Contemporary performance measurement and management (PMM) in digital economies

Abstract

The rate of change in the world is increasing both in scope and magnitude by rapidly developing digital technologies. The challenging problem for performance measurement and management (PMM) in the digital era is twofold: firstly, the constant change in the external environment is compelling PMM to be more dynamic. Secondly, organisations have to deal with different varieties and volumes of data to create competitive advantage. The aim of this paper is to explore how PMM models and practices should be renovated to be resilient and reflect advances in the digital economies. Literature review on the state of the art was conducted covering the issues faced by organisations in the digital economies and their relevance to PMM. A case study was conducted to explore the practitioner perceptions of dealing with the issues faced in digital economies as well as to understand how they are making changes to their PMM. The key findings from the study include: (1) Organisations should refocus their measurement efforts to incorporate evaluation of their performance over a wider network involving various stakeholders. (2) Organisations need to understand how technological developments could create competitive advantage through their strategy and deploy it to relevant positivistic and behavioural measures.

Keywords:

• Performance measurement and management
• big data
• social media
• evaluation
• behavioural measures

1. Introduction

As we move into the twenty-first century, there is an increasing belief and evidence that the rate of change in the world is set to increase further both in scope and magnitude, coming from unexpected directions (Kotter and Cohen 2002; Harrington, Boyson, and Corsi 2011; Bititci et al. 2012). Such change is fuelled by rapidly developing digital technologies, which, in turn, is influencing the way businesses are managed (Barton and Court 2012). An information revolution together with social media is increasing awareness of options for products and services thus raising customer expectations (Harrison and Van Hoek 2011). It is widely recognised that performance measurement and management (PMM) brings improvements in the form of efficiency and effectiveness in many organisations (Neely et al. 1995). Wamba et al. (2015) argue that future organisational performance is intimately interlinked with technological developments in digital economies and highlights the urgent need of empirical research. It is also argued that the majority of PMM-related research has been developed from an assumption that organisations operate in a stable environment. In fact, Andersen, Busi, and Onsøyen (2014) argue that the PMM field was stagnant for the last decade with no significant development and needs future direction and agenda. This study will explore the resilience of PMM systems in dynamic and rapidly changing digital environments, currently not adequately understood (Melnyk et al. 2014).

Hence, the overall aim of this paper is to explore how PMM models and practices should be transformed to be resilient and reflect advances in the digital economies. Specific objectives are:

•	To conduct a literature review on PMM, and its potential transformation to reflect changes within digital economies
•	To explore practitioner thoughts on how PMM has or should be transformed to improve efficacy
•	To propose a supplement to the existing frameworks for measuring business performance in light of advances within the digital economies

Initially, the literature was gathered from secondary sources by searching through online journal databases. Additionally, citation tracking, supplemented by the authors’ own expertise was used, to produce a comprehensive literature review. A case study was undertaken with a nuclear services company. Semi-structured interview pro forma was constructed based on the findings obtained from the literature review. Primary data were collected through face-to-face interviews to gather perceptions of practitioners on how the PMM systems were developed as a result of increasing use of digital technologies. Finally, the data were analysed in the light of literature and discussion presented in the later part of the report.

2. Literature review

In the current competitive environment, the global economy is volatile with fluctuating demand, reflecting changing customer requirements and global economic conditions. Increased usage of digital technologies is increasing customer awareness of options for products and services thus raising customer expectations. Developments in real-time ICT capabilities are enabling information to be readily available across supply chains thus reducing lead times while at the same time increasing responsiveness. Ittner, Larcker, and Meyer (2003) argue that contemporary performance measurement should provide information that allows organisations to identify strategies that offer the highest potential to meet customer requirements. Melnyk et al. (2010) suggest that supply chains operating in the current working environment should have the ability to provide one or more (blend) of the six basic outcomes depending on the customer/market requirements, which are cost, responsiveness, resilience, security, innovation and sustainability.

Franco-Santos, Lucianetti, and Bourne (2012) identify that contemporary performance measurement systems have a significant impact on people’s behaviour, organisational capabilities and performance outcomes. They argue that people’s behaviour with measurement and management processes, i.e. strategy, its implementation and communication would generate the necessary capabilities that, in turn, will enable organisations to succeed and create competitive advantage.

