Preface

21

Who This Book Is For

22

How This Book Is Structured

23

Acknowledgments

26

Conclusion

26

1 Introducing the Autonomous Enterprise: Apps, Data, and AI

29

1.1 The Cloud and Autonomous Mindset

29

1.2 The Autonomous Enterprise Flywheel

31

1.3 Applications: SAP Autonomous Suite

35

1.3.1 SAP Cloud ERP

35

1.3.2 Line-of-Business Applications

36

1.4 Data: The Business Data Foundation

38

1.5 Platform: SAP Business Technology Platform as the Foundation

40

1.6 SAP Business AI: The Intelligence Engine

42

1.6.1 Intelligent Technologies

42

1.6.2 Embedded Intelligence in Applications

46

1.6.3 AI Assistants and Agents

48

1.6.4 The Pillars of SAP Business AI Platform

53

1.6.5 Five Patterns of Business AI Applications

54

1.7 Business AI Maturity Model: From Augmentation to Autonomy

55

1.8 Case Studies

58

1.8.1 The Company

59

1.8.2 The Business Problems

59

1.9 Summary

63

2 SAP Cloud ERP Business Capabilities

67

2.1 Finance

67

2.1.1 Universal Journal

68

2.1.2 Record-to-Report

69

2.1.3 Financial Planning and Analysis

76

2.1.4 Invoice-to-Pay and Invoice-to-Cash

78

2.1.5 Treasury and Cash Management

80

2.1.6 Financial Compliance Management

81

2.1.7 Outcome

83

2.2 Sales

84

2.2.1 Quote-to-Order

84

2.2.2 Order and Contract Management

87

2.2.3 Customer Invoice Management

92

2.2.4 Customer Returns Management

95

2.2.5 Sales Analytics

96

2.2.6 Solution Business Models

98

2.2.7 Advanced Intercompany Sales

99

2.2.8 Outcome

102

2.3 Sourcing and Procurement

103

2.3.1 Source-to-Contract

105

2.3.2 Procure-to-Receipt

108

2.3.3 Central Procurement

112

2.3.4 Invoice-to-Pay

114

2.3.5 Insight-to-Action

119

2.3.6 Public Cloud Versus Private Cloud

122

2.3.7 Outcome

125

2.4 Production Planning and Manufacturing

125

2.4.1 Plan-to-Optimize Fulfillment Strategy

127

2.4.2 Plan and Schedule

131

2.4.3 Manufacturing

139

2.4.4 Quality Management

152

2.4.5 Public Cloud Versus Private Cloud

154

2.4.6 Outcome

156

2.5 Logistics

156

2.5.1 Inventory Management

157

2.5.2 Logistics Execution

161

2.5.3 Integrated Warehouse Management

163

2.5.4 Order Promising: Available-to-Promise

165

2.5.5 Transportation Management

167

2.5.6 Handling Unit Management

168

2.5.7 Public Cloud Versus Private Cloud

169

2.5.8 Outcome

171

2.6 Asset Management

171

2.6.1 Intelligent Asset Management

172

2.6.2 Plan-to-Optimize Assets

175

2.6.3 Operate-to-Maintain Assets

177

2.6.4 Offboard-to-Decommission

183

2.6.5 Managing Assets

187

2.6.6 Public Cloud Versus Private Cloud

188

2.6.7 Outcome

190

2.7 Summary

190

3 Two-Tier ERP Landscapes

193

3.1 What Is Two-Tier ERP?

193

3.2 Deployment Models and Use Cases

195

3.3 Finance Domain: From Consolidation to Strategic Planning

198

3.4 Sales Domain: Order-to-Cash

202

3.5 Procurement Domain: Procure-to-Pay

203

3.6 Integration and Setup

205

3.7 Accelerators

208

3.8 Summary

208

4 LoB Apps and Extended Capabilities

211

4.1 Supply Chain

211

4.1.1 The Strategic Challenge

212

4.1.2 SAP Integrated Business Planning

214

4.1.3 SAP Digital Manufacturing

217

4.1.4 SAP Logistics Management

219

4.1.5 SAP Asset Performance Management

221

4.1.6 SAP Supply Chain Orchestration

223

4.1.7 The Integration Model

225

4.2 Finance and Spend

226

4.2.1 The Strategic Challenge

