male manager hand holding tablet with AR application for check order pick time in smart factory warehouse, technology interface global partner connection for Logistic Import Export background

SAP Positioned as a Market Shaper in the Inaugural 2026 Gartner® Emerging Market Quadrant for Integrated Supply Chain AI Agents – Established Vendors

The supply chain AI conversation is shifting. For years, the focus was on faster insights, better forecasts, and sharper visibility. That era delivered value, but it also revealed a gap: knowing what is happening is not the same as acting on it.

Accelerate outcomes with context-aware agents and assistants that know your work and your business

AI agents are now creating a new chapter. The next frontier is no longer analyzing faster, but letting agents act: working together across planning, procurement, manufacturing, logistics, and operations.

For more than 50 years, SAP has helped organizations run their supply chains by connecting business context, intelligence, and execution across end-to-end processes. 

We are proud to share that SAP has been positioned in the Market Shapers quadrant of the inaugural Gartner® Emerging Market Quadrant for Integrated Supply Chain AI Agents – Established Vendors. This is Gartner’s first formal assessment of this emerging category. In our view, it reflects the progress we have made in bringing AI agents into the heart of supply chain operations, and the direction we continue to take. 

Gartner describes the Market Shapers quadrant this way: 

“Vendors in this quadrant are defined by advanced multiagent solutions available across supply chain functions for greater operational impact. Moving beyond assistive solutions or siloed automation, these agents are able to reason across functions and systems, sense and respond to shifts in data, and execute autonomously, sometimes interacting with other agents or systems inside the enterprise, to solve more complex goals. These solutions are further elevated by optimization techniques such as decision modeling, knowledge graphs, digital twins, and ontology layers to improve agent performance.”

From assistants to orchestrated agents 

Supply chain decisions never happen in isolation. A supplier delay can ripple through production schedules, logistics, customer commitments, and financial results. Yet much of the AI in supply chains today still works within a single function or a single task. It can point out a problem, but people still must weigh the trade-offs and act across several systems. 

With Autonomous Supply Chain Management, people define goals and priorities, AI assistants orchestrate activity across domains, and agents execute the work within governed, end-to-end processes. Through Joule, role-specific assistants coordinate specialized AI agents across design, planning, sourcing, manufacturing, delivery, and operations. Together, they sense disruptions, analyze the impact, simulate alternatives, and execute coordinated responses, with people making the decisions that matter most.  

Joule is where it all comes together. People express what they want to achieve, and Joule Assistants take it from there.  Each assistant is tailored to a specific role, while agents handle specialized tasks within business-defined guardrails. 

For example, when a planner describes a goal, the Supply Chain Planning Assistant coordinates demand, inventory, and capacity agents to build and simulate scenarios, so the planner can focus on evaluating outcomes and making the decision. People direct. Assistants coordinate. Agents execute. 

And because SAP supply chain agents work within the broader SAP Autonomous Suite, a supply chain decision can trigger the right financial, workforce, or customer action as part of the same coordinated response.

Agents that act where the work happens 

We believe AI agents create real value only when they move from recommendation to execution safely. Greater autonomy must be accompanied by greater accountability. As agents take on more responsibility, organizations need visibility into what those agents are doing and why. That requires three things working together. 

First, agents need to work inside the system of record. SAP agents operate directly in SAP Cloud ERP and the SAP supply chain management suite executing production orders, convert requisitions, or direct warehouse tasks, with no middleware between decision and action. They can also extend coordination to trading partners through SAP Business Network. 

Second, agents need business context. SAP Business Data Cloud, SAP Knowledge Graph, and our supply chain semantic model give agents a shared understanding of business entities, relationships, and rules. That helps them understand what a signal means across domains and how a disruption will affect the business. 

Third, agents need governance. Through SAP Business AI Platform, Joule Studio lets customers and partners build agents, and SAP AI Agent Hub governs both SAP and non-SAP agents with identity enforcement, audit trails, and explainability. Joule Work gives people one place to monitor and act on agent recommendations.

