Small-Data Analytical Culture Analytics in ERP

Small-Data Analytical Culture Analytics in ERP

Francisco Cua
Copyright: © 2014 |Pages: 11
DOI: 10.4018/978-1-4666-5202-6.ch198
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Introduction

[C]ulture is an important factor at the policy and strategy levels. The ability to understand and appreciate the role and impact of culture on policy and strategy is increasingly seen as a critical strategic thinking skill. Cultural proficiency at the policy and strategic levels means that ability to consider history, values, ideology, politics, religion, and other cultural dimensions and assess their potential effect on policy and strategy…. [Culture as a framework] includes the following dimensions: cultural considerations at the individual level; cultural considerations in tactical and operational level…; and cultural considerations at the [policy] and strategic levels. Kim, J. (2009, p. vii).

People can improve their performance in key business domains, even if they are inadequate with analytics (Gray, 2012; Terry, 2012a, 2012b). An approach to develop the analytic skill can start with small-data analytical culture analytics.

For instance in an “obligation to dissent” analytical culture, employees regard themselves as decision makers, participate actively to generate solutions to problems, express their dissenting views through debates or dialogues, and open themselves for convergence of opinions toward positive solution (Davenport et al., 2010). Such culture encourages people in the organization to challenge hidden assumptions and convey their perspectives.

But what if the country’s culture (Hofstede, 2010) becomes a barrier for the analytical culture to exist? In the context, a solution designed to improve analytical mindset implies that human performance needs improving; that the system is not optimal; and that practice and performance need to be scrutinize from top management down to line workers. The idea can run counter to the culture (Johnston, 2005)

This research examines the analytics of analytical culture. It explores, examines and analyzes people based on their attributes, biases, and behaviors. The intention is to understand executives’ and employees’ beliefs and their reactions to stimuli, such as the deployment of Enterprise Resource Planning (ERP) and to discover meaningful patterns. The ERP is the software used to execute business process.

Imagine an inverted triangle. The first domain on top is the local setting, which is the company in Kazakhstan. Below is the second domain. It is the phenomenon about the challenges of accountants and other people involved in the ERP project. Further below is the third domain with the issues about (a) the culture and the post-soviet mind-set, (b) reasons for action or no action, and (c) expected behaviours when action or no action occurs. This paper delimits itself to three issues. (Refer to 3.1 in Table 1 for the 3 domains.) The negative bias of accountants is the issue in the context of adopting and implementing a new ERP in Kazakhstan. The purpose of the research is to identify and describe the conditions (constructs) that create challenges experienced by accountants and other stakeholders and to develop testable theory based on these findings.

Key Terms in this Chapter

Obligation to Dissent: Embodies a community of employees who regard themselves as decision makers, participate actively to generation solutions to problems, express their dissenting views through debates or dialogues, and open themselves for convergence of opinions toward positive solution.

Small-Data Analytics: Similar to big-data analytics. The important result is the information gained from the analytics. Unlike big-data analytics that necessarily deploys tools, such as software programming, operation research, and statistics, to generate meaningful visual information and insights from every exhaustive combination of variables, small-data analytics deploys methodology that looks at the small set of data as the “jungle” and examines the “trees.”

Analytics of Analytical Culture: A form of small-data analytics that explores, examines and analyzes people based on their attributes, biases, and behaviors.

Analytical Culture: Embodies a collective set of human attributes and positive and negative biases as well as the reactions and behaviors, which people normally repeat over time.

Hosftede’s Cultural Model: Five dimensions, namely: (1) power/distance (PD), (2) individualism/ collectivism (IDV), (3) masculinity/femininity (MAS), (4) uncertainty avoidance, and (5) long/short-term orientation (LTO).

Innovation Resistance: A concept in the Diffusion of Innovations theory. The reasons for the resistance, such as risk, usage, cultural behavior, image for being care with innovation, and literacy, vary by cultural and individual contexts.

Culture: Can be conceived as software, for the mind, that includes considerations at the individual level, tactical (operational) level, and strategic (policy) level. As sofware, it creates opportunities for people in the organization to challenge hidden assumptions and convey their perspectives.

Analytics: realizes information as competitive advantage. It is the process of analyzing single set or multiple sets of data to discover meaningful patterns in them. It facilitates the creation of the right solutions and the asking and answering of why to find the root causes in the chain of problems.

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