing data for concept development that creates the opportunity to identify new concepts.

After the first cycle of analysis, a total of 149 first-order concepts emerged from data analysis. The codes that represented similar concepts were merged and after repeatedly going through all transcripts and codes again, this eventually led to a total of 75 first-order concepts. Hereafter, code groups were formed to structure the codes, which resulted in a total of nine second-order themes. In turn, they belonged to four aggregate dimensions, that shape the main findings of this study. These four dimensions are found to be the main management activities where BA is used to manage and measure performance.

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4. Findings

This section will describe how BA is used to measure and manage organizational performance as described by the informants from Dutch Logistics BU. The table below illustrates the data structure that was built from analysis and shows the main concepts of this study. The findings that are reported here are found to be of great interest by the researcher or considered of major importance by the interviewees. The focus will be on describing the unique contributions of the study, while using confirmed organizational processes as backbone and support.

Figure 1. Data Structure

In order to reinforce understanding of the findings, information on the KPIs, IT systems and BA tools that are used in the case company are given to familiarize the reader with some background

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4.1 Create Insights on Performance Drivers

Based on data analysis, it became clear that BA has a supporting role in the design of quality performance indicators, however they are still mainly chosen on the premise of experience and long-term vision of management. It all starts with an organizational vision that management wants to translate in order to achieve certain performance results. Under the vision are long- and short-term goals, which are in turn translated into relevant Key Performance Indicators (KPIs). Dutch Logistics BU created an X-matrix, a yearly updated strategic roadmap established by the Management Team (MT), where all of this comes together. The X-matrix is built on the long-term organizational vision and goals, in combination with the current organizational state and business environment.

‘’It all starts with a vision. The MT has to come up with a vision and then you search for ways to translate this vision with help of your employees to performance results. [...] The X-Matrix is what it all combines: our vision, which goals we want to reach and what does that mean for operations, customer management

and commerce. You use KPIs to make sure employees in the operation also know where to focus on regarding performance.’’

Before the introduction of BA, KPIs and related performance targets were always chosen on the basis of experience and long-term vision, recorded in the X-Matrix. Designing key performance indicators was a process through the years and revision did not take place that often in Dutch Logistics BU. Thereby, some KPIs are organizationally wide accepted by Dutch Logistics and logical for the entire logistics industry, such as Timeliness and Hitrate. Timeliness of the carriers shows parcel delivery time in relation to the communicated timeslot and Hitrate the number of successful deliveries, expressed in a percentage. These KPIs are already used for a long time, also in the mother company, due to the same business and are not chosen on the premise of BA.

‘’We do not use BA for deciding on our set of KPIs. The set of KPIs has not changed for a very long time. [...] Timeliness, Hitrate, what do you have to change about these using BA tools?

Mentioned by the general manager was the fact that BA mainly offers a supporting role, not leading, in translating strategy to performance indicators. They rely on the experience and competences of the MT members in deciding on the most important KPIs. This is related to years of experience in Dutch Logistics BU, ability to signal important developments and a feeling of the direction the organization wants to go. They make use of human sensemaking and BA can provide support.

In my opinion, the tool is completely supporting. We start with a business idea, or a gut feeling where the company has to go. For example, the NPS score and then we started to organize the whole Christmas tree

around it. The tool helps us with that, not the other way around.’’

Due to the BA tools, Dutch Logistics BU did start to review KPIs and targets also on the basis of facts in combination with experience, as mentioned by the controller. However, he was the only one, while the other members of the MT did not see the necessity of using BA for PMS design. This shows the differences of personal attitude towards analytics and impact on use.

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Outlined was the fact that involving relevant employees and gathering input from all departments and levels in the organization is useful for designing KPIs and targets. Management mentioned that deciding on performance measures is still completely in their hands, but they try to involve their teams as much of possible and take their input into consideration.

