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11 July

Better Pricing, Faster Approvals: SAP Store Expands Self-Service for Partners

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Winning deals is hard enough for our partners. Building quotes, navigating pricing, and waiting on approvals can make it even harder. A straightforward transaction could stretch into weeks of back and forth.

With updates to SAP Store and SAP for Me, partners now get a self-service purchasing experience that cuts out that complexity, with pricing transparency comparable to what partners get on AWS and Azure marketplaces.

Smarter path from opportunity to purchase

The updated experience connects the full purchasing journey in one place, SAP for Me: from finding the right solution, to submitting a quote, to completing the transaction.

Start with the right catalog

Partners start with a personalized catalog for their specific opportunity. Partner authorization, customer eligibility, product prerequisites, and related products are shown upfront — searchable, sortable, and packaged in an intuitive way, so there is no need to cross-reference multiple systems or wait for someone else to confirm what can be sold.

Know your pricing before you ask

Price transparency is built into the experience. With shopping carts powered by SAP’s own commerce solutions, partners can see what features are included in the product and can explore options and simulate quotes with full pricing visibility from the start, without waiting on internal teams to pull numbers together. More than 70% of B2B buyers prefer to research and validate independently before talking to a sales rep, and this experience is built around that.

Guided selling: No guesswork and easier to learn

SAP’s portfolio is broad, and pricing can get complex, especially for partners newer to selling SAP, that previously had to track price lists, prerequisites, and product relationships on their own before building a quote. The experience now surfaces eligibility requirements, dependencies, and configuration options as partners work, so nobody starts from scratch.

Test scenarios before you submit

Before requesting approval, partners can run simulations to validate pricing and test different quote configurations before quote approval. Fewer surprises going in means fewer revisions coming back.

Faster approvals, less waiting

Internal approvals and administrative complexity have stretched B2B sales cycles by roughly 25% over the past five years, and for many deals, that friction sits in the quote and approval stage. Partners now submit pre-validated, perfectly priced quotes only when they have tried and tested different pricing possibilities in the cart, and even complex scenarios move through a streamlined approval process with fewer delays.

End-to-end, fully digital

Once a quote is approved, the purchase completes digitally from start to finish: no chasing signatures, no manual uploads, no last-mile handoffs. Self-service e-commerce has become the top revenue-generating channel for B2B companies that offer it, and the move to SAP for Me and SAP Store reflects that shift.

See it in action

The experience looks different depending on your partner model. For CC Flex partners, the journey includes commission visibility at every step, from the configurator through to the approved quote. For VAR partners, the flow moves from cart configuration to fully automated quote generation and straight through to checkout, with a confirmation email from SAP once the order is placed.

What’s next

Upcoming enhancements will introduce embedded AI assistance through Joule, guiding partners through the purchasing journey with in-context support at every step. We will also include full partner cloud pricelist coverage and the ability to manage post sales via this kind of guided digital buying journey soon.

Whether you are managing a straightforward opportunity or a complex deal, the updated experience in SAP Store and SAP for Me gives partners clearer pricing, fewer roadblocks, and more control over how they close.

Start your next quote: Visit SAP for Me.

Shreya Datta is senior director of SAP Marketplace Direct Business at SAP.

07 July

SAP PRESS

AI-Driven Autonomous SAP Operations and SAP Basis Modernization

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For three decades, Basis has been the discipline of keeping the lights on: monitoring system performance, applying patches, managing transports, and responding to the inevitable 2 a.m. page when a production instance falls over.

20 June

SAP PRESS

When to Use Behavioral Patterns in ABAP Programming

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Behavioral patterns concentrate on interaction by showing how objects exchange information, distribute tasks, and execute sophisticated logic as part of a unified operation.

10 June

Video_SAPcomm

How Mead Johnson Nutrition Built a Trusted Foundation for AI with SAP Business Data Cloud

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When trusted AI matters, trusted data comes first. See how Mead Johnson Nutrition is building its data foundation with SAP Business Data Cloud.

