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Summary CIMA Managing Finance in a Digital World (E1): Condensed Revision Note

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This condensed guide covers key concepts from the CIMA E1 syllabus, including business environments, digital transformation, data analytics, and the evolving role of finance in modern organizations.Designed for quick reference and efficient revision, this summary highlights important areas for mastery in a concise format.

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Summarized whole book?
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Uploaded on
September 15, 2024
Number of pages
7
Written in
2023/2024
Type
Summary

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Organisation – ops, sales & marketing, HR, IT & finance
The finance function:
 Enables – planning, forecasting & resource allocation
 Shapes how – performance management & control
 Narrates how – financial reporting
CIMA 5 Ethical Principles
Integrity, objectivity, professional competence & due care, confidentiality & professional behaviour
Mendelow’s power interest matrix of power & interest is used for determining who the dominant
stakeholder is
Corporate Social Responsibility – benefits, which should increase long term profitability
 Method of differentiation
 Attract & retain high calibre staff
 Brand strengthening
 Lower costs
 Identification of new market opportunities & changing social expectations
Corporate Governance – guidelines
 Use of AGM
 Board
 Chairman & CEO
 NEDs
 Nominations, remuneration & audit committees
Finance activities from information to impact
Assemble – information – analyse - insight – advise – influence – apply - impact – acumen
To summarise, it is reporting, then questioning, developing & then deploying solutions
Data
Data is raw unprocessed facts & figures, by processing it we turn it into information to give it
meaning, then we can assemble & analyse it for insight.
Good information is accurate, timely, relevant, concise & cost effective
Financial data – quantitative in nature, can suffer from poor data sampling or evaluation, or it can be
inappropriately presented.
Non-financial – can be quantitative or qualitative, qualitative data requires judgement, as it’s
subjective in nature, you can attempt to transform it into quantitative data.
Types of business structure
Entrepreneurial – built around owner/managers
Functional – groups together employees that undertake similar tasks
Divisional – splits it into divisions based on their product or geography
Matrix – combination of functional & divisional
Historically finance focused on operational efficiencies & to reduce operational cost, technology
does a lot of this now, allowing them to focus more on value creation & revenue.
Shared service centres were driven by globalisation & advancements in technology, enabling the
automation of lower level tasks
Level 1 – senior finance team
Level 2 – strategic business partnering
Level 3 – digital centres of excellence
Level 4 – smart finance “factories”


Outsourcing finance operations – adv

, 1. Cost reduction
2. Shift resources from ops to innovation
3. Retained function can focus on role as business partners
4. Access superior capabilities & resources
Disadv
1. Loss of control
2. Time & cost to manage the service
3. Risk of data theft/breaches
4. Erosion of internal knowledge/skills
5. Disruption/resistance to change
Shared service centres are sometimes referred to as internal outsourcing
Level 4 – finance operations
 Financial (corporate) reporting
 Management accounting
 Treasury management
 Internal audit
Level 3 – specialist areas
 FP&A
 Taxation
 Project appraisal
 Project management
Level 2 – strategic partnering
 Communicating insight to influence users
 Business partnering
Level 1 – strategic leadership of the finance team
 Lead key initiatives that support organisational goals
 Execute & fund strategies set by the CEO
 Liaise effectively with internal & external stakeholders
Cloud computing – adv
1. Flexibility & scalability
2. Cost efficient
3. Security
4. Flexible working
5. Environment
Disadv
1. Organisational change
2. Contract management
3. Security, privacy & reliance
Big data – volume, velocity, variety & veracity
Benefits of data analytics (McKinsey):
1. Fresh insight & understanding
2. Performance improvement
3. Improved segmentation & customisation
4. Better decision making
5. Innovation
6. Risk management
Data visualisation – 5 features of an effective data visualisation tool
1. Decision making ability
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