Digital Transformation: Value Disciplines

Digital Transformation

• Case studies include Adobe/HubSpot, and State Street
• The central question is: What are the three value disciplines that companies can emphasize in their strategic response to disruption? What tensions exist between value discipline pairs?
• The three value disciplines are Customer Intimacy, Operational Excellence, and Product Leadership
• Customer Intimacy is a focus on best customer intimacy and efficiency. Amazon exemplifies this by bringing a customer's goods in a timely manner. The profit metric is the lifetime value of customer relationship which mainly informates tendencies.
• Operational Excellence focuses on keeping costs low, as exemplified by Costco leading to reduced expenses by increasing efficiency and effectiveness mainly automating tendencies.
• Product Leadership delivers the best product through superior features, as exemplified by Restoration Hardware with its high quality/luxury furniture with premium pricing justified by superior features mainly innovative tendencies.

Tensions between Value Disciplines

• Operational Excellence vs Customer Intimacy:

  • Operational excellence prioritizes efficiency, cost reduction, and standardization
  • This conflicts with customer intimacy that focus on personalized service and customer engagement.
  • Companies may streamline processes to reduce time spent on customer interactions for efficiency and give a less personalized experience. Customer intimacy requires time.

• Operational Excellence vs Product Leadership:

  • Operational excellence emphasizes cost efficiency and standardized products.
  • This can stifle innovation and product development which are key components of product leadership.
  • A business might avoid investing in new technologies or product features to keep costs low This can hinder its ability to lead in product innovation and design.

• Customer Intimacy vs Product Leadership:

  • Customer intimacy requires understanding and responding to specific customer needs
  • Product leadership often involves pursuing cutting-edge technology and innovation that may not align with current customer preferences.
  • A company may innovate a product that does not resonate with its loyal customer base which is potential disconnection with those customers who prioritize personal relationships and tailored solutions.

The Innovator's Dilemma

• The Innovator's Dilemma describes challenges established companies face when encountering disruptive innovations
• These are new technologies or business models that initially serve niche markets and appear inferior to existing products but eventually displace them
• An example is Netflix vs Blockbuster
• Established companies focus on sustaining current products to meet the current demands of their most profitable customers
• This leads to resource allocation that overlooks emerging disruptive trends.

Avoiding The Innovator's Dilemma

• Embrace a culture of innovation
• Create separate units for disruptive projects
• Monitor emerging trends
• Engage with new customer segments
• Allocate resources for R&D
• Maintain flexible business models
• Encourage collaboration through partnerships/acquisitions
• Ensure that leadership is committed to innovation

Three Levels of Decision-Making & Impact of Information Systems

• Strategic Level:

  • High-level, long-term decisions set the direction for the entire organization
  • Examples include entering new markets, launching new products, mergers and acquisitions, and significant capital investments
  • Decisions are typically made by top executives and involve comprehensive analysis of external environments, trends, and risks
  • Information Systems Improvement includes BI Systems; These systems analyze large volumes of data to provide insights and forecasts to aid strategic planning
  • Info Systems improvement also include Advanced analytics tools to identify patterns and trends, supporting informed decision-making as well as executive dashboards providing real-time metrics and KPIs to help leaders make informed decisions quickly.

• Tactical Level:

  • Decisions are made by middle management and focus on how to implement strategic plans
  • Examples include resource allocation, budgeting, project management, and departmental policies
  • Decisions are generally medium-term and involve analyzing data to optimize resources and meet strategic objectives
  • Information Systems Improvement Decision Support Systems (DSS) to provide data analysis tools and models help managers evaluate options and make decisions based on various scenarios.
  • Info Systems improvement also include Project Management Software like Microsoft Project or Asana which streamlines workflows and tracks project performance
  • Collaboration Tools such as Slack or Microsoft Teams enable effective communication and collaboration among teams working on tactical decisions

• Operational Level:

