Learn how to transform an organization digitally through simulations and case studies by applying the Disciplined Agile Delivery framework to work through three simulations. As a business leader, you may be asking yourself, what’s next? R? Python? Graph Databases? The latest data analytics technology that was launched last week? How do you craft an effective digital strategy from these technologies? How do you build the data transformation roadmap to give your organization a competitive advantage? How will you digitally transform your organization to give the best customer experience? In this course, we will explore three case studies to learn the practical tools and methods used to build a digital organization.
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Champions of digital transformation have many data technologies to choose from:
- Artificial intelligence
- Machine learning
- Cloud computing
- Digitization
- Predictive analytics
- Internet of Things
- Deep learning
The first course gave you the theory of the dynamic capabilities, fitness landscapes, and strategic foresight framework to transform an organization. Now, we will put those theories to use in three types of organizations.
The first organizational type is a new startup. You will learn how to build a digital organization from the ground up using the lean startup methodology.
The second organizational type is an established organization. This type of organization has developed processes and deep-rooted culture. The challenge is to help the organization digitally transform while retaining the best aspects of the organization.
The third organizational type is the organization that turns to digital transformation to help save it. This may be the most challenging digital transformation effort because you need to regain customer trust under a tight deadline while your competitors are eager to capture your customers.
For all three digital transformations, we will use Disciplined Agile Delivery to plan and execute the organizational change programs. "Disciplined Agile Delivery (DAD) is a people-first, learning-oriented hybrid agile approach to IT solution delivery. It has a risk-value delivery lifecycle, is goal-driven, is enterprise aware, and is scalable." DAD is ideal for digital transformation projects.
This course is part of the Transforming Your Company’s Data Analytics: Championing the Digital Enterprise Professional Certificate.
What you'll learn
- Using the Disciplined Agile Delivery framework to manage data analytics projects
- Case Study: The New Start-Up: Building a digital organization from the ground-up
- Case Study: The Established Organization: Transforming existing business processes into digital processes
- Case Study: The Threatened Organization: Using data analytics projects to rescue an organization through digital transformation.
- Managing a Portfolio of Data Analytics Projects
Syllabus
Week One - Disciplined Agile Delivery
Module One - What is Disciplined Agile Delivery?
Module Two - The Disciplined Agile Principles, Promises, and Guidelines
Module Three - The Disciplined Agile Tool Kit
Module Four - The Disciplined Agile Lifecycles
Module Five - The Disciplined Agile Team
Week Two - Case Study: The New Start-Up
Module One - Introducing the Case Study
Module Two - Finding Your Organization's Dynamic Capabilities
Module Three - Mapping the Fitness Landscape
Module Four - Building the Organization's Digital Business Model
Module Five - Creating the Portfolio of Data Analytics Projects
Week Three - Case Study: The Established Organization
Module One - Introducing the Case Study
Module Two - Finding Your Organization's Dynamic Capabilities
Module Three - Mapping the Fitness Landscape
Module Four - Building the Organization's Digital Business Model
Module Five - Creating the Portfolio of Data Analytics Projects
Week Four - Case Study: The Threatened Organization
Module One - Introducing the Case Study
Module Two - Finding Your Organization's Dynamic Capabilities
Module Three - Mapping the Fitness Landscape
Module Four - Building the Organization's Digital Business Model
Module Five - Creating the Portfolio of Data Analytics Projects
