Change Management Consultants

𝗗𝗼𝗻’𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝘁𝗵𝗲 𝗺𝗲𝘀𝘀 - 𝗿𝗲𝗱𝗲𝘀𝗶𝗴𝗻 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗳𝗶𝗿𝘀𝘁 I can’t stop preaching this. Why? Because automation accelerates whatever you feed it: good or bad! Too often we “𝗴𝗼 𝗱𝗶𝗴𝗶𝘁𝗮𝗹” layering tools and workflows on top of processes that were: ❌ Never truly designed ❌ Rarely checked ❌ Barely measured ❌ Never challenged for relevance And i have seen sufficient cases like this. 👉 𝗢𝘃𝗲𝗿𝗮𝗹𝗹 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗔𝗜 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝗶𝗲𝘀. They don’t repair broken flows. If the process is weak, technology will only make the chaos faster, louder, and harder to track. So, before you automate, take a step back: ✔️ Map the process flow (SIPOC it) ✔️ Surface dependencies and constraints (policies, data..) ✔️ Co-design with users (Design Think the process) ✔️ Eliminate non-value adding steps and simplify the flow ✔️ Redesign with Automation in mind ✔️ Add AI where cognition helps (classification, prediction…) Procurement doesn’t need more bots (or AI Agents). 𝗜𝘁 𝗻𝗲𝗲𝗱𝘀 𝗮 𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲 𝘁𝗼 𝗿𝗲𝘁𝗵𝗶𝗻𝗸, 𝗿𝗲𝗱𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝘀𝗶𝗺𝗽𝗹𝗶𝗳𝘆 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝘀𝗰𝗮𝗹𝗶𝗻𝗴. What would you do first, before automating any process?

As a Business Analyst who’s worked across multiple domains, I kept asking: "How can we analyze and improve processes while ensuring alignment with customer experience, automation opportunities, and real-world execution constraints?" So 𝐈 𝐜𝐫𝐞𝐚𝐭𝐞𝐝 𝐚 𝐧𝐞𝐰 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 & 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 called 𝐓𝐑𝐀𝐂𝐄—designed for Business Analysts, by a Business Analyst. 𝐇𝐞𝐫𝐞’𝐬 𝐡𝐨𝐰 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬: 𝐓𝐡𝐞 𝐓𝐑𝐀𝐂𝐄 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 A structured 5-step approach to analyze, redesign, and implement better business processes. ✅ T - Touchpoint Mapping Map every customer, system, and employee interaction throughout the process. ⏩ Why? Because pain points often lie hidden between handoffs and touchpoints. 🔸 Example: While improving a claims process in insurance, we mapped the customer journey and discovered that 4 out of 7 delays occurred during internal handoffs—not external approvals. ✅ R - Root Cause Discovery Go beyond symptoms. Use tools like 5 Whys, Fishbone diagrams, or even process mining to get to the bottom of inefficiencies. 🔸 Example: A healthcare provider noticed repeated data entry errors. Root cause? The patient registration interface required double entry into two systems due to poor integration. ✅ A - Automation & Adaptability Assessment Assess which parts of the process can be automated (RPA, AI, workflow engines), and how adaptable the process is to scalability, policy changes, or compliance. 🔸 Example: In a telecom project, we flagged a manual SIM activation step as a bottleneck. After RPA automation, processing time dropped by 85%. ✅ C - Change Impact Analysis Evaluate how proposed changes will impact stakeholders, systems, SLAs, and compliance. Build readiness through a Change Impact Matrix. 🔸 Example: In a bank’s loan onboarding process, changing document verification impacted 4 systems and 3 departments. Early impact analysis helped us prep all affected users and avoid go-live delays. ✅ E - Execution Blueprint Create a visual and documented blueprint of the improved process: • Swimlane diagrams • RACI matrix • System handoffs • Success metrics 🔸 Example: For a logistics firm, we redesigned the inventory return workflow. The execution blueprint became the training, UAT, and SOP foundation, saving 2 weeks of rollout effort. 𝐖𝐡𝐲 𝐓𝐑𝐀𝐂𝐄 𝐖𝐨𝐫𝐤𝐬: ✔️ Human-centric (starts at touchpoints) ✔️ Analytical (root cause and impact driven) ✔️ Future-ready (focus on automation and adaptability) ✔️ Grounded in BA tools (flows, matrices, UAT, change analysis) ✔️ Outcome-focused (delivers real, implementable blueprints) 𝐎𝐯𝐞𝐫 𝐭𝐨 𝐘𝐨𝐮: Would you try TRACE in your next process improvement initiative? 𝐋𝐞𝐚𝐫𝐧 𝐁𝐏𝐌𝐍 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐟𝐫𝐨𝐦 𝐦𝐞: https://lnkd.in/eYHriqm3 BA Helpline