Delivering real results for customers 

Customers will not value us by how many agents we build, but by the outcomes those agents deliver. Recognition is only meaningful when it reflects real impact for our customers, that are already putting supply chain agents to work with capabilities available today. 

Takeda Pharmaceuticals will use Industry AI for regulated manufacturing, where agents monitor production KPIs, flag deviations, and initiate corrective workflows in GxP environments. The expected results include up to 10% productivity gain and 25% less stock-out revenue loss. 

Lemvigh-Mueller deployed three coordinated agents to handle supplier order confirmations, reaching more than 90% touchless processing of 100,000 confirmations a year. 

RWE is applying Autonomous Asset Management to its offshore wind fleet, where AI agents analyze past incidents, identify root causes, and generate pre-filled work orders for technicians. 

Looking ahead 

Supply chains don’t become autonomous overnight. The journey happens step by step: starting with agents that recommend, then agents that act within clear guardrails, and expanding autonomy as data, processes, and governance mature.  

As we work with our customers and partners, our agent coverage will continue to expand every quarter across supply chain domains.  

We are grateful to our customers, partners, analysts, and SAP teams whose collaboration shapes our products and strategy. We see this recognition as an important milestone, and we remain committed to helping organizations turn their supply chains into a source of resilience and lasting business value. 


Devesh Mishra, General Manager and Chief Product Officer for SAP Supply Chain Management

Sign up for the SAP News Center newsletter to receive weekly news, stories, and highlights

*Gartner, Emerging Market Quadrant for Integrated Supply Chain AI Agents — Established Vendors, Tess Frenzel, Carlton Sapp, October 28, 2026.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. 
Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. 

What’s Holding Product Development Back? | SAP Engineering

What’s holding product development teams back? Disconnected systems and data silos.

Stephan Toebben, VP of Engineering for SAP Integrated Product Development, explains why connecting engineering, manufacturing, quality, and supplier processes end to end is essential to reducing delays and helping AI agents deliver real value.

Discover SAP Integrated Product Development: https://sap.to/6051BHWz73

#ProductDevelopment #PLM #Shorts

10 Questions Board Members Should Be Asking About Security and Compliance

Major security incidents can quickly affect enterprise value, operational continuity, regulatory standing, and reputation.

Securely access cloud services, meet compliance goals, and build customer confidence

As organizations become more dependent on connected infrastructure, cloud services, AI, and third parties, weaknesses in one part of the ecosystem can cascade across the business.

A Board is not expected to make technical decisions. Its role is to exercise informed oversight: set expectations, test whether accountability is clear, require evidence of resilience, and ensure that management integrates security and compliance into strategy, investment, operations, and crisis preparedness.

The following questions are designed for a Board of Directors and its relevant committees. They broaden the original cybersecurity focus to include compliance, privacy, data governance, third-party assurance, regulatory change, and demonstrable control effectiveness. 

1. Are security and compliance roles, decision rights, and escalation paths clearly defined?

Treating security or compliance as an isolated specialist function weakens governance. Accountability should extend across executive leadership, business operations, technology, legal, risk, privacy, internal audit, and the security organization. The Board should understand who owns material risks, what is the risk appetite who can accept them, and how significant incidents, control failures, vulnerabilities, or regulatory concerns reach the appropriate committee or full Board.

Evidence to request:

  • Does the security and compliance leadership team have direct access to executive management and the Board?
  • Are material risks escalated before they materialize into active incidents?
  • Do responsibilities cover prevention, detection, response, recovery, regulatory obligations, and assurance?

2. Are security and compliance built into strategy, investment, and transformation decisions?

Security and compliance should shape strategic choices from the beginning, not be added after commitments have been made. Major investments, cloud programs, acquisitions, new products, AI initiatives, and supplier selections should be assessed alongside security and compliance considerations. Early involvement helps identify structural risk while decisions are still practical to change. 

Evidence to request:

  • Which strategic decisions require a documented security and compliance review?
  • What risks or control requirements influenced the final decision?
  • Are funding and accountability aligned with the risk created by the initiative?

