Automating Business Processes

Enterprises want the speed and intelligence of AI agents and automation, but never at the expense of security or control. Auditability remains essential in making that possible. Organizations need to verify what happened, when it happened, and why, and this level of transparency has shaped how we’ve built trust with enterprises over many years. Protecting sensitive information is equally critical as AI models enter more workflows. Model governance helps safeguard PII, enforce regional and data-handling requirements, and log every model interaction so organizations can innovate without compromising the data they are responsible for. Underpinning all of this is that customers need to know they can trust the companies that platforms and tools they rely on to get work done across their businesses. Governance and security are what allow enterprises to move forward with confidence, and they remain the foundation of the trust we’ve earned and continue to protect as the landscape of agentic automation evolves.

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗦𝗔𝗣 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗧𝗼𝗼𝗹𝘀: 𝗕𝗔𝗗𝗜, 𝗕𝗔𝗣𝗜, 𝗮𝗻𝗱 𝗨𝘀𝗲𝗿 𝗘𝘅𝗶𝘁𝘀 💡 In every SAP implementation, no matter how vast the standard functionalities are, some degree of customization is often necessary to meet specific business requirements. That’s where tools come in Play : 📌 BADI (Business Add-Ins), 📌 BAPI (Business Application Programming Interface), 📌 User Exits Let’s explore what they are and how they work, with a real-world example from an SAP EAM (Enterprise Asset Management) project. 𝗕𝗔𝗗𝗜-- is an enhancement technique used to add custom functionality to standard SAP code without modifying the original SAP objects. It allows for multiple implementations, which makes it flexible and reusable across different projects. 𝙴̲𝚡̲𝚊̲𝚖̲𝚙̲𝚕̲𝚎̲ ̲𝚒̲𝚗̲ ̲𝚂̲𝙰̲𝙿̲ ̲𝙴̲𝙰̲𝙼̲:̲ In a project involving maintenance order processing, the client wanted to send an automated email to maintenance supervisors when the status of an order changes to "Completed." There’s no standard feature for this in SAP, so we implemented a BADI to trigger the email notification based on the order status update in transaction IW32 (Change Maintenance Order). 🔹 BADI Used: 𝘞𝘖𝘙𝘒𝘖𝘙𝘋𝘌𝘙_𝘜𝘗𝘋𝘈𝘛𝘌 🔹 T-Code: IW32 🔹 Functionality: Send email notification when the order is marked as "Completed." 𝗕𝗔𝗣𝗜 is a standardized programming interface that allows external applications to interact with SAP processes. It is often used to create or update SAP data programmatically from third-party systems. 𝙴̲𝚡̲𝚊̲𝚖̲𝚙̲𝚕̲𝚎̲ ̲𝚒̲𝚗̲ ̲𝚂̲𝙰̲𝙿̲ ̲𝙴̲𝙰̲𝙼̲:̲ In another SAP EAM project, the client used an external system to schedule maintenance tasks, but the task execution had to be tracked in SAP. We used BAPI to interface the external system with SAP, allowing automated creation of maintenance orders based on schedules generated externally. 🔹 BAPI Used: 𝘉𝘈𝘗𝘐_𝘈𝘓𝘔_𝘖𝘙𝘋𝘌𝘙_𝘔𝘈𝘐𝘕𝘛𝘈𝘐𝘕  🔹 T-Code: IW31 (Create Maintenance Order) 🔹 Functionality: Automatically create maintenance orders in SAP based on external system data. 𝗨𝘀𝗲𝗿 𝗘𝘅𝗶𝘁𝘀 are predefined enhancement points provided by SAP, where you can insert custom code to enhance or modify the behavior of standard SAP processes. Unlike BADI, User Exits generally allow for only one implementation. 𝙴̲𝚡̲𝚊̲𝚖̲𝚙̲𝚕̲𝚎̲ ̲𝚒̲𝚗̲ ̲𝚂̲𝙰̲𝙿̲ ̲𝙴̲𝙰̲𝙼̲:̲ During an EAM project, the client required additional checks before allowing the creation of a maintenance order (e.g., ensuring the equipment's warranty status). The standard system did not provide this functionality, so we utilized a User Exit to insert the necessary validation before creating a new order. 🔹 User Exit Used: 𝘐𝘞𝘖10006 (Exit for additional checks when creating a order) 🔹 T-Code: IW31 🔹 Functionality: Prevent order creation if the equipment is under warranty, directing users to specific actions. #SAP #EAM #BAPI #BADI #EXIT

