• Improving performance by optimizing resource usage and obtaining customer insights

• Utilizing abundant data through effective storage and analytics enabled by new technologies

• Creating value for stakeholders by boosting profits, reducing costs or improving efficiencies

• IT can help provide strategic capabilities and reduce threats in strategic analysis.

• Implement a focused niche strategy by providing customized capabilities

• Align IT investments with strategic goals to improve performance

• Virtual design tools using CAD that let customers redesign properties digitally

• Providing a better customer experience through information and visualization

Smart devices - automated devices that are programmable but do not require network connectivity.

Example: Programmable thermostats

Smart connected devices - remotely controllable using networks like WiFi or Bluetooth.

Example: Google Nest thermostat controlled via smartphone

• Fully connected "things" that interact within the Internet of Things

• Security of connected devices and data collected: hacking and data theft

• Privacy concerns around data inputs required: exposed over the internet

While benefits can be substantial, managing risks through security, privacy protections, regulatory frameworks and ecosystem governance is critical to realizing the full value of smart technology for users.

• Requirement for robust data protection: Firewalls. Passwords, Training

While mobile technology provides flexibility and accessibility, organizations must adopt security measures to mitigate risks and maximize benefits. The appropriate balance of risk and value will vary by organization.

• SLAs: Cloud providers are responsible for restoring systems and may pay penalties for downtime

• Customization: Systems can be tailored exactly to organizational needs

• SLAs: Own responsibility to restore systems in case of outages

While cloud offers lower costs and on-demand scalability, owned solutions provide more customization and control. A hybrid approach combining the two may be best for some organizations.

The right choice varies case-by-case based on weighing benefits, drawbacks and specific organizational requirements for IT solutions.

• Customization: Limited customization options compared to in-house

• But risks center around loss of control, security and compliance

• Regulatory risks arise from using providers in different jurisdictions

• Reliance on provider performance and continuity

• Efficiency - IoT sensors detect issues early, enabling improvements

• Convenience - Automation frees up time and increases ease of use

• Information - Real-time data alerts users to take prompt action

Advantages:

• Potential for steady cash flows to fund investment in other areas

• Ability to match business needs to technology, a core competence

• Would need enhanced data storage and processing capacity

• Would require recruiting staff with IoT expertise, adding costs

• Higher risks of security breaches and privacy violations, threatening reputation

• Fund riskier IoT investment with government work cash flows

While IoT offers more transformational growth potential, government work provides a safer source of funding.

A balanced portfolio combining both could generate a mix of steady and higher-growth revenues to sustain investment.

Thoroughly evaluating risks, opportunities, needed capabilities and fit with strategy is key for each option.

• Identifying both advantages and concerns for each option proportionately

• Assessing quantitative factors like costs, investment needs and expected returns

• Considering qualitative factors like risks, capabilities and strategic fit

• Proposing a balanced combination that weighs different risk-return tradeoffs

For members:

• Feedback - Instant messaging facility allows members to communicate needs

• Convenience - Access fitness info and club updates anytime, anywhere

• Sense of community - Constant presence in members' lives engages members

For Optima:

• Engagement - Interesting and relevant content will be seen directly by target audience

• Older members - Must ensure technology does not disengage these members; usage will vary by demographics

• Data analytics - Evaluate app usage to identify needs of different customer segments and deliver information in multiple ways

For Optima:

• Interaction - Mobile should complement, not replace, other forms of contact

• Marketing - Instantly contact members with offers, updates and tailored messages

• Customer insights - Collect continuous feedback and data to better understand and serve members

• The director's claim that members only want to exercise and socialize is an oversimplification

• Mobile technology likely engages people of all ages when accessible; usage will vary but under-estimating potential risks disengagement

• Understanding members' varied needs across demographics is key to effective use of technology

• Provide convenience and communication for members

• Enable targeted marketing, customer insights and engagement for Optima

Used effectively with an inclusive approach, mobile technology has significant potential to enhance member experience and business performance for Optima.

However,a narrow view risks disengagement of some members.