3. Do we have a transparent, decision-ready view of security and compliance risk?

Boards need more than technical activity reports. Management should translate important threats, vulnerabilities, control gaps, legal obligations, and business dependencies into clear enterprise risk scenarios. Reporting should show potential operational, financial, legal, and reputational consequences, as well as the residual risk that remains after controls are applied. 

Evidence to request:

  • Which scenarios could materially affect our strategic objectives?
  • How are likelihood, business impact, and control effectiveness assessed?
  • What residual risks have been accepted, by whom, and for how long? 

4. Is our compliance strategy prepared for regulatory change?

Compliance should be managed as a continuing capability rather than a periodic response to individual requirements. The Board should assess whether regulatory developments are monitored, interpreted consistently, assigned to accountable owners, and translated into controls, technology roadmaps, evidence, and reporting. This includes requirements affecting security, privacy, data sovereignty, operational resilience, AI, and third-party services. 

Evidence to request: 

  • Which emerging requirements could materially affect the business?
  • How quickly can new obligations be translated into operational controls? 
  • Can management demonstrate compliance consistently across regions, business units, and technology environments?

5. Are legacy systems and technical debt creating unacceptable security or compliance exposure?

Systems that are no longer fully supported can accumulate security weaknesses, limit monitoring, complicate recovery, and make compliance evidence harder to produce. The Board should view aging critical systems as an enterprise risk and investment issue, not just an IT lifecycle matter. Where modernization is delayed, management should document compensating controls, ownership, and a time-bound plan. 

Evidence to request: 

  • Which critical systems are out of support or approaching end of support?
  • What business processes and regulatory obligations depend on them?
  • What is the modernization plan and how is interim risk independently validated?

6. Are AI security, compliance, and governance embedded in the operating model?

AI introduces security, legal, privacy, data, ethical, and operational questions that require coordinated governance. Whether AI is developed internally or obtained from a third party, management should know what data it can access, how outputs are used, which decisions remain subject to human review, and how systems are tested and monitored as they change.

Evidence to request:

  • Who is accountable for approving and monitoring AI use cases?
  • What controls protect sensitive data and prevent unauthorized use?
  • How are legal, ethical, security, compliance, and human-rights considerations evaluated and evidenced?

7. Are identity and access management strong enough for our risk profile? 

Compromised credentials and excessive access can allow attackers or insiders to reach critical systems and data. Identity and access management should be treated as a business control, not simply an administrative technology process. Strong governance connects employee, contractor, third-party, and system identities to reliable business records and removes access when it is no longer required. 

Evidence to request: 

  • Are strong authentication and least-privilege access applied to critical systems?
  • How quickly is access changed when roles, employment, or supplier relationships change?
  • Are privileged and non-human identities monitored, reviewed, and time-limited where appropriate? 

8. Does our culture measurably reduce human and conduct risk?

Policies and technical controls depend on people making sound decisions. A mature program goes beyond annual training by addressing role-specific exposure, leadership behavior, phishing and social engineering, secure ways of working, speak-up channels, and consequences for repeated noncompliance. The Board should seek measurable evidence that behavior and risk are improving. 

Evidence to request: 

  • Which roles face the highest security and compliance exposure?
  • What do simulations, incidents, training results, and behavioral indicators show over time?
  • How visibly do leaders reinforce expected behavior and accountability?

9. Are third-party and supply-chain risks continuously assessed and governed? 

Security and compliance obligations do not stop at the enterprise boundary. Critical suppliers, cloud providers, software dependencies, advisers, and other partners can create operational, regulatory, data, concentration, and geopolitical exposure. Third-party risk should be integrated into enterprise risk management and monitored throughout the relationship, not treated as a one-time procurement exercise. 

Evidence to request: 

  • Which third parties are critical to operations, data, or regulatory obligations?
  • What independent evidence supports their security, compliance, and resilience claims?
  • How are concentration, subcontractor, geographic, and exit risks managed? 

10. Are we prepared to detect, contain, disclose, and recover from a major incident? 

Prevention alone is not enough. The Board should understand whether the organization can identify significant events early, contain their impact, make timely legal and regulatory decisions, communicate credibly, restore priority services, and learn from the event. Readiness should cover ransomware, account takeover, data compromise, fraud, third-party disruption, and other plausible business scenarios. 