𝑷𝒓𝒊𝒗𝒂𝒄𝒚 𝒄𝒐𝒎𝒑𝒍𝒊𝒂𝒏𝒄𝒆 𝒊𝒔 𝒃𝒆𝒄𝒐𝒎𝒊𝒏𝒈 𝒉𝒂𝒓𝒅𝒆𝒓 𝒕𝒐 𝒎𝒂𝒏𝒂𝒈𝒆, 𝒏𝒐𝒕 𝒃𝒆𝒄𝒂𝒖𝒔𝒆 𝒓𝒆𝒈𝒖𝒍𝒂𝒕𝒊𝒐𝒏𝒔 𝒂𝒓𝒆 𝒖𝒏𝒄𝒍𝒆𝒂𝒓, 𝒃𝒖𝒕 𝒃𝒆𝒄𝒂𝒖𝒔𝒆 𝒐𝒑𝒆𝒓𝒂𝒕𝒊𝒐𝒏𝒂𝒍𝒊𝒛𝒊𝒏𝒈 𝒕𝒉𝒆𝒎 𝒊𝒔. This ISO/IEC 27701 Implementation Guide provides a structured and practical walkthrough for building a Privacy Information Management System (PIMS) on top of ISO/IEC 27001, with clear links to GDPR and other global privacy regulations 𝐖𝐡𝐚𝐭 𝐦𝐚𝐤𝐞𝐬 𝐭𝐡𝐢𝐬 𝐠𝐮𝐢𝐝𝐞 𝐯𝐚𝐥𝐮𝐚𝐛𝐥𝐞 𝐢𝐬 𝐢𝐭𝐬 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐩𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞: -->It connects privacy governance, risk management, and operational controls --> It clarifies controller vs processor responsibilities --> It translates legal obligations into auditable processes and evidence --> It shows how privacy fits into existing ISMS structures rather than standing apart For organizations already working with ISO/IEC 27001, this is a logical next step to move from security compliance to accountable privacy management. For others, it highlights why privacy cannot remain a legal or documentation exercise only. Worth reading for CISOs, DPOs, risk managers, and anyone involved in turning privacy requirements into something that actually works in day-to-day operations. Thank you MoS & ETCISO | Khushi Malhotra | Niranjan V | Soumik Ghosh | Muqbil Ahmar #ISO27701 #PrivacyManagement #GDPR #DataProtection #GRC #InformationSecurity #PIMS

I started my journey as a hotel management student. I knew the challenges of the industry and the missed opportunities. After stepping down as a Director at Barclays, I began building Amanstra Consulting. I wanted to tap into the hospitality sector again That idea came alive when I met Sowmya. She’s someone who lives the “give first” philosophy and our collaboration started with a conversation. As I shared how we’ve used data analytics and AI to improve operations in hospitals, banks, and factories. She asked a simple but powerful question: “Can you apply this to restaurants and hotels?” That one question brought back my roots in hospitality. Most restaurants look at data after something has already happened. Footfalls dropped? Let’s analyze last month’s numbers. Inventory piled up? Let’s check what went wrong. Restaurants today are at the mercy of aggregator platforms. High commissions. Limited access to their own customer data. Minimal control over brand experience. We want to flip that narrative. Together, Sowmya and I are building a model where restaurants can: 1) Use their existing POS, feedback, reservations and inventory data 2) Get forward looking insights, not just reports 3) Improve footfall, marketing, and customer retention 4) Regain control over customer relationships 5) Reduce dependency on aggregators We’re now piloting this model with restaurant owners They can co-create the future of hospitality Powered by data, insight and independence. If you’re in the hospitality space and want to explore this shift, let’s talk. The right question already sparked this journey. Now we’re ready for the right partners. #Hospitality #DataDriven #Restauranttech #AI #Customerexperience

