Change Management

If you live in the Mid-Atlantic region and don't know what PJM Interconnection is, pay attention. PJM was founded 99 years ago to manage the distribution of electricity over Pennsylania (P), New Jersey (J), and Maryland (M). Since then, the nonprofit company has expanded to include Delaware, Virginia, West Virginia, Ohio, Washington DC, half of Kentucky, and significant parts of Michigan, Indiana, North Carolina, and Illinois (including Chicago). It is the largest single power grid in the United States. Headquartered in Valley Forge, PA, PJM provides electricity to 67 million Americans. PJM coordinates the movement of electricity between all the different power companies within its service area, such as PECO in Philly, Delmarva Power in Delaware, and all the other power companies listed in the graph. PJM operates as a traffic cop for electricity generators, making sure that power plants (gas, coal, nuclear, etc.) operating in its service area are distributing electricity as needed across the entire grid so that no area goes without necessary power. Think of what air traffic controllers do at airports, guiding the planes in and out, making sure there is order and no mistakes, 24 hours a day. PJM does that with electricity. The problem is the rapid proliferation of AI data centers, particularly in Northern Virginia and Maryland (around DC) which is the most concentrated collection of data centers in the USA. These data centers just plug into the PJM grid and started sucking up power to the point that PJM is running nearly all the time at max capacity. If you live here and haven't felt the impact of electricity price increases, you will soon. Many power companies have price caps in place, but that won't last. In capacity auctions, where power resources commit to be available in years ahead, prices have gone parabolic; from $2.2B to $14B (a 536% increase), largely due to forecasted load growth from data centers. It's a challenge to generate a political solution with governors of both parties in the service area. Plus, the Trump Administration is now getting involved. The Energy Secretary and Interior Secretary hosted 13 state governors involved at the White House 1/16 where there was an agreement on 2 key principles: 1- Emergency Power Auction - the idea is to compel data centers to participate in financing new power plants by buying 15 years of power in advance. Data centers would bid for these contracts, hence the auction. 2- Price Caps - to shield the 67 million Americans from exponentially higher electric bills, it is proposed to cap electricity bills for 1-2 years. It is unclear who will absorb the risk and cost to make this happen. In many states price caps are already protecting Americans. If a solution can't be reached soon, it is increasingly likely that rolling blackouts will happen across the service area during high-load periods (extreme heat or extreme cold). Be prepared. #riskmanagement #interestrates #fedpolicy

This is the HR challenge that keeps me awake at night. We ask HR to change the engine. Then we don’t give them the keys. That's exactly what we're doing to HR leaders across every industry, every day. Last month, I sat across from a brilliant CHRO who looked defeated. She'd just been handed her third "culture transformation" mandate this year. The brief was crystal clear: Fix engagement, reduce turnover and build a high-performance culture but… Her budget? Unchanged.  Her authority? Non-existent.  Her seat at strategic decisions? Still fighting for it. "They want me to drive change," she said, "but I can't even change the coffee brand without three approvals." Four decades in this industry, and this conversation haunts me more than any other. We've created a fundamental paradox that's destroying HR effectiveness across organisations. Leadership expects HR to: + Transform toxic cultures overnight + Attract top talent in impossible markets + Drive engagement without addressing root causes But denies them: - Decision-making authority - Strategic budget allocation - Real influence over business direction It's like asking someone to architect a building while handing them only a paintbrush. The result? HR professionals burning out faster than the talent they're trying to retain. Organisations wondering why their "people initiatives" keep failing. Executives frustrated that their "people investment" isn't paying off. And the worst part? We blame HR for it. I’ve mentored some of the brightest HR minds in this country…sharp, driven, deeply committed to impact. But they often carry this quiet frustration: “We’re asked to deliver change, but not empowered to lead it.” This isn’t just unfair. It’s ineffective. We're wasting brilliant minds on impossible missions. The CHROs I know aren't just order-takers. They're strategic thinkers who understand that people performance drives business performance. They see connections between culture and revenue that most leaders miss. But we've reduced them to administrative executors of someone else's vision. The companies getting this right have figured out something fundamental: HR isn't a support function that implements people policies. It's a strategic driver that shapes business outcomes. So, to every founder, CXO, and board member reading this: If you want your people strategy to succeed, stop asking HR to drive change from the passenger seat. Give them the steering wheel, or accept that you'll keep going in circles. Because the future of your culture depends on it. #leadership #hrchallenges #hrstruggles