‘’We do this together with employees on the floor, because they can tell us the best what has to be improved and how to do this. I do not believe in a world where the manager tells the employee where to focus on,

that has to come together from top to bottom. ‘’

Furthermore, BA is found to provide great knowledge on the causalities between performance indicators. Only the results, as presented in the weekly report, do not provide explanations on why a certain number is higher or lower than the week before. By using the analytical tools, the real causes can be found, and it enables to go in-depth and work with it.

‘’You can only improve when you are aware of the root cause and the tools support us in the identification. Zoom in, determine the root cause better and set up actions.’’

Once identified, it can support management in prioritizing resources and putting the right actions into place. The general manager explained this in an example.

‘’For example, you saw the big increase in NPS, that surprised us. We start to search where this is coming from. Combining all kind of data sources makes it possible to indicate cause and effect. [...] Once you found these, you can work with it. 1. You can explain it to others. 2. You can focus on it. [...] By having

cause and effect clear, you can use resources as effective as possible.’’

Now, due to the diversity of data sources and systems that are included in BA, it is possible to make specific cuts in order to find cross connections and deeper explanations. Sometimes certain questions arise and analyzing where the root cause lies can be very valuable. Before introduction of BA, Dutch Logistics BU did not have deep knowledge on the relations between performance drivers, because they did not have the possibility to make cross connections due to standalone databases.

‘’What is interesting about the tools is the diversity of data sources that are included. You can try to identify cross-connections and make easy cuts. Per day, per week, per month or the hitrate in combination

with NPS. [...]. This brings us a lot and we waited long for such an instrument.’’

Due to the identification of root causes, the organization can make sure that they focus on the right performance drivers and gain new insights on indicators. An example was observed during the MT meeting. Due to BA, the controller recognized that the high amount of not executed top services was the root cause of the low NPS score that week. The organizational situation before introduction of BA tools would not accommodate identification of this cause, because indicators were not combined.

‘’Gradually you find more explanations on the drivers of performance. We always look for the explanation why something is improving or not and these tools help us in the identification. For example, when there is more cubage for 2M distribution, this increases your distribution costs extremely. Or when the hitrate is

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To summarize, BA is found to be used in the case company to gain new insights on the true drivers of performance, due to the possibility of making cross-connections. However, the introduction of BA tools did not replace the traditional choice regarding KPIs, while this is mainly dependent on the experience, gut-feelings and long-term vision of management. BA tools are found to be supporting, but there is still high emphasis on human sensemaking.

4.2 Create Awareness

Secondly, BA is used in creating awareness of performance and communicating performance to stakeholders. Especially involving external stakeholders by using BA in performance management is a remarkable finding of this study. Before introduction of BA, internal employees were not that aware of their performance results. The weekly, as reported and e-mailed by the controller every week, showed the results on the main KPIs in a standardized format. This report was not accessible for the entire BU and only shared by managers now and then. The use of real-time dashboards created a stage to provide recent information on performance results and keeping track of performance became much easier, up-to-date and less time consuming. A dashboard with results on the main KPI is shown on a big screen in the hall of the Headquarter and all employees can log in themselves as well. Not only BA supported this awareness, management effort played a major role as well and showed that the necessity for human communication in combination with digitalization.

‘’We are more aware of the results we achieve nowadays. BA supports this awareness but also the fact that we discuss the results more broadly. We make all the employees associated and communicate performance

results more towards our teams.’’

Next to introducing BA tools, the MT also introduced a weekly stand-up on Tuesday 10:00 in the canteen where all the results on KPIs are communicated regarding the week before. Everybody is welcome, from operational coordinators to account managers and IT. Performance is communicated and shared more broadly and their goal is to make all the employees associated with the performance results. Embracing the results and carrying it throughout the organization also enables disseminating strategy in the entire organization and BA can play an important role in this. Dutch Logistics BU identified NPS as most important KPI and embraced this KPI by extensively measuring it, visualizing it into a real-time BA dashboard and showing the importance to the entire organization during the stand-up. Moreover, the stand-up provides an effective way to continuously align strategy.