The challenging problem for PMM in the digital era is that the external environment is not stable. This will have an impact on an organisation’s strategy that, in turn, will be linked to their PMM (Bititci et al. 2012; Melnyk et al. 2014). Johnston and Pongatichat (2008) conducted research in public sector organisations to identify that where a mismatch occurred between strategy and performance measures, the practitioners were using different tactics (other than adjusting it) to cope with the misalignment. Bititci et al. (2012) conducted an extended literature review in the light of recent business trends and proposed that organisations should shift their focus of PMM from rational control to cultural control and learning, move from a positivistic approach to pragmatist approach as well as discreet measurement to integrated measurement. Melnyk et al. (2014) argue the need for development of a resilient PMM approach to reflect strategy in volatile environments. They conducted a Delphi study to explore expert opinions to extract the performance matrix with two dimensions on outcomes and solutions, either generic or specific, to provide four options: assessment-driven management, outcome-driven solutions, solution-driven outcomes or measurement-driven management.

Nudurupati et al. (2014), after conducting multiple case studies, propose that organisations operating in rapidly changing environments should monitor the external disruption in the market and take the opportunity to embrace the technical competencies to innovate new products, services, approaches or business models. In order to cope with the recent business trends and external disruptions (due to ICT), Nudurupati et al. proposed three findings to make PMM more resilient. Firstly, the organisations that collaborate with different stakeholders should shift the focus of PMM from measurement to evaluation, i.e., how the stakeholders (customers, suppliers and other partners on the network) evaluate the organisational performance. As suggested by Chaffey and Ellis-Chadwick (2012), there is a need to explore performance evaluation metrics that exist on the marketing interface of the organisation. Secondly, organisations embracing innovation should shift the focus of PMM from a command and control approach (i.e. positivistic measurement) to a more open and non-threatening approach (i.e. interpretivist evaluation rather than evaluation through objective measures alone). In fact, this is echoed by Micheli and Mari (2014) who argue the change needed from an objective view towards a pragmatic view of measuring performance to tackle inherent incompleteness of performance measurement. Finally, organisations that need to align the sustainability agenda to their existing strategy should enable the PMM system to deploy the appropriate measures into balanced categories, i.e., economic, environmental and social aspects (triple bottom line, Elkington 1994).

The shift from product-dominant to service-dominant thinking is enabling organisations to offer different combinations of product and services (Ng and Nudurupati 2010), that require fresh and innovative thinking on how organisations should be configured, measured and managed. The combined offering creates pressure on organisations to fulfil contractual obligations to customers who have extremely diverse and unpredictable requirements (Baines, Lightfoot, and Smart 2011). It should be noted that the capabilities, competences and resources of the organisation have to match the combined offer provided for the contextual needs of the customer (Windahl et al. 2004). A major problem for combined offerings is the lack of shared understanding within the network, often with many disciplines and functions involved (Johansson et al. 2011). Hence, organisations must look beyond the immediate transactions with their suppliers and customers (Johnstone, Dainty, and Wilkinson 2009) towards holistic understanding of resources and competencies within the network that create value (Zott, Amit, and Massa 2011).

The continuing growth of the service economy underpins the increasing need for a shift from value-in-exchange towards value-in-use, in the light of value co-creation (Vargo and Lusch 2008). The key issue for organisations is co-creating value with its customers by deploying the necessary capabilities and resources together for delivering value-in-use (Vargo and Lusch 2008; Barrutia and Gilsanz 2013). Mukhtar, Ismail, and Yahya (2012) articulates the changing role of customer as an average statistic with one-way communication in the 1970s to a co-creator of their own experiences and expectations through multilevel access and communication in the twenty-first century. They proposed various techniques and models for designing encounter processes to co-create value for unlocking innovation in organisations. Hence, organisations require a new business model or approach with a customer focus, collaboration, co-creation and holistic systems thinking for their value creating system (Ng, Ding, and Yip 2012).

According to Aurich et al. (2010), the customer plays an active part in exploiting value-in-use and hence it is necessary to understand and capture knowledge on their behaviour. Recently, this concept was discussed in the literature under the umbrella term called ‘Internet-of-Things (IoT)’. Swan (2012) describes IoT as aspects (either an object or subject) that are readable, traceable, locatable and controllable as well as connecting to each other or networking through sensors and microprocessors. IoT could be used to monitor and control the performance of objects and subjects in the customer domain. Its application is wide ranging such as in automotive, logistics, transport, healthcare, research, bio-technology. Kamalanathan et al. (2013) suggest that IoT could be creatively used as a knowledge management tool in monitoring patients continuously and effectively after discharge from hospitals. As a result of IoT in a wide range of applications, large numbers of objects and subjects emit data at an unprecedented rate. Tyagi, Darwish, and Khan (2014) propose a computer infrastructure for IoT data processing focussing on major challenges for massive data.