  • Decisions are day-to-day decisions made by lower-level management and staff
  • Examples include scheduling, inventory management, and customer service issues
  • Decisions are short-term and routine with focus on the efficient execution of tasks and processes
  • Info Systems improvement includes Transaction Processing Systems (TPS); These automate routine transactions and data collection, which improving efficiency and accuracy
  • Info Systems improvements also include Enterprise Resource Planning (ERP) integrating various business processes, providing real-time data and automating operational tasks; as well as Automated Workflow Systems that streamlines repetitive tasks enabling faster decision-making and reduced human error

New Value Creation Paths with Digital Technologies

• Enhanced Customer Experiences:

  • Personalization uses data and analytics allowing businesses to tailor experiences, which increases engagement and loyalty
  • 24/7 Accessibility allows Digital solutions like chatbots and online support to provide around-the-clock customer service.
  • Omnichannel Integration where Customers can interact with businesses seamlessly across various channels which improves their overall experience and satisfaction.

• Operational Efficiency and Cost Reduction:

  • Robotic Process Automation (RPA) and AI-driven solutions reduce manual tasks, increasing speed and accuracy while lowering costs
  • Predictive Maintenance uses IoT and analytics allowing companies to predict and prevent equipment failures, reducing downtime and maintenance costs
  • Supply Chain Optimization uses digital supply chain management tools to provide real-time data on inventory and logistics enabling better forecasting and reducing waste

• Data-Driven Decision Making:

  • Machine learning and AI helps analyze large volumes of data to make better, faster business decisions
  • CRM and customer data platforms like HubSpot help organizations understand customer behaviors and preferences aiding in creating improved targeted marketing and product development

• New Business Models and Revenue Streams:

  • Subscription Models: Create recurring revenue streams by offering products as a service, like Adobe Creative Cloud
  • Platform Ecosystems: Companies like Uber and Airbnb leverage platform business models to create value by connecting users and service providers directly
  • Digital Marketplaces: E-commerce and digital marketplaces reduce the need for physical storefronts and creates opportunities for global sales

• Enhanced Product and Service Innovation:

  • Agility in Product Development: Digital technologies allow for faster prototyping and testing accelerating time-to-market for new products
  • Data-Driven Innovation: customer feedback data and market trends are used to continuously improve and innovate products and services
  • Customization and Modular Offerings: Digital platforms allow for customized product bundles or add-ons, to create flexible offerings that appeal to diverse customer needs

• Network Effects and Ecosystem Growth:

  • Platform Growth: Digital platforms benefit from network effects with exponential value growth
  • Ecosystem Partnerships: Companies can partner within digital ecosystems to offer complementary services, enhancing the overall value to customers like the Apple App Store ecosystem

Digital Transformations and Organizational Changes

• Achieving positive impacts often requires significant organizational changes alongside overcoming potential barriers

• Organizational Changes Required to Generate Positive Impacts:

  • Agile and Flexible Structures: Digital transformation demands flexibility, so shift towards agile frameworks, cross-functional teams, and flat structures
  • Employee Training and Upskilling: digital transformation demands new technology so invest in staff training on upcoming tools, data literacy, and cyber security
  • Data-Driven Culture: a culture that values data-driven decision-making is needed for positive impacts so companies need data driven governance policies and ensuring data quality as well as training data analytics
  • Customer-Centricity: it involves integrating CRM systems, personalizing services, and seamless omnichannel experience across digital platforms
  • Investment in Technology Infrastructure: upgrade or replace outdated systems to ensure scalability, security, and integration capabilities

• Organizational Barriers That Might Hinder Positive Impacts:

  • Resistance to Change: Employees and management may resist new technologies or processes
  • Siloed Departments: In many organizations, departments operate in silos which limit information flow so need a connected flow of data across systems
  • Limited Digital Literacy: Employees and leaders who lack digital skills or data literacy may struggle to adapt to new limiting to fully capitalize on digital investments

• Inadequate Budget and Resources: Digital transformation requires long term investments in new tech that some don't have the money for

  • Security and Compliance Concerns: data breaches and regulations create compliance concerns that delay initiatives.