70% of change initiatives fail. (And it's rarely because the idea was bad.) Here's what actually kills transformation: You picked the wrong change model for the job. It's like performing surgery with a hammer. Sure, you're using a tool. But it's the wrong one. I've watched brilliant CEOs tank their companies this way: Using individual coaching (ADKAR) for company-wide transformation. Result: 200 people change. 2,000 don't. Running a massive 8-step program for a simple process fix. Result: 6 months wasted. Team exhausted. Nothing changes. Forcing top-down mandates when they needed subtle nudges. Result: Rebellion. Resentment. Resignation letters. Here's what nobody tells you about change: The size of your change determines your approach. Real examples from the field: 💡 Startup pivoting product: → Used Lewin's 3-stage (unfreeze old way, change, refreeze) → 3 months. Clean transition. Team aligned. 💡 Enterprise going digital: → Used Kotter's 8-step process → Created urgency first. Built coalition. Enabled action. → 18 months later: $50M in new revenue. 💡 Sales team adopting new CRM: → Used Nudge Theory → Made old system harder to access → Put new system as browser homepage → 95% adoption in 2 weeks. Zero complaints. The expensive truth: Wrong model = wasted months + burned budgets + broken trust Right model = faster adoption + sustained results + energized teams Warning signs you're using the wrong model: • High activity, low progress • People comply but don't commit • Changes revert within weeks • Energy drops as you push harder • "This too shall pass" becomes the motto Match your medicine to your ailment: Small behavior change? Nudge it. Individual performance? ADKAR it. Cultural shift? Influence it. Full transformation? Kotter it. Enterprise overhaul? BCG it. Stop treating every change like a nail. Start choosing the right tool for the job. Your next change initiative depends on it. Your team's trust demands it. Your company's future requires it. Save this. Share it with your leadership team. Because the next time someone says "people resist change," you'll know the truth: People don't resist change. They resist the wrong approach to change. P.S. Want a PDF of my Change Management cheat sheet? Get it free: https://lnkd.in/dv7biXUs ♻️ Repost to help a leader in your network. Follow Eric Partaker for more operational insights. — 📢 Want to lead like a world-class CEO? Join my FREE TRAINING: "The 8 Qualities That Separate World-Class CEOs From Everyone Else" Thu Jul 3rd, 12 noon Eastern / 5pm UK time https://lnkd.in/dy-6w_rx 📌 The CEO Accelerator starts July 23rd. 20+ Founders & CEOs have already enrolled. Learn more and apply: https://lnkd.in/dwndXMAk

Risk is bad, isn’t it? Not always. Some risks are bad, but others you want to embrace. Why? Because they add value and allow you to serve your customers better. A little over a decade ago, in 2012, Robert S. Kaplan and Anette Mikes wrote a Harvard Business Review article “Managing Risks: A New Framework.” In this article they lay out a useful typology of three types of risk: Type 1: External Risk Definition: Risks outside your control, coming from external sources Examples: Climate change, recession, pandemic Mitigation: Reduce impact in case the event occurs  Tools: Scenario-planning, war games, stress-testing Type 2: Preventable Risk Definition: Risks arising from what happens within an organization Examples: accidents, mistakes, fraud Mitigation: Eliminate or prevent to minimize occurrence  Tools: Standard operating procedures, audits, norms and values Type 3: Strategic Risk Definition: Risks taken to create better strategic returns Examples: credit risk, R&D investments, location risk Mitigation: Reduce likelihood and impact in a cost-effective way Tools: Risk-maps, key risk indicators, Risk-based resource allocation In a nutshell: external risks you want to prepare for, preventable risks you want to avoid, and strategic risks you manage carefully. Of the three categories, I find Strategic Risk the most interesting type. Because, unlike the other two, it can add substantial value to a company and be an important part of its strategy. This means it comes with an interesting question: → Can we take on MORE risk to improve the performance of our organization? While seemingly unnatural from a risk management perspective, it’s more common than we might think. Because, taking over risk from your customers is a very common way of adding more value for them. Here’s some examples: - Any type of insurance - Any type of payment arrangement, especially no-cure-no-pay - Any type of leasing and renting model - Any type of X as a service approach To finalize, here’s a high-level risk approach based on the three types 1. List all the risks your organization faces 2. Categorize them in each of the three types 3. Reduce the possible impact of the external risks 4. Reduce the likelihood of the preventable risks 5. Investigate which strategic risks make sense to add 6. Manage likelihood and impact of strategic risks #riskassessment #forecasting #managementdevelopment

