Big Data in Managing and Measuring Performance - Desklib

This report discusses the impact of big data on performance management systems and how it can improve performance measures. It covers the concept of big data, its role in managing and measuring performance, and how it can impact changes in PMS. The report also provides evidence of how big data has been used in performance measurement systems by a Brazilian multinational cosmetics company. The subject is Accounting for Management and the course code is not mentioned. The report is relevant for students and professionals interested in performance management and big data analytics.

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ACCOUNTING FOR MANAGEMENT

Big Data
Executive Summary
With the sharp increment in the field of technology, the scope and importance of performance
management has undergone a sea change. Big data can be said to be a new revolution that has
changed the face of performance management as it influence the manner in which the
companies perform. The report is based on the concept of big data where big data support
organizations in terms of measurement and management of performance. Further, big data
enhances the performance that leads to change in the system of performance management.
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Contents
Introduction................................................................................................................................4
Big Data in managing and measuring performance...................................................................5
Big Data in managing and measuring performance...................................................................6
Whether big data can improve performance measures and impact changes in PMS.................7
Evidences...................................................................................................................................8
Conclusion................................................................................................................................10
References................................................................................................................................11
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Introduction
Big Data is associated to an opportunity to change the design of business models and their
decision-making through assessment of huge volume of data gathered from varied sources.
Many researchers anticipate that BDA (big data analytics) can facilitate management in an
effective way, thereby paving a path for smarter decisions and better decisions. Nevertheless,
in relation to performance measurement, the same can be regarded as analysis and
procurement of information about exact attainment of plans and objectives that can impact
plan realization (Chugh & Gandhi, 2013). However, currently such performance
measurement systems have been encountering issues owing to enhancement in performance
complexities. Some state that such complications are because of increasing competitiveness
whereas some regard it as sustainability and supply chain problems (Fanning & Grant, 2013).
Despite the entire scenario, it can be said that big data is a potential weapon for the
organization as it leads to ample opportunities. Such exaggeration of complications has
resulted in increment of amount of data to be procured, processed, and evaluated to offer
meaningful information to facilitate decision-making in organizations. Big data comprises of
five V’s namely variety, veracity, value, volume, and velocity. These assist in enhancing the
competitive position of organizations, thereby facilitating in management and measurement
of performance. When it comes to performance, the organization needs to be alert because
performance management can lead to immense benefits (Fanning & Grant, 2013). In simple
words, big data has become a new revolution in the management of information that can
affect the way an organization conducts its business.
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Big Data in managing and measuring performance
Organizations has always intended to attain insights from information so that they can make
smarter, better, factual-based, and real-time decisions. The primary reason why the demand
and growth of big data platforms and tools has enhanced can be attributed to the fact that
there is a massive demand for in-depth knowledge within the organizations (Ramlukan,
2015). Further, organizations that intend to lead such change have included big data from
both outside and within their enterprises that includes both unstructured and structured data,
mobile and online data, machine data, etc to supplement their data and thereafter, provide an
effective basis for forward-looking and historical viewpoints.
Few scholars and practitioners have gone very far and considered big data analytics (BDA) as
science’s fourth paradigm or a fresh paradigm of assets encompassed with knowledge. The
reason behind these assertions can be attributed to the fact that big data can assist
organizations in managing and measuring performance through BDA enabled tools,
infrastructure, and technologies that includes mobile devices, social media, cloud-enabled
media, etc that can facilitate in sustaining competitive advantage (Ramlukan, 2015). For
instance, BDA can assist in improving data-driven innovative and decision-making ways to
learn, innovate, and organize, thereby facilitating in reinforcement of managing customer
relationship, maximizing the operational effectiveness of organizations, improving operations
risk management, and performance of the organization on a whole. Big data can significantly
alter the way organizations operate and compete, as companies that contribute in and
efficiently attain value from their data can pursue a competitive advantage over others
(Tucker, 2017). This results in a performance gap that continues to increase as more
significant data is generated. Performance measurement plays a key role in setting targets and
objectives to assist the process of decision-making and performing efficiently to sustain in a
risky competitive scenario. Presently, performance measurement primarily focuses on a
balanced set of both non-financial (flexibility, quality time, satisfaction of consumers, etc)
and financial measures to allow continuous improvement. Further, in this era, the level of
complications has also enhanced because of sustainability pressures (Barney & Ray, 2015).
This is the reason why a multi-dimensional metrics ser must accommodate both social and
environmental measures of performance.
Broadly, such big data has become extremely significant to management of performance in
various ways. Firstly, it facilitates in gaining insights about qualitative attributes like
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preferences of customers that can be utilized to enhance sales and marketing, thereby
assisting in maximizing shareholders’ wealth and profits on a whole. Secondly, it assists in
better forecasting like forecasting the spending patterns of customers in the upcoming tenure,
thereby assisting in implementation of more efficient decisions. Thirdly, it permits
automating of enhanced level business procedures that can result in overall organizational
effectiveness and lastly, it also offers more detailed and updated measurement of
performance (Junk, 2015). Big data analytics can recognize innovative opportunities in
significant processes, roles, and functions. It can establish a catalyst for change and
innovation and by provocating the status quo, it can assist in the creation of fresh possibilities
for organizations and their people. Further, sophisticated techniques can facilitate in
permitting organizations to discover primary causes, evaluate microsegments of their
respective markets, transform procedures, and make effective forecasts about the events
related to future.