For Mead Johnson Nutrition, supporting the health and nutrition of families and infants means every decision must meet a higher standard. In a highly regulated industry, AI can’t be directionally right, occasionally wrong, or unclear in how it reaches a recommendation. It needs trusted business context, strong governance, and transparency by design.

In this customer story, Mead Johnson Nutrition shares how SAP Business Data Cloud helps bring SAP and non-SAP data together with metadata, definitions, lineage, and governance intact. By replacing fragmented, market-specific data pipelines with a unified data fabric and reusable SAP data products, teams can spend less time wrangling numbers and more time acting on reliable insights.

With a trusted foundation in place, Mead Johnson Nutrition is preparing for enterprise AI that is consistent, governed, and scalable across the business. The result: better decisions made faster and with confidence, supporting availability, responsiveness, reliability, and the standards families depend on.

Explore SAP Business Data Cloud: https://www.sap.com/products/data-cloud.html

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09 June

BUSINESS NEWS

How the SAP Tool Chain Fuels Fast Growth at Harbour Energy

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“Why do oil and gas remain important today?” asked Graham Young, VP EMS Operation at Harbour Energy, at the recent TAC Insights conference for SAP for Energy and Utilities in Toulouse.

“The global energy demand won’t stop growing,” he explained. “As renewables only provide a small share of the energy we currently use, we’ll still need oil and gas that are safely produced as we transition to a lower carbon world.”

Crude oil still remains indispensable where alternatives are limited, particularly in heavy transport and the chemicals industry, and natural gas plays a key role in the low-carbon transition, both as an energy source and in large-scale hydrogen production.

A unique model

What’s interesting about Harbour Energy, one of the world’s largest and most geographically diverse independent oil and gas companies, isn’t just that it’s big. What’s interesting is how it got big and how it operates differently from traditional energy companies. The company was founded in 2014 by private equity firm EIG Global Energy Partners with a goal to build a global, independent company by acquisition.

“We’re basically trying to solve a very hard problem. How do we scale like a major, but stay agile like a startup?” Young said during his presentation about Harbour’s rapid growth journey. He explained that in a company that grows through acquisitions and runs multiple ERP systems, the role of technology is less about “one system” and more about connecting everything, standardizing insight, and accelerating change.

Masters of integration

Most oil and gas giants grew over decades. Harbour did it in about 10 years by pursuing an aggressive strategy of mergers and acquisitions, buying assets such as oil fields from industry giants like Shell. The company also scaled rapidly across 11 countries giving it a broad geographical reach. Crucially, Harbour Energy was often able to integrate acquisitions within a year, demonstrating a rare combination of speed and integration.

“A lot of companies struggle after acquisitions,” Young said. “Systems break, processes clash, value gets lost. At Harbour, we focus on quickly stabilizing new assets, extracting synergies early, and reducing operating costs even while growing.”

Young’s team took a different approach to technology. While most companies push for one massive ERP system, Harbour doesn’t blindly take that path. It runs multiple ERP systems when it makes sense, focuses on fit-for-purpose architecture, and uses tools to connect processes rather than force everything into one box. Such flexibility is a big advantage for a company that keeps acquiring new businesses.

The digital backbone

Because Harbour Energy operates multiple ERP systems rather than a single monolithic platform, complexity is unavoidable. SAP’s integrated tool chain, particularly SAP LeanIX solutions and the SAP Signavio portfolio, connects this landscape by aligning processes, linking capabilities to systems, and providing a unified view of ‘what’s where,’ ultimately creating visibility across an otherwise fragmented environment.

“Before we implemented the SAP tool chain, processes were hidden in Excel and PDFs. It was all part of the local knowledge we acquired,” Young said. “We had no clear view of duplication or inefficiencies. For example, we found that we had dozens of HR systems, which we were able to reduce by half. We were able to consolidate 33 different ways to do travel expenses into just one.”