Although Unity Catalog is a great offering from Databricks for Data Governance, tracking lineage and auditing but setting it up from scratch across a multi-team, multi-workspace environment can be challenging. While the architecture looks clean on paper, trust me, the reality is far more nuanced. There are some practical challenges that you need to know before you start with its setup or you're already in the process. 1️⃣ Metastore region mismatch I know about teams who have learned the hard way that their Unity Catalog metastore needs to be in the same region as their workspaces. If you have your workspaces across regions, you might have to rebuild a few or compromise on workspace placement. 2️⃣ Managing workspace assignment Assigning the metastore to workspaces isn't enough. Users continue to use Hive tables and read data from Delta paths until you completely block that usage and enforce Unity Catalog-based access patterns. 3️⃣ External locations + storage credentials Setting up secure externals locations could be painful if you don't understand the fundamentals. You could've to: ☘️ Manually create Managed Identities -> Role Assignment mappings in Azure. ☘️ Ensure that the access connector has the Storage Blob Data Contributor role at the right scope. ☘️ Double-check that the path-level ACLs aren't blocking Unity Catalog reads. Better to validate and test external location connectivity per environment before signing off. 4️⃣ Migrating existing Delta tables Ohhh! Because of poor governance in the past, you might notice that many existing delta tables don't follow proper naming conventions, lack proper ownership or point to inconsistent storage paths. You might need to build a migration tool that: ☘️ Extracts metadata from these tables. ☘️ Validate the table formats based on new governance strategy. ☘️ Render CREATE TABLE ... USING DELTA LOCATION statement for Unity Catalog table registration. It could also be a case that manual intervention is still required if there are plenty of schema inconsistencies. 5️⃣ Volume adoption still unclear I still see that most devs confuse volumes with external locations. Please create clear guidelines for it: ☘️ Volumes are for notebooks/scripts/artifacts and raw files. ☘️ While external locations are for managed ingestion pipelines. 6️⃣ Auditability gaps Using system tables, you could easily track audit logs but not everything is captured out-of-the-box. You might need to integrate system tables with observability tools like Grafana and set up alerting (e.g., for unauthorised alerting or privilege escalations). 7️⃣ Onboarding new users/teams A strong & robust backend is needed for: ☘️ Table registration and tag management. ☘️ Applying row level filtering and column masking on tables. ☘️ Assigning permissions on UC objects. Doing this manually will cause delays and sync issues. #Databricks #UnityCatalog #DataGovernance #Lakehouse #DeltaLake #DataPlatform

Everyone's freaking out about GEO, LLMO, and AEO. After 7 months of running tests across tons of sites… I can tell you this: It's all built on SEO fundamentals. The same principles that rank you on Google also get you cited in ChatGPT, Claude, and Perplexity. So before you buy into shiny new tactics that promise “AI visibility”…here's what actually moves the needle: 1. Trust Signals AI tools pull from review platforms to assess business credibility and expertise. Build trust signals in the right places: - Local businesses: prioritize Google Business Profile reviews and responses - SaaS companies: maintain strong G2 and Capterra profiles  - Ecommerce: focus on Trustpilot or industry-specific review platforms - Respond to reviews professionally and keep profiles updated 2. Document Structure LLMs love well-structured documents. Instead of optimizing just for human readers, structure content for AI platforms too: - Add company context throughout documents. Instead of "our latest update," write "Acme Corp's Q4 2024 update" - Use clear headings and comprehensive sections that can stand alone - Include key facts in multiple formats (inline text, bulleted lists, data tables) 3. Link Building for Relevance Quality and topical relevance matter more than quantity for AI visibility. Focus your link building efforts: - Target industry-relevant sites where your brand mention makes logical sense - Pursue guest posts and collaborations within your industry - Don't ignore nofollow links from high-authority sites in your niche - Seek brand mentions even without direct links. (the mention itself carries weight) Avoid completely unrelated sites. 4. Topical Authority Still Rules LLMs are trained on the same web content that Google indexes. The more deep, high-quality content you publish around your niche, the more AI systems recognize you as the go-to source, the more you get mentioned. Take out the trash. Delete random blog posts about topics unrelated to your business. They're actually hurting your AI visibility. 5. Be everywhere LLMs crawl Repurpose your content across Reddit, Medium, LinkedIn, and YouTube. These platforms get crawled heavily by AI, and showing up on them regularly builds brand visibility. LLMs love patterns. The more places they see you, the more they assume you’re an authority. 6. Technical setup - Use HTML-driven pages - Add schema markup - Clean site architecture (no page more than 3 clicks from homepage) - Ensure your critical content loads server-side (most AI crawlers don't render JavaScript) 7. Traditional Search Feeds AI Most AI tools use Bing or Google's index for real-time data. Better search rankings directly improve AI visibility.