For IT staff:

• More opportunities for growth and motivation within an IT specialist firm: learning, skill development, new technologies

Risks of outsourcing IT: job security, cultural adjustment and potential cost savings pressures.

Outsourcing IT:

• Careful management of the transition and selection of an outsourcing partner that shares the authority's objectives will be critical to maximizing benefits

• while mitigating potential downsides for both the authority and its IT employees.

• Timing is opportune given marketing director vacancy

• Agency expertise can overhaul marketing approach to fit strategy

• Current site focuses on reliability, not core messages for target market

• Greater visibility can promote products and provide up-to-date image

• Engage loyal customers and facilitate two-way dialogue for feedback

• Consistent with Yexmarine's strength of customer relationships

• Can systematically build targeted online relationships and reach

• Agency can ensure marketing is effective and costs are known to assess investment viability

• Agency expertise can strengthen Yexmarine's marketing and image to compete more effectively

• Improved website, social media and personalization can enhance customer loyalty, experience and feedback

• Targeted launch marketing can maximize chances of international sales success for new investments

• Competitive advantage may be gained over rivals with weak online presence

By upgrading its marketing, Yexmarine can strengthen its brand, relationships and launch execution to improve its competitive position and chances of growth. The agency's services offer a structured approach to achieve these benefits.

the key potential gains are stronger marketing capabilities, brands and customer relationships - all crucial factors for competitive advantage. The agency offers expertise and experience to realize these gains systematically.

• Improve outsourced call center's performance in the short term

• Focus on core business - Letting an expert call center focus on support frees SE to focus on retailing

• Consider insourcing over the longer term for cost competitiveness and greater control of customer experience

• Financial - Outsourced costs are $600/day vs $1,500/day to provide in-house

• Reducing call volume and resolution times could make outsourced costs competitive

• Publicize insourcing decision for potential marketing and ethical benefits

• Cost savings could be achieved in-house through online support, FAQs and process improvements

• Cost gap could narrow with in-house efficiencies

• Support is not SE's core competency but a critical part of the customer experience

• Customer dissatisfaction - Difficulty understanding offshore agents and long wait times

• Negative publicity - Offshoring seen as job export, potential reputational damage

• Loss of control - Outsourcing a critical customer touchpoint risks service quality

• Ethical considerations - Bringing jobs in-house could boost sales through perceived social responsibility

While outsourcing currently provides clear cost benefits, factors like customer satisfaction, reputation and control increasingly favor bringing call handling in-house - especially as improvements reduce the cost gap.

• Potential marketing benefits from perceived social responsibility

• Increased costs over time - Supplier power if locked into single provider

• Choosing wrong provider - May not meet all future legal service needs

• Leak of confidential information - Especially for unpublished articles

• Loss of expertise - May require making legal staff redundant

• Detailed service level agreement to specify all included fees and additional charges

• Ensure detailed SLAs (cover all needed legal services)

• Signed confidentiality agreement

• Careful selection and agreements with multiple providers can mitigate risks around expertise, confidentiality and control

• Outsource to multiple law firms, not a single supplier

• Using multiple suppliers prevents lock-in and maintains competitiveness over time

• Loss of control over quality
But:

• Specialist legal firm likely to deliver higher quality service than in-house legal department

IT activities typically require specialized technical skills that can be hard for a company to maintain in-house. IT outsourcing providers specialize in these skills and can leverage economies of scale.

Call handling, on the other hand, requires more general communication and customer service skills that are easier for companies to find and retain.

IT costs tend to be more fixed and predictable, making them easier to outsource effectively.

Call volume and duration can fluctuate more, making call handling costs harder to manage when outsourced.

IT outsourcing contracts tend to be longer term and specify fixed deliverables. This allows for more strategic planning.

Call handling outsourcing often requires more flexibility to adjust to changing call volumes and priorities.

Companies tend to want more direct oversight and control over customer interactions like call handling.

IT outsourcing can often operate more independently once requirements are specified.

IT outsourcing providers can often bring new ideas and technologies that the company itself may not have access to.