Evidence to request: 

  • When were crisis, incident response, business continuity, and recovery plans last exercised together?
  • Are decision rights clear for regulatory disclosure, law enforcement, ransom demands, customer communication, and service restoration?
  • What gaps were found in recent exercises or incidents, and are remediation actions closed?

From reactive oversight to demonstrable resilience 

These 10 questions help a Board move the discussion from technical activity to governance, accountability, evidence, and business outcomes. Effective oversight requires an ongoing dialogue with management, constructive challenge of assumptions, and decisions that reflect the organization’s risk profile, regulatory obligations, and digital maturity.

Modernization can be an important governance lever when it improves standardization, transparency, control automation, resilience, and the ability to produce reliable compliance evidence. Responsibility, however, remains shared across leaders, business owners, technology teams, security, compliance, legal, risk, audit, employees, and critical partners. 

Board takeaway

Security and compliance are not separate from business strategy. They are essential to continuity, lawful operation, stakeholder trust, and long-term value protection. 


Marielle Ehrmann is chief security officer and a member of the Supervisory Board of SAP SE.

Sign up for SAP News Center news, stories, and highlights delivered straight to your inbox

Note: This piece has been adapted from the German article “Cybersicherheit – Zehn Leitfragen für den Aufsichtsrat” by original authors Dr. Friederike Rotsch and Sebastian Lange alongside Marielle Ehrmann.

Morgan Foods: AI That Helps Supply Chains Deliver | SAP Connect 2026

See how Morgan Foods uses SAP S/4HANA and SAP Integrated Business Planning to connect supply chain operations, improve visibility, and move from reactive planning to predictive decision-making.

At SAP Connect 2026, Morgan Foods shares how it manages a complex supply chain that supports hundreds of private-label products across multiple facilities. From soups and beans to aseptic products, the team coordinates forecasting, ingredients, production scheduling, warehousing, and distribution to keep products moving to grocery shelves every day.

The conversation explores how SAP S/4HANA and SAP Integrated Business Planning helped Morgan Foods move away from manual processes, silos, and spreadsheets. When demand for canned food surged in 2020, Morgan Foods had already built a connected SAP foundation that helped the business see its full supply chain, plan ahead, and continue providing high service levels to customers.
Morgan Foods also explains how SAP IBP helps the team plan for seasonal spikes, optimize factories and inventory, and respond faster to large customer requests.

What previously took three or four weeks can now be assessed in about five minutes. The discussion closes with practical advice for organizations beginning their AI journey: start with clean master data, strong business processes, documented ways of working, and people who provide the judgment and oversight that AI agents need.

Watch the full keynote. 👉 https://sap.to/6058BG4VHk
Watch all SAP Connect replays on demand. 👉https://sap.to/6059BG4VHZ

Chapters:
00:00 – Managing a complex food supply chain
00:24 – Morgan Foods’ product and operational footprint
00:52 – Moving from manual silos to SAP S/4HANA and SAP IBP
01:04 – Responding to demand spikes with a connected SAP foundation
01:43 – Planning ahead with SAP Integrated Business Planning
02:21 – Reducing customer response times from weeks to minutes
03:04 – Connectivity as the foundation for Autonomous Suite
03:21 – Moving from reactive to predictive supply chain planning
03:55 – Advice for organizations starting with AI
04:24 – Why people remain critical in AI-enabled supply chains
05:11 – Human oversight, judgment, and the future of supply chain

Follow us on social:
LinkedIn: https://sap.to/6050BG0v3M
Instagram: https://sap.to/6052BG0v3O
Facebook: https://sap.to/6053BG0v3P
Threads: https://sap.to/6054BG0v3u

About SAP:
As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://sap.to/6055BG0v3R

#SAPSupplyChain #SAPBusinessAI #SAPConnect2026

How Redwood Software Drives Seller Engagement with SAP Store | SAP Partner

See how Redwood Software uses SAP Store to create greater opportunity visibility, strengthen seller engagement, and support growth through co-selling with SAP.

