Operations Consulting Services

Operating model transformation is now a necessity for sustained organizational health and performance, not a one-time fix. Especially considering changes brought on by AI, this means organizations should build redesign readiness as a capability, not just as a reactive measure.   Our new research identifies nine essential rules to help leaders redesign their operating model with value at the core—and flip the odds of success.   The data is clear. Organizations that follow these practices can see a significant boost in outcomes: 97% of redesigns that applied all nine rules met success, compared to just 29% that didn’t apply any.   These rules highlight the importance of:    - Leadership alignment: It’s not just about writing it down; it’s about living it  - Mindset shifts: Change perspectives before changing actions - A people-first approach: People drive the redesign, not the other way around   Discover the redesign practices that can deliver measurable results and align your organization to value: https://mck.co/4lsaANA   It was a privilege to collaborate on this work with my colleagues, Deepak Mahadevan, Elizabeth Mygatt, J.R. Maxwell, Olli Salo, and Tristan Allen. I’m proud to contribute to this latest thinking on our Organize to Value approach, which helps leaders navigate complexity through operating model transformation.   #OrganizeToValue #Transformation #Performance

𝗛𝗼𝘄 𝗘𝗔 𝗗𝗿𝗶𝘃𝗲𝘀 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: 𝟯 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝗳𝗼𝗿 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 Operational inefficiencies—legacy systems, fragmented processes, and siloed teams— challenge large enterprises. They 𝗱𝗿𝗶𝘃𝗲 𝘂𝗽 𝗰𝗼𝘀𝘁𝘀, 𝘀𝗹𝗼𝘄 𝗱𝗼𝘄𝗻 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲, 𝗮𝗻𝗱 𝘀𝘁𝗶𝗳𝗹𝗲 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻. Enterprise Architecture (EA) provides a roadmap to tackle inefficiencies head-on. With a holistic view of systems, processes, and technologies, EA can 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗯𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸𝘀, 𝗿𝗲𝗱𝘂𝗰𝗲 𝗿𝗲𝗱𝘂𝗻𝗱𝗮𝗻𝗰𝘆, 𝗮𝗻𝗱 𝗲𝗻𝘀𝘂𝗿𝗲 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 with business objectives. How can organizations leverage EA to transform operational efficiency into a competitive advantage? Here are 𝟯 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 𝘁𝗼 𝘀𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 and boost performance: 𝟭 | 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻 Business Architecture identifies inefficiencies in workflows to simplify, standardize, and automate processes. Eliminating redundancies improves speed and reduces human error. 𝙏𝙞𝙥: Map out current processes in detail and involve cross-functional teams to spot inefficiencies that might be invisible to a single department. 𝟮 | 𝗕𝗿𝗲𝗮𝗸 𝗗𝗼𝘄𝗻 𝗗𝗮𝘁𝗮 𝗦𝗶𝗹𝗼𝘀 𝗳𝗼𝗿 𝗦𝗺𝗮𝗿𝘁𝗲𝗿 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 Data trapped in silos creates blind spots. EA promotes data consolidation to create a unified operational view, driving smarter decision-making. Unified data enables real-time insights and better collaboration across departments. 𝙏𝙞𝙥: Align data consolidation projects with business goals, ensuring measurable outcomes like faster decision-making or improved customer experience. 𝟯 | 𝗠𝗼𝗱𝗲𝗿𝗻𝗶𝘇𝗲 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝘁𝗼 𝗨𝗻𝗹𝗼𝗰𝗸 𝗔𝗴𝗶𝗹𝗶𝘁𝘆 Legacy systems are often the root of inefficiency. EA can provide a roadmap to migrate to modern, scalable solutions like cloud-based platforms. Modern technology supports agility and scalability, reducing maintenance costs and improving system performance. 𝙏𝙞𝙥: Hybrid approaches allow technology upgrades that deliver quick wins while aligning with long-term business objectives. 𝗪𝗿𝗮𝗽-𝗨𝗽: Enterprise Architecture can transform operational inefficiencies into opportunities for growth. By optimizing processes, unifying data, and modernizing technology, EA reduces costs and enhances performance and innovation. Start small, focus on measurable outcomes, and let EA guide your journey to operational excellence. _ 👍 Like if you enjoyed this. ♻️ Repost for your network.  ➕ Follow Kevin Donovan 🔔 _ 🚀 Join Architects' Hub!  Sign up for our newsletter. Connect with a community that gets it. Improve skills, meet peers, and elevate your career! Subscribe 👉 https://lnkd.in/dgmQqfu2 Photo by Amir Balam #OperationalEfficiency #EnterpriseArchitecture #ProcessOptimization #DataConsolidation #DigitalTransformation #InnovationStrategies