‘’We carried the NPS dashboard very broadly in the entire organization, because there is a philosophy behind it. We used the NPS dashboard as a way to take people along with our new way of working, the focus on NPS, and everybody has to understand that. Employees should breathe it and be frustrated when

there is a low NPS.’’

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‘’Where I am really proud of above all is measuring the NPS score, which we started two and a half years ago. At first, we did not have any clue what it was. We started with a score of 12, that was definitely not 100. We really embraced this and that is beautiful to see. We are now above 40.’’

A noteworthy finding drawn from this study is the fact that external stakeholders are made part of their own and the joint performance of the company using BA. Dutch Logistics BU is very dependent on the performance of their external stakeholders, which are subcontractors that deliver the products and clients who outsource the delivery of their products. When internally introducing BA tools, access was also given to the external parties, aimed at creating broad performance awareness. Performance results are shared by giving them access to the dashboards and the ability to monitor their performance on a real-time basis.

‘’It is a way to make them aware of performance and to let the subcontractors proactively work on improvements. Not on the basis of our signals, but that they proactively engage in conversations with their

carriers. For example, when a bad comment is mentioned and signalled in the dashboard, what are we doing to work on this? [...] They can now monitor it themselves. We think it is important that they can put

actions on this themselves.’’

It resulted in a closer engagement between Dutch Logistics BU and its external stakeholders. Due to BA, they are able to provide external parties fact-based evidence that involves useful knowledge. This eventually supports the revenues of all parties and more proactive engagement in performance improvement.

‘’We are already on the right track, while a lot of them have an account for the NPS dashboard to login at home and use it for directing their carriers.[...] Ever since we use SAP, we can really show what the costs

and benefits of a carrier are, that definitely brought about. In the positive way for our organization.’’ Due to introduction of BA, the case company also established a stronger feeling of responsibility for performance. As employees are now aware and able to monitor their own performance, the MT uses this as an incentive for employees to improve and put actions on performance. They cannot hide behind a lack of knowledge on root causes and responsibilities are being stretched from top to bottom now.

‘’The goal is to cultivate responsibility and the address each other. When this is the case, everyone from the floor till the top will be working on the results.’’

This is also the case for the external stakeholders. Subcontractors and clients are held accountable for improving their own performance, because Dutch Logistics BU provides them useful information to improve performance. In exchange for this knowledge, actions should be put into place. An example was made clear by the manager in charge of quality delivery.

‘’My work did change. I am less intensive working on actions to improve the performance of the carriers. The responsibilities for that are more deposited with the subcontractors now.’’

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‘’There was a need for more information and in the old systems this was very difficult to access and only for a limited group of people. The new system SAPbw is for a way bigger group of people available and

information is easier to obtain.’’

Higher and middle management addressed the fact that they have quicker access to a much bigger variety of information than before, due to the tools.

‘’Back in the days we used different systems, which were less insightful. The information is now much easier available for managers and employees. There is also more information in it, and I can get

knowledge from it.’’

Due to BA, all the data is combined into one comprehensive database and everything can be found there. The information existed already, however was cut into many pieces, which made the collection of information for analysis very time consuming and challenging.

‘’The biggest advantage is the simplicity with which you can combine data sources. [...] Especially for SAPbw, I think we have made great steps and real value has been added here. [...] The entire organization

is now able to combine these sources.’’

Moreover, BA stimulated tailored self-service, while employees, managers and external parties are now able to make the analysis themselves. Before, internal employees had to ask someone, mainly the controller, to make a certain analysis and tie information together or the external stakeholders had to ask the sales managers for reports. Currently, it became self-service, because they can extract the information from the tools themselves and exactly search for the explanation they are looking for. This is less time consuming and more effective, because they know exactly what they want to analyze and do not have to wait to receive the analysis.