Digital transformation fails when companies try to automate a broken process. A Lean Consultant plays a vital role in making sure digitalization delivers real business results. The focus is always on simplifying processes, removing waste, and preparing people for a new way of working. Here is how a Lean Consultant guides the journey. 1. Understand the current process Everything begins with Gemba. We study the entire workflow, speak to teams, and analyze data to reveal the real problem. This step ensures that the organisation does not automate the wrong process. 2. Identify waste early Manual handovers, duplicate data entry, unnecessary approvals and long waiting times are major reasons for digital failures. Waste must be removed before any digital solution is built so the system will not automate waste. 3. Redesign and simplify the future workflow A simplified and standardised process becomes the foundation for digital success. The goal is to create a flow that is stable, clean, visual and easy to automate. 4. Translate business needs into system requirements Lean helps convert operational expectations into clear digital requirements. This includes data rules, workflows, permissions, triggers and behavioural expectations that designers can build accurately. 5. Align all stakeholders Production, planning, finance, quality, IT and leadership must work in one direction. Strong alignment prevents rework and ensures that everyone supports the future process. 6. Prepare people for change Digital transformation requires behaviour change. Teams need awareness, training and communication so they are ready to use the system from day one. 7. Validate the digital workflow Testing is not a technical task alone. It is a business requirement. The system must work exactly the way the redesigned process expects. This step prevents expensive corrections after launch. 8. Ensure continuous improvement After go live, data becomes the driver of improvement. Lean Consultants help teams monitor performance and carry out continuous improvements so the digital system remains effective. Digital transformation is successful when Lean thinking guides every step. Technology becomes a powerful enabler only when the process is ready, the people are ready and the organisation is aligned.

𝗛𝗲'𝘀 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝗵𝗮𝗿𝗱𝗲𝗿 𝘁𝗵𝗮𝗻 𝗲𝘃𝗲𝗿. 𝗔𝗻𝗱 𝗻𝗼𝘁𝗵𝗶𝗻𝗴'𝘀 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝘁𝗶𝗴𝗵𝘁𝗲𝗿. He's focused. He's grinding. He's giving everything he has to tighten that nut. Meanwhile, his partner is quietly removing the wrench every time he looks away. This is what invisible friction looks like in your organization. Your best people aren't failing. The system is silently undoing their work. I saw this exact pattern at NASA's Goddard Space Flight Center. The Hubble Space Telescope was operating at 20% capacity. Scientists faced 18-month wait times just to use it. Picture quality was sub-standard. Leadership blamed budgets. They blamed hiring freezes. They blamed atrophied expertise. They were wrong. The real problem? A "command and control" structure where every line of business had its own siloed engineering department. Massive duplication. Redundant resources. Engineers isolated in specific programs instead of collaborating. 3,000 engineers. All working hard. All being quietly undermined by the system they worked inside. We partnered with GSFC leadership to implement a different approach. 𝗧𝗵𝗲 𝘀𝗵𝗶𝗳𝘁: → Cross-functional teams mapped and streamlined core operations → Eliminated non-value-added bureaucracy → Transitioned from fragmented departments to a centralized resource pool → Moved from "Push" (command and control) to "Pull" (resources allocated when needed) The transformation started with Hubble operations. As more managers became fluent in the process redesign methodology, the structural change became organic. Those 3,000 siloed engineers? Consolidated into a single, centre-wide resource pool. No massive re-org committee. No top-down mandate. Just a shared language that let managers see the friction and fix it themselves. If your best people are grinding and nothing's moving, stop blaming them. Look for the invisible hand removing the wrench. ♻️ Share this with a leader whose team is working hard but going nowhere. 🔔 Follow for more on leadership and organizational transformation. #Leadership #SystemsThinking #NASA #OrganizationalDesign