Waiting Two Weeks for Quotes is Hurting Your Business and the channel! As I wander around the various countries and discuss efficiency and RevOps issues with executive leadership at Vendors, Distributors and SPs, I am aghast that some distributors are taking up to 2 weeks to get a quote out the door! 🤯 How is this even viewed as normal???? When I heard this, I was like you can’t be f$%king serious!? When distributors take this long to deliver quotes to their partners, it stalls decision-making, delays projects, and frustrates customers and ultimately harms your business's scalability and reputation. Same-day quotes (at the minimum) should be the norm! In today's digital age, it's entirely reasonable to expect same-day quotes, even for complex requests. How do achieve fast turn arounds quickly? Adopt Automated Quoting Tools - Implement platforms like iasset.com (no such thing as a free post 😉) that streamline the quoting process by integrating with your existing systems, reducing manual input and errors. Improve Data Management - Ensure all relevant data is easily accessible and updated in real-time to facilitate quick quote generation. Collaborate with IT - Work closely with your IT department to ensure seamless integration of the CPQ into the ERP and the vendors. A real-world example from my Distribution Central days… We had Avaya as a vendor, they have very, very complex quotes for their Call Centre platform and my competitor at that time (who I won’t name to shield the guilty but DM me if you want to name names 😂) would take more than 2 weeks to get the customer the localised quote. Distribution Central would quote that in less than fifteen minutes. That’s right 1,5 minutes So where do you think the business went every time? It's time for distributors to prioritise efficiency and embrace modern solutions for quicker quote turnarounds. The channel waits for no one, and those who can deliver fast, accurate quotes will have a significant competitive edge. #revops #cpq #productlifecycles #automation [And just in case the image doesn't work for you in your country, it's just me hitting my head against a brick wall]

Focusing on AI’s hype might cost your company millions… (Here’s what you’re overlooking) Every week, new AI tools grab attention—whether it’s copilot assistants or image generators. While helpful, these often overshadow the true economic driver for most companies: AI automation. AI automation uses LLM-powered solutions to handle tedious, knowledge-rich back-office tasks that drain resources. It may not be as eye-catching as image or video generation, but it’s where real enterprise value will be created in the near term. Consider ChatGPT: at its core, there is a large language model (LLM) like GPT-3 or GPT-4, designed to be a helpful assistant. However, these same models can be fine-tuned to perform a variety of tasks, from translating text to routing emails, extracting data, and more. The key is their versatility. By leveraging custom LLMs for complex automations, you unlock possibilities that weren’t possible before. Tasks like looking up information, routing data, extracting insights, and answering basic questions can all be automated using LLMs, freeing up employees and generating ROI on your GenAI investment. Starting with internal process automation is a smart way to build AI capabilities, resolve issues, and track ROI before external deployment. As infrastructure becomes easier to manage and costs decrease, the potential for AI automation continues to grow. For business leaders, identifying bottlenecks that are tedious for employees and prone to errors is the first step. Then, apply LLMs and AI solutions to streamline these operations. Remember, LLMs go beyond text—they can be used in voice, image recognition, and more. For example, Ushur is using LLMs to extract information from medical documents and feed it into backend systems efficiently—a task that was historically difficult for traditional AI systems. (Link in comments) In closing, while flashy AI demos capture attention, real productivity gains come from automating tedious tasks. This is a straightforward way to see returns on your GenAI investment and justify it to your executive team.

🔗 SAP Datasphere & Apache Kafka: The Future of ERP Integration SAP ERP is the backbone of enterprises worldwide, but integrating it with other platforms, databases, and APIs is a major challenge. 🚀 This is where SAP Datasphere and Apache Kafka come in—together, they create a scalable, real-time, and open data fabric for seamless ERP connectivity. Key Takeaways: ✅ SAP Datasphere – A next-gen cloud-based data platform for SAP ERP integration ✅ Apache Kafka – A real-time data streaming powerhouse for scalable, event-driven architectures ✅ Hybrid & Multi-Cloud Ready – Connect on-prem SAP ECC & S/4HANA with cloud-native applications ✅ Seamless Data Flow – Synchronize real-time, batch, and request-response interfaces Why Apache Kafka for SAP Integration? • Real-time event streaming for operational & analytical workloads • Decoupling systems for better flexibility and scalability • Transaction support & exactly-once semantics for ERP-critical processes • Built-in integration with SAP Datasphere, Snowflake, Databricks, and other modern platforms Confluent & SAP: A Strategic Partnership Confluent is now available in the SAP Store, offering fully managed Kafka-powered data streaming. Enterprises can now build event-driven architectures for ERP modernization, just-in-time operations, predictive analytics, and more. 📌 How does your organization handle SAP integration today? Are you exploring real-time event-driven architectures? Let’s discuss in the comments! 🔗 Read the full blog post here: https://lnkd.in/eSd-ZKAY #DataStreaming #SAP #Kafka #S4HANA #ERPIntegration #EventDriven #Cloud #RealTimeData #ApacheKafka #Confluent