Redwood Software helps organizations orchestrate the critical background processes that keep their businesses running. Its RunMyJobs solution helps customers automate and manage these processes, with deep integrations across SAP solutions including SAP Business Suite, SAP Business Technology Platform, and SAP Business Data Cloud. Redwood describes SAP Store as a launchpad that has helped the company accelerate and grow its business with SAP over the past three years.

For Redwood, SAP Store also serves as a system of record for opportunities and closed deals, creating greater visibility for sellers. That visibility can translate into stronger engagement as Redwood and SAP work together on co-selling opportunities. Looking ahead, Redwood also sees value in connecting the predictable, deterministic processes businesses depend on with the goal-oriented processes enabled by AI agents.

Redwood’s advice to other partners is clear: learn how to use SAP Store as part of your go-to-market motion. Beyond marketplace presence, it can provide a platform for communication, reference, and greater seller visibility.

• Explore RunMyJobs by Redwood on SAP Store:
https://sap.to/6052BGvj36
• For SAP Partners, learn more about selling through SAP Store:
• Marketplace 101 for partners: https://sap.to/6053BGvj3B
Onboarding Partner Solutions to SAP Store with SAP Solution Hub: https://sap.to/6054BGvj38

Follow us on social:
LinkedIn: https://sap.to/6055BGvj3D
Instagram: https://sap.to/6056BGvj3E
Facebook: https://sap.to/6057BGvj31
Threads: https://sap.to/6059BGvj3H

About SAP:
As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://sap.to/6051BGvj3J

#SAP #SAPStore #SAPPartner

Sometimes the job of the FBI is not only to track criminals, but also to collect evidence, documents, photos, and witness statements.

AI’s Finance Challenge: Managing Token Spend Without Slowing Innovation

AI token spend is emerging as a new enterprise resource—one that finance must learn to forecast, allocate, and optimize against the value it delivers.

Generative AI is moving quickly from experimentation to essential infrastructure. Employees have woven it into routine daily tasks, and teams and applications are leaning on it more heavily every quarter. That growth comes with a new cost category finance wasn’t designed to handle: AI token consumption.

When AI is writing code and powering agents, token consumption can outpace traditional planning processes. Finance leaders suddenly find themselves in unfamiliar territory, needing to bring discipline to AI spending without becoming the function that kills adoption. Getting the balance right means treating tokens as an enterprise resource that must generate returns commensurate with its cost.

At SAP, we have been working through these questions firsthand. Here’s what we’ve learned from building, testing, and adjusting that framework.

Accelerate outcomes with context-aware agents and assistants that know your work and your business

You can’t manage what you can’t see

Most finance leaders wouldn’t manage a major cost category from a single line item, yet that’s exactly where companies start with AI. Total spend matters, but it won’t tell you which teams, workloads, or usage patterns are driving that spend, or whether the consumption is actually producing useful outcomes.

Getting that visibility requires real collaboration across commercial, engineering, finance, and product teams. Finance brings the forecasting questions and accountability framework. Other functions bring the operational context that makes the numbers meaningful.

In our experience, repeated forecasting cycles generally improved our financial models as we layered in more operational detail around usage. The broader lesson: when a cost category is new and fast-moving, don’t wait for precision before acting. Start with enough transparency to make better decisions, then sharpen the model as patterns emerge.

Someone has to own it

Our most consequential insight was philosophical rather than financial. We learned that visibility alone isn’t enough and that consumption needs an owner.

A centralized AI budget makes early experimentation easy, but it also disconnects the people spending tokens from any financial accountability for them. As AI becomes more deeply embedded in business processes, that model breaks down.

This isn’t an argument for immediately charging back every LLM call with forensic accuracy. It’s an argument for managing AI consumption the same way companies manage other enterprise resources such as software, external services, and labor. Give decision-makers a clear picture of what their teams are consuming and what outcomes that consumption is expected to produce.

At SAP, allocating token costs to business areas has shifted the conversation from “How much are we spending?” to “What are we getting for this?” and “Is this the right place to invest more?” That’s a healthier conversation.

Token spend is not a technology line item. It is a strategic and operational investment decision. The goal is to make AI spending intentional, not just cheap.