"The Day a #Coffee Shop Became a Case Study in #Operations #Management" A few months ago, during a weekend break, I visited a #small but #popular #coffee #shop near campus. Despite great reviews, the queue kept growing, customers looked #impatient, and the staff seemed #overwhelmed. As I waited, the Operations Management teacher in me quietly switched on. I noticed something interesting: #Orders arrived faster than the barista could process — a forecasting gap. Brewing, heating milk, adding flavors, serving — all happened in the same tiny corner — a process layout challenge. #One person multitasked while two others stood idle — a process management imbalance. #The shop was operating like a job shop, even though demand required a batch or line-flow process. #The bottleneck — a single espresso machine — dictated the entire café’s capacity — classic process analysis. #The owner believed hiring more staff would solve everything. But the real issue wasn’t manpower — it was operations strategy and process design. If the café’s strategy was speed and convenience, the operations system needed to reflect it — better forecasting, redesigned workflow, clearer role allocation, maybe even pre-preparation or changed layout. And suddenly, this everyday coffee shop looked like #BHEL, #Zara, #Amazon, or any business we study — because every organization succeeds or suffers based on how well it aligns strategy, demand, capacity, and processes. When I shared this story in class, students immediately connected theory with reality — Operations Management isn’t confined to factories; it lives in restaurants, #airports, #hospitals, #NGOs, and #universities — everywhere systems exist. Think of a real-life situation you recently observed — a food outlet, bank, metro station, #hotel reception, #online delivery, or #campus process. 👉 Where did you notice operational #inefficiency, a #bottleneck, #wrong process type, poor forecasting, or misaligned strategy? #How would you #redesign the process to #improve #flow, #customer satisfaction, and #productivity? Share your reflections below — because observing operations is the first step toward improving them. #OperationsManagement #MBA #OperationsStrategy #ProcessDesign #ProcessAnalysis #Forecasting #Productivity #LeanThinking #ServiceOperations #JaipuriaJaipur #LearningByDoing #FromClassroomToLife

𝗠𝗼𝘀𝘁 𝗔𝗜 𝗶𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀 𝗳𝗮𝗶𝗹 𝗳𝗼𝗿 𝗮 𝘀𝗶𝗺𝗽𝗹𝗲 𝗿𝗲𝗮𝘀𝗼𝗻: They automate broken processes. When I bolt AI onto legacy workflows, I don’t get leverage. I get faster confusion, prettier dashboards, and the same bad decisions — just sooner. The real work comes before automation:   • Question whether the process should exist.   • Strip it down to the decision it’s meant to support.   • Only then apply AI to what remains. AI rewards clarity, not activity. If you recognize this pattern in your own organization, this CRIT™ prompt is a useful way to pressure-test where AI should actually be applied. Try this in your LLM of choice. ⸻ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 I’m investing in AI across my organization, but I’m concerned we’re automating existing processes without rethinking whether those processes should exist at all. Work is moving faster, but decision quality, alignment, and business impact are not improving at the same rate. 𝗥𝗼𝗹𝗲 You are my AI thought partner, helping me evaluate where AI should—and should not—be applied so it creates real strategic and financial value. 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 Ask me a series of questions to: • Identify one core leadership or operating process we are considering automating • Surface what decisions that process is actually meant to support • Expose where steps exist only to manage ambiguity, politics, or lack of ownership • Clarify what would break—and what would improve—if this process were reduced by 80 percent Push me when my answers are vague or based on legacy assumptions. 𝗧𝗮𝘀𝗸 Based on my responses: 1. Help me redesign the process so it is simpler, decision-driven, and clearly owned 2. Identify which parts should be deleted, simplified, or restructured before automation 3. Recommend where AI should be applied to scale what now matters 4. Output a short before-and-after view showing how the redesigned process will improve speed, alignment, and value creation