• Legacy Systems and Technical Debt: outdated systems aren't compatible which may delay and limit transformation efforts

Enterprise Information Systems with Wayfair as the case study

• Key Question is: What are the four IT architectures and the business scenarios that could produce each IT architecture?

• The four main types of IT architectures are Centralized, Decentralized, Service-Oriented (SOA), and Cloud-Based.

• Centralized Architecture:

  • IT resources and processing are concentrated within a central system or data center
  • Provides a single point of control to manage, secure, and maintain data consistency.
  • It is suitable for large enterprises with a focus on strict data governance, security, and control such as banks handling sensitive customer data

• Decentralized Architecture:

  • Distributes IT resources across multiple locations or departments within an organization
  • Each business unit or location may has independently managed systems
  • Useful in organizations like multinational corporations with geographically spread-out operations as well as require localized control over its IT resources.

• Service-Oriented Architecture (SOA):

  • SOA is a modular architecture with functions that are organized as services that can be reused and combined to support different business processes
  • This allows flexibility and scalable
  • SOA is ideal for organisations that need flexibility in integrating new applications like e-commerce platforms with modular approaches to deliver different services

• Cloud-Based Architecture:

  • Hoses IT resources IT resources are hosted on cloud platforms for scalability, flexibility, and lower infrastructure costs
  • Cloud providers offer management and scaled usage
  • It suits companies with fluctuating demands or looking to reduce infrastructure costs such as startups adopting architecture to scale during peak shopping seasons without incurring high hardware costs.

• Each architecture offers distinct benefits tailored to different operational needs, depending on security needs, organizational structure, and resource availability

• Key factors to successful implementation include People, Process, Technology

Implementing enterprise-wide information systems

• Implementing enterprise-wide information systems like ERP, SCM, and CRM can bring both tangible and intangible benefits

• Tangible Benefits:

  • Improved Efficiency: ERP streamlines business processes by automating tasks streamlining accounting, procurement, and human resources whereas SCM optimizes supply chain management for logistics and CRM improves sales and customer service

• Cost Reduction:

  • ERP reduces redundancies, and improves decision-making
  • SCM's resource management can lower production and transportation costs
  • CRM's targeted marketing and sales efforts reduces resources and improves campaign ROI

• Data Accuracy and Consistency:

  • ERP ensures all departments use same data
  • SCM improves coordination and real-time updates
  • CRM keeps all the customer data across all the departments inline

• Scalability through easier expansion of business operations as systems are designed to grow

• Regulatory Compliance - to help follow legal requirements

• Intangible Benefits:

  • Improved Decision Making through providing insights on customer behaviour as well as enables real time forecasting based on market change
  • Better Collaboration through communication between multiple departments - marketing, sales and service

• Customer Satisfaction - efficient operation means products and services can be delivered quicker and will create a more personalised service

• Enhanced Agility and Adaptability - streamlining processes that help to respond to changes in market and insights improve in all aspects faster which enhances customer needs

• Employee Satisfaction - automates routines for more strategic and meaningful work

Key Enabling Technologies for a Decision Support System (DSS)

• In what ways does a DSS support decision-making at each organizational level?

• A DSS is a computer-based system that helps in making decisions by analyzing data, providing insights, and supporting problem-solving processes.

• Key Enabling Technologies for a DSS:

  • Data Management Technologies store and manage large volumes of structured and unstructured data for a foundation to the DSS to retrieve and analyse relevant data

• Modeling and Analysis Tools include mathematical, statistical, and optimization models to simulate different decision scenarios and predict outcomes

  • User Interface (UI) and Reporting Tools allow users to interact the DSS easily through graphs reports and dashboards -Communication Technologies for Email and Collaboration Software tools allow the team to enable based decision-making

• Cloud Computing facilitates the sharing of DSS resources, in a distributed manner allowing for remote access

• Artificial Intelligence (AI) and Machine Learning technologies allow DSS to to learn patterns that help improve the decision making

DSS Supports Decision-Making at Different Organizational Levels

• At the Operational Level: the DSS is used to streamlined and routine tasks with a goal of streamlining operations, transactions and making immediate operational decisions

• At the Tactical Level: it support decisions that involve short to medium- planning and resource allocation. It help with ensure the effective allocation of resources for manpower, materials and finances

• At the Strategic Level: the DSS supports high-level that impacts long-term goals and corporate strategy where is help helps provide insights into market trends, forecasts and business opportunities.