227

4.2.2 Financial Core and Office of the CFO

228

4.2.3 SAP Ariba

229

4.2.4 SAP Concur

231

4.2.5 SAP Fieldglass

232

4.2.6 The Integration Model

233

4.3 Customer Experience

237

4.3.1 The Strategic Challenge

237

4.3.2 SAP Customer Data Cloud

239

4.3.3 SAP Marketing Cloud

240

4.3.4 SAP Commerce Cloud

241

4.3.5 SAP Sales Cloud

242

4.3.6 SAP Service Cloud

243

4.3.7 The Integration Model

244

4.4 Human Resources

245

4.4.1 The Strategic Challenge

247

4.4.2 SAP SuccessFactors

247

4.4.3 The Integration Model

257

4.5 Summary

257

5 Embedded AI in Business Processes

259

5.1 How SAP Makes the Autonomous Enterprise Real

260

5.2 Finance

264

5.2.1 Overview of Autonomous Finance

265

5.2.2 Plan to Optimize Financials

269

5.2.3 Invoice-to-Cash

273

5.2.4 Invoice-to-Pay

281

5.2.5 Treasury and Working Capital

287

5.2.6 Accounting and Close

292

5.2.7 Governance, Risk, and Compliance

297

5.3 Lead-to-Cash

300

5.3.1 Overview of Autonomous CX

301

5.3.2 Order-to-Fulfill

302

5.3.3 Opportunity-to-Quote

310

5.3.4 Invoice-to-Cash

315

5.3.5 Manage Customer and Channels

316

5.4 Source-to-Pay

319

5.4.1 Overview of Autonomous Spend

320

5.4.2 Source-to-Contract

321

5.4.3 Procure-to-Receipt

325

5.5 Plan-to-Fulfill

328

5.5.1 Overview of Autonomous Supply Chain Management

329

5.5.2 Plan-to-Schedule

330

5.5.3 Manufacturing

337

5.5.4 Quality Management

339

5.5.5 Logistics

342

5.6 Acquire-to-Decommission

347

5.6.1 Plan-to-Optimize Assets

348

5.6.2 Acquire-to-Onboard

350

5.6.3 Operate-to-Maintain

351

5.6.4 Offboard-to-Decommission

354

5.6.5 Manage Assets

355

5.6.6 Industry AI for Asset Management

357

5.7 Summary

362

6 Industry-Specific Autonomous Scenarios

365

6.1 Life Sciences: Traceability, Compliance, and Controlled Supply Chains

365

6.2 Consumer Products: Demand Volatility and Omnichannel Fulfillment

367

6.3 High Tech: Configurable Products and Rapid Innovation Cycles

369

6.4 Industrial Manufacturing: Supply Constraints and Production Continuity

370

6.5 Oil, Gas, and Energy: Distributed Operations and Asset Coordination

371

6.6 Summary

372

7 The New Platform

377

7.1 The Platform Architecture

378

7.2 Build with SAP BTP and Joule Studio

379

7.2.1 Joule Studio

379

7.2.2 SAP Integration Suite

380

7.3 Knowledge Core with SAP Business Data Cloud

381

7.4 SAP AI Core and SAP AI Launchpad

383

7.5 The Generative AI Hub

384

7.6 Joule Work

386

7.7 SAP AI Agent Hub

387

7.8 Business Transformation Management

388

7.8.1 SAP Signavio

388

7.8.2 SAP LeanIX and Enterprise Architecture Management

389

7.9 Governing AI at Enterprise Scale

390

7.10 Summary

391

8 SAP Business Technology Platform

393

8.1 Clean Core

394

8.1.1 Grading System

395

8.1.2 In App Versus Side by Side

397

8.2 Accounts and Runtime Environments

401

8.3 SAP Build

403

8.3.1 Low-Code Tooling in SAP Build

404

8.3.2 Pro-Code Tooling

408

8.3.3 SAP Joule for Developers

413

8.3.4 Joule Studio

415

8.4 Platform Integration Capabilities

417

8.4.1 Integration Services

417

8.4.2 Event-Driven Integration

418

8.5 Lifecycle Management

419

8.6 Summary

422

9 SAP Business Data Cloud

423

9.1 Vision and Architecture

423

9.1.1 Positioning and Value Drivers

423

9.1.2 Applications, Data, and Business AI

425

9.1.3 Current Data Challenges