One major impact is speed. Whereas traditional transformation planning took up to 24 months, now, with the tool chain and process modeling, key design cycles can sometimes be achieved in four to six weeks. This is enabled by standard process templates and automated modelling for faster validation cycles leading to faster execution of integration and transformation programs.

In addition, tools like the SAP Test Automation solution by Tricentis and SAP Cloud ALM for application lifecycle management help ensure that releases are safer and fewer operational surprises occur during go-lives, which is critical in an industry where downtime is expensive.

By connecting systems and processes, the tool chain enables cost transparency across business units and investment prioritization based on real data. This directly supports financial discipline and shareholder value creation

For a company built on acquisitions, probably the biggest value driver is that the tool chain helps rapidly map the systems of acquired companies and compare them against Harbour’s core model identifying what to keep, retire, or migrate. This is why Harbour can integrate acquisitions quickly instead of getting stuck in years of IT consolidation.

Structure before automation

Only when processes are structured and visible can they be used for automation, which is why these tools all play a crucial role in enabling AI adoption. Standardized workflows and process maps are input for AI tools, and digital adoption platforms guide users through systems.

The three key engines provided by the SAP tool chain include:

Transparency engine makes the business visible end-to-end
Standardization engine aligns processes, systems, and capabilities globally
Acceleration engine speeds up M&A integration and transformation delivery

Together with SAP Analytics Cloud for global forecasting and planning, these tools are at the heart of the company’s successful business transformation.

Young listed the three strategic levers keeping the company strong, resilient, and ambitious. The first is maintaining strict financial discipline, followed by using data driven insights that ensure the company remains competitive, and, last but not least, equipping the business teams with advanced capabilities ensures resilience.

“The SAP tool chain allows us to grow aggressively through acquisitions without collapsing under complexity,” Young concluded. “It’s essentially the difference between chaotic expansion and controlled, scalable growth.”

Check out the SAP integrated tool chain and its core capabilities here.

01 June

BUSINESS NEWS

How E.ON Is Building the Digital Backbone of the Energy Transition

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Sebastian Weber, CIO of E.ON, one of Europe’s largest energy companies, is quite amazed that humans don’t freak out more as technology that seems like science fiction becomes subtly ingrained in our lives.

He mentioned driverless cars in San Francisco, autonomous drones conducting warfare, and robots that are trained to care for humans as real humans would. Speaking at the recent TAC Insights sponsored conference featuring SAP for Energy and Utilities, Weber admitted he finds it all rather scary, but also very exciting.

For an energy company operating critical infrastructure, this pace of technological change is not just fascinating or frightening—it creates a responsibility to adopt innovation in a controlled, resilient, and purpose‑driven way.

Riding the waves

Weber sees these developments as a continuation of various “big waves” of technology that keep touching our hearts and minds as they shape the world around us. Who can imagine the world without the internet? Who can deny that the mobile phone didn’t revolutionize the consumption of IT when people started expecting the same ease of use in the workplace?

“AI is creating the same response,” Weber explained. “ChatGPT makes my life easier at home solving gardening issues, so I expect it to make my life easier at work.”

One of E.ON’s biggest challenges is closing the widening gap between the rapid pace of technological innovation in the outside world and the organization’s internal ability, shaped by its structure and DNA, to absorb and implement these changes effectively.

This tension became evident when leadership questioned whether sustained IT spending at large scale was justifiable. It soon became clear that continuous investment is the price of system stability, affordability, and resilience in a digitized energy system if E.ON is serious about becoming the leading playmaker in Europe’s green energy transformation.

To achieve this ambition, the company has defined three strategic priorities—growth, sustainability, and digitalization—recognizing that falling behind in digital capabilities would carry far greater long-term costs.

“Bringing the system up to speed requires internal readiness. It means we must think deeply about investments, prioritization, and most importantly, people and culture,” said Weber. “One thing is sure: we won’t be going back to what was normal speed before.”

