Unsold Australian apples that once would have gone to waste now find buyers or beneficiaries through a digital platform. Refresh:Food, a joint initiative of Woolworths and BCGX, is a profit-for-purpose marketplace connecting farmers, wholesale buyers, and food rescue organisations. This tech-driven initiative redirects surplus produce, in collaboration with strategic partners such as OzHarvest, thereby reducing food waste and cutting greenhouse gas emissions.

Refresh:Food is one example of how Woolworths integrates data analytics and sustainability into its performance measurement practices. Across the organisation, key sustainability measures are captured and analysed, leading to over 80 per cent of supermarket food waste being diverted from landfill in 2025 and reductions in scope 3 emissions that drive down carbon output. Real-time supply chain data helps Woolworths to optimise delivery routes and refrigeration, reducing fuel use and spoilage. In-vehicle monitoring systems in its HomeRun delivery fleet act to improve safe driver behaviours, and new safety training is provided in VR and online modes to improve employee and contractor safety. Woolworths also monitors customer engagement with green initiatives – from reusable bag uptake to changes in sustainable product preferences – to gauge how well its strategy resonates.

All these data points feed into Woolworths’ performance measurement systems, capturing sustainability measures alongside traditional sales and profit measures. The message is clear: in today’s business environment, what gets measured includes planet and people, not just profit.

We are at a pivotal point where the performance measurement landscape is changing dramatically, a topic examined in the Research Handbook on Performance Measurement for Management Control. We both authored chapters in the Research Handbook, alongside leading international academics from across the fields of performance management and management accounting. In this article, we highlight five key research insights from the Research Handbook, alongside examples from leading organisations that illustrate the rapidly changing domain of performance measurement.

The new performance measurement landscape: Five key research insights

1. Data analytics is transforming performance measurement practices

Big data and advanced analytics are redefining how organisations measure success. As Professor Jennifer Grafton and Professor Anne Lillis (The University of Melbourne) observe in the Research Handbook, “technology is driving a regime shift in both the practice of performance measurement and the way we research it”. Organisations now have access to real-time streams of data on nearly every aspect of performance, from employee productivity and customer behaviour to machine efficiency and social media sentiment. They can tap “not just big data but fast data, text-based data, dark data, synthetic data, and more”, greatly expanding the volume and variety of performance measures available to managers.

This array of information enables retailers, like Woolworths, to measure things once impossible to quantify in real-time; for example, tracking refrigeration unit temperatures and shelf stock levels across hundreds of stores each hour. Such analytics-driven measures help managers respond swiftly (for example, redirecting stock to prevent waste) and tailor decisions store-by-store. The result is a performance measurement approach that is more immediate, granular, and predictive than ever before. The downside is complexity: handling ‘fast’ and unstructured data requires new data wrangling skills and poses integration challenges.

Learn more: Three ways data analytics will change the future of accounting

In the Research Handbook, Professor Matthias Mahlendorf (Frankfurt School of Finance & Management) identifies innovative data sources for performance measurement enabled by advances in data analytics, such as using chatbots to regularly check in on employee satisfaction, engagement and wellbeing.  The chatbot can provide dynamic feedback to the employee on their sentiments, and aggregate and analyse the data collected in (almost) real-time for executive decision-making. These are more tailored and interactive ways to capture employee sentiment, offering many potential advantages over traditional infrequent employee job satisfaction or workplace culture surveys.

Similar data analytics-enabled approaches can be used to monitor and understand workplace creativity. Prof. Mahlendorf describes how organisations, including Microsoft and IBM, are actively tracing internal communications to better understand which employees are key idea generators within the firm and the paths through which innovations are initiated, developed and disseminated. These are just some of the ways organisations are capitalising on opportunities in their data-rich information environments.

2. Sustainability is the new strategic frontier for performance measurement

Sustainability has moved from a corporate social responsibility sidebar to a core dimension of performance, reflected in organisational strategies, measured, and managed. While now being reinforced through mandatory climate-change reporting requirements in Australia, target setting and performance measurement in this space are well-established in many organisations. At Qantas, sustainability is referenced in its strategy framework and in the climate- and employee engagement-related performance measures captured in executive remuneration plans. Other core performance measures used within the organisation include aviation fuel consumption, CO2 emissions reductions, and waste-to-landfill reductions.