Leaders need to have reserves of resilience to deal with crises as they arise. If as a leader you are depleted and running on empty when a crisis occurs, it's very hard to operate at your best. The world got a lesson in the value of supply chains and the consequences of what happens when they break down during the pandemic. But for supply chains to be always on, the people who run them can’t be. And that goes for all of us, even if we don't work in supply chains!   Here is some advice I shared with supply chain leaders at the Association for Supply Chain Management (ASCM)'s Connect 2024 conference. ➡️  Most important: You have to put on your own oxygen mask first. Too many leaders still buy into the misguided notion that urgent or chaotic times require them to be in constant motion and always on, or that they somehow have to match the frenetic pace of the moment. In fact, the opposite is true. Because it is judgment that we need from leaders in moments of crisis, not just stamina. So it starts with prioritizing well-being for yourself, and being a role model for well-being to give others the permission to do the same. ➡️ Technology is a double-edged sword: Technology accelerates burnout when we try to be always on. What's funny is how much better care we take of our technology than ourselves. But unlike machines, humans have to unplug to recharge. In the human operating system, downtime is a feature, not a bug. ➡️ The qualities that define a successful leader: Empathy, being able to listen, being open to new voices. Not just being a broadcaster all the time, but being a receiver as well. It first requires not constantly being in fight-or-flight mode. We can’t be open to others and their creativity and innovation when we’re marinating in stress hormones and just trying to get through the day or through the next hour. ➡️ To create a Thriving Culture: Communication is key! One of our core values at Thrive is Compassionate Directness, which empowers team members to surface feedback or any problems and challenges they’re having in real time. That allows not only team members to course-correct and grow, but the company as well. In any company, and certainly in supply chains, there are obstacles to growing the bottom line. There are challenges with engagement and innovation. Wouldn’t you want to know those sooner rather than later? Knowing them — and getting to work in solving them — in real time as they arise has huge benefits to all the metrics that go into the bottom line. ➡️ And finally: Well-being needs to be embedded into the fabric of company culture and into the workflow. A company is only as resilient as its people so an investment in the healthy future of your employees is an investment in the future of your company. To build resilience into your industry, you have to build it into your people.

McKinsey & Company shows how Danone turns operations into a growth engine. A sharp interview by Pierre de la Boulaye and Søren Fritzen with Vikram Agarwal highlights a structural shift across the FMCG industry. For decades, operations were treated as a cost center. That paradigm is changing. Leading companies now position operations as a driver of growth and competitiveness. The transformation at Danone shows how AI, digital manufacturing and advanced supply chains are reshaping the sector. Several insights stand out. 1) AI turns factories predictive Operators increasingly monitor production lines via tablets instead of control rooms. AI systems detect potential equipment failures before they occur, for example overheating motors in packaging lines. Maintenance shifts from reactive repair to predictive intervention, improving uptime and efficiency. 2) Capacity planning becomes strategic Danone distinguishes three ways to build manufacturing capacity: • Release capacity from existing assets • Transform capacity by converting underperforming lines • Create capacity through new production investments Transforming existing lines enables growth with much lower capital intensity than building new factories. 3) AI reshapes supply chains Danone uses AI models to forecast ingredient costs and supply chain dynamics across global agricultural markets. Instead of analyzing thousands of variables, systems process millions of data points. For a company managing roughly €13.7B in COGS, forecasting accuracy becomes a competitive advantage. 4) Digital manufacturing at scale Danone’s Digital Manufacturing Acceleration program already covers 80+ factories, with 40 more joining soon, across 140+ production sites globally. The ambition goes beyond Industry 4.0 toward Industry 5.0, combining machines, AI and human expertise. 5) People remain central Danone employs 47,000+ people in operations, about half of its workforce. Through its Industry 5.0 Academy, the company has already trained around 20,000 employees in digital manufacturing capabilities. Why this matters The global FMCG industry generates over $4 trillion in annual sales and operates on tight margins. Even small improvements in forecasting, manufacturing efficiency or capacity utilization can translate into billions in value creation. As demand shifts toward health, high-protein and plant-based products, supply chains must become faster and more flexible. AI-driven operations are becoming a strategic advantage. The signal for FMCG leaders is clear: Competitive advantage is increasingly built beyond brands and marketing — in operations. #operations #manufacturing #ai #digitaltransformation #foodindustry #foodtech #retailtech #innovation #procurement #datadriven #danone #france #europe #startup #investors #marketing #sales #technology #logistics