On one hand, it is evident from past research (see Bourne 2005) that advances in technology (such as ICT) is supporting the performance measurement system throughout its life cycle. Geri and Geri (2011) discovered that organisations exacerbate their own information overload challenge by using and integrating advanced technology for creating more information, which is often redundant. This is not new and can be traced back to the 1950s where March and Simon (1958) argue that organisations are viewed as information processing systems that capture data from different streams and transform them into meaningful information. Mendelson and Pillai (1999) identify that organisational financial performance is associated with organisations’ ability to process information and make effective decisions in a dynamic environment. Even today, the challenge remains valid for practitioners to develop resilient performance measurement systems (in dynamic contexts) that present sensible information to enable proactive decision-making (Melnyk et al. 2014). On the other hand, the advent of social media is enabling customers to evaluate business performance and hence is presenting organisations with a different type of challenge. While Aral, Dellarocas, and Godes. (2013) argue that social media is changing the way we operate business and communicate with stakeholders, Keegan (2011) claims that social media enables B2Cs and C2Cs to communicate in open and public forums thus providing an opportunity to directly engage with potential customer groups to both promote sales and obtain feedback through evaluation. Social media is an emerging tool for organisations to monitor consumer communications and discussions on their brands, products and services. As suggested by Micheli and Mari (2014), the positivistic view of measuring performance should shift to the pragmatic view, particularly when understanding the organisational performance evaluated in social media.

With the advent of technological developments (high speed network connections, web stream data, voice and video data) as well as social media (Facebook, LinkedIn, Twitter, etc.), organisations are dealing with varieties and volumes of data never encountered before (Chen, Chiang, and Storey 2012; Davenport, Barth, and Bean 2012). The challenge for performance measurement is to process the data into meaningful information to enable decision-making (Bititci et al. 2012) which, when involving large volumes of data, is often referred to in the recent literature with terms such as ‘big data’ or ‘data analytics’ (McAfee and Brynjolfsson 2012; Waller and Fawcett 2013). Boyd and Crawford (2012) define big data using three dimensions, technology, analysis and mythology. Wamba et al. (2015) define big data as an approach to manage, process and analyse data available in different forms, i.e. 5Vs (volume, variety, velocity, veracity and value) for delivering value, measuring performance and creating competitive advantage. Davenport, Barth, and Bean (2012) argue that organisations looking to derive competitive advantage from big data will use real-time information from sensors, radio frequency identification tags (RFID) and other identifying devices to understand their business at a micro level. For instance, there is lot of evidence that the use of RFID will increase efficiencies and effectiveness in organisations (Fosso Wamba and Ngai 2015). Big data have the capability of improving the decision-making processes by enhancing visibility on macro and micro aspects of business operations thus creating new PMM opportunities (McAfee and Brynjolfsson 2012). McAfee and Brynjolfsson (2012) argue that organisations relying on data-driven decision-making demonstrate superior performance over those that do not.

Chen, Chiang, and Storey (2012) articulate that big data and data analytics terms are used to describe data-sets and analytical tools in the applications that are so large and complex that they require advanced data storage, management, analysis and visualisation technologies. While these terms are often discussed by information technology practitioners in their board meetings as well as academics in their research meetings, Mello, Leite, and Martins (2014) argue their relevance and impact on performance measurement and highlight the need for further research in this area. At first, it leaves an impression that big data are only relevant to large organisations that are dealing with high volumes of data, but it is equally challenging to SMEs who are generating large amounts of unstructured data. Davenport and Patil (2012) further argue the dearth of data scientists as a serious concern in several sectors such as e-commerce, marketing intelligence, science and technology, public and private health, public security. Chen, Chiang, and Storey (2012) argue that, unlike traditional data, the big data that e-commerce systems collect from the web is often less structured and contain information on customer opinions and behaviour that are useful for an organisation’s decision-making.

As demonstrated in Figure 1, Barton and Court (2012) propose three areas where organisations need to focus and build strengths in order to improve the performance and benefit from big data and its advanced analytics. Firstly, the organisations have to think of creative ways of sourcing data, i.e., from web analytics, networks, social media, etc., and collate the necessary infrastructure/software to capture, store and analyse data. Secondly, organisations have to understand the critical success factors that are important to their business and build models to predict and optimise performance outcomes. Finally, the presentation of the information to the decision-makers needs to be user friendly and have easy to use tools. The usefulness of data analysis and information depend on how well the results are understood by decision-makers (Hogarth and Soyer 2015). They also have to transform the culture of the organisation by upgrading the analytical skills and literacy of the decision-makers. However, the three areas discussed by Barton and Court are also echoed in PMM literature, for instance see Bourne et al. (2000), who discuss the three stages of performance measurement, i.e. design, implementation and use of performance measurement. As a first step, Davenport, Barth, and Bean (2012) argue that organisations that are capitalising on big data should move their data analytics from the IT function to core operations and production functions.

