Capacity Utilization Enhancement

A tiny utilization increase could be worth over €2 million for the average CPO. Even one extra top-up charge can unlock millions in additional revenue—without adding a single new charge station. • Current average utilization rates in Europe are approximately 17%. And that's me being generous. • Each connector is used for around 4 hours daily, delivering an average of 125 kWh. • A 10 min utilization increase per connector adds over 5 kWh a day. • At an average revenue of €0.60 per kWh, that's €3 extra per day per connector. • Or over €1000 extra per connector per year. For an average EU CPO managing 2,000 connectors, that's €2.2 million in extra revenue from just one additional 10-minute top-up charge. That's significant growth — and without building a single new station. So, what’s keeping CPOs from increasing utilization? CPOs have been set up like highly subsidized real estate companies. They were focused on capturing market share and securing high-value land concessions. As the market matures and funding requirements change, they must transition to selling electrons. If we want to create a market selling electrons to personal and commercial drivers, the real question in most regions isn’t how to build more chargers—it’s how to get more drivers to the ones we already have. More hardware won’t increase utilization. Dynamic pricing won’t help users find your station. Owning the driving and charging journey is the only way to move the needle. Drivers make charging decisions before they get into their vehicles, and they want a better user experience than an ICE. The CPOs who understand this aren’t waiting for utilization to improve—they’re taking control of it. • Their stations appear in front of drivers when they’re planning their trips. • They make their stations attractive and amenity rich • Their network is prioritized in route planners. • They guide drivers to their chargers instead of hoping they show up. And this works. Chargetrip routing sends over 30 GWh of energy demand to our customers every month, and they see their utilization go up. The highest-grossing CPOs in Europe use routing to steer energy demand. CPOs understanding the driver journey and using strategic demand management through routing aren’t just increasing utilization. They’re securing millions in additional revenue without adding a single new charger.

𝐀𝐖𝐒 𝐣𝐮𝐬𝐭 𝐥𝐚𝐮𝐧𝐜𝐡𝐞𝐝 𝐄𝐂𝟐 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲 𝐌𝐚𝐧𝐚𝐠𝐞𝐫 - 𝐚 𝐠𝐚𝐦𝐞-𝐜𝐡𝐚𝐧𝐠𝐞𝐫 𝐟𝐨𝐫 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐜𝐥𝐨𝐮𝐝 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 If you're managing EC2 infrastructure at scale across multiple accounts and regions, you know the pain: jumping between Cost Reports, CloudWatch, EC2 APIs, and the console just to understand your capacity utilization. That operational overhead ends now. 𝐖𝐡𝐲 𝐲𝐨𝐮 𝐬𝐡𝐨𝐮𝐥𝐝 𝐜𝐚𝐫𝐞: EC2 Capacity Manager consolidates ALL your capacity data into a single dashboard - On-Demand, Spot, and Capacity Reservations across every account and region. No more custom automation or manual data collection. 𝐓𝐡𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐢𝐦𝐩𝐚𝐜𝐭: • Identify underutilized Capacity Reservations instantly (direct cost savings) • Analyze Spot interruption patterns to optimize workload placement • Cross-account visibility for enterprise-wide capacity optimization • Automated prioritized optimization recommendations 𝐊𝐞𝐲 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: • Unified view of capacity metrics with hourly refresh • Historical data analysis (90 days via console, extended via S3 exports) • Granular filtering by account, region, instance family, and AZ • Direct reservation management from the interface • AWS Organizations integration for centralized governance The technical win: Instead of building custom solutions to aggregate capacity data from multiple AWS services, you get enterprise-grade analytics out of the box. Available at no additional cost in all commercial regions. For organizations running hundreds of instance types across complex multi-account environments, this eliminates weeks of custom development while providing insights that directly impact your cloud spend optimization. Time to consolidate your capacity management workflow. Get more details in this launch blog - https://lnkd.in/gjqSPkVw #AWS #CloudOptimization #EC2 #CostOptimization #CloudArchitecture