Call handling tends to involve more routine tasks where providers offer mainly cost savings.

Process automation: Using technology to automate repetitive workflows and tasks with low human interaction.

Robotic process automation (RPA): Software that acts like a "robot" performing repetitive rule-based tasks across systems. Multiple RPAs form a virtual workforce, reducing human labor for routine tasks.

Automation offers huge potential to improve processes during digital transformation. But you must analyze how and where to implement it, prepare workforce for change, and maintain data quality for reliable AI outcomes.

Faster processing - Robots can process higher volumes and work 24/7, speeding up transaction times.

Fewer errors - Robotic processes are rule-based and consistent, reducing errors and improving accuracy.

Lower costs - Using software "robots" reduces the need for human labor, lowering costs.

Staff focus on value work - Humans can focus on more complex tasks once repetitive processes are automated.

Example:

Bonduelle, a French canned vegetable producer, is developing robotic harvesters in collaboration with Fieldwork Robotics.

The robotic arms use machine learning and AI to identify and pick ripe cauliflowers.

The aim is to address labor shortages and gain productivity and consistency benefits.

While automation can replace some human labor for routine tasks, for more complex work it typically augments humans rather than replacing them entirely.

Programs/machines that mimic human cognitive abilities like reasoning, learning and problem solving, learning from data to make decisions with little human input.

AI powers technologies like chatbots, image recognition, and smart recommendations.

AI is suitable for complex cognitive tasks, unlike robotic process automation (RPA) which is for repetitive rule-based tasks.

Ensure high-quality data for reliable outcomes, to avoid AI bias

Closely monitor AI systems to avoid bias in decisions, for potential issues

AI augments human intelligence and abilities rather than aiming to replace humans. It is an integral part of digital transformation by enabling insights and decisions at scale

Netflix programs analyze every minute of content to identify key themes and details about shows. This data is fed to machine learning models that:

• Assign a weighting to factors that influence viewer choices

• Place viewers in "taste communities" to tailor recommendations

The more data Netflix collects, the more accurate recommendations become, helping build subscriber loyalty.

AI can improve customer experience through targeted insights but must be implemented responsibly to avoid negative outcomes.

Drivers are responsible for being vigilant while autopilot is engaged, but the technology can reduce vigilance.

Autopilot technology is designed to avoid accidents, but may have failed in this case.

While the pedestrian had right of way, he was in an area with fast-moving traffic.

Systems that can reliably perform as intended to protect all road users

Drivers trained to understand technology limitations and maintain supervision

Rules and infrastructure that properly allocate liability in complex situations

Overall, this tragic accident highlights the need for a holistic, human-centered approach involving technology developers, policymakers, road users and the public to ensure ethical deployment of autonomous systems.

No single party alone can be considered fully responsible.

The Internet of Things creates data from sensors and connected devices

Social media, smartphones, and internet use generate user data trails

Car insurance companies traditionally set premiums based on broad metrics like age and gender.

Inform and implement strategies based on data and customere needs

Understand their environments to identify opportunities and threats

• This data-driven approach aims to make organizations more responsive, competitive and able to target the right customers.

• However, data quality and privacy issues must also be managed responsibly.

Big data refers to the large volumes of data created and available today.

Large, complex data sets from a variety of sources, both structured and unstructured

Requires storage, processing and analysis to transform raw data into useful information

Predictive modelling to predict behavior and inform new strategies

Tailor content and rewards based on social metrics like reach and engagement

businesses must implement responsible data use and ethics policies to ensure data accuracy, privacy and security.

• Characteristics of effective use:

• Be skeptical of data-driven conclusions
•Use data ethically, responsibly and securely to minimize risk

Benefits include:

15 million less minutes of idling time, saving 103,000 gallons of fuel
1.7 million fewer miles driven, saving 183,000 gallons of fuel

This data enables a personalized customer experience. But critics argue Walmart makes judgements about customers' personal lives.