Figure 1. Organisational strengths in three areas to benefit from big data (Barton and Court 2012).

In summary, the literature review presented resilient features that contemporary PMM should consider in organisations operating in a digital economy, which are documented in Table 1. The aim of this research is to explore practitioner thoughts and perceptions on the resilient features of contemporary PMM and propose a framework for organisations operating in the digital economy. The next section will describe the methods used for achieving the overall aim of this research.

Table 1. Resilient features of contemporary PMM.

No	Resilient features of contemporary PMM	Sources of evidence
1	Organisations collaborating on global network and the need to move from measurement to evaluation	Aurich et al. (2010), Chaffey and Ellis-Chadwick (2012), Keegan (2011), Micheli and Mari (2014), and Nudurupati et al. (2014)
2	Collaborating organisations co-creating value together in improving performance	Tuli, Kohli, and Bharadwaj (2007), Payne, Storbacka, and Frow (2008), Vargo and Lusch (2008), Vargo, Maglio, and Akaka (2008), Mukhtar, Ismail, and Yahya (2012), Barrutia and Gilsanz (2013), and Nudurupati et al. (2015)
3	Organisations do integrate sustainable agenda into PMM	Elkington (1994), Melnyk et al. (2010), Walker and Jones (2012), Taticchi et al. (2014), and Marshall et al. (2015)
4	Using IoT for innovative ways of improving performance	Geri and Geri (2011), Swan (2012), Kamalanathan et al. (2013), Tyagi, Darwish, and Khan (2014)
5	Organisations need to capture, store and process big data? Why and how does it influence PMM	Barton and Court (2012), Bititci et al. (2012), Chen, Chiang, and Storey (2012), Davenport and Patil (2012), McAfee and Brynjolfsson (2012), Waller and Fawcett (2013), and Mello, Leite, and Martins (2014)
6	Organisations need to innovate by transforming positivistic to pragmatic view of PMM	Chaffey and Ellis-Chadwick (2012), Bititci et al. (2012), Micheli and Mari (2014), and Nudurupati et al. (2015)
7	Organisations should transform its culture: • Develop capabilities to handle big data sets • Develop skills such as analytical and literacy • Develop knowledge workforce • Encourage facts/information based decision-making	Johnston and Pongatichat (2008), Bititci et al. (2012), Chen, Chiang, and Storey (2012), Davenport and Patil (2012), Franco-Santos, Lucianetti, and Bourne (2012), Barton and Court (2012), Melnyk et al. (2014), and Hogarth and Soyer (2015)

3. Methods

The case study approach was adopted in this research mainly for two reasons (Eisenhardt 1989; Meredith 1998). Firstly, this research was exploratory in nature. As discussed earlier, it was carried out to find insights of practitioners who are dealing with contemporary PMM issues and their perceptions on its resilient features. Secondly, the case study approach generates richness and a depth of understanding that could be used as a basis for understanding and evaluating the research problem in its real-life context (Yin 2014). While it is difficult to generalise from single case study, we agree with Flyvbjerg (2006) that a single case study can be central to scientific development and act as ‘the force of example’. Other researchers also echo that the use of a single case study is more natural in describing the case and hence capable of delivering richer theoretical insight (Dyer and Wilkins 1991; Yin 2014; Josefsson 2015). In this paper, it argued that PMM has been stagnant for the last decade and hence we have attempted to revive this field by demonstrating via a case study how the PMM field can be steered into a new direction with technological developments in digital economy. For this research, we selected Nuclear Service Company through purposive sampling (Guest, Bunce, and Johnson 2006) for two reasons. Firstly, the authors have access to this organisation and hence it is convenient for the study. Secondly, this organisation is relevant to the conceptual issues presented in Table 1 and hence has the potential to generate rich information (Miles and Huberman 1994). This fits, although a little loosely, within the category of revelatory case studies as presented by Yin (2014). In this instance, the type and size of organisation did not influence the case selection as it has less relevance to the purpose of this study.