How much more could #supplychain operations achieve by using #AI to automatically optimize for consistent flow? The numbers might surprise you.    Many operations stop and start too frequently for the purpose of preventing congestion at bottlenecks and managing work prioritization. The common approach of a "wave" in work planning is an example of that tradeoff - wave-based planning sacrifices resource utilization for better bottleneck and flow management. Other manual work planning methods share similar characteristics. What most of us don't think about is the cost of all that stopping and starting can be as much as 20% of overall operational capacity based on what we've seen in data from our customers and prospects! That adds up to as much as 12 idle minutes per hour for all your people and machines! The hard part is that it rarely comes 12 minutes at a time. Instead, it comes 30 seconds or a minute at a time per resource spread over multiple events in the course of an hour at unpredictable intervals. There is no way for a person to see all these relatively brief events and do something to avoid them because everything is moving too quickly, and the operation "looks busy". Operational #AI removes gaps and maintains consistent flow by continuously releasing the right work to the right resource at the right time to maximize overall resource utilization while also proactively preventing congestion, orchestrating work execution, and responding in real-time to changes in demand and resource availability. What is the capacity impact of manual work planning on your operation?

𝐈𝐬 𝐘𝐨𝐮𝐫 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐑𝐞𝐚𝐝𝐲 𝐭𝐨 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐆𝐫𝐨𝐰𝐭𝐡, 𝐨𝐫 𝐈𝐬 𝐈𝐭 𝐇𝐨𝐥𝐝𝐢𝐧𝐠 𝐘𝐨𝐮 𝐁𝐚𝐜𝐤? One Aerospace & Defense client, a global leader employing over 87,000 people across 40+ countries, faced this exact challenge. With new long-term contracts fueling rapid growth, their shared warehouse operation struggled to keep up: • 85% 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐮𝐭𝐢𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 created a space crunch. • 3-𝐝𝐚𝐲 𝐩𝐢𝐜𝐤 𝐜𝐲𝐜𝐥𝐞 𝐭𝐢𝐦𝐞𝐬 delayed critical orders to the production line. • Poor layout forced pickers to waste time searching for parts. • The receiving dock became a bottleneck, slowing inbound inventory. • No strategic staffing plan was in place to manage future growth. 𝐓𝐡𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: We partnered with the client to re-engineer their warehouse operations using a three-phase approach: 1. 𝐏𝐢𝐜𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 – Eliminated unnecessary tasks and designed a picking strategy to maximize output. 2. 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐑𝐞-𝐥𝐚𝐲𝐨𝐮𝐭 – Created product-based picking zones to improve accessibility and reduce travel time for both pickers and equipment. 3. 𝐑𝐞𝐜𝐞𝐢𝐯𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 – Streamlined dock operations to eliminate bottlenecks and established leadership processes with key performance metrics. CLICK HERE to read the case study: https://lnkd.in/gtFwm5jR 𝐓𝐡𝐞 𝐑𝐞𝐬𝐮𝐥𝐭𝐬: In less than a year, the client transformed their warehouse into a growth-ready operation: • 𝐈𝐧𝐜𝐫𝐞𝐚𝐬𝐞𝐝 𝐩𝐢𝐜𝐤𝐢𝐧𝐠 𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐲 𝐛𝐲 42% (from 4 picks/hour to 7 picks/hour). • 𝐑𝐞𝐝𝐮𝐜𝐞𝐝 𝐨𝐫𝐝𝐞𝐫 𝐩𝐢𝐜𝐤𝐢𝐧𝐠 𝐥𝐞𝐚𝐝 𝐭𝐢𝐦𝐞𝐬 𝐛𝐲 67% (from 3 days to 1 day). • 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐫𝐞𝐜𝐞𝐢𝐯𝐢𝐧𝐠 𝐥𝐞𝐚𝐝 𝐭𝐢𝐦𝐞𝐬 𝐛𝐲 75%, allowing faster inventory turnover and fewer errors. 𝐋𝐞𝐬𝐬𝐨𝐧𝐬 𝐋𝐞𝐚𝐫𝐧𝐞𝐝: 1. 𝐂𝐚𝐩𝐚𝐜𝐢𝐭𝐲 𝐂𝐚𝐧 𝐁𝐞 𝐇𝐢𝐝𝐝𝐞𝐧 𝐢𝐧 𝐈𝐧𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐢𝐞𝐬 – Even a high-utilization warehouse can unlock capacity by streamlining processes and layout. 2. 𝐆𝐫𝐨𝐰𝐭𝐡 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐚 𝐏𝐥𝐚𝐧 𝐢𝐬 𝐑𝐢𝐬𝐤𝐲 – Rapid expansion without a strategy leads to bottlenecks that can threaten customer commitments. 3. 𝐌𝐞𝐭𝐫𝐢𝐜𝐬 𝐌𝐚𝐭𝐭𝐞𝐫 – Implementing the right KPIs allowed the client to manage growth proactively and sustain performance improvements. Is your warehouse prepared to handle future growth—or are inefficiencies quietly eroding your margins and delivery performance? #lean #leadership #culturechange #privateequity #manufacturing #alphanovaconsulting #operations #leanmanufacturing

