The Role of Business Analytics in Performance Management

The Role of Business Analytics in Performance Management

Kijpokin Kasemsap (Suan Sunandha Rajabhat University, Thailand)
DOI: 10.4018/978-1-4666-7272-7.ch010
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Abstract

This chapter introduces the role of Business Analytics (BA) in Performance Management (PM), thus explaining the theoretical and practical concepts of BA, Performance Management Analytics (PMA), and organizational performance; the overview of performance measurement and PM; the application of Performance Management System (PMS) through BA; and the significance of BA in PMA. This chapter also explains the practical areas of BA and their advantages within the foundation of PM. BA can be used to validate causal relationships within traditional input, process, output, and outcome categories toward business success. Extending the domain of PM to PMA requires new business data analysis skills to gain organizational effectiveness. PMA fills the existing gap between PMS and effective PM adoption. Understanding the role of BA in PM will significantly enhance the organizational performance and achieve business goals in the global business environments.
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Introduction

The driving force of BA is to create a win-win situation between business partners through creating valuable trust, strong commitment and improved organizational performance. To gain the business success, it is crucial to continuously monitor and evaluate the individual partners’ performances within the business networks. It is quite challenging to know how BA should assess the organizational performance. These business competition requirements challenge PM to effectively support the decision making process. BA is an emerging field that can potentially extend the domain of PM to provide an improved understanding of business dynamics toward better decision making. Many organizations across the globe have been using BA as a competitive differentiator in their operations (Xavier, Srinivasan, & Thamizhvanan, 2011). Organizations have been developing more sophisticated PMS to support decision makers with relevant information. Increased business competition requires more rapid and sophisticated information and data analysis (Schlafke, Silvi, & Moller, 2013). A collaborative business aspires to reach competitiveness, world excellence and business agility within the market segments (Ferreira, Shamsuzzoha, Toscano, & Cunha, 2012). The business networking paradigm implements common strategies and goals, upholds mutual trust, interoperable processes and infrastructures for business practices (Zacharia, Nix, & Lusch, 2009).

In order to manage performance effectively, top executives in organization need to be aware of information processing tendencies and practices within the organization in order to choose a suitable PMS (Sahoo & Jena, 2012). PM is a shared process of the day-to-day management of employees based on their agreement of objectives, knowledge, skills, and competence requirements (Sahoo & Jena, 2012). PM potentially makes the most significant contribution to organizational learning and helps to raise organizational efficiency and promote business growth (Adhikari, 2010). PMS is used to evaluate performance data and identify key success factors (KSFs) within an organization (Schlafke et al., 2013). PMS is commonly used to illustrate an organization’s essential means (Garengo, Biazzo, & Bititci, 2005; Broadbent & Laughlin, 2009). PMA is about the data and analytical methods to understand relevant business dynamics, to effectively control key performance drivers, and to actively increase organizational performance (Schlafke et al., 2013). PMA can be a potential success factor of the use of PMS. Conventional PMS focuses on controlling strategy execution, while it is less interested in understanding business dynamics for strategy formulation and decision making (Schlafke et al., 2013). PMA provides a possible explanation for the missing link between highly sophisticated PMS and their effective business implementation. The relationship between the distribution of such PMA systems and organizational success is inconclusive (Micheli & Manzoni, 2010). This chapter introduces the role of BA in PM, thus explaining the theoretical and practical concepts of BA, PMA, and organizational performance; the overview of performance measurement and PM; the application of PMS through BA; and the significance of BA in PMA.

Key Terms in this Chapter

Business Performance Management: A business management approach which looks at the business as a whole instead of on a division level. Business performance management entails reviewing the overall business performance and determining how the business can better reach its goals. This requires the alignment of strategic and operational objectives and the business' set of activities in order to manage performance.

Operational Performance Management: The alignment of the various business units within a company in order to ensure that the units are helping the company achieve a centralized set of goals. This is done by reviewing and optimizing the operations of the business units.

Performance Management: An assessment of an employee, process, equipment, or other factor to gauge progress toward predetermined goals.

Organizational Performance: An analysis of a company's performance as compared to goals and objectives. Within corporate organizations, there are three primary outcomes analyzed: financial performance, market performance and shareholder value performance.

Business Analytics: Process of determining and understanding the effectiveness of various organizational operations. Business analytics can be either focused on internal or external processes. Different specializations exist, encompassing most major aspects of business, including risk analysis, market analysis, and supply chain analysis.

Balanced Scorecard (BSC): Management practice that attempts to complement drivers of past performance with the drivers of future performance in an organization.

Benchmarking: A measurement of the quality of the organizational policies, products, strategies, and their comparison with standard measurements or similar measurements of its peers

Analytics: The field of data analysis. Analytics often involves studying past historical data to research potential trends, to analyze the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario. The goal of analytics is to improve the business by gaining knowledge which can be used to make improvements or changes.

Performance Measure: A quantifiable indicator used to assess how well an organization or business is achieving its desired objectives.

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