Time Warner uses data to:

• Track and optimize bandwidth for customer experience

• Target advertising for clients based on viewer demographics and data

Netflix analyzes viewing data from 44 million subscribers watching 2 billion hours of content monthly. This data helps them decide:

• Which shows to invest in

• Estimated viewership before a show airs

Popular communication types (data, calls, texts) to design optimal tariffs

In summary, analysing and leveraging customer data through big data management can form the basis of an effective strategy to address MC's challenges.

But MC must balance data-driven opportunities with risks through responsible data governance.

Morgan Stanley analyzes vast investment and client data using Hadoop.
This allows them to identify the best investments for clients.

Volume:
Larger amounts of customer data can improve understanding of:

• Purchasing patterns

• Product demand

• Potential new store locations

Volume: More data over a longer time period could provide a better understanding of customer requirements and purchasing patterns to develop strategies that capitalize on trends.

Volume

Large amounts of data improve reliability of analysis and conclusions.

Organizations need adequate storage and processing capabilities.

Velocity:
Processing data in real time allows RW to:

• Quickly respond to product trends

• Make real-time recommendations to online customers

Velocity: Analyzing real-time data from transactions and social media could allow RW to continually update strategies for competitive advantage, such as quickly marketing trending products.

Velocity:

Data is generated and accessed in real time from transactions and interactions.

Information is available immediately to inform decisions.

Veracity:
Accurate data is critical for RW's store expansion strategy due to its fast growth.

Veracity:

Data must be accurate and reliable to be useful.

Ensuring data quality is critical for effective analytics.

Variety:
Data from diverse sources can provide a deeper understanding of:

• Competitors

• Industry trends

• Customer segments

Variety: Tapping different data sources beyond RW's control could provide the deepest understanding of customers to develop effective strategies. This includes competitor and industry data from online keywords and social media.

Variety:

Data comes from many types of sources and in different formats.

Both structured and unstructured data provide richer insights.

Potential to identify new trends and patterns to gain insights and understanding not previously known.

Ability to analyze large data sets in real time allows faster response to changing conditions.

Access to more diverse types of data including unstructured data sources.

Potential to gain more accurate and detailed performance data in real time.

Greater risk of data breaches and hacker attacks due to larger data stores.

Risk of focusing too much effort on analyzing data rather than running the business.

Cost and challenges of upgrading IT infrastructure to capture and store larger data sets.

Issues of data reliability and truthfulness impacting decision making.

Around 25% of fish caught globally is illegally caught, so Sainsbury's partnered with Satellite Catapult to track fishing vessels in real time via satellite data.

Using algorithms, Sainsbury's can determine if a vessel is behaving as expected based on this data.

This enables Sainsbury's to:

Detect illegal, unreported and unregulated fishing
Protect ocean life and fulfill sustainability commitments

In summary, big data and satellite technologies are giving Sainsbury's unprecedented visibility into its supply chain to combat illegal fishing and source sustainable wild fish for its customers.

Optimizing new store locations based on customer shopping habits data

Discovering previously unknown trends to capitalize on before competitors

Generating new revenue streams by selling customer data to manufacturers

The finance director is right to consider big data, otherwise RW risks falling behind competitors. However, RW must consider the costs and benefits before implementation.

In summary, all 3 'Vs' could enhance RW's strategic development through deeper customer insights, faster strategies and potential new revenue sources, if implemented appropriately.

Ability to perceive environment and take actions to achieve objectives

Algorithms are vital for artificial intelligence. They are step-by-step processes for solving problems or accomplishing tasks.

Autonomous investment practices and high-speed trading in finance

Uses algorithms to gain experience from data and learn without being programmed

Can predict and provide guidance based on historical data and new inputs

Deep learning uses neural networks to analyze unstructured data

Self-learning computes decisions based on programmed 'emotions'

Demonstrates intelligence through tasks such as learning, problem-solving, perceiving and deciding

Uses algorithms, machine learning, data analysis and adaptation

Applications include personalized services, automating tasks, optimizing processes and faster decision making

Used where accuracy, repeatability and hazardous conditions are important

Reduces costs and increases precision, reliability in manufacturing

Perform welding, quality control and surgery through machine vision and telemanipulators

Robot learning algorithms acquire skills through self-exploration and human interaction

In summary, artificial intelligence relies on algorithms, machine learning and big data. It is being used across industries to improve processes, optimize operations and gain competitive advantages. However, the rapid development of AI also raises ethical concerns about its impact on jobs, privacy and accountability. Regulatory frameworks may be needed to govern emerging AI technologies.