427

9.1.4 Key Components

429

9.2 Setting Up SAP Business Data Cloud

432

9.2.1 Technical and Administrative Steps

432

9.2.2 Provisioning the SAP Business Data Cloud Environment

433

9.2.3 Creating the SAP Business Data Cloud Formation

436

9.2.4 Users and Connecting Data

438

9.3 Integration with SAP Cloud ERP and LoB Applications

439

9.3.1 Prerequisites

439

9.3.2 SAP S/4HANA Cloud Private Edition

440

9.3.3 LoB Applications

442

9.3.4 SAP S/4HANA Cloud Public Edition

443

9.4 Intelligent Content and Data Products Economy

443

9.4.1 Data Products

444

9.4.2 Intelligent Packages and Domain Content

448

9.5 Zero-Copy Data Sharing

459

9.6 SAP Knowledge Graph and Integration with Joule Studio

462

9.7 Embedded AI Capabilities

465

9.7.1 AI-Assisted Features in SAP Datasphere

465

9.7.2 AI-Assisted Features in SAP Analytics Cloud

466

9.7.3 Agents

469

9.8 Governance

471

9.9 Use Case Patterns

475

9.9.1 Working Capital

475

9.9.2 On Time, In Full (OTIF)

478

9.9.3 Total Spend

479

9.9.4 Advanced Spend Intelligence Capabilities

480

9.9.5 SAP Business Warehouse in the Private Cloud

481

9.9.6 SAP Business Data Cloud Connect

484

9.10 Summary

485

10 Extensibility and Agent Development

487

10.1 In-App Extensibility for Key Users

488

10.1.1 Extending the Order-to-Cash Process

489

10.1.2 Transporting Key-User Extensibility Artifacts

490

10.2 Developer Extensibility

490

10.2.1 The ABAP RESTful Application Programming Model

490

10.2.2 Building a Credit Risk Scoring Service

491

10.2.3 Git-Enabled Transport Management for Developer Extensibility

492

10.3 Side-by-Side Extensibility

493

10.4 The Extensibility Wizard

496

10.5 Joule Skills and Agent Development

497

10.5.1 Joule Skills

498

10.5.2 The Joule Collections Agent

498

10.5.3 What’s Ahead for Joule Studio

502

10.6 Custom AI Services and Development

503

10.6.1 SAP AI Core

503

10.6.2 Integration with SAP Business Data Cloud

506

10.7 Summary

506

11 Integration Capabilities

509

11.1 Integration Strategy

509

11.1.1 Strategic Imperatives

510

11.1.2 SAP Integration Solution Advisory Methodology

511

11.1.3 SAP Business Accelerator Hub

512

11.1.4 SAP Integration Suite

513

11.2 APIs and Integration Flows

517

11.3 Event-Driven Integrations

522

11.3.1 Event Mesh and Advanced Event Mesh

523

11.3.2 Example: Advanced Event Mesh

526

11.4 AI for Integration

528

11.4.1 AI-Assisted Integration Development

529

11.4.2 Future AI Enhancements

530

11.5 SAP Master Data Integration

530

11.6 Summary

531

12 Developing a Business Case for Your Autonomous Enterprise

535

12.1 Where Is the Value Lost?

535

12.2 What Agents and Assistants Actually Change

536

12.3 The Flywheel Model: How Autonomous Capabilities Amplify Traditional Value

537

12.4 Top-Down Value Versus Bottom-Up Value

539

12.4.1 Top-Down View: The Outcome That Matters

539

12.4.2 Bottom-Up View: Where the Cash Actually Gets Stuck

540

12.5 How the Autonomous Enterprise Bridges the Gap

542

12.6 Building a Value-Based Roadmap

543

12.7 From Rotterdam to Outcomes

545

12.8 Summary

546

13 Leveraging Tools for Transformation

549

13.1 Process Optimization with SAP Signavio

551

13.1.1 Process Analytics in SAP Signavio

552

13.1.2 Process Management in SAP Signavio

557

13.2 Architecture Management with SAP LeanIX