Becoming strategic

E.ON operates across three domains: energy grid, customer solutions, and energy infrastructure solutions. This broad scope creates a high level of operational complexity, requiring scalable, transparent, and collaborative ways of working across the organization.

To meet these challenges, E.ON is strengthening its internal capabilities and investing in its people. By expanding in-house expertise, the company has welcomed over 1,000 specialists, including more than 500 in data and 300 in cybersecurity, fostering greater ownership, collaboration, and innovation across the organization.

This move reflects a broader philosophy. IT is no longer just a support function; it is foundational to pioneering the energy transition and delivering competitive advantage.

As E.ON’s transformation unfolds against a backdrop of rapid technological evolution, AI is at the heart of the current inflection point. Technologies like AI-powered assistants and automation tools are not novelties; they are actively redefining how customers interact with services. E.ON recognizes this shift and is embedding advanced technologies directly into its core systems, rather than treating them as add-ons.

Closing the gap

Weber explained that digital transformation at E.ON means putting the right technology into the core of the business to better serve its 47 million customers.

It starts with platform standardization, followed by cloud ERP transformation and the SAP S/4HANA migration. Instead of building fragmented custom solutions, this strategy allows the company to integrate leading technologies into a cohesive architecture, ensuring scalability while avoiding unnecessary complexity. These basic investments in foundational infrastructure have delivered tangible results, including an 77% reduction in IT downtime within five years.

A key lesson from E.ON’s journey is the importance of embedding digital capabilities into the heart of operations. “We’ve moved away from isolated innovation hubs such as digital labs or experimental ‘garages’ in favor of integrating digital tools directly into business processes,” Weber explained.

While innovation is essential, E.ON places equal emphasis on governance and control. Managing a digital ecosystem at this scale requires strong oversight to ensure security, consistency, and cost discipline. The company implemented centralized governance structures, including standardized contracting and unified IT system management to help maintain control without stifling innovation.

Equally important is investment in people. Through targeted training and capacity building initiatives, employees are empowered to turn new technologies into measurable business impact.

Harnessing AI

As with many companies, AI is at the center of E.ON’s forward-looking strategy, but the company is approaching it with deliberate caution. Rather than rushing to build proprietary platforms, E.ON is leveraging partnerships with established technology providers while maintaining flexibility in its IT portfolio. This approach allows the company to explore the potential of AI in customer service automation, predictive maintenance, and operational optimization without overcommitting to unproven solutions.

“In essence, our experience highlights a broader truth about digital transformation,” said the IT expert. “Success really depends on balance. We absolutely must push innovation forward, but not at the expense of stability, cyber security or governance.”

Equally, digital tools alone are not enough. Without proper training and alignment with business needs, even the most advanced technologies can fail to deliver value. E.ON addresses this through a “BizDevOps” mindset, ensuring that digital initiatives are an integral part of business goals and supported by the right capabilities.

In summary, E.ON’s transformation illustrates what it takes to modernize at scale in a complex, highly regulated industry. By doubling down on IT investment, bringing expertise in house, and adopting a disciplined yet forward-looking approach to innovation, the company has positioned itself for the future of energy.

The result is not only improved system performance or reduced downtime. It’s a fundamental shift in how technology drives business success, turning technology into a cornerstone of making new energy work—reliably, affordably, and at scale.

23 May

SAP PRESS

What Is ABAP Doc?

by wendy@eyeconz.com 0 Comments

ABAP Doc enables the documentation of ABAP objects on the basis of specific comments.

24 April

BUSINESS NEWS

The Real Risk to AI in HR Is Fragmentation

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HR leaders often worry about moving too fast—embracing new trends, over-investing in new technology, or introducing more change than the organization can absorb. But a new business value study from IDC sponsored by SAP*, based on organizations using SAP SuccessFactors solutions to run core HR, time, and payroll, points to a different risk altogether: fragmentation. And not only as an operational inefficiency, but as a fundamental barrier to realizing the full potential of AI in HR.