Cost per token is the wrong scorecard

A large AI bill draws attention, but optimizing purely on cost can lead to exactly the wrong decisions.

The more useful question is the relationship between consumption and business impact. An AI tool that meaningfully accelerates software development, reduces repetitive work, or improves customer service will carry real token costs. Cutting that usage simply because the line item is visible could destroy more value than it saves.

We saw this firsthand. After rolling out AI developer tools at SAP, we recorded a mid-double-digit percentage increase in pull-request merge rates, a clear signal that development work was moving faster. The consumption was worth it.

Finance needs a paired view: cost metrics alongside value metrics. Governance without that view risks optimizing for cost at the expense of value creation.

Guardrails should target waste, not adoption

As usage scales, controls become necessary, but the right controls are surgical, not sweeping. When we examined consumption patterns in detail, three root causes of disproportionate spend emerged: power-user and automated-agent concentration, model misalignment, and tool proliferation.

Those are the areas where guardrails earn their keep. Controls matter because they focus on the sources of avoidable spend rather than putting a blanket brake on usage. At SAP, our response centered on three levers: token capping to prevent runaway consumption, model routing to better match capability and cost to the task, and tool rationalization to eliminate redundancy and concentrate investment where utilization justified it. That work helped contain a triple-digit-million-dollar financial risk while keeping adoption moving forward.

The principle is simple: remove waste, preserve productive demand.

From cost control to value governance

AI isn’t going to pause for the next planning cycle. Its capabilities, usage patterns, and economics will keep shifting, and the governance model around it needs to keep pace.

The work is not complete. The next step is to embed these practices into regular planning and reporting, assign clearer ownership, improve allocation, and build forecasting capabilities that can anticipate where costs are heading before they arrive.

Companies that do this well will still have an AI bill to pay. But they will have the transparency and accountability to tell the difference between consumption that is creating value and consumption that isn’t and direct investment accordingly.


Lukas Deutsch is chief controlling officer at SAP.
David Imbert is chief marketing officer for SAP Financial Management.

Subscribe to the SAP News Center for the latest SAP news each week

Kimi Antonelli: The Call That Changed Everything | Significant Figures

One phone call changed his career. One season taught him how to carry it.

Kimi Antonelli talks honestly about the day everything changed, a call into Toto’s office at Silverstone, the phone call with @MercedesAMGF1 that followed, and the tough European season that tested him, on this episode of Significant Figures.

Watch the full episode here: https://sap.to/6052B1rlDn

George Russell: “The Dream was to Reach Formula 1.” | Significant Figures

For George Russell, arriving at Formula 1 was just the beginning.

In the latest episode of Significant Figures, the @MercedesAMGF1 driver opens up on why he can’t stand still and why every goal reached only sharpens his focus on the next one.

Watch the full episode here: https://www.youtube.com/watch?v=S58Uqz4mDRw

Build Things That Matter. Register Now. | SAP TechEd 2026

Join SAP’s premier technical event to build what matters. Get hands-on with SAP’s end-to-end platform, learning how to create AI-powered systems that turn intent into execution.

What you can expect:
– Learn how to build AI that moves from intent to execution.
– Discover how to create scalable, secure, and extensible apps.
– Connect with a global developer community to accelerate your impact.

Join us October 27–29, 2026 in Berlin or virtually: https://sap.to/6054BDQ9jr

Follow us on social:
LinkedIn: https://sap.to/6055BDQ9jT
Instagram: https://sap.to/6056BDQ9jp
Facebook: https://sap.to/6057BDQ9jV
Threads: https://sap.to/6058BDQ9jn

About SAP:
As a global leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit: https://sap.to/6059BDQ9jX

#SAPTechEd

How to stand out on digital platforms 🌟

On digital marketplaces, everyone looks the same. Kyle Milan breaks down how B2B suppliers can rise above the competition through sponsored listings and profile optimization, because at the end of the day it’s all about eyes and attention.

Learn more about SAP Business Network and sign up for a supplier account today: https://www.sap.com/products/business-network/suppliers/overview.html

Previous Next
Close
Test Caption
Test Description goes like this