‘’Before, data analysis always came from me. I had to do the complicated data stuff. Now, people can get it themselves from the data tool. It became way more accessible for others. The analysis also got better for

that reason, they are more involved in that subject and there is more information available for them.’’ In creating awareness of performance and actively working with results, the trustworthiness of BA systems and the included performance results are found to be of high importance. It is important to create trust among the users of BA so that they can rely on it in performing their daily job.

‘’ It is also about trust, that people know what is begin reported and that you can blindly rely on that. That is not always the case here. For example, I should be able to extract the NPS score blindly from SAPbw, however I do not, because I do not trust it. Trust in a system is very important, if that is present

people will use it.’’

Dutch Logistics BU showed that creating trust can be supported by ensuring high quality data without major gaps, build it on a lot of measurements and showing where the data comes from. Additionally, there should be consistency in the outcomes of performance results from different BA tools. In the case company this is identified as a reason for lower trustworthiness. Due to its functionalities, multiple BA systems and files are used in conjunction, however this leads to confusion and people losing their trust.

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meeting. There are 2 different numbers and you never want that. We see the weekly as truth, we calculate with that one.’’

To summarize, BA is used in conjunction with management effort to create broad awareness of performance results. Dutch Logistics BU mainly uses BA to create this awareness externally, while they are very dependent on the performance of external stakeholders and insights are broadly shared now. Stronger performance awareness stretches responsibilities from top to bottom and vitalizes engagement. Moreover, there is a move towards tailored self-service analytics, due to broad accessibility and comprehensive data tools, which can improve performance. It is more effective and less time-consuming.

4.3 Effective Control

As derived from the interviews and observations, the third use of BA in PMS is the creation of a deeper understanding of performance numbers in order to effectively control and take actions on performance. Before the introduction of BA tools, the discovery of explanations and in turn deciding on focus of control was very difficult. Actions were set out on the premise of intuition and a feeling of the root cause. However, the general manager argued that in order to manage performance, a much deeper understanding of numbers is necessary.

‘’ A result is only a result; you cannot manage and control that. You have to understand how the results are achieved and then you can manage and steer in the right direction. [...] It all starts with results, either positive or negative, like a traffic light. On the basis of these traffic lights, we try to go the reality of today

and create understanding. This enables us to turn the right buttons. ‘’

From higher to lower employees in different fields, BA now provides deeper information and enables the search for explanations, which supports their understanding of what is going on in the business. The tools make it possible to slice results, such as per subcontractor, client or service, and search for deeper explanations. Thereby, outliers and disruptors can easily be spotted, which enables adjusting focus in the short run.

‘’The goal for me when using BA is to provide insights on why we are having a good or less good NPS score that week. In this way we can identify who the disruptors are. Based on that we invite the

subcontractors for awareness meetings.’’

On the long run, higher managers can create a more integral view by combining data from all departments, analyzing future scenarios and putting the right resources in place.

‘’By combining we can create an integral view of costs, revenues and all the resources needed. This helps you to analyze future scenarios and decisions.’’

In order for BA to be effectively used in creating understanding, it is important that employees and managers are able to extract the real value from the data and turn it into valuable information. In order to extract value, a real understanding of the numbers must be established.

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‘’In my opinion, it is really basic to look at a number without knowing how it comes about.’’ Experience with data analysis, experience in the business and some basic data skills can support people in drawing the right conclusions from data. This was mentioned as the most important threat in the case company, while sometimes the wrong conclusions are drawn, and therefore they plan to invest in the field of analytics. They acknowledged that there are more opportunities.

‘’We can do way more with the measurement of NPS, there is a lot of data behind it, but we still do not understand why it is increasing or decreasing. We are making plans for 2020 with the management team to

make steps in this field.’’

To support employees in extracting the right value from data, a pioneer with data competencies can be of great help. In the case company the controller was this person. He introduced the tools, set up the trainings and had great knowledge in translating data to information. It was mentioned by employees and other managers that they appreciate the open culture where it is accepted to ask questions and that they know who to turn to when they struggle with data analysis. A downside here is the fact that there is much dependency on one person in extracting value from data.