How Data and Analytics Leaders Structure Delivery Models to Scale Operations: Data and analytics leaders are under increasing pressure to meet the needs of business units and demonstrate the value of their initiatives. To address this demand, leading organizations are empowering business units to design, develop and manage their solutions with D&A’s guidance. Key Findings 🔵 Gartner’s CDAO Agenda Surveys for 2024 and 2025 reveal that chief data and analytics officers (CDAOs) are increasingly expected to support business partners and clarify how data and analytics (D&A) can help achieve business goals, which is putting pressure on their delivery models. 🔵 Over 200 Gartner client interviews show that innovative D&A leaders successfully scale user-centric solutions by connecting D&A and business teams, empowering users to create and manage their own D&A solutions for better decision making. Recommendations D&A leaders trying to scale their operations can adapt their delivery models by: 🔵 Integrating business units into their delivery process and aligning efforts with business outcomes to ensure user-centric solutions. 🔵 Providing ongoing coaching to business units to enhance their D&A maturity, enabling them to develop their own solutions and create innovative ways to use data. Are you establishing or updating your D&A delivery model? That includes the organizational structure for data and analytics, the specific skills and competencies required, the sequence and funding of delivery, and a roadmap for developing new capabilities and technology. I've just contributed to this brand new research lead by Richa Jha, Sarah Turkaly and Cameron Roche, along with valued contributions from Dalia Naguib, Brian Foster, Nate Novosel, Jorgen Heizenberg, David Pidsley, Kurt Shlegel and Anna Toncheva. How Data and Analytics Leaders Structure Delivery Models to Scale Operations ( 🔗 link in comments, for Gartner subscribers ) [Published 24 March 2025) #DataAnalytics #Data #Analytics #CDAO #CDO #DataProduct

Sustainable Supply Chain Cheat Sheet 🌎 Supply chains play a central role in environmental, social and governance performance, beyond operational efficiency. Strategic alignment with ESG priorities, materiality assessments and science based targets form the foundation. Cross functional governance ensures sustainability is integrated across operations. Lifecycle integration addresses sustainability at every stage. From circular design and responsible sourcing to low carbon logistics and take back schemes, each phase offers clear opportunities. Core practices include supplier codes of conduct, digital traceability, climate scenario analysis and internal carbon pricing. These tools reshape procurement, investment and risk strategies. Reference frameworks such as ISO 20400, GHG Protocol, SA8000 and ISSB standards support implementation across environmental, social and reporting areas. Metrics span the full value chain, including emissions intensity, landfill diversion, water consumption, diverse supplier spend and product performance at end of life. Technology enables real time monitoring and innovation. Digital passports, AI tools, geospatial tracking and cloud platforms are enhancing transparency and impact. This cheat sheet consolidates key principles and actions for sustainable supply chain management, aligned with leading global standards and practical application. #sustainability #business #sustainable #esg #supplychain

