SAP AI for SAP PP Consultants
Published 9/2026
Created by Srinivas Vanamala
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 15 Lectures ( 50m ) | Size: 173.3 MB
Use AI for MRP, shortages, BOMs and routings, capacity and production orders - without bypassing SAP planning logic
What you'll learn
Explain where AI adds value across SAP PP and manufacturing-planning activities Distinguish deterministic SAP planning logic from probabilistic AI assistance Use AI for MRP exception grouping, shortage interpretation and planner communication Apply AI to review material masters, BOMs, routings, work centers and production versions Identify capacity bottlenecks and build alternatives before recommending overtime Prepare a scheduling explanation from requirement date to basic and operation dates Troubleshoot late production orders through status, material, operation, confirmation and variance Structure root-cause analysis as testable hypotheses rather than an instant five-why chain Recognise risks from stale data, invented planning facts, over-automation and confidential data Build a controlled AI-assisted PP workflow and a 30/60/90-day adoption roadmapRequirements
Practical familiarity with SAP PP or production planning work is helpful, but no expert-level knowledge is assumed No AI, machine learning, data science or coding experience required No specific AI tool, subscription or licence needed - the principles apply to any assistant No SAP system access required; this is a slide and narration course with no system demos An open mind about using AI to challenge your assumptions rather than confirm themDescription
Production planning produces more information than any consultant can read line by line. One MRP run can leave hundreds of exception messages, and behind each message sits demand, receipts, stock, lead times, lot sizes, safety stock, BOMs, routings, work centers, capacity and production order status. AI is genuinely good at summarising, classifying, comparing and explaining that volume. What it cannot do is replace the planning logic, the master-data discipline, the production controls or the accountable human judgement that manufacturing requires. That gap - between fast interpretation and correct decisions - is what this course is about.
This is a one-hour, slide-and-narration course for SAP PP consultants, S/4HANA Manufacturing consultants, production planners, manufacturing process leads, solution consultants and support consultants. You follow Meera, a fictional PP consultant at Apex Components, a multi-plant manufacturer facing frequent shortages, unstable lead times, capacity bottlenecks, inconsistent master data and constant requests to explain why the plan changed.
You do not need to be an AI specialist, a data scientist or a prompt engineer. You do not need coding, machine learning knowledge, a specific AI tool or licence, or access to an SAP system. There are no system demos and nothing to install. What you need is practical familiarity with SAP PP or production planning work, and a willingness to verify before you conclude.
Throughout the course you will learn
• Where AI adds real value across MRP, shortages, master data, capacity, production orders and root-cause work
• The difference between deterministic SAP planning logic and probabilistic AI interpretation
• How to reduce hundreds of exception messages into a few workable patterns, then prioritise them by business impact rather than value alone
• How to give AI proper planning context - plant, MRP type, lot size, procurement type, lead times, safety stock, production version, factory calendar - and how a weak prompt compares to a strong one
• How to tell AI to leave unknown planning facts unknown instead of inventing them
• How to review material masters, BOMs, routings, work centers and production versions for outliers, and connect an outlier to its planning consequence
• How to structure a capacity bottleneck investigation and build at least five alternatives before recommending overtime
• How to troubleshoot a late production order through status, material, operation, confirmation and variance
• How to run root-cause analysis as testable hypotheses, separate root cause from corrective action, and interpret planning KPIs in context
• The risks - stale data, wrong assumptions, poor confirmation discipline, over-automation and confidential manufacturing information
• A controlled daily shortage-review workflow, a PP consultant review checklist, and a 30/60/90-day personal adoption plan
By the end, you will be able to analyse a shortage using a demand, supply, master-data, execution sequence; explain why an MRP result can be technically correct yet operationally unexpected; challenge a capacity assumption before agreeing to overtime; write a five-line issue, impact, cause, evidence, action summary that a manager can act on; and distinguish a genuine PP problem from an MM, SD, QM, EWM, maintenance or finance one. SAP plans. AI assists. You decide.
Who this course is for
SAP PP consultants SAP S/4HANA Manufacturing consultants Production planners and MRP controllers Manufacturing process leads and supervisors SAP solution consultants and functional analysts SAP support and AMS consultants SAP project team members in manufacturing rollouts Supply chain and materials planners working with SAP SAP consultants moving from ECC to S/4HANA Manufacturing Junior SAP consultants building PP fundamentals Team leads setting AI usage standards for planning teamsHomepage
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