Data Management (DP IB Business Management)

Big Data

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

• Businesses have more opportunities than ever before to gather vast amounts of data

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

 New Ways Businesses Collect Big Data

Customer Loyalty Programmes

• Customer loyalty programmes are a way to gather large amounts of data on spending habits and behaviour of customers

  • Financial and transactional data includes information about payment methods and details of products purchased 

  • Interaction data relates to how customers engage with surveys, feedback on in-store and online shopping experiences and CCTV data such as queue monitoring or number plate recognition

  • Marketing data includes customer interaction with online marketing such as the opening of marketing emails and interaction with adverts while browsing the internet

• In return for allowing access to this amount of data loyalty schemes often offer discounts or reward points that can be very attractive to customers

  • Customers feel connected to a business that rewards them and are more likely to remain loyal over time

  • Loyal customers frequently recommend the business to others and provide meaningful feedback

  • Promotional costs may be reduced as there is less of an urgent need to attract new customers

• Loyalty schemes help a business to differentiate itself from rivals and allow for greater personalisation of promotional activity 
   

• Loyalty programs have several drawbacks

  • Operating loyalty schemes can be expensive - especially for businesses with limited resources

  • Customers may come to expect discounts which could devalue a businesses products 

  • Customers may be disinterested by too many loyalty programs

  • Storing customer data for loyalty programs raises concerns about privacy and data security

Digital Taylorism

• Digital Taylorism involves using technology to carefully monitor workers' use of the tools and techniques for completing their work tasks

  • In 2022, 80% of large US corporations in the United States had their employees under regular surveillance

  • Examples include Amazon, FedEx and Deliveroo

• Pay and other financial rewards are linked to achieving performance targets

  • In some cases workers may receive sanctions based on data collected automatically

    • In 2020 Amazon workers complained of facing disciplinary action for taking toilet breaks during their shifts

• Technological innovations have made it much easier for managers to quickly and cheaply collect, process, evaluate and act upon vast amounts of employee performance information

  • In logistics computer systems control vehicle fleets and employees

    • Sensors track location, timing, driving and other aspects of performance

    • Complex algorithms and analytics software instruct truck drivers which routes to take as well as expected schedules

  • In retail employee performance data can be gathered from programs running in the background of the computerised cash register

    • Keystrokes can be logged, audio/video can be recorded and time taken to serve customers can be continuously collected

Benefits of Using data to Monitor Employee Performance

Using Data to make Decisions

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

Diagram: the common uses of data mining

• Marketing Planning 

  • Identify successful marketing strategies

  • Determine market segments

• Sales Forecasting

  • Identify sales trends

  • Set revenue budgets based on past performance

• Consumer Profiling

  • Connect purchasing habits with demographic data

  • Target promotions that appeal to specific groups of customers

• Personalising loyalty rewards

  • Compare success of previous loyalty rewards 

  • Target rewards that appeal to specific groups of customers

• Market research

  • Predict future customer preferences based on past consumption

• Identifying purchasing patterns

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

  • Tailor product availability

• Research & Development

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

• Production Planning

  • Identify supply chain disruptions

  • Prioritise availability of products based on past demand

Criticisms of Data Mining

Evaluating the Impact of Technology on Decision Making and Stakeholders

• Technology has had a significant impact on business decision-making and stakeholders in recent years

  • Technology provides tools for data analysis which improves efficiency and communication

  • Innovation is driven by technological advances and provides a competitive advantage

  • Employees may benefit from these advancements through improved workplace experiences

Positive Impacts of Technology on Business Decision Making and Stakeholders

Legal, ethical and practical concerns