• Mistakes - AI may make different types of mistakes than humans.

• Bias - AI may reflect the biases of its creators or have unintentional programmed bias.

• Security - As AI capabilities increase, effective cybersecurity is critical.

• Unintended consequences - AI may achieve intended solutions but have unforeseen negative impacts.

• Control - There are concerns about AI ultimately surpassing human control.

• Unemployment - AI and robotics may displace human jobs with few alternatives.

• Income distribution - Benefits of AI may concentrate in hands of owners, not workers.

• Behavior influence - AI interactions may inadvertently influence human behavior.

• Treatment of AI - There are debates about ethics of "negative reinforcement" of AI systems.

Example: Amazon Echo which can play music, make calls, answer questions, control lights, etc.

It involves:

• Connected sensors, processors and transmitters
• Smart devices that can collect data and control the physical world

Businesses should consider:

• How IoT can be part of their business model
• Strategic and operational uses across sectors

Monitoring for problems through warning systems and predictive analytics

However, businesses must determine where and how IoT can add value to their specific strategies, operations and customer propositions.

Effective adoption depends on identifying and assessing relevant opportunities based on organizational goals.

Transport sector:

• Smart devices like traffic cameras and sensors warn of traffic issues
• Collect data to identify routes for simplification and optimization

• Security - IoT applications have not kept pace with security development, creating risks

• Security risks from connected devices

• Privacy - Data collection raises concerns about individual monitoring and behavior prediction

• Ethical issues around privacy and data protection

• Technical - Platform fragmentation, device obsolescence, data costs and complexity

• Technical challenges of integrating diverse systems and technologies

• Implementation challenges - Many pilots do not scale, lack of clear business case, long time horizons, legacy infrastructure limitations

• Barriers to successfully implementing and scaling IoT initiatives

• Assess the opportunities and risks specific to your organization's industry and operations

• Develop strategies to mitigate threats, ensure compliance and optimize IoT initiatives

• Consider the organizational changes needed to support widescale IoT adoption

• Guide how IoT can create new business models or transform existing ones

Determine how big data can transform your business model and strategies

Leaders play a vital role in articulating a clear vision, setting the right "tone from the top" and designing governance systems to maximize benefits and manage threats.

while big data and analytics offer great opportunities, organizations must balance opportunities with risks.

Their ability to assess and evaluate potential applications based on organizational needs will determine the value realized from big data and analytics.

volume, velocity and variety of data provide opportunities for deeper insights.

However, veracity and value determine whether those insights are trustworthy and actionable for businesses.

• Evaluate how much and what types of data are relevant for your needs

• Translate insights into strategic recommendations and value creation

refers to extracting insights from large or unstructured/raw data.

Provides information to answer business questions and make better decisions

Goes beyond prediction to recommend courses of action

Optimizes decisions based on complexity, constraints and trade-offs

All techniques provide insights to support better business decisions. But prescriptive analytics has the greatest potential to transform business performance by recommending optimal (best) actions based on data.

Selecting and implementing the right analytics technique for the right purpose is critical for extracting maximum value from data.

Uses statistical models, AI and machine learning to predict future outcomes based on past and present data

Allows businesses to evaluate strategies and foresee different scenarios

Tools like Excel's Scenario Manager and Data Analysis pack can be used

Goes beyond prediction to recommend optimal courses of action

Optimizes decisions based on constraints, trade-offs and complexity

Tools like Excel's Goal Seek and Solver can generate optimal solutions

Example:

Minimizing transportation costs by optimally allocating TV deliveries from depots to stores

determine which technique is most appropriate for a given business problem and apply insights to:

interpret findings skeptically and question assumptions