Integrating Change In Business Processes

If we want value from data, it’s not enough to teach people how to read charts. We also need to teach them how to read themselves. It’s a simple but counterintuitive fact: Understanding data doesn't automatically lead to better decisions. Think about it: How often have you seen someone presented with perfect data, clear insights, and compelling visualizations... only to make the same decisions they would have made without them? A lack of Data Literacy can be part of the problem. But that’s just one piece of the puzzle. An even more common—and oftentimes overlooked—issue is misunderstanding how humans actually make decisions when presented with data. A lack of Decision Literacy. The psychology of decision-making runs deeper than we think. Even with the most robust data governance, clear metrics, and advanced analytics capabilities, organizations will still fall prey to human tendencies, such as loss aversion, anchoring bias, and the sunk cost fallacy. These psychological factors don’t just interfere with our decisions once the data is there—they already shape how we collect, analyze, and interpret data in the first place. The more skilled we become with data, the more sophisticated our self-deception can become. Cognitive biases don’t disappear just because we know how to interpret bar charts and probabilities. On the contrary! The illusion of data mastery can make us even more vulnerable to confirmation bias. Our brains are excellent at finding data that supports our pre-existing beliefs while unconsciously filtering out contradictory evidence. True data mastery requires us to be as fluent in psychology as we are in programming. We must therefore expand our common definition of data-driven transformation to account for this: ▪️ Beyond teaching people how to analyze data, we must help them understand decision-making. ▪️ In addition to building databases, we must also build decision-making frameworks that account for human nature. ▪️ When asking, “What does the data tell us?” we must also ask, “What might prevent us from seeing what the data tells us?” The most successful organizations I've worked with understand that reading data and reading ourselves are equally critical skills for success. They create environments where it's safe to challenge assumptions, and decisions are reviewed not just for outcomes but for processes. So ask yourself this: When was the last time your team discussed cognitive biases, group dynamics, and decision frameworks with the same rigor as your data stack?

𝐈𝐧 𝐭𝐡𝐞 𝐥𝐚𝐬𝐭 20 𝐲𝐞𝐚𝐫𝐬, 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐚𝐭𝐞 𝐭𝐡𝐞 𝐰𝐨𝐫𝐥𝐝. 𝐈𝐧 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 20 𝐲𝐞𝐚𝐫𝐬, 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐞𝐚𝐭 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞—𝐚𝐧𝐝 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐥𝐢𝐤𝐞 𝐄𝐑𝐏 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐚𝐫𝐞 𝐧𝐨 𝐞𝐱𝐜𝐞𝐩𝐭𝐢𝐨𝐧. The transformation ahead will be monumental for ERP software providers, developers, consultants, and users. With AI advancing rapidly, traditional ERP systems, which rely on rigid, predefined processes, will evolve into adaptive, real-time decision engines. Instead of static workflows, ERP platforms of the future will make the next best decision dynamically for every order, resource, and demand scenario. 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐞𝐚𝐧? - No more fixed processes. AI will determine the optimal next step for an order by analyzing material availability and production capacity in real time. - No more waiting for batch jobs or manual inputs. AI-powered ERP systems will continuously learn and respond instantly to changing conditions. - A shift from process management to outcome management, transforming how we manage supply chains, production, and financial planning. This won’t happen overnight. It’s a gradual evolution starting with today’s composable, cloud-based ERP systems, which already enable centralized updates and innovations. Over time, these platforms will progress into AI-centric frameworks where the traditional ERP core becomes a repository for orders, while execution is driven by outcome-focused AI. 𝐀𝐧𝐝 𝐰𝐡𝐚𝐭 𝐚𝐛𝐨𝐮𝐭 𝐮𝐬𝐞𝐫𝐬 𝐚𝐧𝐝 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭𝐬 𝐢𝐧 10–20 𝐲𝐞𝐚𝐫𝐬? Of course, there will still be those who claim that SAP ECC or early on-premises S/4HANA releases “get the job done.” But they will be much fewer since many will be out of business because of missing abilities to adapt to changing circumstances and paradigms. For consultants, the landscape will also shift: - Fewer roles for traditional SAP Basis or technical application specialists. - More opportunities for visionary consultants who can align a customer’s strategy with cutting-edge technology and guide them toward value-driven adoption of AI-powered ERP systems. This is my personal vision for the "Future of ERP". Probably it will happen even sooner. Prove me wrong.

