A Level Business WJEC

This subject is broken down into 29 topics in 4 modules:

  1. Business Opportunities 8 topics
  2. Business Functions 4 topics
  3. Business Analysis and Strategy 10 topics
  4. Business in a Changing World 7 topics
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  • 4
    modules
  • 29
    topics
  • 11,692
    words of revision content
  • 1+
    hours of audio lessons

This page was last modified on 28 September 2024.

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Business

Business Opportunities

Enterprise

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Enterprise

Definition of Enterprise

  • Enterprise represents the combination of opportunity and willingness to create a business venture or company.
  • It's the process of identifying a business opportunity, creating a product or service based on it, assembling the necessary resources and taking on the associated risks and rewards.

Characteristics of Entrepreneurs

  • An entrepreneur is an individual who spots a business opportunity and decides to exploit it.
  • They are often characterised by their creativity, innovation, risk-taking propensity, and resilience.
  • Entrepreneurs need to be good decision makers, able to lead and motivate a team and have a strong understanding of the marketplace.

Importance of Enterprise

  • Enterprise is a key driver of economic growth and job creation. It helps diversify the economy, makes it more resilient and can drive innovation and competitiveness.
  • It encourages the creation of new goods, services or processes, opening up new markets and creating competition.

Processes Involved in Enterprise

  • Opportunity recognition: Entrepreneurs must be capable of identifying gaps in the market.
  • Idea generation & evaluation: Once a need or opportunity is identified, next is to brainstorm possible solutions. Ideas are then evaluated against market potential, resources, and strategic fit.
  • Business planning: Planning involves creating detailed operational and financial plans. This includes setting objectives, identifying resources required and crafting marketing and sales strategies.
  • Resource allocation: It involves securing necessary resources such as capital, staff, materials etc.
  • Implementation: Finally, launching the business or introduction of the new product, and closely monitoring its performance.

Challenges Facing Enterprise

  • Risk and uncertainty: Business ventures involve risk, including financial risk, market risk, operational risk, and so forth.
  • Financial constraints: Entrepreneurs may have difficulties securing sufficient funding to start businesses or to expand.
  • Regulatory environment: Entrepreneurs must comply with a wide range of laws and regulations, which can impose significant costs.
  • Market competition: New businesses need to establish themselves in competitive markets. This may involve a significant outlay of marketing and promotional activities.

Enterprise Culture

  • An enterprise culture is one that encourages entrepreneurial behaviour such as taking risks, innovating, and embracing change.
  • In a strong enterprise culture, individuals are encouraged to undertake entrepreneurial activities, and there is usually ample support and incentive for doing so.
  • Evidence of such a culture might include levels of new business startups, or the prevalence of entrepreneurial role models and success stories.

Course material for Business, module Business Opportunities, topic Enterprise

Business

Business Analysis and Strategy

Data analysis

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Data analysis

Understanding Data Analysis

  • Data analysis is a process of inspecting, cleaning, modulating and modelling data with the objective of discovering useful information, drawing conclusions, and supporting decision-making.
  • It is an essential part of the business decision-making process, empowering businesses to make informed strategic choices.
  • Data analysis involves a multitude of techniques such as textual, quantitative, qualitative, exploratory and confirmatory data analysis.

The Importance of Data Analysis

  • Informative insights gleaned from data analysis can give businesses a competitive edge by helping them understand their market, customers, and performance.
  • Problem-solving: Data analysis assists in identifying problems in business operations and processes by providing evidence-based insights.
  • Trend identification: Through the examination of datasets over time, businesses can identify trends and patterns that can inform future strategy.
  • Risk management: Data analysis assists businesses in predicting potential risks and the impact they could have on the organisation.

Data Analysis Tools and Techniques

  • Microsoft Excel: A commonly used tool for data analysis, it offers a variety of statistical functions, data visualization tools, and pivot tables.
  • SQL (Structured Query Language): Often employed for manipulating and analysing data stored in relational databases.
  • Python: This programming language is popular for data analysis due to its versatile libraries like Panda and NumPy.
  • Tableau: This data visualization tool helps make sense of complex data through interactive dashboards.
  • Regression Analysis: This statistical method predicts the relationship between two variables.
  • Data Mining: A technique that involves exploring and analysing detailed data to extract meaningful patterns.

Data Analysis Process

  • Defining objectives and questions: The first step involves understanding what the business wants to achieve with the analysis.
  • Data collection: This involves gathering relevant data from a variety of sources like financial reports, social media, customer surveys, etc.
  • Data cleaning: This step involves removing errors or inconsistencies in the data to ensure accuracy in analysis.
  • Data analysis: Here, the clean data is analysed using techniques and tools suitable to the data type and the objectives of the analysis.
  • Interpretation and reporting: The findings from the data analysis are interpreted and communicated in an accessible way to inform business decisions.

Ethical considerations in Data Analysis

  • Businesses must respect individual's privacy rights while collecting and using data.
  • Any personal data should be anonymised or pseudonymised as early as possible to protect individual identities.
  • Without proper consent, businesses should avoid using individuals' data.
  • Data security measures must be in place to protect data from breaches and other misuse.
  • Data analysis results must be reported honestly and accurately, avoiding any manipulations to match preconceived ideas.

Course material for Business, module Business Analysis and Strategy, topic Data analysis

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