"𝗜𝗻𝗷𝗲𝗰𝘁𝗶𝗼𝗻 𝗠𝗼𝗹𝗱𝗶𝗻𝗴: 𝗘𝗻𝗱-𝘁𝗼-𝗘𝗻𝗱 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗠𝗮𝗽𝗽𝗶𝗻𝗴" As an injection molding professional, you know that optimizing your process is key to delivering high-quality products on time and within budget. But have you ever stopped to think about the entire process, from raw material to final dispatch ? I have created a comprehensive table that breaks down the injection molding process into 10 critical stages. For each stage, I've outlined key activities and checks, purpose and objectives, tools and documents used, common defects or risks, and best practices and recommendations. 𝗧𝗵𝗶𝘀 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗺𝗮𝗽𝗽𝗶𝗻𝗴 𝘄𝗶𝗹𝗹 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂: - Identify bottlenecks and areas for improvement - Optimize your process for efficiency and quality - Reduce defects and risks - Improve customer satisfaction 𝗙𝗼𝘂𝗻𝗱 𝘁𝗵𝗶𝘀 𝗵𝗲𝗹𝗽𝗳𝘂𝗹? 𝗦𝗵𝗮𝗿𝗲 𝗶𝘁 𝘄𝗶𝘁𝗵 𝘆𝗼𝘂𝗿 𝗰𝗼𝗻𝘁𝗮𝗰𝘁𝘀 𝘁𝗼 𝗵𝗲𝗹𝗽 𝘁𝗵𝗲𝗺 𝗯𝗼𝗼𝘀𝘁 𝘁𝗵𝗲𝗶𝗿 𝘀𝗸𝗶𝗹𝗹𝘀 ! 𝗙𝗼𝗹𝗹𝗼𝘄 𝗺𝗲 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝗳𝘂𝗹 𝗽𝗼𝘀𝘁𝘀 𝗼𝗻 𝗾𝘂𝗮𝗹𝗶𝘁𝘆, 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴, 𝗮𝗻𝗱 𝗺𝗼𝗿𝗲 !

Many thought leaders emphasize driving transformations through the lens of people, which I wholeheartedly agree with. People remain the heart of how an organization operates. How do we achieve this? One often overlooked aspect is high-quality procedure documentation.   Procedures are detailed instructions for completing tasks. They are crucial because they: - Improve productivity by eliminating the need to decipher unclear documentation - Break down silos, enhancing team collaboration - Facilitate scalability and growth by simplifying onboarding of new employees - Are the key to consistent and great customer experiences - Manage risks and ensure regulatory compliance - Foster problem-solving and continuous improvement   I’ve seen many organizations struggle with maintaining quality procedure documentation. In one of my consulting projects, we cleaned up a disorganized repository that was a massive pain point for the company.   What’s the key to success? Defining a consistent structure aligned with the business context. The best practice is to organize procedure documentation according to your complete inventory of processes using the Process Inventory framework. This approach offers several benefits: - Scope Definition: Clearly defined boundaries ensure no overlaps in documentation. - Ownership: Assigning a Process Owner for each process ensures accountability for creating and maintaining high-quality documentation. - Employee Alignment: Provides clarity on which employees execute processes, making it easier to close knowledge gaps. - Risk Management Alignment: Helps the risk organization verify that procedures provide the right risk and compliance controls.   This is only possible if an organization inventories every process they perform through the Process Inventory framework. To learn more about this framework, check out my book 'Digital Transformation Success' https://a.co/d/bmYf0oG   #Transformation #PeopleFirst. #ProcessInventory #BusinessScalability #ContinuousImprovement