Across many enterprises, HR, time, and payroll systems have evolved through years of growth, acquisitions, and regional customization. The result is a patchwork of disconnected tools, duplicated data, and manual handoffs that quietly slow decision-making and increase operational risk. These systems may still “work,” but they carry a hidden cost on productivity, accuracy, and confidence, as expectations on HR continue to rise and AI becomes central to how work gets done.

Fragmentation is the hidden bottleneck behind “slow” decisions

The impact of fragmentation isn’t always visible, but it shows up clearly in how decisions get made.

When decisions stall, leaders often point to approvals, governance, or external constraints. In reality, much of the friction happens earlier, when teams reconcile data across systems before decisions can even begin.

According to the research, organizations with unified HR foundations gained faster access to trusted workforce information, generating insights 60% faster and creating new position listings 53% faster. Rather than adding tools, these organizations removed friction by eliminating manual validation, shadow spreadsheets, and repeated checks to confirm data accuracy.

As organizations look to AI to accelerate workforce planning, surface risks, and guide decisions, this foundation becomes even more critical. AI is only as effective as the data it can access and trust. In disconnected environments, AI inherits the same inconsistencies, delays, and gaps, limiting its ability to generate reliable insights and recommendations.

Consider a simple workforce planning decision like headcount approval. In a fragmented environment, HR pulls data from one system, finance validates it in another, and managers reconcile discrepancies in spreadsheets. What should take hours stretches into days—not because the decision is complex, but because the data is.

With real-time, consistent workforce information, leaders can act faster and with greater confidence in their decisions. More importantly, unified data allows AI to move beyond reactive reporting to deliver proactive, decision-ready intelligence.

Most payroll errors aren’t human—they’re structural

Disconnected systems don’t just slow work; they also increase errors.

When employee data, time records, and payroll information live in different places, every handoff becomes an opportunity for mistakes. Manual reconciliation and corrective actions become routine, especially during high-pressure cycles like payroll close.

Organizations with unified platforms see a clear shift. Payroll error rates drop by 64% and payroll cycles are completed 44% faster by eliminating data gaps and automating validation across connected processes.

This is where AI begins to shift from reactive to preventative. With unified data, AI can identify anomalies before payroll runs, flag potential compliance risks, and continuously learn from patterns across the organization. Instead of fixing errors after the fact, HR and payroll teams can prevent them altogether.

That structural shift changes the nature of work for HR and payroll teams. Payroll teams saw a 21% productivity increase, while HR teams improved productivity by 14%, as time previously spent tracking down discrepancies, correcting entries, and responding to escalations was redirected toward oversight, compliance, and continuous improvement.

Fragmentation quietly erodes trust and limits AI adoption

When systems are fragmented, trust erodes quietly. Employees lose confidence when pay errors occur or self-service tools don’t reflect their reality. Managers hesitate to act when dashboards conflict. HR teams become intermediaries between systems rather than strategic partners to the business.

Integrated HR, time, and payroll systems reverse this dynamic. Employees gain easier access to self-service tools, with 28% more employees able to directly access HR and time entry platforms. Managers benefit from real-time visibility into approvals and team data. And HR teams regain credibility as the source of accurate, timely workforce information.

Over time, this trust compounds. When people trust the system, they use it. Increased usage improves data quality, and better data strengthens decision-making.

This foundation becomes even more important as organizations scale AI across HR. Employees and managers are far more likely to rely on AI-driven recommendations—whether for career growth, scheduling, or compensation—when they trust the underlying data. Without that trust, even the most advanced AI capabilities remain underutilized.

Fragmentation doesn’t just slow execution—it narrows what leaders believe is possible, forcing decisions to be shaped by system constraints rather than business needs.

The cost of standing still

The cost of fragmentation isn’t just operational; it’s financial, and it compounds over time.