𝗪𝗵𝘆 𝗱𝗼 𝘀𝗼 𝗺𝗮𝗻𝘆 𝗘𝗥𝗣 𝗺𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗮𝗶𝗹? 𝗕𝗲𝗰𝗮𝘂𝘀𝗲 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝘁𝗿𝗲𝗮𝘁 𝗶𝘁 𝗹𝗶𝗸𝗲 𝗮 𝘀𝗶𝗺𝗽𝗹𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗽𝗮𝘁𝗰𝗵, not the business transformation it truly is. Listening to my network, there seems to be a rush to complete ERP migrations, as fast as possible, with SAP S/4HANA plans driving most of it. But an ERP system is more than just an IT upgrade. It’s a chance to redesign how your business operates and build a solution architecture that supports agility and innovation. While necessary, these migrations often become redundant without proper alignment to business goals. Something, I've seen happen! Here some get rights to consider: ◉ 𝗔𝗹𝗶𝗴𝗻 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗻𝗱 𝘁𝗲𝗰𝗵 𝗴𝗼𝗮𝗹𝘀 Ensure that IT and business leaders are on the same page. ERP systems serve broader business objectives, such as innovation, improving procurement strategies, and enhancing supplier relationships. ◉ 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗼𝗼𝗹𝘀. Instead of getting caught up in the technology itself, be clear about the business benefits you'd like to achieve. New ERP functionality can be of support to achieve goals like efficiency, cost reduction, and agility. ◉ 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝘆 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗮𝗻𝗱 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 Don't just migrate complex, outdated processes but streamline them end-to-end. Reevaluate processes for efficiency and desired outcomes. ◉ 𝗜𝗻𝘃𝗲𝘀𝘁 𝗶𝗻 𝗰𝗵𝗮𝗻𝗴𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 - 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗶𝗻 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 ERP migrations often fail due to poor user adoption. Beyond training, invest in communication & ongoing support showing the value and relevance of the system to users. ◉ 𝗜𝗻𝘃𝗼𝗹𝘃𝗲 𝗰𝗿𝗼𝘀𝘀-𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝘁𝗲𝗮𝗺𝘀 ERP impacts every area of the business, so cross-team collaboration is essential. Involve stakeholders from finance, procurement, IT, and operations ensures the system meets everyone’s needs. ◉ 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗱𝗮𝘁𝗮 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 - 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗰𝗼𝗺𝗽𝗿𝗼𝗺𝗶𝘀𝗲 An ERP system is only as good as the data it processes. Ensure that data is clean, consistent, and reliable before migration. Dirty or incomplete data is one of the biggest challenges post-go-live. ◉ 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘀𝗲 𝗦𝘆𝘀𝘁𝗲𝗺 𝗳𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗼𝘀𝗮𝗯𝗶𝗹𝗶𝘁𝘆 Choose an architecture which allows for future-proofing and integration of new features, scalability and integration. Business models evolve, and your ERP must evolve with them." ◉ 𝗦𝗲𝘁 𝗿𝗲𝗮𝗹𝗶𝘀𝘁𝗶𝗰 𝘁𝗶𝗺𝗲𝗹𝗶𝗻𝗲𝘀 - 𝗶𝘁'𝘀 𝗻𝗼𝘁 𝗴𝗼𝗶𝗻𝗴 𝘁𝗼 𝗯𝗲 𝗾𝘂𝗶𝗰𝗸 𝗶𝗳 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 Don’t rush an implementation. ERP migrations are complex and require time to integrate properly. A phased approach allows for troubleshooting and mitigates a risk for failure. ❓Any other "get rights" i missed and you would add from your experience. #erp #businesstransformation #migration #sap4hana

