Overview

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Organizations invest in automation that fails to deliver value because they automate the wrong processes or skip the analytical work that separates high-impact candidates from low-return distractions. This course, Foundations and High-Impact Process Identification, builds the analytical foundation that prevents that outcome. You will study the automation continuum from manual work through RPA to AI-powered and agentic automation, tour IBM watsonx Orchestrate and the broader IBM Business Automation portfolio at a business-user level, and develop a structured approach to process decomposition and automation readiness assessment. Through discovery interviews, observation, and IBM Process Mining interpretation, you will surface how work actually happens rather than how people describe it. You will then apply a value-versus-feasibility framework to prioritize candidates, design a future-state process with human-in-the-loop checkpoints and exception paths, and build a defensible business case with ROI estimates, risk framing, and an adoption plan. By course completion, you will have produced a Process Opportunity Portfolio Deliverable ready for stakeholder review.

Syllabus

The AI-Powered Automation Landscape and watsonx Orchestrate
- In this opening module, you will build an accurate mental model of how work is automated today and what changes when AI assistants enter the picture. You will trace the automation continuum from manual work through rule-based RPA to AI-augmented and agentic workflows, see where traditional RPA breaks down, and tour IBM watsonx Orchestrate and the broader IBM Business Automation portfolio at a business-user level. The lab has you place your own function on the continuum and explore watsonx Orchestrate hands-on in its self-service free trial.
Process Thinking, Decomposition, and Automation Readiness
- In this module, you will acquire the analytical discipline that underpins everything that follows. You will learn to decompose any business process into the six elements automation acts on — triggers, inputs, decisions, actions, exceptions, and outputs — capture it with a lightweight mapping notation, and judge whether the process is genuinely ready for AI augmentation. The lab has you map and classify a provided invoice-exception process and write a readiness assessment.
Discovering and Prioritizing High-Impact Processes
- In this module, you will take on the practical work of finding and qualifying the right processes to automate. You will run structured discovery interviews, conduct non-intrusive observation, and interpret process mining output at a business-analysis level, then move from a long list of candidates to a defensible prioritized shortlist using a value-versus-feasibility framework you can defend in front of stakeholders. The lab combines a simulated interview, a mining reconciliation, and a scoring exercise.
Designing the Future State and Building the Business Case
- In this module, you will turn a chosen process into an AI-augmented future-state design and then into a fundable business case. You will decide where humans stay in the loop and at what confidence thresholds, design exception paths so the assistant fails gracefully, estimate ROI you can defend, and frame risk and adoption honestly so decision makers can act. The lab produces a complete future-state map and a business case for a process from earlier labs.
Cumulative Project and Course Wrap-Up
- In this final module, you will assemble everything from Modules 1 through 4 into a cumulative project: a Process Opportunity Portfolio. The deliverable is a discovery summary, a prioritized shortlist with scoring rationale, a future-state design with human-in-the-loop checkpoints and exception paths, and a business case with a recommendation on which process should advance into the build phase. The module closes with a wrap-up featuring an SME interview, a day-in-the-life view of an Automation Business Analyst, and a bridge into Course 2's hands-on build work.

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