The practitioner insights were collected from the case study to explore and identify a framework for resilient features of contemporary PMM. In-depth semi-structured interviews were used predominantly for collecting primary data. The interview protocol, as demonstrated in Table 1, included elements of a focused and semi-structured nature (Merriam 1998; Yin 2014). The in-depth interviews were conducted with five participants, i.e., media manager, continuous improvement manager, contracts manager, head of finance and lawyer. After five interviews, the authors felt that no new information or themes observed in the data emerged and hence decided saturation was reached (Guest, Bunce, and Johnson 2006). On average, each interview lasted approximately 50 min. The primary data obtained from interviews was supplemented by collecting other relevant documentation (through secondary sources: meeting notes, presentation slides, performance measurement data) and literature to triangulate the findings (Yin 2014).

Finally, analysis was conducted using Yin’s (2014) analytical techniques such as pattern matching where it used empirically obtained patterns from multiple interviews with the predicted aspects obtained through literature (theory) to strengthen its internal validity. Where applicable and necessary to understand the case in detail, further information/evidence was gathered from secondary sources such as examples of behavioural measures used in the organisation, meeting notes and information on subjective evaluation across the network of suppliers and customers. It used case study to support some of the findings from the literature, build an overall general explanation and hence attempted to enhance the existing theory by proposing a new framework on resilient features of contemporary PMM as a stepping stone. While the findings are based on a single case study (limiting its generalisability), it serves as preliminary research leading its way to other researchers to enhance this research, given the newness of the topic. Although PMM is not a new topic, the need for its resilience in a dynamically changing environment needs immediate attention (Bititci et al. 2012; Franco-Santos, Lucianetti, and Bourne 2012; Andersen, Busi, and Onsøyen 2014; Melnyk et al. 2014).

4. Findings and discussion

Nuclear Service Company (NSC), a UK-based company with over 40 years of experience, deals with irradiated fuel management. It offers a wide range of solutions including design and approval of equipment and services to meet customers’ specialist requirements while meeting government regulations.

In addition to the protocol demonstrated in Table 1, the analysis of interviewed data suggested the emerging themes that are presented and discussed in the following sections.

4.1. Collaboration and co-creation – impact on PMM

All the participants agreed that several stakeholders (i.e. suppliers, contractors, government, society) are involved in developing and delivering services to customers. They all responded that there is certainly virtue in collaborating and co-creating with various stakeholders. One of the participants said that NSC had tried to engage and create a platform for collaboration and co-creation activity in the past. However, the participant said that some of the stakeholders with more power (directly dealing with customers) exhibited opportunistic behaviour and were reluctant to participate in such collaborative activity.

All the participants, however, argued on three factors that are important for collaborated activity, i.e., trust, security and responsibility. Trust and security is important for collaborating and co-creating solutions with other stakeholders as NSC is providing nuclear services and solutions that could otherwise pose a huge threat. However, two participants added responsibility as another important factor in collaborative activity, i.e. which stakeholder should take responsibility for organising such activity. One participant reported that government, being one of the stakeholders, has recently initiated a platform called a ‘knowledge hub’ to promote collaboration and co-creation to enhance engagement and innovation. The representatives from all stakeholders will come together four to five times a year in search of opportunities for betterment. One of the participants argued that any collaboration or co-creation activity will become fruitful only if they share relevant skills and resources and engage jointly in continuous improvement activities and identify necessary actions that result in improved performance. This is echoed in the literature, where Nudurupati et al. (2015) present a case where a health care company has taken responsibility in creating a common platform for all its strategic suppliers for undertaking collaborative activities (such as lean, six sigma and other continuous improvement projects) thus co-creating value. The health care company subjectively evaluated their co-creation activities through eight behavioural factors and linked them to their balanced scorecard (reflecting objective measures).

Although the majority of their contracts are traditional, i.e., based on transaction costs, they have recently started an outcome-based contract with a major customer. Although the contract works on a fixed fee model for delivering standard measures, it also incorporates a bonus for delivering certain behaviours (such as communication, customer focus, etc.) in enhancing customers’ service experience (see Vargo and Lusch 2008; Patricio et al. 2011). Unlike a traditional contract model, where the outcomes are only measured through numbers (which tends to be positivistic), the new contract, in addition, will evaluate service outcomes through subjective measures (which tends to be more pragmatic) in their collaborative meetings (represented by both NSC as well as its customer) every two months. This is also echoed in the literature where Nudurupati et al. (2014) argue that performance measurement should move towards evaluation while Chaffey and Ellis-Chadwick (2012) argue that the attitude of companies should move from a positivistic to pragmatic view.