This CFO thought they needed 2 new hires. They didn’t hire anyone and freed up $420K instead. A mid-market finance org I worked with didn’t have a “cost problem.” They had a process problem. Here’s what changed 𝗠𝗼𝗻𝘁𝗵-𝗘𝗻𝗱 𝗖𝗹𝗼𝘀𝗲 Before: 14 days After: 6 days Impact: 96 hours/month saved = $115K/year 𝗔𝗣 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 Before: $16/invoice (manual entry, email approvals, paper filing) After: $5.50/invoice (automated capture, workflow approvals, digital storage) Impact: 8,000 invoices/year = $84K/year saved 𝗥𝗲𝗰𝗼𝗻𝗰𝗶𝗹𝗶𝗮𝘁𝗶𝗼𝗻𝘀 Before: 60 hours/month of manual work After: 12 hours/month (80% automated) Impact: 48 hours/month saved = $58K/year 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 Before: 40 hours/month building reports from scratch After: 8 hours/month (templated dashboards, auto-refresh) Impact: 32 hours/month saved = $38K/year 𝗩𝗲𝗻𝗱𝗼𝗿 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Before: $125K in duplicate/unused software licenses After: $0 (license audit + optimization) Impact: $125K recovered 𝗧𝗼𝘁𝗮𝗹 𝗔𝗻𝗻𝘂𝗮𝗹 𝗜𝗺𝗽𝗮𝗰𝘁: $𝟰𝟮𝟬𝗞 Investment Required → Software & automation: $45K one-time + $18K/year → Process redesign: $25K → Training: $8K Payback period: 4.2 months What actually changed (no fluff) Weeks 1–2: Discovery • Mapped current-state processes • Interviewed the finance team (30+ pain points surfaced) • Ran a time study to see where hours were really going • Benchmarked against peers Weeks 3–6: Quick Wins • Implemented AP automation • Built reconciliation templates • Created a standard close calendar with hard deadlines • Killed unused software licenses Weeks 7–10: Process Redesign • Rebuilt the month-end close (eliminated wait times) • Automated 12 recurring reports • Implemented real approval workflows (goodbye email hell) • Launched self-service dashboards Weeks 11–12: Training & Handoff • Trained the team • Documented new processes • Set up performance tracking • Established quarterly efficiency reviews What the CFO said “I thought we’d need to hire two more people to keep up with growth. Instead, we’re handling 30% more volume with the same team, and everyone’s working fewer hours.” The bottom line This wasn’t magic. It wasn’t a full system overhaul. It was fixing the things everyone knew were broken, but never prioritized: • Manual work that should be automated • Processes designed in 2012 • Software sprawl with zero governance • “That’s how we’ve always done it” thinking Most finance orgs have $300K–$500K hiding in plain sight. If you want to know what your number is, shoot me a note, and I'll take a look for free.

“We’ve got processes…but nobody really knows what they are.” That line from a process director at a growing regional bank stuck with me. He wasn’t complaining. He was describing what most financial institutions quietly face: - Process maps scattered across Visio files and SharePoint. - Risk and compliance teams building controls on tribal knowledge. - Manual discovery sessions that depend on who happens to be in the room. Then growth hits. New branches. New assets. New regulators. And suddenly, “the way we’ve always done it” doesn’t scale. Here’s what separates banks that cross thresholds confidently from those that scramble: ✅ They start early. Before the $10B mark, they build a single process repository — not a collection of diagrams, but a living system that ties people, systems, risks, and controls together. ✅ They blend disciplines. Former Lean and Kaizen experts from manufacturing are now leading banking transformation — bringing the rigor of process improvement to financial services. ✅ They trust data, not memory. Process mining, simulation, and AI assistants now uncover how work actually happens, so process redesign starts from truth, not assumption. ✅ They prepare for automation and AI safely. You can’t hand work to an algorithm until you understand how humans are doing it today. The goal isn’t another software rollout. It’s clarity — the kind that makes audits smoother, change faster, and teams aligned. At iGrafx, we’re helping community and regional banks move from “this is how we’ve always done it” to “this is how we know it works.”