OLAP VS Data Mining

• Question: How does OLAP analysis differ from data mining analysis?

• Question: In what ways can data mining analysis techniques help us think about how artificial intelligence capabilities might be most effectively used in enterprises?

• OLAP (Online Analytical Processing) serves purpose in data management - Data Mining

• OLAP focuses on multidimensional data that enables users to query from different perspectives primarily by summarising the historical data

• Data Mining on discover hidden patterns with the aim of finding trends in the large data sets with machine learning techniques to identify behaviour and insights

• Data Analysis Depth using OLAP provides high level summaries as well as digging into the data to reveal some data

• Data Mining is less structured compared to OLAP. Results may need interpretations

• While OLAP supports tradition data mining enables strategic business plans and improvements AI use

How to use Data mining for AI

• Pattern Recognition and Prediction: Data mining can enable more AI by improving classification and analysis by analysing customer behaviours
• Enhance Decision-Making through Automation: mining data can enable quick decisions
• Training AI Models with Quality Data - Mining helps train AI models
• Identifying areas of Process optimization - process mining can improve optimization

Web Evolution & Technologies

• Question: What are the three evolutionary stages the web has gone through and what are distinctive features of each?
• Question: What are key enabling technologies of each stage?
• Question: What user-facing functionality was present at each stage?
• Question: What three tiers must be considered for web/eCommerce?
• Question: What are the main technologies used at each tier and how do they interact with each other (flow of information)?
• Tiers - Presentation Tier (Frontend), application/backend

Application Tiers

• Presentation Tier (Frontend):

  • The presentation tier of a web application is responsible for everything the user interacts with directly
  • includes the elements like HTML. Javascript and CSS which handles the UI/UX

• Logic Tier (application or backend): handles requests from presentations, to backend. Performs calculations. Languages like PHP, Python are used

• Data Tier:

  • Manages and ensures that storage, retrieval, manipulatin such as product listings, information etc are on point

Platform Compétition

• Question: What are the main people, process, and technology attributes of platforms and how does platform-based competition differ from product-based competition?
• Platform- and product-based competition involve different strategies and business models

Platform Attributes

• People: mainly focuses on participants like buyers and service providers.
• Process - transaction facilitation such as payment and scalability
• Technology: involves algorithms for matching

Process

Platform vs Process

• Platform based competition vs process based competition

5 Phases of Project Management Lifecycle (PMLC)

• Question: What are the phases and activities.
• Phases are Initiation, Planning, Execution, Monitoring and Closing
• Initiation: define and get authorization to begin
• Planning: define objectives, timeline, costs.
• Execution: carry out tasks per requirements
• Monitoring- ensure project is on track in respect to scope, risks and budget
• Closed : Complete all goals and objectives

Triple constraint triangle

• Involves Scope, Time and Cost where objectives for meeting agree goals When using to determine: Scope meeting
• Are things on schedule? If not why.
• Are things on budget while considering use of efficiency?

Combining both phases

• Assesses if project is proceeding on TIME, and evaluating the the other constraints and adjusting along to those aspects

Managing IT projects

• Challenges involve unorganized requirements- to solve this, gather the valid data at the beginning
• Lack of engagement can be solved by maintaining open engagements
• Resource constraints solved by managing expectations Technical issues: analysis to occur
• Resistance : have stakeholders on it

Project IT sourcing

• Can involve vendor challenges
• IT can be a factor
• Data security
• Management skills
• All these can be mitigated with transparency, communication and contract compliance.