Reducing Steel Logistics Costs in India: Strategic Framework Logistics accounts for 10–20% of steel’s delivered cost and up to 28% of factory cost. Reducing this burden is key to improving competitiveness. A multi-pronged strategy involving infrastructure, modal shifts, digital tools, and policy reforms can yield significant savings. 1. Shift to Rail, Water, and Pipelines Road transport, though flexible, is 2–3x costlier. Rail movement via rakes and sidings can cut costs by 20–30%. Inland waterways (e.g., Ganga, Brahmaputra) save 40–60% for long-haul bulk cargo. Slurry pipelines, at Rs. 80–100/tonne for 250 km, are vastly cheaper than rail or road and must be expanded for inland plants. 2. Leverage PFTs and DFCs Private Freight Terminals reduce first/last-mile costs. Eastern and Western DFCs offer faster, reliable movement. Time-tabled rakes and rake-sharing improve predictability and lower costs. 3. Improve First & Last-Mile Efficiency Rail sidings, Ro-Ro services, and containerization reduce handling loss and costs. Better road access to ports via PPPs boosts multimodal efficiency. 4. Upgrade Infrastructure Developing dedicated rail/road corridors and multimodal logistics parks under Bharatmala and Sagarmala enhances connectivity. Coastal hubs at Vizag, Kandla, Paradip allow direct port loading, avoiding double handling. 5. Adopt Technology Use of Transport Management Systems (TMS), GPS tracking, and AI-based route optimization improves asset utilization and reduces fuel use. Automation in loading/unloading cuts turnaround time and damages. 6. Streamline Supply Chain Set up regional hubs near consumption centers. Aggregate demand to enable full-rake dispatch. Just-in-Time (JIT) inventory models cut warehousing and demurrage. Collaborate with 3PLs for cost-effective delivery and tracking. 7. Align with Policy & Incentives Leverage the National Logistics Policy’s aim to reduce logistics costs to 5–6% of GDP. Tap freight subsidies, tax incentives for logistics infra, GST pass-through, and single-window clearance for sidings and terminals. 8. Optimize Last-Mile & Maintenance Route planning tools reduce last-mile costs. Strategically located warehouses shorten delivery time. Preventive maintenance of fleets improves uptime and fuel efficiency. Impact Snapshot Rail over road: 20–30% cost saving Waterways: 40–60% Route optimization/backhauling: 10–15% Terminal/siding access: 5–10% Conclusion Combining modal shift, infrastructure upgrades, tech adoption, and policy alignment can reduce logistics costs by up to 40%. This is critical to meeting India’s steel production target of 255–300 million tonnes by 2030 and boosting global competitiveness.

Third-Party Risk Management (TPRM) in #GRC— As organizations increasingly rely on vendors, contractors, and service providers, third-party risk management (TPRM) has become a critical part of GRC programs. Poor vendor management can expose companies to data breaches, regulatory penalties, and operational disruptions. 1. TPRM • Regulatory Compliance: Frameworks like PCI DSS, GDPR, and ISO 27001 require organizations to assess and monitor third-party risks. • Vendors often manage critical business functions, so disruptions in their processes directly impact your operations. • A vendor breach could tarnish your brand and lead to legal or financial penalties. 2. TPRM Lifecycle • Assess vendor security practices before engagement (e.g., security questionnaires, contract reviews). • Identify risks specific to the vendor (e.g., data handling practices, access to systems). • Continuously monitor vendor performance and compliance through audits, reporting, and SLAs. • Ensure proper data disposal and de-provisioning of access after vendor offboarding. 3. Frameworks / best practices • NIST SP 800-161 focuses on supply chain risk management for federal systems. • ISO 27001/27036 provides guidance on third-party security requirements. • Shared Assessments Program offers standardized tools like SIG (Standardized Information Gathering) for vendor assessments. 4. Key Tools • Vendor management platforms like OneTrust, BitSight, or Prevalent help automate risk assessments and ongoing monitoring. • Use third-party security ratings to assess vendor vulnerabilities in real time. 5. Building strong TPRM programs • Establish clear policies and procedures for vendor risk management. • Conduct periodic risk assessments and ensure vendors comply with applicable regulations. • Collaborate with stakeholders across procurement, legal, IT, and compliance teams. TPRM integrates seamlessly into GRC.