560

13.2.1 SAP LeanIX Application Portfolio Management

561

13.2.2 SAP LeanIX Technology Risk and Compliance

564

13.2.3 SAP LeanIX Architecture and Road Map Planning

565

13.3 Lifecycle Management with SAP Cloud ALM

566

13.4 Testing Automation with Tricentis

568

13.5 Data Migration with Syniti

570

13.6 Content Management with OpenText

571

13.7 Digital Adoption with WalkMe

572

13.7.1 Data and Analytics in WalkMe

573

13.7.2 Platform and Experience in WalkMe

574

13.8 Toolchain Convergence

576

13.8.1 SAP Transformation

577

13.8.2 Continuous Improvement Effort

587

13.9 Summary

589

14 AI Governance and Responsible AI

591

14.1 Ethical AI Guidelines: Principles into Action

592

14.1.1 SAP’s 10 Ethical AI Guiding Principles

593

14.1.2 Operationalizing Ethics: The Business AI Lifecycle and Risk Assessment

594

14.1.3 Ecosystem Governance and Global Regulatory Alignment

595

14.2 Privacy and Auditability: The Data Sanctuary

597

14.3 Sovereign AI and Global Compliance

599

14.3.1 Navigating the Regulatory Frontier and the EU AI Act

600

14.3.2 ISO/IEC 42001 and the Gold Standard for Governance

600

14.4 Autonomous Suite Resilience and the Secure Core

601

14.4.1 The Defense Architecture and Emerging Threat Mitigation

601

14.4.2 The Generative AI Hub as a Hardened Processing Enclave

602

14.4.3 Securing the Digital Assistant: The Joule Architecture

603

14.5 Agent Lifecycle Management

604

14.6 Summary

606

15 Operationalizing Your Vision

607

15.1 Deployment Strategy and Instance Planning: Choosing Your Starting Architecture

607

15.2 Organization Readiness Assessment

611

15.2.1 Scope and Value

611

15.2.2 Non-Negotiables

612

15.2.3 Capabilities and Processes

613

15.2.4 Data, Systems, and Integration

613

15.2.5 Governance

615

15.2.6 Change and Adoption

617

15.2.7 The Baseline Assessment Framework

618

15.3 From Readiness to Target Architecture

619

15.4 Multiyear Roadmap

620

15.5 The AI Golden Path: From Business Intent to Deployment

623

15.6 Value Realization Plan: Measuring and Governing the Outcomes

627

15.7 Summary

630

16 Change Management

633

16.1 Why Change Management Is Crucial

633

16.1.1 The Problem: Technology Does Not Transform Organizations

634

16.1.2 What Actually Changes

634

16.1.3 The Adoption Gap

635

16.2 Structured Change Management

635

16.2.1 Phase 1: Readiness

636

16.2.2 Phase 2: Adoption

637

16.2.3 Phase 3: Sustainment

639

16.2.4 Adoption Patterns Across Functional Domains

640

16.3 Measurement and Diagnosis: When Adoption Stalls

641

16.4 AI Fluency and Certification

643

16.5 Learning Journeys and Consultant Enablement

644

16.5.1 Learning Journeys: Structured Paths

644

16.5.2 Consultant Enablement Programs

646

16.6 Summary

648

17 From Analog Transactions to Autonomous Value

651

17.1 The Three Layers of the Autonomous Enterprise

651

17.2 Where Korindal Started: One Layer, Not Three

652

17.2.1 Phase 1: The Foundation: Standardize, Connect, and First Intelligence

653

17.2.2 Phase 2: Intelligence Activated: Agents as Advisors

655

17.2.3 Phase 3: Autonomous Within Guardrails: Agents as Decision-Makers

657

17.2.4 Phase 4: Coordinated Autonomy: The Flywheel in Motion

659

17.3 The Starting Point: What to Do Now

661

17.4 The Moment in History

662

17.5 Summary

663