PILLAR 5: PROCESS REDESIGN & WORKFLOW INTEGRATION The uncomfortable truth about why adoption fails Here's what I see most enterprises get catastrophically wrong about AI adoption: They bolt technology onto broken processes. Then they're confused when adoption stalls. MIT's was explicit: most pilot failures stem from treating AI as technology deployment rather than business transformation. Organizations deploy tools without redesigning workflows. They expect adoption without change management. They're surprised when people ignore systems that create friction rather than eliminating it. The pattern looks like this: Procurement purchases AI tool IT integrates it into existing workflow Training happens (one session, mostly ignored) Adoption metrics are disappointing Organization concludes "our people resist change" What process redesign actually requires: ✓ Understanding how work actually happens ✓ Identifying steps AI genuinely eliminates versus just made faster ✓ Removing obsolete activities ✓ Creating new roles that didn't exist in the old process ✓ Redesigning decision frameworks for how humans and AI collaborate ✓ Training teams on the new workflow, not just the tool This is 70% of the work—and most enterprises allocate 30% of their budget here. Harvard's field experiment with P&G professionals found that individuals with AI assistance matched multi-person team performance. This has profound workflow implications. Traditional structures with junior people handling routine work, coordination layers managing dependencies, and senior people making decisions become obsolete when AI handles execution and coordination. But organizations won't accept that implication, so they deploy AI without restructuring, expect adoption, and blame resistance. McKinsey found that organizations treating AI as change initiative (not technology initiative) see 2x adoption rates. This isn't psychology—it's mathematics. When you change how work happens without understanding human constraints, adoption fails. Questions your implementation team should answer: How does this process actually work today? (Not the org chart version—the real version) Which steps does AI genuinely eliminate? Which steps become unacceptable to do manually once AI exists? What new roles or responsibilities emerge? How do humans and AI collaborate in the redesigned workflow? What training does this require? How do we create psychological safety for this change? If you can't answer these before deploying technology, you're setting adoption up to fail. The technology isn't the constraint. Organizational willingness to actually redesign how work happens is. 💭 When you deployed your most recent AI tool, what percentage of effort went to process redesign versus tool configuration? Neil D. Morris | Head of IT at Redaptive | Former CIO Ball Aerospace & Maxar | IT Leadership & Innovation 🔄 Share this with your change management leadership

Redesign Before You Digitize. One of the biggest mistakes I see in digital transformation? Trying to automate broken processes with shiny new technology. Before rolling out a new ERP, WMS, or eCommerce platform, every distribution business should pause and ask: 👉 “Are our current workflows worth automating?” Because if you digitize inefficiency, you just create faster inefficiency. Here are 5 best practices we recommend before introducing new technology: 🧩 1️⃣ Map Your Current State Document how work actually happens—not how you think it happens. Include every handoff, delay, and manual step. Visibility drives improvement. ⚙️ 2️⃣ Identify Waste and Bottlenecks Look for redundant approvals, paper-based tasks, or duplicate data entry. Use Lean or Six Sigma tools (Value Stream Mapping, 5 Whys) to pinpoint friction. 🔁 3️⃣ Redesign Around Value Every process should serve a clear purpose: customer value. Ask: does this step add value, or does it just make us feel busy? 💬 4️⃣ Involve the Frontline Early The best process insights come from the people doing the work. Co-design solutions with your warehouse, purchasing, and sales teams—they’ll spot what leadership misses. 📊 5️⃣ Validate Before You Automate Pilot the redesigned process manually or with simple tools. If it works in Excel or on paper, then it’s ready for ERP automation. Technology is an amplifier—it magnifies whatever foundation you build on. If your foundation is solid, ERP accelerates growth. If it’s weak, ERP just exposes the cracks faster. At Scaled Solutions Group, we help distributors optimize people, process, and systems—so technology becomes the final step, not the first one. Have you "SCALED"? https://lnkd.in/g3peD894 #ProcessImprovement #DigitalTransformation #EpicorP21 #DistributionERP #LeanSixSigma #ContinuousImprovement #ChangeManagement #OperationalExcellence #ERP #WarehouseManagement #ProcessRedesign #ValueStreamMapping #BusinessProcessOptimization #ScaledSolutionsGroup #PeopleProcessSystems