Big Data in managing and measuring performance
In relation to managing and measuring performance, it has become insufficient for
organizations to simply understand present procedures or affairs with a perspective to
improve what already persists, when there is presently the ability to question if a procedure is
significant to the organization, or whether there is an innovative way of redressing a problem.
In simple words, the primary innovation driver within organizations is to continuously
challenge present practices instead of consistently accepting the same (Barney & Ray, 2015).
For instance, in the case of Tesco, the company has operations in various countries
throughout the globe. Moreover, in Ireland, it developed a unique way to evaluate the
temperature of its refrigerators that were placed in their stores. The company placed sensors
in the refrigerators that measured the temperature every 3 seconds and thereafter, sent the
data over the internet to a specific warehouse of central data (Griffin & Wright, 2015).
Nonetheless, evaluation of the same information permitted the company to recognize unites
that were functioning at inappropriate temperatures. Further, it discovered that various
refrigerators were functioning at temperatures below the recommended ones that was costing
it immense amount of energy. Gathering and evaluation of such data allowed Tesco to rectify
the temperatures of such fridges. Therefore, considered that the company was expending ten
million pounds every year on cooling costs, an anticipated reduction of twenty percent in
such costs can be a potential saving (Vasarhelyi et. al, 2015). Further, the system also
permitted the engineers to supervise the performance of refrigerators remotely. Besides, when
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they recognized malfunctioning of a specific unit, they could easily evaluate the issue and
allow corrective actions to come forward. In relation to previous tenures, the same
refrigerators were only fixed when a particular issue had been discovered manually by the
store manager that would generally be the scenario when the problem had become more
serious.
This is the reason why big data analytics has now been regarded as the primary game changer
in facilitation of improved business effectiveness owing to its strategic potential and high
operational. Such BDA can also allow organizations to manage and analyse their strategies
through a data lens. In fact, it is increasingly becoming a potential aspect of organizational
decision-making process. Therefore, it is now regarded as a primary differentiator betwixt
low and high-performing organizations. Overall, BDA is expected to pursue immense
influences within a variety of organizations (Griffin & Wright, 2015). For instance, potential
retailing organizations are currently leveraging abilities of big data to enhance their customer
experiences, minimize fraud, and make corrective actions just in time. In relation to
organizations associated to healthcare, such BDA is also expected to minimize the
operational expenses and enhance the quality of life. In contrast to this, BDA is also regarded
as an enabler of business and asset process monitoring, enhanced manufacturing, supply
chain visibility, and industrial automation. Overall, big data can facilitate in management and
measurement of performance on the part of organizations.
Whether big data can improve performance measures
and impact changes in PMS
Measures of performance and performance management system (PMS) has been studied from
varied viewpoints throughout the years. The natural domain of the same lies within
management control research. Further, its contemporary form is also associated to a balanced
scorecard approach and advantage from a proliferation of measures across several disciples.
In general, PMS has been utilized to facilitate implementation of strategy and enhancing
overall organizational performance, thereby resulting in facilitation of decision-making and
accountability on a whole (Cokins, 2013).
Despite a recognized fragmentation of research, slow progress in this segment, and doubts
regarding the utilization of performance measures and PMS, big data is claimed to pursue a
significant part in the use or design of performance measurement systems. IT advancements
can enhance the collection, analysis, measurement, and communication of information
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betwixt and within organizations (Cokins, 2013). Further, innovation in IT incorporation with
control of management leverages the utilization of database of enterprise systems and
thereafter, offer powerful analytic abilities together with enhanced assistance for decision-
making, control, and planning on a whole. In order to determine whether big data can
influence changes in performance management systems, the transformation of movie rental
experience can be taken into consideration. In other words, before when movies were rented
from various non-reliant neighbourhood stores, the agent (rental) would apply or assert their
recommendations on which specific movies customers said that they liked and a huge amount
of their own idea. In the present scenario, movie rental organizations and content delivery
services can use a broad array of data points so that recommendations can be generated for
better effectiveness. Hence, by evaluating what was seen, when, and on what specific device
(even whether such content was rewound, paused, or fast forwarded), together with all the
activities on the part of users like searches on internet, scrolling, and browsing within a
specific page, effective recommendations can be attained for innumerable number of
customers. This illustration clearly sheds light on the impact of big data on PMS in the
current scenario.
The primary reason behind the use of performance measurement systems and big data
analytics can be attributed to the fact that both are equivalent in nature in the sense that both
support action-taking and decision-making on a whole. This is a major evidence of an
interconnection betwixt both these aspects. On one hand, while the PMS supports decision-
making to offer appropriate and meaningful data through a series of affairs like evaluation
and interpretation of data from the past actions so that future performance can be influenced.
