Data as an Asset: Valuation, Accounting, and its Strategic Importance

This report provides a comprehensive overview of data as a crucial asset in the modern business landscape. It begins by defining data and emphasizing its importance in the Fourth Industrial Revolution, highlighting its role in customer interaction and business success. The report then delves into data valuation, exploring various methods, including market-based approaches and cost analysis, and discusses how to manage data effectively. It also examines the accounting perspective of data, classifying it as an intangible asset and outlining the relevant accounting standards. The report emphasizes the strategic importance of data, its role in decision-making, and the need for proper data management to maximize its value. The content covers data definition, data as an asset, data valuation, and accounting data view.

UNIVERSITY OF SUNDERLAND PROGRAMME
ASSESSMENTCOVERSHEET/ FEEDBACK FORM
Module Name/Code:
APC311 International Financial Reporting
Student Name & ID:
KUVONDIKOV CHINGIZ
B1702518/bh59on
Due Date:06 May 2022Center / College: MDIS in Tashkent Hand in Date:03 May 2022
Assessment Title: Individual Assignment
Learning Outcomes Assessed: 100%
Learning
Outcomes
Assessed:
Feedback relating learning outcomes assessed and assessment criteria given
to students:
Areas for Commendation:
Areas for Improvement:
General Comments:
Assessors Signature: Overall Mark (subject to
ratification by the assessment
board)
Moderators Signature:
Students Signature: (you must sign this declaring that it is all your own work and all sources
of information have been referenced)

Contents
Introduction...................................................................................................3
Data definition............................................................................................4
Data as an Asset..........................................................................................5
Data Valuation............................................................................................6
Valuation Methods......................................................................................7
Accounting Data View................................................................................8
Conclusion...................................................................................................11
References...................................................................................................12

Introduction
The Fourth Industrial Revolution, in my opinion, is about to herald in a completely new period in
the history of the human race. Advances in technology have made it simpler than ever before for
companies and organizations to interact with their consumers on a personal level. Client data, in
particular, is a precious resource that must be protected at all costs by all workers in any business
that wishes to achieve financial success via providing outstanding customer care to its customers.
In order for this data to be useful, structured data, such as user preferences, must be given. In this
circumstance, extreme vigilance must be used at all times. In order to boost efficiency, it is
necessary to prioritize customer service above all other considerations. Cash, which was perhaps
the most highly valued business asset, has fallen out of favor in recent years. The data held by a
corporation may be used to help increase sales by offering useful information about potential
clients. The information gathered by businesses is increasingly being utilized to develop artificial
intelligence systems (AI). The use of data-driven technology distinguishes this technology from
its competitors. Many of the activities we do on the job are now capable of being handled fully by
software, lowering or even eliminating the need for human interaction. Advanced versions of the
same technology, such as deep learning and predictive analytics, are used by sales and marketing
teams to boost their efficacy. In the long run, these new features will be advantageous to the
organization's growth as it continues to grow. The use of artificial intelligence (AI) may be
beneficial in the case of labor-intensive activities. Technological improvements may enable us to
be more intelligent and proactive in our decision-making processes. Companies may also be able
to anticipate their own actions and decisions in the same way. It is in everyone's best interests to
assist a client before an issue emerges; thus, please do it as quickly as possible. Not only that, but
it also employs artificial intelligence to choose which transactions should be cracked first, which
is quite inconvenient.

Data definition
Using data, the Organization connects with the problem and works to solve it. It's far simpler to
interact with consumers if you know what they want before they arrive. It is vital that products
and services have both pre- and post-communication obligations. Effective communication may
be improved with the use of high-quality data. A company needs data to help them solve their
problems if they want to become more productive. A great method to start building a stronger
connection with a client is to use data collected at the beginning of their journey. There are a
number of ways in which a company's success might be improved by using this technology. In
most cases, pertinent data helps businesses anticipate what their customers want. In any situation,
the most useful knowledge is the one that best meets the needs. With this information, managers
may use it in a number of ways, like prioritizing customers who are most likely to buy above
those already available. Because of this, the firm will be able to predict its success, since correctly
filtered data aids in sales. Businesses might therefore efficiently broaden their primary offerings.
Customers in every scenario may benefit from this method, which was created to deal with any
and all problems that may arise. Data facilitates a company's capacity to conduct business as it
sees appropriate. Data blocks may be utilized to address a wide range of organizational
challenges. We need a shot in the arm if we want to grow as a business or a person. We may take
use of this great asset data to help us succeed in life or company, for example. It captures
everything we do and arranges it into manageable portions.

