The Value and Use of Digital Technology (AQA A Level Business): Revision Note

The value of digital technology

• Digital technology has become increasingly important for businesses to gain a competitive advantage - and stay competitive in fast-moving markets

How digital technology helps

1. Boosting efficiency and cutting costs

   • Automating repetitive tasks with robots or AI reduces human error, speeds up processes and frees employees for higher-value work

   • This often leads to lower overall operating costs

     • Amazon’s warehouse robots streamline order picking and packing

2. Reaching broader customer base

   • E-commerce platforms let businesses operate a virtual shop open 24/7

   • This removes geographical limits and the need for physical stores

     • ASOS sells fashion worldwide through its online store

3. Smarter, faster decision-making

   • Analysing large sets of data in real time uncovers trends and patterns

   • These can inform pricing, inventory management and promotions accurately and quickly

     • Tesco uses Clubcard data to adjust stock levels and target its offers

4. Personalising customer offers

   • Data-mining customer behaviour, such as past purchases or browsing history, enables firms to send tailored recommendations and promotions

   • This can improve customer engagement and increase loyalty

     • Netflix recommends shows based on individual viewing habits

5. Enabling new products and business models

   • Digital platforms connect supply and demand in novel ways

   • This allows businesses to create services or generate revenue in new ways

     • Uber’s app links drivers with riders in real time

Automation

• A range of computer-based technologies can be used to automate production and logistics processes

Automation in business operations

• Computer-aided design (CAD)

  • The process of digitally creating design simulations of products in 2D or 3D

  • It can also include the use of computer software to create mapping processes for industrial machinery, e.g. the movements required by a robotic arm in a car factory

• Computer-aided manufacturing (CAM)

  • The use of computers to assist in operations of a manufacturing plant, such as production processes, planning, management, transportation and storage

• Computer-integrated manufacturing (CIM)

  • The complete automation of a manufacturing plant, with all processes functioning under computer control with digital information tying them together

• Drones

  • Unpiloted aircraft used to carry out an increasing range of business tasks including package delivery, photography and security

    • E.g. Large agriculture businesses use drones to spot failing crops and areas of concern in large fields, mapping boundaries and even applying pesticides

• Robots and AI

  • Robots are programmed to collect information from their environment using sensors and use artificial intelligence (AI) to improve production performance

    • E.g. Hotel chain Yotel employs ‘robotic staff’ that can move around anywhere in the hotels, carrying guests' luggage, delivering laundry, cleaning rooms and making coffee

How do businesses use robots?

The pressure for automation

• Cost reduction

  • Robots, AI scheduling and automated warehouses cut labour time and waste, lowering unit costs

• Speed and reliability

  • Machines work around-the-clock with few errors, helping firms produce quickly and meet next-day delivery promises

• Labour shortages

  • In tight job markets, automation fills gaps where skilled staff are hard to recruit or retain

• Quality consistency

  • Sensors and self-adjusting equipment keep product quality within narrow tolerances, reducing returns and customer complaints

Evaluating the use of automation

E-commerce

• E-Commerce is the trade of goods and services over the internet

  • Businesses can trade through their own websites

  • Alternatively, platforms such as Amazon, Ebay and Etsy offer the chance for small businesses to sell their products online

• E-commerce has become increasingly important for a range of reasons

1. Changing consumer behaviour

   • Shoppers expect to browse, buy and track orders online 24/7 on any device

2. Global reach

   • A web store lets even small firms sell abroad without costly physical outlets

3. Competitive pressure

   • Competitors with easy-to-use online services make customers expect better overall service

4. Data capture

   • Every click reveals customers' buying preferences, allowing personalised offers and better stock planning

Opportunities and threats of e-commerce

Big data

• Big data refers to large volumes of data that inundate businesses on a day-to-day basis

  • It can be used to understand customers better, make informed strategic decisions and offer more personalised services that meet customer needs

  • Analysing trends across millions of records uncovers patterns humans would miss, improving pricing, demand forecasting and risk assessment

• Cloud storage and faster processors have significantly reduced the cost of storing and analysing vast amounts of data

Ways businesses collect big data

Data mining

• Data mining occurs when raw data is extracted from large data sets and converted into useful information

• This information is used to make data-driven decisions that reduce risk and help a business to increase revenue, reduce costs and improve customer relations

Common uses of data mining

1. Marketing Planning 

   • Identify successful marketing strategies

   • Determine market segments

2. Sales Forecasting

   • Identify sales trends

   • Set revenue budgets based on past performance

3. Consumer Profiling

   • Connect purchasing habits with demographic data

   • Target promotions that appeal to specific groups of customers

4. Personalising loyalty rewards

   • Compare success of previous loyalty rewards 

   • Target rewards that appeal to specific groups of customers

5. Market research

   • Predict future customer preferences based on past consumption

6. Identifying purchasing patterns

   • Compare products bought at particular locations, times and combinations with other goods

   • Tailor product availability

7. Research & Development

   • Allocate future spending on R&D based on extrapolation of past trends

8. Production Planning

   • Identify supply chain disruptions

   • Prioritise availability of products based on past demand

Criticisms of data mining