MSME Digital Loans: A Game Changer for Small Businesses Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in economic growth, but access to timely credit has always been a challenge. Traditional lending processes involve extensive documentation, long approval times, and strict collateral requirements. However, digital lending has revolutionized MSME financing by offering quick, hassle-free, and collateral-free loans. What Are MSME Digital Loans? MSME digital loans are financial products offered through digital platforms, fintech companies, and banks using technology-driven processes. These loans leverage data analytics, artificial intelligence, and automation to assess creditworthiness, reducing dependency on traditional credit scores. Key Benefits of MSME Digital Loans 1. Quick Approval & Disbursal – With AI-powered credit assessment, digital loans can be approved within hours, compared to weeks in traditional banking. 2. Minimal Documentation – MSMEs can apply using Aadhaar, PAN, and GST details, avoiding cumbersome paperwork. 3. Collateral-Free Loans – Many digital lenders provide unsecured loans, helping small businesses without significant assets. 4. Flexible Loan Amounts & Tenure – MSMEs can access customized loan options ranging from ₹50,000 to ₹5 crores, with repayment tenures suited to their cash flow. 5. Enhanced Financial Inclusion – Digital loans extend credit to underserved businesses, including those with limited credit history. Challenges & The Way Forward While digital lending boosts MSME financing, risks like data privacy concerns, high interest rates, and regulatory challenges need attention. The RBI has introduced guidelines to regulate digital lenders, ensuring transparency and borrower protection. With increasing fintech adoption, MSME digital loans will continue to drive financial inclusion, enabling small businesses to grow and contribute to the economy effectively. We at State Bank of India (SBI) developed Digital Business Rule Engine for MSME loans upto Rs 5 cr, which uses the informations available on various Digital Public Infrastructure platforms and other data points in the ecosystem. And are able to deliver GO/NO-GO decision in 30-40 minutes, along with the lendable amount. Happy to share that we at SBI have crossed one lac loan sanctions using this Digital tool in the last one year. Aiming to triple the pace in the coming months. #MSME #DIGITALSMSELOANS

Yesterday I posted a case study on how we reduced a client's time to contract and invoice by 30% and saved them 5-7 hours per week. Here's exactly how: After posting this yesterday, I'm receiving a lot of messages asking how we did it. I thought I'd make a post about this. Here's exactly how we did it: First, we mapped out the process. Before working with us, the company relied on a fragmented and unreliable system. Their order-taking, contracting, and invoicing processes lacked automation, leading to delays, errors, and a poor experience for both their team and clients. Then we optimized it. We designed a fully integrated workflow that begins with a Typeform order form, which feeds directly into Monday and Airtable to manage requests, generate contracts, and track invoices with a Softr interface for easy access to order updates and relevant documents. Then we implemented. The new system helped the sales team save approximately 5-7 hours per week by streamlining client intake and ensuring name cohesion across tools. It also reduced the time it took to send invoices and contracts by about 30%. Finally, we optimized again after implementation. Key features include automated contract and invoice generation, real-time order tracking, and a client-facing portal built with Softr. All of which improved efficiency, accuracy, and the overall client experience. The result? A centralized, user-friendly experience that eliminated manual steps and improved operational efficiency. The takeaway: Don't just automate. Optimize first, then implement, then optimize again based on real usage. Follow me Luke Pierce for more automation case studies like this.

"Stop building privacy compliance programs. Start building privacy operations systems." Here's a pattern I'm seeing with alarming frequency: Companies react to each new privacy law by creating another siloed compliance program, another checklist, another set of disconnected processes. This approach is collapsing under its own weight. With 19 state laws (and counting), treating each as a separate compliance exercise is both unsustainable and ineffective. What's the alternative? Privacy operations. Privacy operations means: Building ONE centralized system that maps all data flows Creating scalable processes that work across regulatory requirements Embedding privacy controls into everyday business functions Measuring operational effectiveness, not just document completeness I recently worked with a midsize tech co. that scrapped their regulation-by-regulation approach. Instead, they invested in core privacy operations infrastructure. Result? Reductions in compliance costs. Faster responses to regulatory changes. And significantly reduced risk. Who's made the shift from compliance programs to operations systems? I'd love to hear what's working. 💬 #PrivacyOperations #DataGovernance #PrivacyTransformation #ComplianceStrategy