Data as an Asset
This raises the issue of whether or whether asset management calls for or demands the use of data,
or if it is merely another word for "information" in another context. A balance sheet search may
be useful in the case of a possible sale since it might reveal critical information. Similarly to how
raw materials might come from both inside and outside of a manufacturing plant, data can come
from both within and outside of a firm. The cost of storing data until it is needed increases storage
costs as well as additional administrative costs such as insurance premiums and tax assessments.
The ability to make a mistake is critical when it comes to data management and security. Before
data to be used successfully, it must first be updated and enhanced to be current. This is how raw
components are prepared in order to be used in the production of a finished product. The use of
analytics, machine learning, and a professional perspective all work together to maximize the
value of the data collected. This kind of data collection may result in the development of new
goods or the enhancement of existing ones. As a consequence, it would be possible to conduct a
thorough investigation and apply the findings. It is also necessary to identify and control
conversion dangers as well. The output of transformation algorithms must be consistent, and data
must only be disposed of by those who have been granted permission to do so. It is also necessary
to limit access to data. It is understood that there will be no exceptions to any of the restrictions
listed above. Data must be transformed into monetary value and relevant information in order to
be turned into an useable asset. When generating new information of this caliber, it is necessary to
have the ability to reuse and duplicate data, as well as the ability to combine data from several
different sources. Before the conversion process can begin, the data collection must be free of
errors and big enough to accommodate the conversion procedure. In order to achieve its
objectives, the organization needs have access to relevant and up-to-date information. In order to
make use of data, it is necessary to recognize patterns within it first. Using data to improve
operations and income, establish stakeholder relationships, encourage revenue growth or just
improve present items are all possibilities for businesses today. The utilization of an
organization's information assets to produce new revenue streams is a viable business strategy that
may be implemented.

Data Valuation
Developing a data-driven approach may help firms get the most out of their investment. Many
companies keep track of their physical assets and important information in an asset register, which
helps them locate them. It's pointless for a contemporary company to invest in one unless it
already possesses the same collection of digital assets as its predecessor. The inventory register
must include all of the organization's details, including its location. The inventory registry should
be prioritized in accordance with the company's aims. Information that is no longer relevant for
the organization's goal and objectives must be removed from its archived records. It is feasible to
steadily raise the value of data by treating it as such. Qualitative qualities, international regulatory
requirements, and organizational goals all need to be met for an asset to be considered a best
practice. In order to make informed judgments, the firm's personnel will not utilize data that does
not fit the standards specified by them. It is an indication of shoddy decision-making if data
management is inadequate to assess the influence of information strategy on company operations
and other firm activities. As a consequence of a lack of coordination and faith in data as a
foundation for decision-making, organizations are more ready to accept low quality. To optimize
the value of a company's data assets, it is vital to manage and reuse data assets. Many companies
are hampered by ineffective methods of data handling. There are many different ways to project
management out there. An agile data management method is a fantastic place to begin when
establishing new procedures. In an ever-changing data environment, agile approaches are needed
to perform quick analysis and make modifications to service delivery plans on the fly. The more
conventional "waterfall" method to data management is often preferred by many persons who
want to adopt this project management style.

Valuation Methods
Data is an intangible asset according to IAS 38. No matter how unique a dataset may be, effective
evaluation processes may still be used to examine data. These strategies take into account all
aspects of risk, profitability, and growth. Methods like the ones outlined below may be put into
practice:
More and more companies are relying on advanced analytics to have a better grasp on their data
and to look for licensing prospects. Data exchanges are also being built within various ecosystems
to enable market participants to purchase and sell data assets and participating organizations to
share data so that their respective firms' assets may be greatly boosted in value. Asset value
forecasts may be based on market-based information gleaned through data analysis and model
development carried out by these organizations. However, despite this, I think that as markets
grow and firms find new methods to participate, data transactions will become de facto norm for
measuring the value of data assets.
Consider the cost of replacing the item in question when determining its worth. I'll go on like this.
An investor would not pay more for an item than it would cost to replace its usefulness, plus the
needed financial gain to encourage someone else to substitute the asset. If a corporation doesn't
possess data assets, it might assume that a hypothetical third party will be willing to license them.
Companies are willing to give up a share of their revenues in return for access to third-party data.
Following the deduction of "contributory asset charges," or acceptable returns on contributory
assets utilized by the company to earn revenue and profit from data assets, economic benefits are
assessed using an income-based technique of evaluation. To evaluate data assets, one must first
calculate the impact on cash flows of upgrading the assets while assuming that all of the
company's management resources stay intact and produce the same amount of revenue.