‘’We are becoming more data-driven. [...] Our controller is a good example of someone who really wants to work with data and is good with it. He looks at the data that is available and which benefits we can get

from it. He has a yellow disc profile, showing initiative.’’

Moreover, BA enables a ‘shorter on the ball’ mentality and one of the main activity’s BA is used for is deciding where to focus on, adjust direction and take actions on performance.

‘’When something can be better, I base my control decisions on BA. It shows me where more attention is needed or whom I need to call to let him put more focus on something.’’

‘’If you put actions on this, for example supporting to turn low scores NPS into high scores, then you get the ‘pollution’ out. We were able to see in the dashboard that it had to do with someone's timeliness, and we coached him. [...] We supported him. We were able to track this in BA and subsequently take actions on

focus points.’’

BA assists in signalling problems before they get out of hand. Future problems can be tackled predictively, which in turn leads to long-term better performance.

‘’It is possible to go into depth with these tools. [...] By making a deepening, we can track down a problem. Subsequently, you can understand where the problem is and try to tackle it. [...] Managing performance became easier, because you quicker identify where the problem is and where it goes wrong. [...] Because

we now know where it goes wrong, we can quickly act and make structural improvements. ‘’ Moreover, structural improvements could be added due to insights from BA, which leads to faster progress and better results. An example was made clear by the manager Operations.

‘’ By analyzing the NPS and the impact of emergency rides, which are rides on the same day to minimize the irregularities, we found out that it did not have the positive effect we were expecting. [...] These rides are expensive, but did not provide the desired results, so we decided to eliminate them, and our overall

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To summarize, BA enables the establishment of a deep understanding of performance results, in order to take quick actions on the short-run and effectively manage the long-run, due to stronger predictive analysis and signalling problems. However, extracting this value showed to be the main challenge, while the wrong conclusions can easily be drawn. A data pioneer with strong knowledge of analytics and the business dynamics can support this.

4.4 Evidence-based Reviewing

The final dimension drawn from the interviews and observations is the use of BA in evidence-based reviewing, due to decision-making based on facts and substantiated discussions in review meetings. The increased amount of information available and performance awareness is also visible in performance review meetings. Several performance review meetings are held in the case company. Examples are the weekly MT meeting including a stand-up in the canteen, two-weekly Operational MT meeting, daily Operational meeting and scheduled awareness meetings with subcontractors. Due to the introduction of BA, these meetings are moving away from discussions looking only backward at the performance results, to discussions on problem-solving, actions for improvement and forecasting. The discussions in these meetings became way more substantiated due to BA.

‘’Since we are using the BA tools, I have more discussions and conversations on how to improve the results on the basis of data. People who use the tools can base their story really on facts. This is a major

improvement, by looking further instead of using the old methods that are used for years.’’

The dashboard is now shown live during the internal meetings to evaluate performance, which enables more specific discussions than before. Because all results are now transparent, they cannot be ignored, and managers need to have their story straight. Next to the live use, BA is also used before and after review meetings to build these stories and collect explanations of certain deviations. When these deviations are detected during a meeting, actions are directly set out.

‘’When I am in the daily operational meeting at 12 o’clock I see the standard reports. Something has happened during the day before, for example a person that is not behaving. [...] I am curious to see what his hitrate, NPS score and other results are. I can get these from SAPbw and then I have a story. A feeling

is being substantiated by facts. That is how you can start a good discussion.’’

Interesting in this respect, is the fact that external stakeholders are invited for ‘Awareness Conversations’ on the premise of insights from BA. After introducing BA tools, Dutch Logistics BU was able to spot disruptors and decided to proactively engage in performance improvement by organizing these special meetings on a weekly basis. BA is used live here to substantiate the story and to address certain issues. They go way deeper during a conversation and multiple cuts can be made in order to look for improvement. So, BA is not only used to increase the awareness of the external stakeholders, also to engage in substantiated conversations with them.

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call this Awareness Conversations and we talk about the results of a carrier, by opening and using SAPbw. This is really based on facts; you cannot make it any flatter.’’