In a world where AI and automation reshape every industry we know, leaders must master the human side of work. Forward-thinking leaders are focusing on three cultural pillars that will define the next era of work. Here's a guide I have put together, insights from my work with organisations. The 3 Cultural Shifts every leader needs to know: 1️⃣ Culture of Innovation 📌 Why it matters: ➜ Rapid technological change demands a mindset of continuous reinvention. ➜ Innovative cultures empower employees to challenge the status quo and uncover new opportunities 📌How to build it: ➜ Celebrate experimentation and learning from failure. ➜ Foster cross-functional collaboration and knowledge sharing - create "innovation labs" where diverse teams tackle big problems ➜ Equip leaders to model innovative behaviors and create psychological safety for risk-taking 2️⃣ Culture of Connection 📌 Why it matters: ➜ Remote and hybrid work can erode interpersonal bonds, leading to isolation and disengagement ➜ Strong relationships drive higher employee engagement, wellbeing, and retention 📌 How to build it: ➜ Cultivate authentic human interactions beyond just task completion ➜ Promote a sense of shared purpose and community through company-wide initiatives and volunteering opportunities ➜ Empower managers to foster belonging on their teams through team-building activities and inclusive practices 3️⃣ Culture of Learning 📌 Why it matters: ➜Rapid technological shifts and evolving job requirements demand ongoing skills development ➜ Employees with a growth mindset are more adaptable, innovative, and engaged 📌 How to build it: ➜ Provide diverse learning opportunities, from formal training programs to experiential projects and job rotations ➜ Encourage knowledge sharing and reverse mentoring - enable junior employees to upskill senior leaders ➜ Equip managers to have regular career development conversations and create personalized learning plans The content is adapted from REINVENT 4.0 - Your Keys to Unlock Success and Thrive in Uncertainty (Author: Adeline Tiah) ♻️ Share this to help share the future of organisations. Follow Adeline Tiah 謝善嫻 for content on future of work and leadership culture.

The system didn’t crash. The people did. A hospital launched a sleek new documentation system; 🔸 Training? Done 🔸 Interface? Clean 🔸 Leadership? Proud By the end of Week 1: 🔸 Nurses were scribbling on post-its 🔸 Doctors opened a shadow Google Doc 🔸 Admins retyped notes just to “make the system look used” No one raised alarms. No one filed complaints. They just.. worked around it. From the boardroom, it looked like success. On the ward, it felt like sabotage. This is not uncommon in big hospitals, small clinics, and everywhere in between. The tech might change, but the pattern doesn’t. And with AI tools, interoperability mandates, and shrinking workforces hitting all at once, getting this balance wrong costs more than ever. Because when transformation is treated as just an IT project, it wobbles. When it wobbles, staff feel it. And when staff feel it, patients feel it even more. Real transformation happens when people, systems, and technology move together. If one lags, the whole thing tilts. That alignment doesn’t happen because you held a training session. It happens because you manage the change, the beliefs, the behaviors, the trust. Change management isn’t “send an email and cross your fingers”. It’s: 🔹 Surfacing resistance before it hardens 🔹 Involving frontline voices, not just top-down decisions 🔹 Creating safety to fail, reflect, and iterate 🔹 Addressing the emotional toll of “yet another system” People don’t resist technology. They resist systems that make them feel unheard, unsupported, and replaceable. The bigger picture: 🔹 People need to believe in the change and see their role in it 🔹 Systems need to adapt so workflows make sense 🔹 Technology needs to fit into those workflows, not bulldoze them Miss one, and the transformation tips over (as I like to say: Transformation isn’t an upgrade, it’s an alignment). Let's go beyond noise💡 What’s a time you saw the tech work, but the transformation fails, and why? === 🍎 Missed my previous posts? Stay updated though my WhatsApp channel (no numbers shared) www.gobeyondnoise.com/#wa Like, repost if the content resonates with you. 🍎 This post is part of 'Rethinking Digital Health Innovation' (RDHI) #GoBeyondNoise

Digital Transformation Advice. Time for a Reality Check? 🤔 Trenches wisdom coming your way... 𝗧𝗵𝗲 𝗚𝗹𝗼𝘀𝘀𝘆 𝗕𝗿𝗼𝗰𝗵𝘂𝗿𝗲 𝗦𝗮𝘆𝘀 → Define corporate strategy → Align with business goals → Pick the perfect tech → Secure executive buy-in → Throw money at it 𝗧𝗵𝗲 𝗠𝗲𝘀𝘀𝘆 𝗥𝗲𝗮𝗹𝗶𝘁𝘆 → Misalignment = Project graveyard → Teams clueless about goals → Analysis paralysis → Budget? What budget? → Change resistance on steroids 𝗧𝗵𝗲 𝗗𝗶𝘀𝗺𝗮𝗻𝘁𝗹𝗶𝗻𝗴 𝗣𝗹𝗮𝘆𝗯𝗼𝗼𝗸 1. 𝗦𝗵𝗮𝘁𝘁𝗲𝗿 𝘁𝗵𝗲 𝗠𝗼𝗻𝗼𝗹𝗶𝘁𝗵 Reality. One-size-fits-all strategies crumble Action. Break transformation into agile fragments 2. 𝗘𝗺𝗽𝗼𝘄𝗲𝗿 𝘁𝗵𝗲 𝗙𝗿𝗼𝗻𝘁𝗹𝗶𝗻𝗲𝘀 Reality. Top-down approach breeds resistance Action. Let teams innovate their piece of the puzzle 3. 𝗘𝗺𝗯𝗿𝗮𝗰𝗲 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁 Reality. Static alignment leads to obsolescence Action. Align on vision, flex on execution 4. 𝗖𝘂𝗹𝘁𝗶𝘃𝗮𝘁𝗲 𝗠𝗶𝗰𝗿𝗼-𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻𝘀 Reality. Big bang changes often fizzle Action. Encourage small, rapid improvements 5. 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝗮𝗻𝗱 𝘁𝗵𝗲𝗻 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝘀𝗼𝗺𝗲 𝗺𝗼𝗿𝗲 Reality. Silos kill transformation Action. Share wins, learnings, and challenges across teams What piece of your digital strategy could you dismantle for better results? Drop your thoughts below 👇 #DigitalTransformation #StrategicDismantling #AgileTransformation ♻️ → Repost if you found this useful!