Across organizations studied, the average annual quantified benefit totaled US$649,400 per 1,000 employees supported, driven by productivity gains, reduced errors, faster cycles, and better business decisions. Over three years,organizations achieved a 284% return on investment, with a payback period of approximately 15 months.

Beyond these quantified gains, there is a growing competitive gap. Organizations operating on unified platforms are not only more efficient, but they are also better positioned to embed AI across the entire employee lifecycle, from hiring and onboarding to development and workforce planning. Those still operating with disconnected systems risk falling behind—not just operationally, but strategically.

The real risk isn’t innovation

Innovation draws attention because it’s new, visible, and often disruptive. Fragmentation, by contrast, builds quietly in the background until it starts to limit how the organization operates. But as organizations ask HR to deliver more—better insights, faster planning, stronger compliance, and improved employee experiences—the limits of disconnected systems become harder to ignore.

Modern HR outcomes don’t come from layering new tools on top of outdated foundations. They come from reducing complexity, unifying data, and creating consistency across the most essential people processes. This is where platforms like SAP SuccessFactors are evolving—not just to unify core HR, time, and payroll, but to embed AI directly into the flow of work. By combining a trusted data foundation with AI-driven insights and automation, organizations can move from reactive operations to predictive, insight-led workforce management.

The question isn’t whether organizations can afford to modernize HR. It’s whether they can afford to limit the impact of AI by building on fragmented foundations.

AI doesn’t transform HR on its own; it amplifies what’s already there. And without a unified, trusted core, even the most advanced AI will struggle to deliver on its promise.

Learn how leading organizations are reducing fragmentation and building a strong foundation for AI by unifying core HR, time, and payroll with SAP SuccessFactors.

*IDC Business Value White Paper Sponsored by SAP, The Business Value of SAP SuccessFactors Core HR, Time, and Payroll Solutions, #US53971225-BVWP, January 2026.

Lara Albert is chief marketing officer for SAP SuccessFactors.

24 March

Video_SAPcomm

Top New Features in SAP HANA Cloud | Q1 2026 Release Highlights

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Discover what’s new in SAP HANA Cloud Q1 2026 in under 7 minutes.

In this short update, Thomas Hammer (Lead Product Manager, SAP HANA Cloud) walks you through key innovations in the Q1 2026 release, focused on making it easier to explore enterprise data, integrate across SAP platforms, analyze performance, and build intelligent applications.

You’ll learn how the new Discovery Agent and Data Agent help reduce the barrier to working with enterprise data. Instead of relying on deep database expertise and manual SQL, you can describe what you need in natural language. The Discovery Agent uses a custom database object knowledge graph to find relevant data, while the Data Agent turns your request into SQL and executes it in SAP HANA Cloud. This enables a more intuitive path from question to insight.

Next, see how semantic onboarding brings existing SAP HANA Cloud calculation views into SAP Business Data Cloud, selectively and without data movement, using remote connectivity. This supports reuse of existing models while complementing them with SAP Business Data Cloud capabilities.

Thomas also introduces the new Performance Analysis application in SAP HANA Cloud, designed to simplify troubleshooting with guided workflows and predefined presets for common scenarios, like CPU bottlenecks, memory pressure, and lock contention. It also includes an on-demand chart library for deeper investigation. Finally, the release includes improvements to text classification in the predictive analysis library, enhancing performance, efficiency, and ease of use, including text feature processing with automated machine learning models.

Chapters:
0:00 – Intro
0:47 – Discovery Agent and Data Agent in SAP HANA Cloud
2:24 – Semantic Onboarding of calculation views into SAP Business Data Cloud
3:25 – Performance analysis application in SAP HANA Cloud
4:28 – Improvements in text classification capabilities
5:16 – Further innovations

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24 March

SAP PRESS

Common Challenges When Adopting SAP BRIM and How to Think About Them Early

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Implementing SAP Billing and Revenue Innovation Management (SAP BRIM) can feel a bit like moving into a new house.