Open Banking is a misleading term. Because it makes you think that it’s a variation of banking, whereas in fact it goes far beyond. Let’s take a look. The name comes from the idea of opening up financial information, usually held by banks, to third parties (i.e. FinTechs) so that they can build #innovation on top of existing structures. Which is exactly the reason why OB is not confined to a few, big regulated financial institutions, but it tries to disperse the benefits that come via the access of data to the entire FS ecosystem. The OB value proposition consists of 4 main elements: —    open APIs acting as the connecting rails —     #data as the overarching element —    an open, cloud-based landscape consisting of closely intertwined services running across marketplaces, platforms and ecosystems —    a shift from vertical silos and legacy infrastructure to an open set-up   Here is why OB is such a big game changer: 1. OB converts web APIs - the technology behind the fintech revolution – into open APIs, bringing about what we call APIsed #finance: building value directly from sharing, providing and leveraging access to data.   2. OB has become the main enabler of the two (most) dominant business models of our time a) Platform economics b) Embedded finance 3. OB is broadening the opportunity scope of the entire FS ecosystem by a) delivering better services b) finding novel growth sources c) improving the appeal of existing FS 4. OB fundamentally changes not only the structure of the FS value chain, but also its breadth and reach by a) involving a plethora of new actors (i.e. governments, regulators, API standardization bodies, industry associations) b) forcing old ones (i.e. banks) to radically reposition themselves 5. Via OB we are witnessing for the first time in a long time the build-up of a new infrastructure layer that is quickly becoming the foundation of the digital #economy These are my picks for the most important trends shaping OB going forward: —  In its initial conception most of the OB models globally have focused on use cases that evolve around the account: aggregation & visualization, verification, access to balances or payment initiation.  The next phase of the journey – known under the term open finance – is driving contextual, predictive, and hyper-personalized experiences across the board (i.e. savings, lending, investments, insurance) —  Look at both Europe and the US and data is in the driving seat. Mainly in 2 ways: 1) customers are being given control of their financial data 2) data monetization models take center stage —  The matching of OB with instant payment rails will become a killer combination —  The synergies between AI and OB will increase exponentially: AI-driven insights on top of OB data access, mass personalization, etc —  OB use cases for non-traditional players (i.e. telcos, insurers, retailers) will proliferate Opinions: my own, Graphic sources: WhiteSight, AFS, Brankas, Spire    

Sitting in Epic’s massive UGM auditorium, the 100+ new AI features didn’t feel exciting. They felt overwhelming. Because it’s clearer than ever: AI is on an exponential curve, while humans and healthcare orgs are stuck on a flat line, barely nudging the slope. The gap isn’t a technical one — it’s change management. And until someone closes it, AI will keep sprinting ahead. I’ve rolled out tech to physicians for a decade. The hardest part is never the software; it’s the change management. Especially in healthcare, where you can’t just close the office for an "AI inservice." Doctors are already sprinting — 100 patients a week, fires everywhere — and just when they finally get comfortable with one workflow, someone moves the button they’re supposed to click. The most common complaint I hear? 𝘏𝘦𝘺, 𝘺𝘰𝘶 𝘮𝘰𝘷𝘦𝘥 𝘮𝘺 𝘤𝘩𝘦𝘦𝘴𝘦! Which brings me to the paradox doctors live every day: 👩⚕️ There’s no time for doctors to train or learn — because that means lost revenue. Everyone wants max efficiency out of us, but also zero errors. 📱 Tech companies brag about “hallucination-free copilots” but won’t take responsibility when they’re wrong. The fine print: the clinician is always liable. 👨⚕️ Doctors are left carrying the load: supposed to instantly learn, perfectly apply, and reconcile both demands — while still doing the actual job. And if you think AI will just replace doctors? All you’ve done is shove the change management onto patients. Good luck with that. Need proof this isn’t just doctors? Linkedin News says 41% of professionals report AI’s pace is taking a toll on their well-being — and more than half say learning AI feels like a second job. The ultimate winners here are those who can educate and do change management the best.