4.2. Sustainable agenda – impact on PMM

As guided by the interview protocol, sustainability in this study is associated with three aspects as suggested by Elkington (1994), i.e. economic, environmental and social aspects. All the participants agreed that NSC is measuring economic aspects of the business. NSC has now repositioned the business to be sustainable for long-term growth. They have also mentioned that some of the environmental measures are included to cover government and customer regulations in handling nuclear services. NSC has embedded long-term plans to manage the adverse impact to the environment. NSC also interacts with society engaging in various ranges of activities with business and communities. One participant claimed that he is responsible for internal and external communications. This not only includes communications with their stakeholders (including customers), but also local communities where NSC organises public meetings to ensure that although the impact of failure in their activity is high, the risk of such an occurrence is very low. They encourage the public to engage and share their opinions which, if relevant, are incorporated into NSC’s activities.

However, all participants agreed that although they have explicit measures for economic aspects, there are no explicit measures for environmental and social aspects other than that required by government regulations as well as one-off activities with communities. In other words, the latter aspects are not integrated into and deployed from their strategy. One participant claimed that there is no comprehensive strategy that brings together all three aspects and provides a basis for environmental and societal metrics. This is also reflected in the literature where Walker and Jones (2012) argue that there is a wide gap between what practitioners say and do about sustainability. They argue that organisations only provide lip service and undertake one-off activities which give no real advantage. Hence, as suggested by Taticchi et al. (2014), organisations need an overall strategy encompassing all three aspects of sustainability for creating competitive advantage. The real challenge is not only identifying metrics from all three aspects but also making organisations use these measures in creating competitive advantage.

4.3. Big data and IoT – impact on PMM

While the majority of participants argued the importance of IoT for NSC, two of them emphasised the fallacy of embracing technology for the sake of doing it without understanding its benefits. Nevertheless, all the participants agreed that some of their equipment, for instance, ships that handle nuclear fuel have integrated sensors that measure G-forces, temperatures, etc., sensors to monitor the location of their carriers, finite element modelling, etc. One participant, however, argued that while NSC is good at monitoring their ships (over sea), they also need to monitor and track their on ground vehicles and equipment not only to ensure safety and visibility but also in their planning and scheduling when the information is communicated and shared with management and administration. The above benefits of IoT are also reflected in the literature where Swan (2012) and Kamalanathan et al. (2013) discussed it in various sectors including automotive, logistics and health care.

Aral, Dellarocas, and Godes. (2013) support the use of social media is changing the way we are doing business and enabling businesses to promote sales as well as obtain feedback through evaluation. However, the participants at NSC did not find social media a useful medium for promoting their actions or activities for the two reasons discussed earlier, i.e., trust and security. One participant, however, argued that monitoring social media is very important to control the speculation in case of an incident by quoting an example ‘Recently, there was a road incident involving a heavy vehicle that resulted in speculation of spilling nuclear fuel creating panic on social media. Monitoring and controlling that speculation has eliminated quite a lot of ambiguity and distress in public and involved communities’

While the participants generally agree that technology is creating huge amounts of data, one participant agreed with Geri and Geri (2011) that if organisations are not careful, they are often overloaded with information that is often redundant. However, two participants believe that they need to capture data, process data and communicate it to decision-makers with simple and easy to use tools and techniques. This is also echoed by Barton and Court (2012) who propose that organisations need to focus on three areas and build strengths, in order to improve performance and benefit from big data and its advanced analytics. The organisations should explore how technology could create competitive advantage at a strategic level, which could be deployed through PMM (see the three stage model of Bourne et al. 2000) thus benefitting from big data.

4.4. Organisational culture – impact on PMM

All the participants identified that behavioural transformation is an important factor in enhancing business performance. The organisation has embraced technology in assessing 360-degree feedback and scoring the behaviours of people and supporting their personal development plans to enhance their capabilities and skills. This is also echoed in the literature where Nudurupati et al. (forthcoming) argue that a health care company identified eight behaviours that enhanced their business performance. Three participants argued that organisations need to develop simple but easy to use analytical skills and capabilities to process both objective and subjective data for enabling proactive and evidence-based decision-making (Neely 1999).

All the participants agreed that a knowledge work force is important in the digital era in order to cope with the business trends as claimed by Bititci et al. (2012) in the literature. One participant identified that people should not only demonstrate their technical skills but also need to demonstrate people skills as echoed in the literature (Vargo and Lusch 2008). Two participants believed that engagement is another important factor and hence organisations need to provide several opportunities for people to engage in the development of overall business objectives.