Due to more performance review meetings that are supported by BA, decision-making during these meetings and overall became more fact-based. Traditional decision-making was based on intuition and feeling. Due to BA, they are now able to test if this feeling is right and hypotheses can be confirmed or neglected. Important to recognize here, the hypothesis has to arise there needs to be a good balance of human judgement and data analysis.

‘’We have a hypothesis, because often there is intuitively already an expectation. Subsequently, we translate this into an action, and someone starts to test the hypothesis. You can do this by using the data.’’ By using the BA tools for decision-making, decisions became more data-driven. This is also assisted by the fact that more numbers are available and accessible. Before, decisions were mostly made on the basis of experience or the number of complaints. Now, decisions are fact-based and recognized by middle and higher management as better decisions.

‘’Now I get a number on the quality of a specific carrier. I have something to measure and before it was on the basis of complaints about the carriers. Sometimes they are completely out of proportion, so not representative to base decisions on. Now we extract a number and that is way more trustworthy. The

information is better, so my decisions also.’’

Moreover, BA is used to make analysis for the future, in terms of investigating trends and developments, explaining certain patterns and producing predictive scenarios. This helps analyzing for future decisions, while you can build on numbers and facts.

In order to move towards a data-driven organization and make decisions on the premise of data, an organization should be open towards a change in working in order to capture all the benefits BA offers. It is important that the organization is not afraid of change and is open towards new working methods by embracing new innovations and opportunities. This was mentioned in the case company as an important threat, while some of the employees are to reactive instead of proactive and remain focused on old habits.

‘’Some people linger in old habits and working methods. Some people are more progressive in this respect than others. It is necessary to be open towards it and management should provide enough attention.’’ Thereby, people have to be familiarised with new systems and see the importance in order to extensively use it. A hurdle for effective use in the case company is the fact that people are not yet used to working with the system.

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managers got assignments to practice with the tools. The controller who introduced the tool was walking around answering questions when necessary.

‘’The people who are using it more often encounter no problems. For the people using it for the first time, it is more difficult to understand how it exactly works. I wish the systems were a bit more intuitive.’’ Moreover, the role of management in promoting BA use is found the be of high influence. Management showing the benefits and importance of advanced data analysis, activating the use and promoting the change is recognized as a prerequisite to move towards a data-driven organization. Management should have a proactive mindset towards their employees, by supporting and embracing data analysis, instead of reactive.

‘’I think that management has to carry out and stimulate, so people will use it themselves. It does not have to come purely from management as a message, but they do have to stimulate working with it and familiarise people with the systems, for example by organizing trainings. When people who are more involved in the day-to-day operations think about improvement ideas, this can be very beneficial. Thereby,

I try to communicate it in my teams. Carrying it out is very important.’’

When use is activated and promoted, BA should be user-friendly to facilitate effective use and make sure that less time is spent on analyzing and combining drivers. A difference was visible in the case company, while the PowerBI dashboard was evaluated as easier and more user-friendly than the SAPbw tool. User-friendliness was recognized as having a big influence on the number of users.

‘’It is the question whether the user-friendliness will stay the same or if it gets better. This will help to make more people work with the tools.’’

Subsequently, employees should have a feeling of interest and relevance in using BA. When information for specific functions is not included or representative for the activities the employee is involved in, there will be no use and a company effort is not achieved. This was the case for the operational employees in the company, because they did not have interest in use.

‘’The tools are used way less in the operation, because for the operation not all the relevant information is included. There are possibilities for use though, but more information has to be added. What is now in the systems is information on the rides, relevant for the carriers. The data is less comprehensive on activities in

the operation and warehouse itself. We want to add this in the future, so BA will also be used in the operational processes.’’

BA must ensure a complete information set of all relevant organizational indicators in order to be extensively used. When driving factors of performance are missing, this implies that there is a gap in the information and BA cannot be completely effective. The tools should maintain its relevance and be comprehensive. The case company does that in the following way, by adding relevant factors to the visualization of the NPS score in their PowerBI dashboard on a regularly basis.