Importantly, sustainability measures force organisations to adopt a longer-term outlook. As Professor Jan Bouwens (University of Amsterdam) argues in the Research Handbook, “a commitment to sustainability demands that managers focus on the long term in their decision making”. Traditional accounting measures often fixate on short-term financial performance, but sustainable performance measures push organisations to invest in future payoffs.

For example, Qantas’ investments for the development of sustainable aviation fuels are central to achieving its target of net zero emissions by 2050. Bouwens demonstrates that while such investments may dampen shorter-term financial performance, these initiatives can yield environmental and financial benefits well into the future, and performance measurement is key to encouraging longer-term time horizons in managers’ decision-making. With the introduction of Australia’s climate-related financial disclosure regime from 2025, sustainability performance measures, and the careful development of associated targets, are progressively becoming mandatory for many Australian companies. Moving forward, the challenge remains in balancing these sustainability measures with immediate financial pressures.

3. Performance measurement must adapt in a hybrid and remote work world

The rise of remote and hybrid work challenges managers to rethink how to measure employee performance when face time at the office is no longer the default. Without traditional ‘line of sight’ supervision, some organisations have turned to digital tracking and algorithmic management.

Indeed, Professors Grafton and Lillis note in the Research Handbook that “many firms, particularly in the gig economy, are adopting forms of algorithmic control to optimise productivity and efficiency”. The benefit of data-centric approaches is consistency and scale: a manager can oversee a large, distributed team using performance data dashboards.

BHP, for example, managed both on-site iron ore mine workers and remote office workers in Western Australia through its Integrated Remote Operations Centre (IROC), well before the COVID-19 lockdowns demanded such innovations. For more than a decade, BHP’s IROC, in the Perth CBD, has remotely managed logistics and processing across the Pilbara, providing vast amounts of performance data and enabling real-time communication and human monitoring.

For organisations newer to this process, the challenges of measuring remote work can be significant. Over-reliance on digital measures can erode trust or encourage ‘gaming’ the system (e.g., employees appearing active online without truly being productive). Think of a professor grading students solely based on their online attendance. It is an easy measure to implement, but potentially misleading.

Many organisations are redefining performance measures for remote roles, emphasising output quality, customer outcomes, and collaboration measures over activity logs. Additionally, managers are using more subjective, supportive check-ins to complement digital measures, recognising that engagement and well-being drive long-term performance. The bottom line is that hybrid work demands a more thoughtful approach to performance measurement, one that leverages data analytics without losing the human element when work is no longer a place, but an activity.

As teamwork is increasingly demanded in remote and hybrid work environments, performance measurement is evolving to capture collaborative success, rather than just individual contributions. Modern projects often require cross-functional teams spread across locations, using virtual collaboration tools. This means individual performance measures don’t tell the whole story of performance. Organisations are responding by measuring team-based outcomes and networked performance indicators.

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They are also changing the performance management process at the employee level. For example, in the tech sector, traditional HR performance rating processes (think “set and forget”) are not well-suited to the rapid pace of change and sometimes high employee turnover rates. In response, organisations such as Atlassian have adopted an agile, collaborative and continuous feedback process. In doing so, knowledge workers have been compared to elite athletes, in which continuous coaching and feedback are essential to reaching their full potential.

4. There’s no magic one-size-fits-all performance measure

Atlassian’s bold move in how it manages employee performance acknowledges that what motivates creative software teams may be different from what drives mine operators or store managers. Context-dependence in performance measurement means each organisation must design measures that align with their unique strategy, culture, and objectives.

The complexity of modern enterprises defies any universal formula. As Professors Grafton and Lillis note, “when you influence behaviour through performance measures and incentives, you often do not get what you expect! There are many confounding factors, including the complexity of measures, learning curves, and interaction with other controls” that can make outcomes unpredictable. Organisations are increasingly appreciating that effective performance management must be flexible, strategically aligned and context-aware, rather than standardised and static.

In the Research Handbook, Professor Kerry Humphreys (UNSW Sydney) considers how data analytics are driving enhancements in balanced scorecard development and use. Organisations can now move from building scorecards based on simple strategy maps of the causal relationships between their performance measures, to scorecards underpinned by detailed system dynamics models of their distinct performance metrics utilising their data analytic capabilities.  In this way, data analytics offers a powerful competitive advantage to organisations that harness it, turning performance measurement into a dynamic – and organisation-specific – feedback loop, rather than a static report.