Capacity Optimization (Optimization Part-5) Efficient PRB (Physical Resource Block) usage is crucial for improving DL user throughput. High PRB utilization can lead to network congestion and degraded performance, especially in areas with high traffic demand. Here's a breakdown: High Utilization Challenges (example): Carrier 1 - 800 MHz: •13% of samples show PRB utilization > 70%, resulting in DL user throughput < 4 Mbps. Carrier 2 - 1800 MHz: •7% of samples show PRB utilization > 90%, with DL user throughput < 4 Mbps. Ways to Cater to High Utilization: 1. Channel Optimization: Optimize channel allocation and resource scheduling to improve PRB efficiency. 2. Add New Sectors in Sites / Load Balance: New sectors can help distribute traffic evenly across the network, reducing congestion and improving throughput. 3. Enhance Antenna Technology: Leverage advanced antenna tech (e.g., MIMO) for better signal distribution and capacity handling. 4. Add New Sites / Carrier / Spectrum Refarming: Deploy additional sites to expand coverage and capacity. Implement spectrum refarming to repurpose underutilized frequency bands for more efficient resource use. Key Takeaways: • High PRB utilization is directly linked to poor DL throughput, especially in congested areas. • Capacity optimization strategies, including channel optimization, sector addition, and spectrum management, are key to enhancing network performance and user experience. By applying these strategies, operators can reduce congestion, improve DL throughput, and better cater to high utilization areas, ensuring optimal network performance. To learn more, refer to the course on RAN Engineering - https://lnkd.in/e9TpSHzF

Most factories already have the capacity they need; it’s just trapped in changeovers, imbalance, high buffers, and unclear standards. We buy machines to increase capacity. But it’s important to have a clear picture of the actual capacity vs. current utilization before making any investment decisions. Decisions to buy machines or hire more people can be very costly to the company. Manufacturing leaders can evaluate the actual capacity vs. current utilization. If I were in that situation, I would: 1️⃣ Pick a high-runner item and its process group. 2️⃣ Gather a small team of related people. 3️⃣ Draw a VSM to understand the process, lead time, changeovers, WIP, etc. 4️⃣ Calculate the takt time and cycle time of each process step. 5️⃣ Find the bottleneck process. From this point, you can understand whether the bottleneck process is a real bottleneck or a constraint. You can also understand what the hidden capacity is in the process. Before making any expensive investment decisions, your job is to unlock the buried capacity. Once you solve the bottleneck/constraint and smooth the process, you can always buy more machines for future growth—but not because of low production capacity without knowing the constraints. #optimizeacademy #continuousimprovement #processflowoptimization

3 Simple Fixes you can implement with zero capital for your capacity strapped biz: -------- Regardless of the industry I'm in I see businesses make mistakes in how they understand capacity. And here's how I'd solve them: 1️⃣ ) They confuse capacity and utilization Utilization is how often you use something. Capacity is more theoritical. Example: - Say a machine can make 1k widgets a week if it ran 24/7. - But it is only staffed 40 hrs a week and is maxed out those 40 hours. - I see businesses claim that their open capacity is ZERO. False. It's just the way you are staffing it. 👉 Fix # 1: do a true capacity analysis to understand your opportunities 2️⃣ ) They instantly go towards hiring people, instead of fixing their broken processes. In the above example, let's say you do staff 24/7. But your up time is 50%. You are constantly doing changeovers. Maybe the machines are always breaking down. Whatever it is, you are not EFFICIENT 👉 Fix # 2: determine your maintenance and scheduling issues. Then optimize those first before hiring. 3️⃣ ) Their operations have never been process mapped Every step, every SOP, every process, is mostly in someone's head. Instead of being: Mapped out. Optimized. Documented. And trained on. 👉 Fix # 3: process map your ops and optimize your operations. Reduce friction. TL;DR 👉 Fix # 1: perform capacity analysis 👉 Fix # 2: Optimize scheduling and maintenance 👉 Fix # 3: process map your ops and optimize. Reduce friction. If you need help with these, I've done them at every stop.