MANAGEMENT BY NUMBERS

Mojca MARC, PhD

School of Economics and Business, University of Ljubljana

Kardeljeva ploscad 17, 1000 Ljubljana

E-mail: mojca.marc@ef,uni-lj.si

Abstract

Historical accounts demonstrate that numbers developed because of accounting. Throughout history, the

tendency to quantify and monetize was constantly increasing. Nowadays, technology enables us more

quantifying and more monetizing than ever before. As a parallel to that, the scope of things we want to

measure and monetize increased as well. Based on works by Latour (1987) and Robson (1992) on

accounting inscriptions and inscription devices, Miller (2007) noted that any calculative practice

involves not just inscriptions (numbers), but the tools as well. Hence, the numbers are usually not taken

alone but are embedded in more or less complex analytical models. Simultaneously to the increased

complexity of data collected, ever more sophisticated calculative tools developed as well. The academic

and professional literature in accounting and finance typically contends that more advanced analytical

models should be preferred to heuristic approaches. Consequently, a management style granting

numbers the pivotal role in decision-making (also known as management by numbers) has spread as

numerical information became more available, and complex analytical models became the modern

oracles.

However, individuals and organizations have different preferences to how numbers and analytical

models are used in managerial decision making. They have different needs regarding the amount as well

as the precision of numerical information required to make decisions. As shown by psychology

literature, subjective decision-making by individuals and small groups, like a board management team,

is influenced by cognitive simplifications and diverse preferences (Luft & Shields, 2009). Furthermore,

the same research strand shows that people simplify quantitative scientific models by incorporating in

their subjective decision-making only the signs of relations between variables and gross differences in

the magnitudes, but not the exact magnitudes (Luft & Shields, 2009). Shared activities, like e.g. board

meetings, provide an opportunity to develop a shared frame of interpretation that is relied on by group

members while processing numerical information (De Bondt, Mayoral, Vallelado, 2013; Vollmer et al.,

2009) used in decision-making. A shared scheme of numerical interpretation manifests a management

board team's calculative culture by showing the prevailing logic underlying the calculation and number

interpretation performed by the board members (Marc & Peljhan, 2019; Mikes, 2009; Power, 2007). It

is believed that a shared calculative culture leads to more effective teamwork and better decision-making

from the group's perspective, ultimately also influencing organizational performance.

Alas, despite the remarkable technological advancement in collecting and analysing quantitative data,

management's top problems remain the same: how to execute the numerically carefully elaborated

plans? In light of this, the danger lies in the overload of numerical information, and as ever, the challenge

is still to pick the important ones to steer a business. Hence, the main challenge posed for the future is

not how to collect and analyse more numbers, but what to do with them. Can technologies such as

machine learning and artificial intelligence lead us to a more holistic analytical approach? And how will

this redefine the role of accounting and accountants?

References:

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overview and assessment of selected research. Spanish Journal of Finance and Accounting, 42(157),

99–118.

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Milton

Keynes: Open University Press.

Luft, J., & Shields, M. D. (2009). Psychology Models of Management Accounting. Foundation and

Trends in Accounting, 4(3-4), 199–345.

Marc, M, & Peljhan, D. (2019). Calculative Culture in Management Control Systems: Scale and

Typology Development. Spanish Journal of Finance and Accounting, 49(2), 171–209.

Mikes, A. (2009). Risk management and calculative cultures. Management Accounting Research, 20(1),

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Shields (Eds.), Handbook of Management Accounting Research (pp. 285–295). Oxford: Elsevier.

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