5. The (surprising) importance of subjectivity in performance management

With all this talk of data, algorithms, and dashboards, one might assume that the best performance measurement is 100 per cent quantitative and objective. But the research delivers a twist: subjectivity – that squishy, human element of judgment – remains crucial. And in some cases, it’s intentionally built into performance evaluations.

Professor Anne Lillis (The University of Melbourne) notes in the Research Handbook that the “pervasiveness of subjectivity in practice” doesn’t line up with how economic theory often treats it. In theory, subjective performance ratings have been seen as a last resort when objective metrics fail or don’t exist. Yet in reality, organisations frequently use subjective judgments by design. They are “consciously adopted to enhance incentive alignment and employee sorting”, meaning managers deliberately use discretion to recognise contributions that numbers miss, and to allocate rewards in a way that motivates the right behaviours.

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Moreover, organisations aren’t naive about it – they “actively mitigate the risk of errors and bias in subjective assessments.” That is, good organisations work to check and balance their managers’ gut feelings (for example, calibrating performance ratings across departments to ensure fairness, and training leaders to minimise personal biases).

Based on extensive research across manufacturing, financial, and professional service organisations, Prof. Lillis reports that instead of viewing subjective performance evaluation as a necessary evil, leading organisations treat it as a feature, not a bug. Subjectivity offers them a way to incorporate context, encourage the right behaviours, and deal with the limitations of objective measures. Of course, it must be done carefully. The balance of art and science in performance measurement is delicate: too much subjectivity and you risk bias; too little and the big picture can be missed.

The insight here is that effective performance management blends data with managers’ judgment, using the latter to fill gaps and correct course, where the former does not (or cannot) yet capture the whole reality.

Risks and rewards of the new performance measurement landscape

There are both substantive promises and pitfalls facing Australian organisations, and those around the world, as we navigate this new performance management landscape. The rewards are clear: done well, modern performance measurement can drive better decisions (thanks to data analytics), foster innovation and long-term thinking (by including sustainability and teamwork metrics), and motivate employees in meaningful ways (blending objective results with subjective recognition). Business can become more agile and resilient. Imagine being able to spot a downturn in employee morale or a spike in carbon emissions early, because your measures and analytics are tuned to highlight and respond to them.

Learn more: How a new carbon accounting system helps reduce emissions

However, the risks are equally relevant. With great data comes great responsibility: misuse measures or blindly relying on algorithms, and you will encourage the wrong behaviours and decisions, or demotivate your employees. There is also the danger of performance measure overload, drowning in data but not seeing the insights, and the peril of ignoring the human element, leading to a culture of surveillance or burnout in a remote work environment. Sustainability measures, if handled poorly, can devolve into greenwashing and/or diversity washing measures that do little for the planet, the organisation, or our society.

The Research Handbook underscores a unifying theme in performance measurement: balance. Effective performance measurement in the era of data and sustainability is about balancing data and judgment, short-term and long-term goals, individual and team rewards, and financial and non-financial measures. It is about understanding that every measure operates in a context, and designing performance measurement systems that reflect that context thoughtfully.

We are at a pivotal point; an inflection where new technologies and pressing global issues are rewriting the rules of performance management. The organisations that succeed will be those that harness the power of analytics and address the imperatives of sustainability, while keeping sight of their strategy, culture, financial management, and people-related needs. In the quest to measure what matters, the ultimate performance measurement system draws heavily on human judgment: knowing what to measure, how to measure it, and how to adapt when the world, or your workforce, inevitably changes again.

The message to business leaders is clear: embrace the data, embrace the broader purpose, but remember that performance measurement is a means to an end in creating sustainable, well-controlled, and high-performing organisations.

Jennifer Grafton is a Professor of Management Accounting in the Department of Accounting and currently the Associate Dean (International) for the Faculty of Business and Economics at the University of Melbourne. Her research investigates issues of performance measurement and management control system design and use, particularly in inter-firm contexts.

Kerry Humphreys is a Professor in the School of Accounting, Auditing and Taxation at UNSW Business School. Her main research interests currently focus on when managers make effective decisions incorporating strategy and performance information (including the balanced scorecard, sustainability and ESG information), and how new managers can learn to make better decisions using this information.