Let's talk about how organizations use their data. When we look at the big picture, we can split data analytics systems into two categories. The first category is Business Analytics (BA) systems. These systems analyze large volumes of historical data to uncover strategic insights for decision-makers, supporting long-term planning and strategic decisions. E.g Business intelligence (BI) reporting The second category is Operational Analytics (OA) systems. They use real-time or near-real-time data from operational systems (e.g., transactional databases, ERP, CRM, IoT systems) to drive immediate decision-making and optimize business processes. Unlike traditional business intelligence (BI), which focuses on historical reporting, OA is focused on real-time insights that directly impact day-to-day operations. ✳️ Real-time and Near Real-time Data Analytics OA systems can be further divided based on the amount of data they use for decision-making and their time sensitivity. Real-time systems process data as it arrives and make immediate decisions based on the freshest data available. These systems typically handle individual events or very small windows of data, making split-second automated decisions. They typically operate in an automated, event-driven manner, making decisions without human intervention. For example, a credit card fraud detection system automatically blocks suspicious transactions based on predefined rules and patterns, or an automated trading system executes trades based on market conditions. Near real-time systems, while still focused on current operations, incorporate slightly larger datasets and may include some historical context in their analysis. These systems typically operate with data that's minutes or hours old and can handle more complex analyses. They can function either as decision-support tools for human operators or operate autonomously. For human decision support, these systems provide actionable insights. For example, a customer service dashboard alerts representatives to potential customer churn based on recent behavior patterns, enabling proactive outreach. In autonomous operation, these systems make decisions without human input—like an inventory management system that automatically generates purchase orders based on predefined rules and historical demand when it detects low stock levels. In the next post, we'll explore the implementation architectures for both OA and BA systems. #dataanalytics #operationalanalytics #sketchnotes

There's a gap between digital transformation and operational excellence. A gap that can be narrowed with a lean approach. For true operational excellence, we need technologies to work seamlessly across departments and functions. But...companies are investing and 'going digital' without fully aligning new technologies with existing systems, processes and people! So people are often spending more time figuring out how to use a new tool or duplicating efforts across disconnected systems 🤷♀️ Done right...a lean approach can provide a structured framework for integration that takes into account organizational culture and people.  Here's how it can help: 1️⃣ Sets clearer goals for the technology 💠 Lean thinking and tools help you figure out what problem the technology should solve and how it will make things better. 💠 Discussions about the technology involve the people doing the work so people feel involved from the start and are more likely to support the changes. 2️⃣ Improves processes before adding technology 💠 Lean thinking and tools encourages cleaning up messy or inefficient workflows first, so you don’t end up using technology to automate bad processes. 💠 Streamlining things first ensures the technology works smoothly and brings real improvements. 3️⃣ Builds a mindset for ongoing improvement (not once-off solutions) 💠 A Lean approach shapes a culture where change is the norm and people are always looking for ways to do things better. 💠 It encourages small, manageable changes and pilot programmes that build trust and confidence in new technologies. 4️⃣ Helps people adjusts to change 💠 A lean approach emphasizes people development, good communication and training so that everyone understands how to use new technology and why it’s helpful. 💠 Leadership development is part of a Lean approach (it is in my book anyway) so leaders are coached and trained to address concerns and enable smooth transitions. 5️⃣ Supports data management 💠 Advanced technologies produce a LOT of data, and a lean approach helps teams focus on what’s important and use that data to improve processes. 💠 People then feel empowered when they see how data can help them work smarter, not harder. 6️⃣ Standardizes how the technology is used 💠 A lean approach ensures new technology works across different teams and locations by standardizing how it’s used. 💠 It provides a framework for scaling up successful changes so the pace of change is not overwhelming for people. Basically...a #lean approach helps us to invest in technologies that can actually fix problems. It ensures that we involve people along the way and make work easier for everyone. Any thoughts on the topic? Leave your comments below 🙏