Accounting Data View
Before you get started, take a moment to learn about financial reporting. Accounting standards are
designed to ensure that financial data is understandable, reliable, relevant, and consistent by
presenting it in accordance with generally accepted accounting principles. Statements of financial
condition are used to describe the assets and liabilities of a company or legal body. By examining
at a company's assets, liabilities, and equity balance sheets, one may have a better understanding
of its activities.
The term "assets" refers to anything that can be used at some point in the future. The term
"producing machine" may be used to any physical object in this sense. As a result, data has
become the most precious commodity for any organization working in this environment. Prior
transactions or events that have occurred are represented by an asset in accounting as the expected
future economic benefits. Intangible assets, including as patents, franchise agreements,
copyrights, marketing rights, customer lists, video or audio content, software, or goodwill, may all
be classified as data sets. Intellectual property, goodwill, and the value of a brand are all examples
of intangible assets.
An intangible asset is defined by the International Accounting Standards Board as a nonmonetary
asset that does not have a physical existence and is recognized either as a result of a contractual or
other legal right, IAS 38. Assets that meet applicable recognition criteria are first valued at cost
and then revalued at cost or using the revaluation model, unless the asset has a lengthy useful life
and so does not need to be amortized, in which case it is not amortized.."
Companies strive to meet the demands of intangible assets to the greatest extent feasible by using
their data resources. Because of its critical nature, accounting for it as an intangible asset severely
limits its use and value appreciation potential.
The identification of an asset necessitates the compliance of a corporation with a set of standards
and rules. A misclassification on the balance sheet may be caused by the difficulty of identifying
data as an asset, even when there are no legal restrictions on doing so. In accordance with
accounting principles, the classification of data as an asset is subject to the following limitations:

• All of the intangible assets that a company has bought should be shown on its balance sheet.
These assets can be amortized over a wide range of lifecycles by figuring out their value, figuring
out how useful they are, and using the right amortization methods, among other things. Under
International Accounting Standards 38, many people don't pay attention to assets that were made
at home. There can't be any intangible assets for a company if this is the case. This is because
these assets were either bought as part of another company's acquisition or bought on their own as
a separate asset. They are shown on the balance sheet of the company. In part because there isn't a
market for data's correct value, it's hard to identify data as an intangible asset because there isn't a
market for it. Despite the fact that Google's logo is made up of data, the company doesn't include
it in its financial report because the logo doesn't have enough characteristics to make it an asset in
the first place.
• According to International Financial Reporting Standards (IFRS 13), assets on a company's
balance sheet should have a computed fair value, which is a commonly recognized accounting
standard (Fair Value Measurement). As a result, if data is to be considered an asset, the expenses
associated with its collection or development must also be included. It is necessary to evaluate not
just the time and money spent gathering and purifying data, but also the resources needed to keep,
process, and analyze it. Previously, this technique was complicated due to the large number of
components and time needed. Accounting principles make it difficult for businesses to measure
and value such an asset. In contrast to equipment and buildings, the value of such an asset may be
established by independent appraisers using suitable valuation processes.
• Physical assets decline with time, according to IAS 16. As a result, an appropriate depreciation
plan for the asset's useful life must be created. A data asset's value, on the other hand, may
decrease or increase as it matures. Predicting the usefulness of data is more difficult by definition.
In certain cases, the value of master data, which represents business entities such as customers or
items, may increase with time. As a result, data that is solely transactional in nature, such as
invoices and deliveries, would lose relevance and value over time. Furthermore, if the data is
insufficient or incorrect, its use may be limited to a few weeks or even days. Data, on the other
hand, may gain value when it is used more often. As a result, it may become impenetrable, very
long-lasting, or even strategic. IAS 38, on the other hand, is concerned with the amortization of
intangible assets, which includes data. However, as previously stated, some characteristics
exclude data from being regarded an asset.

If data is not adequately safeguarded and governed, it might quickly become a significant
problem. Compared to physical assets, such as equipment or buildings, intangible assets, such as
data, depreciate at a much quicker pace, while physical assets, such as equipment or buildings,
appreciate at a slower rate. Data, despite its potential value, has so far failed to find a home on the
balance sheet of any corporation. None of these techniques has acquired general recognition or is
completely satisfying despite the efforts of academics, financial regulators, and politicians.
Whatever the case, data should be included on the balance sheet as soon as possible due to its
inherent value. The ability to appreciate it is the most significant characteristic in this situation.
When NFTs (Non-Fundable Tokens) were first introduced, they were considered to be digital
assets that reflected physical assets like as art collections, music and audio, or other commodities.
This has resulted in the development of value algorithms being accelerated. Because there is a
market for NFTs, anything can be valued, even if the price is erroneously determined. Due to the
growth of this sector and the accompanying investment vehicles, accounting regulations may be
pushed to reevaluate their approach and begin to view data as an asset in the future.

Conclusion
The vast majority of businesses have systems in place to track both physical and intangible assets.
Because data is not considered an asset in conventional accounting, it is often left unmanaged
because it is not recognized as such. When it comes to data, it should be seen as a valuable
resource that must be handled appropriately. In the near future, the translation of data into
information is projected to be the most important profession for enterprises. As a result,
businesses will need to treat data gathered from it as genuine assets. When dealing with massive
volumes of data, it is critical to use analytical tools and value drivers in order to make sound
investment choices. You may acquire the most precise results by using the Income Approach. It is
possible that data value drivers may assist you in increasing your cash flow. Businesses employ
value drivers to look deeper into these new cash flows and get a better knowledge of them. As
digital asset trading becomes increasingly common, the Market Approach will become more
significant.

References
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