‘’We take actions ourselves to make sure that our data systems are relevant for use in practice. We ask Markteffect to make adjustments in the dashboard and add the factors we wish for. For example, it is possible to now monitor and visualize NPS based on zip code area. We add factors and update the system

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5. Discussion

The findings of this study show that Business Analytics is used to gain insights on performance drivers, to create awareness of performance for (external) stakeholders, to achieve effective and proactive control of the business and finally, to move to effective reviewing with substantiated discussions and fact-based decision-making. In this section, these findings will be discussed in light of the existing body of literature.

In line with existing extant literature, BA is found to be beneficially used for identifying causalities between performance drivers and search for root causes and relationships (Ittner & Larcker, 2005; Klatt et al., 2011; Silvestro, 2016). The possibility of making cross-connections, due to the combination of multiple data sources in BA, brings valuable information and new information to the table. It is said that in order to improve key decisions, KPIs should be based on BA and the insights from analytics, to move away from performance indicators based on intuition (Ittner & Larcker, 2005; Davenport et al., 2010). However, the findings show that KPIs and related targets are still mainly based on the premise of experience and on the long-term vision of management instead of analytics. Although BA provides useful knowledge on the true drivers of performance, most managers of the case company stated that they do not see the necessity to use BA in designing performance indicators. The main reasons for this are the fact that they have built a strong long-term vision, have years of experience and there are a bunch of logical KPIs already for this specific industry. This study found that BA provides a supporting, not leading, role and that the insights are mainly used for effective control and reviewing. The case study showed that BA holds potential for generating new insights and densities, but the sense-making aspect of the process should not be ignored (Lycett, 2013). We can even say in this case that the sense-making aspect is more important, while the KPIs are not emerging from data analytics.

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Appelbaum et al., 2017; Raffoni et al., 2018). Stakeholders are able to search for the exact explanation themselves, showing to be less time-consuming and more effective. However, inconsistencies from different BA tools, leading to lower trustworthiness, slows this down (Barton & Court, 2012; Fosso Wamba et al., 2015).

An important confirmation of this study is the creation of a deeper understanding of performance results in order to take quick actions on performance, which enhances the diagnostic use of PMS (Barton & Court, 2012; Raffoni et al., 2018). Dutch Logistics BU was able to signal problems early on and add structural improvements, due to the use and analysis of recent operational data (Silvi et al., 2010; Davenport & Harris, 2019). However, the extraction of real value from data showed to be challenging and can limit effective control (Appelbaum et al., 2017). This challenge can be tackled by a data pioneer, who supports employees in drawing the right conclusions and utilizing data. This person has strong knowledge of BA tools and the organizational environment in which it operates.

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6. Conclusion

This section will first describe the objective of the study, followed by a summary of the most important findings. Hereafter, the limitations of the study will be elaborated on and directions for future research will be provided. Finally, the managerial and practical implications will be presented and discussed.

6.1 Main findings on Research Question

This research has been conducted to provide practical evidence on how BA is used in PMS, to shed light on challenges and implications faced by organizations during the design and use stages and to provide useful lessons for the future. An in-depth single case study was conducted in a growing BU of a postal company in the Netherlands, resulting in several interesting contributions.

To summarize, the findings of this study confirmed that some of the challenges faced by traditional PMS can be improved by integrating BA, such as continuous strategic alignment and the identification of causal relationships. However, the case company also showed that making use of Big Data and extracting real value remains a challenge and that a strong combination of human and data capabilities is needed. BA offers a supporting role in creating new insights, enhancing performance awareness, understanding performance results and taking quick actions. Nevertheless, it should not be considered as a replacement of human intuition and judgement.

6.2 Limitations and directions for future research

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6.3 Managerial Implications

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The Supporting Force of Analytics: How Business Analytics is used to measure and manage Organizational Performance