Management Accounting ACC7040

Module title

Management Accounting

CRN

56959 - 56698

Level

7

Assessment title

Assignment

Weighting within module

This assessment is worth 20% of the overall module mark.

Submission deadline date and time

TBC

Module Leader/Assessment set by

Dr Maryam Musa

Room 311, 3^rd Floor, Maxwell Building

Email: M.a.musa2@salford.ac.uk

How to submit

Your submission must be word processed using Microsoft Word. All assessments must be in Arial 12 font with 1.5 line spacing. Please insert page numbers in your submission.

Do allow plenty of time to make your submission and obtain and retain your Turnitin receipt as proof of submission on time.

Difficulties with IT systems or equipment will not be accepted as a valid reasons for late submissions.

The assessment could be submitted via Turnitin within the assessment folder on Management Accounting Blackboard space.

Please note: any submission you make to the final submission area will be treated as your final submission.

Background Information

In relation to digitisation of firms and big data, Artificial Intelligence (AI) and Machine Learning are important issues that have been discussed for several years. Automated cars, chatbots and automated payment systems are examples of AI that becoming part of our everyday world.

The accounting world has used computer systems to aid in producing accounting information since the 1950s, but AI and machine learning can be seen as significantly changing the future role of accounting.

The ICAEW Thought Leadership report (p. 8) on AI discussed areas AI and machine learning might be helpful in -

using machine learning to code accounting entries and improve on the accuracy of rule-based approaches, enabling greater automation of processes.

improving fraud detection through more sophisticated, machine learning models of normal activities and better prediction of fraudulent activities.

using machine learning-based predictive models to forecast revenues; and

improving access to, and analysis of, unstructured data, such as contracts and emails, through deep learning models.

Reference:

ICAEW (2018) Artificial Intelligence and the future of accountancy report, ICAEW. https://www.icaew.com/-/media/corporate/files/technical/technology/thought-leadership/artificial-intelligence-report.ashx?la=en, accessed 9/2/23.

Assessment task details and instructions

The assessment is to be produced as a strategic document and is to cover the following areas these topics can be used to form the subheadings in your report.

• Clearly explain AI and machine learning and then develop the concepts in terms of challenges and opportunities in management accounting in the short-term.

• Critically analyse three management accounting topics and the impact of AI and machine learning for these areas in the future. The topics can include budgeting and forecasting, investment appraisal, decision making under risk and uncertainty, variance analysis, modelling for cost control and stock management; environmental resource management (other topic areas can be chosen).

• Chose a multi-national company - You must research the firm and be able to access financial data for the firm (check the annual report or other data). Very briefly, define the firm. Firstly - find out how technology (inclusive of big data, digitisation, AI and machine learning) is helping the firm to develop and achieve its financial targets; secondly exploring three management accounting issues and how AI can enhance performance in these areas. This could include stock and resource management; working capital management; budgeting and forecasting; capital investment appraisal; just-in-time systems; standard costing and variance analysis; environmental metrics.

You must include financial data to develop the issues in terms of the materiality of these to the firm. Useful ratios can include the Contribution Sales ratio; Operational leverage ratio, break even ratio (units/sales); Return on Capital Employed.

• Summarise the short-term challenges and future opportunities for the firm and management accounting in respect of AI and machine learning.

marking criteria:

• Defined AI and machine learning (5%)

• Challenges for AI and machine learning and management accounting (15%)

• Critical analysis of management accounting topics and AI (30%)

• Multi-national firm extended analysis of AI/machine learning/big data/digitisation and management accounting issues (30%)

• Summary evaluation and analysis (10%)

• Presentation and research skills (10%)

Assessed intended learning outcomes.

On successful completion of this assessment, you will be able to:

Knowledge and Understanding

1. Critically evaluate the impact of big data, management information systems and digitalisation on the role of management accounting and performance management.

Key Subject Specific Skills:

2. Synthesise complex financial information and apply analytical and research skills into a management accounting related business issue.

3. Make decisions by applying critical and strategic thinking.

Module Aims

1. To empower students to identify and evaluate effective management information systems and recognise the impact of technological developments on generating and using management accounting information.

2. To develop students knowledge of advanced management accounting techniques so students are capable of supporting businesses to plan, control and monitor performance.

3. To empower students to critically evaluate business environments to devise effective socio-economic strategies that also includes sustainability aspects.

4. To further develop students knowledge and skills in assessing businesses.

Word count/ duration (if applicable)

2,000 words -/+ 10%

Your assignment must follow these formatting requirements:

Your submission should be typed using 1.5 spacing, Arial 12.

Feedback arrangements

You can expect to receive feedback as soon as the coursework marks are verified and ratified by the assessment board. Provisional marks will be available after 3 teaching weeks.

Formative feedback will be posted on the modules BB space as an announcement. Written

summative feedback will be available within your Turnitin document. You should make an

appointment to see your assignment marker who will discuss your result with you, explaining

your good points and areas where marks may have been lost.

Support arrangements

You can obtain support for this assessment by contacting the module leader (Dr. Maryam Musa).

The team is happy discuss any concerns/queries. You can visit the team during the

modules designated online guided study hour, alternatively you can come meet them during their on-line office hours. You can also email the team to arrange an appointment (on-line) outside of the hours mentioned.

The University offers a range of support services for students through askUS.

Good Academic Conduct and Academic Misconduct

Students are expected to learn and demonstrate skills associated with good academic conduct (academic integrity). Good academic conduct includes the use of clear and correct referencing of source materials. Here is a link to where you can find out more about the skills which students require http://www.salford.ac.uk/skills-for-learning.

Academic Misconduct is an action which may give you an unfair advantage in your academic work. This includes plagiarism, asking someone else to write your assessment for you or taking notes into an exam. The University takes all forms of academic misconduct seriously. You can find out how to avoid academic misconduct here https://www.salford.ac.uk/skills-for-learning.

Assessment Information

If you have any questions about assessment rules, you can find out more here.

Personal Mitigating Circumstances

If personal mitigating circumstances may have affected your ability to complete this assessment, you can find more information about personal mitigating circumstances procedure here.

Personal Tutor/Student Progression Administrator

If you have any concerns about your studies, contact your Personal Tutor or your Student Progression Administrator.

Assessment Criteria

The assessment criteria can be accessed via the module Blackboard space. (Please select

Assessment on the module BB space and then select grade descriptors).

You should look at the assessment criteria to find out what we are specifically looking at during

the assessment.

In Year Retrieval Scheme

Your assessment is not eligible for in year retrieval.

Reassessment

If you fail your assessment, and are eligible for reassessment, you will need to resubmit during

UoS resit period (actual date will be provided in the event of your requiring resit). For students

with accepted personal mitigating circumstances, this will be your replacement assessment

attempt. Students should be aware that there is no late submission period at reassessment

(this includes those students who have an accepted PMC request from a previous attempt).