On the other hand, the purposes and goals of big data analytics are also similar in nature
(Wamba et. al, 2017). Further, the same is applicable to all the professionals who undertake
the job of performing such evaluation. Nonetheless, analytics offering meaningful or
significant information to the users for decision-making is a primary example or evidence of
the fact that big data can influence PMS’s. Further, big data can also broaden the horizons of
such systems of performance measurement, thereby empowering the analytics to process
huge amounts of both unstructured and structured data.
Evidences
There are evidences of a Brazilian multinational cosmetics company that highlight the use of
big data in relation to performance measurement systems. It had been observed that such
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company also applied big data analytics (BDA) on its sales. Even though the utilization of
BDA in measurement of performance was prohibited to sales department in such company,
yet the evidences clearly prove the aforesaid. There were two different analytics used by the
company namely predictive and prescriptive. The prescriptive evaluations enriched clustering
assessments and drill down. Further, the users of performance measurement were also
capable to examine more complicated hypothesis and enhance their discovery of knowledge
through application of fresh prescriptive analytical methods. In addition, the utilization of
predictive tools also allowed the establishment of sales strategies of products in the event of
market niches, thereby exploring the capabilities of sales representatives (Krahel & Titeraa,
2015). They also utilized such models to improve and control their sales. The changes
reflected in the PMS of such company necessitated few investments on data infrastructure
and skills of employees. Moreover, the sales department of such company established a
different area to tackle big data analytics and big data. Nevertheless, a group of skilled
employees was being hired by the company to operate this are that corroborated with the
introduction of a data scientist. Further, additional investments were also required in order to
build data marts (Krahel & Titeraa, 2015). In relation to this, it must be noted that many
organizations only possess transactional databases but as per the evidence of such study, it
was reflected that change in perceptions towards performance was required to undertake new
evaluations. The data scientists helped the related parties and assisted the decision maker by
providing them relevant information. In this scenario, it is significant noting that such
variation is vital to return on investment on hiring professionals and data infrastructure. This
highlights the significance of financial performance measures to measure performance of
sales. The study signified that return on investment on sales was the most vital performance
measure while the causal interconnection of such ROI with non-financial measure was also
clear in nature (Wamba et. al, 2017).
Overall, Big data can be considered as an alternative to the failures or disgraces of traditional
performance measurement systems. This is because such systems do not operate effectively
when it comes to accuracy and quality in addition delivery and cost. Furthermore, such big
data plays a vital role in influencing PMS and performance measures like financial measures
(ROI, etc) can be improved through the adoption of such tool.
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Conclusion
The segment of big data analytics has been evolving rapidly and companies cannot ignore its
benefits. However, they must also observe at the way they utilize data so that it can be
ensured whether they are controlling the fresh opportunities in alignment with management
of new risks. Since, organizational information is incomplete, historical, etc in nature, a
predictive and statistical modelling is needed that can enrich these with external information.
Big data is the primary player behind this requirement as traditional approaches and systems
are inflexible and slow and often fails to handle such huge complications and volume of data.
Overall, big data has immense potentiality as it can create value for various sectors through
the process of decision-making. The process of decision-making helps in balancing the
organization and leads to further opportunities. Furthermore, the same can be effectively used
when it comes to management and measurement of performance. Moreover, the
interconnection between performance measurement and big data deserves more attention
because the same can play a key role in creating enhanced value for the organizations, and
can lead to better sustenance in such competitive and complicated environment. Overall, it
can be commented that big data is a boost to the overall organization as it leads to the
enhancement of the work culture and strengthens the value.
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References
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competitive advantage in customer service. Planning for Information Systems. [online]. 3(2),
pp. 444-460. Available from DOI: 10.4236/me.2015.63038
Barney, J. and Ray, G. (2015). How information technology resources can provide a
competitive advantage in customer service. Planning for Information Systems [online]. 3(2),
p. 444-460. Available from: DOI: 10.4236/me.2015.63038
Chugh, R & Gandhi, S. (2013) Why Business Intelligence? Significance of Business
Intelligence tools and integrating BI governance with corporate governance. International
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https://pdfs.semanticscholar.org/f4e6/d7c508f019de176980a8562dfc5eb3f2190a.pdf
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and auditing. Accounting Horizons. [online]. 29(2), 377-379. Doi:
https://doi.org/10.2308/acch-51066
Junk, D. (2015) Business Intelligence vs Analytics vs Big Data vs Data Mining [online].
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analytics-vs-big-data-vs-data-mining
Krahel, J.P & Titera, W.R. (2015) Consequences of big data and formalization on accounting
and auditing standards. Accounting Horizons.[online]. 29(2), 409-422. Doi:
https://doi.org/10.2308/acch-51065
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Ramlukan, R. (2015) How big data and analytics are transforming the audit. EY Reporting.
[online]. 9, 10-13. Retrieved from https://www.ey.com/gl/en/services/assurance/ey-reporting-
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Wamba, S.F., Gunasekaran,A., Akter, S., Ji-fan Ren,S., Dubey,R., Childe,S.J. (2017) Big
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