In today’s fast-paced business landscape, the 𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐭𝐨 𝐥𝐞𝐯𝐞𝐫𝐚𝐠𝐞 𝐝𝐚𝐭𝐚 for smarter decision-making is a game-changer. Ashok Leyland, one of India’s leading commercial vehicle manufacturers, is a prime example of how embracing data-driven strategies can transform an organization. Their journey highlights the importance of leadership, the right tools, and a culture of collaboration in building a successful analytics-driven business. 𝐻𝑒𝑟𝑒’𝑠 ℎ𝑜𝑤 𝐴𝑠ℎ𝑜𝑘 𝐿𝑒𝑦𝑙𝑎𝑛𝑑 𝑡𝑢𝑟𝑛𝑒𝑑 𝑑𝑎𝑡𝑎 𝑖𝑛𝑡𝑜 𝑎 𝑐𝑜𝑟𝑒 𝑑𝑟𝑖𝑣𝑒𝑟 𝑜𝑓 𝑖𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑜𝑛 𝑎𝑛𝑑 𝑠𝑢𝑐𝑐𝑒𝑠𝑠: 1️⃣ Leadership Commitment: Top executives championed data-driven strategies, setting a company-wide example. 2️⃣ AI Tools for Smarter Decisions: The adoption of AI-powered platforms gave teams access to real-time data, empowering smarter decisions. 3️⃣ Data Literacy: By investing in training, Ashok Leyland ensured employees could understand and use data effectively. 4️⃣ Cross-Department Collaboration: Breaking down silos encouraged teamwork, leading to process improvements and innovation. Impact: ✅ Reduced operational costs and enhanced efficiency. ✅ Created customer-centric vehicle designs through data insights. ✅ Unlocked new revenue opportunities by embracing analytics. Building a culture of analytics isn’t just about tools—it’s about creating a mindset where data drives every decision. 𝑾𝒉𝒂𝒕’𝒔 𝒕𝒉𝒆 𝒃𝒊𝒈𝒈𝒆𝒔𝒕 𝒄𝒉𝒂𝒍𝒍𝒆𝒏𝒈𝒆 𝒚𝒐𝒖’𝒗𝒆 𝒇𝒂𝒄𝒆𝒅 𝒊𝒏 𝒇𝒐𝒔𝒕𝒆𝒓𝒊𝒏𝒈 𝒂 𝒅𝒂𝒕𝒂-𝒅𝒓𝒊𝒗𝒆𝒏 𝒄𝒖𝒍𝒕𝒖𝒓𝒆 𝒘𝒊𝒕𝒉𝒊𝒏 𝒚𝒐𝒖𝒓 𝒐𝒓𝒈𝒂𝒏𝒊𝒛𝒂𝒕𝒊𝒐𝒏? 𝑺𝒉𝒂𝒓𝒆 𝒚𝒐𝒖𝒓 𝒕𝒉𝒐𝒖𝒈𝒉𝒕𝒔 𝒊𝒏 𝒕𝒉𝒆 𝒄𝒐𝒎𝒎𝒆𝒏𝒕𝒔 𝒃𝒆𝒍𝒐𝒘! #DataDrivenDecisionMaking #AnalyticsCulture #AshokLeyland #DigitalTransformation #Leadership