The empirical findings discussed in the above four themes are cross validated against the findings obtained from the literature (Table 1) and synthesised in Table 2. While the participants agreed with the majority of the findings obtained from the literature, their perceptions has advanced this knowledge base further. For instance, they articulated that trust, security and responsibility are important in collaboration and co-creation, which will have an impact on PMM by evaluating various collaborative partners and their performance. Similarly, participants highlighted the fallacy of adopting new technology without understanding its significance and benefits to an organisation. Exploring its significance to business and integrating its implementation through strategy would influence PMM throughout its life cycle, i.e. design (new measures), implementation (new ways of data collection and analysis) and use (simple to use visualisation techniques) phases. The participants also identified that developing the necessary people skills through 360-degree feedback would support business change.

Table 2. Resilient features of contemporary PMM: evidence from case.

Themes	Resilient features of contemporary PMM	Findings from case
Collaboration and co-creation	• Organisations collaborating on global network and the need to move from measurement to evaluation • Collaborating organisations co-creating value together in improving performance	• Trust, security and responsibility are important in collaboration and co-creation • Create common platform to share relevant skills and resources and thus engage in joint continuous improvement activities through common goals and measures • Substitute traditional contracts with standard cost (positivistic) measures with outcome based contracts supplemented with behavioural measures
Sustainable agenda	• Organisations do integrate sustainable agenda into PMM	• In addition to economic measures, environmental and societal measures are necessary for competitive advantage • A comprehensive strategy should bring together all three aspects and provide a basis for environmental and societal metrics
Big data and IoT	• Using IoT for innovative ways of improving performance • Organisations need to capture, store and process big data? Why and how does it influence PMM	• Fallacy of embracing technology could lead to business disadvantage • Understand the benefits of new technological advancements and integrate its adoption through strategy • Most of the technological developments discussed lead to more data and hence simple to use techniques are needed for decision-makers • Useful technology that enhanced decision-making include: IoT and social media
Organisational culture	• Organisations need to innovate by transforming positivistic to pragmatic view of PMM • Organisations should transform its culture: • Develop capabilities to handle big data sets • Develop skills such as analytical and literacy • Develop knowledge workforce • Encourage facts/information based decision-making	• Transforming positivistic to pragmatic measurement mentality requires huge effort in behavioural transformation • Develop simple but easy to use analytical skills and capabilities to process both objective and subjective data for enabling proactive and evidence based decision-making • Knowledge work force is important in the digital era in order to cope with the frequent external business fluctuations and hence changes to their PMM • People should not only demonstrate their technical skills but also need to demonstrate people skills

The findings obtained from this case clearly demonstrate that organisations need new business models that will influence their existing PMM to improve performance and create competitive advantage. Ng, Ding, and Yip (2012) argue that collaboration and co-creation requires a new business model that is customer centric as well as a whole system approach, i.e. the value-creating system of an organisation should extend its boundaries and focus on all activities in wider network that contributes to that system as whole. Similarly, embracing new technological developments transform the organisations and the way they operate businesses. Hartmann et al. (2014) argue the need for big data and analytics from two perspectives. Firstly, it can be used for incremental improvement of current business practices, services and their performance. Secondly, the use of big data can create new products and business models to create competitive advantage. More unstructured data emerging in open markets enable the transition of a positivistic approach of measuring to a pragmatic approach of evaluating using behavioural (or other qualitative) measures. This requires a new business model with a change to their existing PMM.

5. Conclusions, limitations and further work

In summary, the key findings from the research are that with the technological development, organisations should consolidate and refocus their measurement efforts to incorporate evaluation of their performance over wider networks involving various stakeholders. The traditional beliefs and values of measurement should extend their positivistic view to incorporate the beliefs and values of evaluation through a pragmatic view. Organisations should engage with suppliers through outcome- or performance-based contracts for unlocking innovation, where the performance is not only measured through traditional metrics (usually incorporating financial aspects) but also is evaluated through behavioural metrics. The role of PMM should incorporate learning, developing and nurturing the necessary capabilities and skills to promote behaviours and become a vehicle for cultural change.

While it is argued that technological developments (be it IoT or social media) are inundating organisations with huge amounts of data, it will be in the interest of organisations to discover how that data could create competitive advantage. On one hand, organisations identify how competitive advantage will be created in their strategy by embracing technological developments, on the other hand, PMM deploys the strategy to lower levels to measure and evaluate their performance against set objectives. While sustainability attracts more attention with a wider range of stakeholders (consumers, government, society, employees, etc.) than ever before, it is again in the interest of the organisations to tightly integrate this element into their strategy for creating competitive advantage. This will further be deployed across the organisations through PMM to identify appropriate sustainability metrics.

