Process Automation and Workflow Design

Question 1

What problem does this lecture address?

Answer 1

Repetitive, manual workflows (e.g., invoice approvals, leave requests) cause delays, errors, and frustration.

Question 2

Core promise of AI-driven automation

Answer 2

Reduce errors, speed up processes, and free people for higher-value work.

Question 3

Why automate now?

Answer 3

AI + BPM platforms integrate easily, enable real-time decisioning, and remove bottlenecks in common back-office flows.

Question 4

Typical manual pain points

Answer 4

Data entry, routing/approvals, status chasing, and exception handling.

Question 5

Immediate benefits cited

Answer 5

Lower errors/costs, faster approvals/cycle times, happier teams and stakeholders.

Question 6

Invoice approvals—what changed with AI?

Answer 6

Anomaly detection + threshold-based routing cut cycle time and improved accuracy.

Question 7

High-level automation flow (pattern)

Answer 7

Trigger → Validate/enrich → Route/approve → Update systems → Notify/escalate → Monitor/optimize.

Question 8

Role of ChatGPT in automation design

Answer 8

Brainstorm target workflows, define steps/logic, surface risks, metrics, and training needs.

Question 9

Role of Power Automate in execution

Answer 9

Build the actual flow, connect data sources, apply conditions, route approvals, and send notifications.

Question 10

Key trigger used in demo

Answer 10

Microsoft Form submission (“When a new response is submitted”).

Question 11

Primary data stores used

Answer 11

SharePoint lists (Leave Balances, Leave Register).

Question 12

Why SharePoint lists here?

Answer 12

Simple, cloud-hosted tables that Power Automate can read/write for state and records.

Question 13

Validation step for leave requests

Answer 13

Check requested days against the employee’s leave balance in SharePoint.

Question 14

Auto-approval rule in demo

Answer 14

If requested days ≤ current leave balance → approve and update records.

Question 15

Auto-denial rule in demo

Answer 15

If requested days > current leave balance → deny and notify employee + HR.

Question 16

Notifications used

Answer 16

Email to requester (approved/denied); HR CC’d on denials.

Question 17

What gets logged on approval?

Answer 17

Employee ID, start/end dates, status=Approved, action=Leave balance updated (in Leave Register).

Question 18

What gets logged on denial?

Answer 18

Employee ID, dates, status=Denied, action=HR notified (in Leave Register).

Question 19

Where the balance is updated

Answer 19

Leave Balance list: new balance = old balance − approved days.

Question 20

How requested days are computed

Answer 20

Power Automate “Compose” with a date-difference expression (End Date − Start Date).

Question 21

Why “Apply to each” was needed

Answer 21

SharePoint “Get items” returns an array; loop ensures correct per-record handling.

Question 22

Routing object used for approvals (alt pattern)

Answer 22

“Start and wait for an approval” (email/Teams card to manager) when needed.

Question 23

Escalation path in design

Answer 23

Unresolved or insufficient-balance cases escalate automatically to HR.

Question 24

Example KPIs to track post-automation

Answer 24

Cycle time, auto-approval (STP) rate, exception rate, SLA attainment, user satisfaction.

Question 25

Error-reduction mechanisms

Answer 25

Automated validation, threshold routing, anomaly checks, and standardized updates.

Question 26

Data integration points

Answer 26

Microsoft Forms (input), SharePoint (state), Outlook (notifications) — all wired by Power Automate.

Question 27

How ChatGPT accelerates build-out

Answer 27

Drafts step list, conditions, edge cases, RACI, test cases, and even CSV/Excel templates.

Question 28

Governance best practice

Answer 28

Keep a human-in-the-loop for high-risk/ambiguous cases and maintain change logs/audit trails.

Question 29

Security consideration with LLMs

Answer 29

Disable model training on sensitive prompts/data; avoid pasting PII unless policy allows.

Question 30

Change management must-do

Answer 30

Communicate the “why,” provide training, and publish a quick-reference SOP for the new flow.

Question 31

Common pitfall to avoid

Answer 31

Automating a flawed manual step without fixing policy/ownership/root cause first.

Question 32

Pilot-first approach

Answer 32

Start with one form + two SharePoint lists + one KPI, prove value, then scale.

Question 33

Scaling the pattern

Answer 33

Template the flow, parametrize lists/thresholds, reuse connectors across similar HR/finance requests.

Question 34

When to add AI beyond rules

Answer 34

For anomaly detection, priority scoring, or NLP-based triage on free-text requests.

Question 35

Example ChatGPT prompt (design)

Answer 35

“Outline a leave-management workflow for Power Automate: trigger=Form, check balance (SharePoint), update registers, notify.”

Question 36

Example ChatGPT prompt (refine)

Answer 36

“List edge cases and mitigation steps for the leave workflow; include owner, impact, and test scenario.”

Question 37

Example Copilot/flow question

Answer 37

“Which condition branches fire most often, and where do denials cluster by employee or date range?”

Question 38

Business outcome to report

Answer 38

Faster approvals, fewer errors, reduced admin load, and clearer auditability.