Ever felt blindsided by workplace disruption? Workplaces can feel like churning seas of constant change which leave many employees adrift. What’s more, whether it’s a sudden reorg, a new system rollout, or shifting strategic priorities, leaders often respond too late—after confusion sets in, productivity dips, or morale takes a hit. But what if the secret to managing disruption is acting before change hits? In our latest Forbes article, my colleague Mailys M. George and I explore how proactive sensemaking, narrative-building, and culture shaping can equip teams to thrive amid uncertainty. Our research shows that rather than focusing on the change itself, leaders should focus on employees’ unfulfilled needs—relational, psychological and physical—prior to the disruption. We also outline four practical steps leaders can take to turn threatening change into opportunities for growth. ➤ Read the full article here: https://lnkd.in/de7fcDAC We would love to hear your thoughts: How do you prepare your team for the unexpected? #Disruption #Leadership #Change #Culture #Globalwork

𝗔𝗜 𝗶𝘀𝗻’𝘁 𝗷𝘂𝘀𝘁 𝘁𝗮𝗸𝗶𝗻𝗴 𝘁𝗮𝘀𝗸𝘀 𝗮𝘄𝗮𝘆. 𝗜𝘁’𝘀 𝗿𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝘄𝗼𝗿𝗸 𝗲𝘃𝗲𝗻 𝗺𝗲𝗮𝗻𝘀. Across industries, roles are being redesigned, not eliminated. The question is no longer “𝘞𝘪𝘭𝘭 𝘮𝘺 𝘫𝘰𝘣 𝘦𝘹𝘪𝘴𝘵?” but “𝘞𝘩𝘢𝘵 𝘸𝘪𝘭𝘭 𝘮𝘺 𝘫𝘰𝘣 𝘭𝘰𝘰𝘬 𝘭𝘪𝘬𝘦 𝘸𝘩𝘦𝘯 𝘩𝘢𝘭𝘧 𝘰𝘧 𝘪𝘵 𝘤𝘩𝘢𝘯𝘨𝘦𝘴?” When AI automates routine tasks, what’s left isn’t less work... it’s different work. • It demands new skills. • It challenges old identities. • It forces organisations to re-draw the boundaries between human and machine. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗮𝘁 𝗛𝗥 𝗺𝘂𝘀𝘁 𝗹𝗲𝗮𝗱 𝗶𝗻 𝘁𝗵𝗲 𝗮𝗴𝗲 𝗼𝗳 𝗿𝗼𝗹𝗲 𝗿𝗲𝗱𝗲𝘀𝗶𝗴𝗻: 𝟭. 𝗗𝗲𝗰𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁 𝗷𝗼𝗯𝘀 𝗶𝗻𝘁𝗼 𝘁𝗮𝘀𝗸𝘀 See clearly what’s human, what’s machine, what’s shared. 𝟮. 𝗥𝗲-𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 Design partnerships, not replacements. 𝟯. 𝗥𝗲𝘀𝗸𝗶𝗹𝗹 𝗳𝗼𝗿 𝗯𝗼𝘁𝗵 𝘀𝗸𝗶𝗹𝗹 𝗮𝗻𝗱 𝗶𝗱𝗲𝗻𝘁𝗶𝘁𝘆 Help employees find meaning in new versions of their work. 𝟰. 𝗦𝗲𝘁 𝗲𝘁𝗵𝗶𝗰𝗮𝗹 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 Ensure AI enhances trust, not erode it. 𝟱. 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗽𝘂𝗿𝗽𝗼𝘀𝗲, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗼𝘂𝘁𝗽𝘂𝘁 Because productivity without meaning won’t sustain. The future of work isn’t about defending old jobs. It’s about re-imagining new ones. #DrJaclynLee #FutureOfWork #AIinHR #RoleRedesign #StrategicHR #PeopleStrategy

One of the most fundamental Kanban change management principles is “Start with what you do now.” To be able to achieve your business goals, you should first and foremost address the challenges that you face in your own context, then use your performance data to make informed decisions about how to make gradual long-term improvements that are here to stay. Every single initiative you want to take, no matter how large or small, should have a measurable goal and a metric tied to it. If you find that the metric isn’t meeting its goal, then you need to stop, rethink, adjust and retest it. Keep repeating this process until you hit your target. This means evaluating your performance trends every day and not only tracking the metrics but also revealing the context underpinning them. Let’s explore how data-driven decision making ultimately improves your business outcomes. #NavigateYourFlow #Kanban #AgileLeadership #AgileManagement #AgileProjectManagement