As demonstrated in Figure 2, organisations should inform their existing strategy with the technological developments and their relevance to their business. They need to establish a sustainable agenda and understand how it creates competitive advantage thus linking to the existing strategy. In other words, organisational strategy should reflect three more new dimensions, namely the creative use of technology, unlocking innovation through collaboration and co-creations as well as a sustainability agenda to create competitive advantage. The organisation would deploy its strategy using an existing performance measurement framework. However, this framework, in addition to its existing measures (predominantly positivistic), should also incorporate behavioural as well as environmental and social measures. Finally, organisations should manage their performance not only by measuring their performance internally but also by evaluating their performance in collaborative networks as well as in social media (where relevant).

Figure 2. Transforming organisational strategy and PMM in the digital era.

This study contributed to the existing PMM literature and practice. It explored that the fundamental premise of performance measurement should change to performance evaluation. It serves as a positional paper (study) to steer research in the area of PMM to deal with creative use of technology such as big data, IoT to enhance decision-making. This sets a new direction to the field of performance measurement, which was stagnant for the last decade with no significant development (Andersen, Busi, and Onsøyen 2014). The findings from this study could influence organisations at three levels: strategic, performance measurement and performance management. Practitioners can use three dimensions to create competitive advantage: (1) creative use of technology and big data (2) unlocking innovation through collaboration and co-creation and (3) a sustainability agenda. Organisations can use their existing PMM frameworks, however they need to integrate the above three aspects into their strategy and deploy the relevant measures at various levels (i.e. update their existing PMM frameworks). They also need to consider behavioural measures to balance the measurement attitude as well as cover more business areas and ways of measuring and managing performance.

While, the study is of an exploratory nature in identifying new PMM aspects, readers must be cautious when interpreting results as they are based on a single case, hence limiting the generalisability of its findings and results (Lee 1989). However, this serves as a preliminary case giving the opportunity for researchers to undertake further case studies on a larger scale to collect and analyse data to consolidate and generalise the findings. More studies need to be carried out to see if these findings are similar or different in various industrial sectors. Given the nature of technological developments discussed in this paper, i.e. IoT, social media, big data, it would be interesting to see how PMM is transforming organisations that are affected by it. For instance, it will be interesting to see how IoT will affect PMM in the health care sector and understand how social media (with unstructured data) will affect PMM in the retail sector. Similarly, more studies are necessary to explore how organisations evaluate their performance in their supply network through collaboration and co-creation. Further studies are also needed to support the premise that PMM needs to move from a positivistic to pragmatic approach with more examples of behavioural metrics/measures. It will be of particular interest to see how the findings obtained in this study are applicable to organisations of various sizes, i.e. small, medium or large organisations.

Notes on contributors

Sai S. Nudurupati is a reader at Manchester Metropolitan University Business School (MMUBS). Sai gained his PhD from the University of Strathclyde in the area of performance measurement, for which he obtained an Outstanding Doctoral Award from Emerald and EFMD. Sai then spent six years in the construction industry implementing continuous improvement projects and attained Lean Six Sigma Black Belt certification with BSI. Later, Sai joined Exeter University as a research fellow working on an EPSRC project in association with MoD and BAE Systems. He has published over 16 peer-reviewed journal papers and received two best paper awards. Sai is currently involved in three KTP projects and one NEMODE small grant.

Sofiane Tebboune is a senior lecturer at the Manchester Metropolitan University Business School. He holds a PhD in Information Systems from Brunel University. Sofiane’s research interests are in the area of information systems outsourcing, enterprise systems and the strategic value of information technology. His work was published in various conferences, Business Process Management Journal, and the Journal of Information Technology.

Julie Hardman is an associate head in the Department of Marketing, Operations and Digital Business at Manchester Metropolitan University Business School. Julie came to academia as an undergraduate student 14 years ago after a lengthy career in retail management with various retail organisations and has been a member of teaching staff for the last 6 years with a number of conference and journal articles published in that time. Julie gained her PhD 2 years ago from MMU in the area of evaluation of large-scale HE system with a particular focus on Learning Analytics.

Acknowledgements

This work was supported by the Research Councils UK (RCUK) Digital Economy Theme – New Economic Models in the Digital Economy (NEMODE) Network through Exeter University.

Disclosure statement

No potential conflict of interest was reported by the authors.