Connecting the United Kingdom through sustainable infrastructure
Morgan Sindall Infrastructure is a Business Reporter client
A personal reflection from a company that supports the UK's connectivity through infrastructure, with a workforce of over 2,000 employees playing their role in delivering sustainable infrastructure across seven key infrastructure sectors.
Every day, the UK's infrastructure connects us in ways we often take for granted. It's everywhere, and it's always a hot topic, especially when it comes to energy.
But as the country's population grows and its assets age, the demand on existing infrastructure skyrockets. The government's Clean Power 2030 Action Plan sets ambitious goals: 43 to 50GW of offshore wind, 27 to 29GW of onshore wind and 45 to 47GW of solar power, all aimed at drastically reducing our reliance on fossil fuels.
Energy has been in the spotlight for years, but recently, three critical factors have driven the urgent need to upgrade our energy infrastructure: affordability, security of supply and environmental impact. These elements have never been more crucial.
Affordability
Remember the cost-of-living crisis? While the term might not be as common now, we're still feeling the pinch with rising energy bills. This doesn't just affect our daily expenses; it ripples down the supply chain, increasing the cost of the products we buy and use.
Security of supply
Global unrest, such as the war in Ukraine, has highlighted the need for national resilience. As conflicts continue, the importance of home-grown power becomes clear. We need to be self-sufficient to ensure a stable energy supply and cut down the spikes we see in costs.
Environmental impact
This is a big one. We all have a role in reducing our environmental footprint. In November 2024, world leaders gathered at COP29 to discuss this very issue. Our demand on electricity networks will only grow, especially with the rise of electric vehicles. There are now around 1.8 million electric and hybrid vehicles in Britain, increasing the strain on our already pressured energy network. Adding yet further to this is our increased technological requirements, in an era where technology is playing a far more central role in reducing our environmental impact.
This is why infrastructure connectivity is so vital and why it's a top priority for the government. To put the challenge into perspective, the industry will deliver more infrastructure upgrades in the next decade than in the past three combined.
In 2024, National Grid announced the Great Grid Partnership, a groundbreaking initiative we are proud to be part of.
This partnership aims to accelerate the delivery of essential national electricity infrastructure by addressing UK supply chain and skills issues. By co-ordinating planning and execution, each supplier can pool its resources, skills, insights and experience with those of the National Grid. Meanwhile, ScottishPower Energy Networks announced a major contract in 2024 to undertake the biggest rewiring of the electricity grid since its inception.
As a tier-one contractor in the infrastructure sector, we at Morgan Sindall Infrastructure understand the critical role we play in upgrading the network and are committed to this mission alongside our supply chain partners.
A key enabler to the above is our supply chain and skills. The upgrade of the network will create jobs and opportunities for thousands of people, but the scale and size of the project is so large it provides longevity of work up and down the supply chain.
To start preparing to meet demand, in early 2024, we opened our first overhead lines training centre in Staffordshire. The training centre has been designed to upskill and train individuals who will be working on upgrading and erecting the overhead lines and towers. This is a unique experience and skillset, but one that will be a key enabler for the mission to be met.
Our supply chain family also bring their own increased skillsets. Whether they be an SME or tier two contractor, the delivery of the energy infrastructure, as highlighted in some of the delivery frameworks announced last year, will be down to collaboration. Our longstanding relationships with our supply chain partners are essential to the successful delivery of our projects. Our supply chain network is part of our extended team, delivering high-quality solutions and services. The Morgan Sindall Supply Chain Family consists of more than 415 members who benefit from tailored training, on-site advice, access to contract information and dedicated relationship management teams.
Our relationship with the Supply Chain Sustainability School (SCSS) remains a critical partnership for delivering climate-related education to our suppliers to drive down value chain emissions. As shared at the start, one key enabler for the energy sector is environmental impact.
We are proud to play a part in delivering a new UK energy infrastructure for the future, and alongside our robust and ever-growing supply chain network we are committed to supporting a stronger energy network for tomorrow, along with all the other infrastructure that we are rely on and use each day.
Morgan Sindall Infrastructure delivers some of the UK's most complex and critical infrastructure across seven core sectors: energy, water, nuclear, highways, rail, defence and aviation for public and private customers. Working on projects and long-term frameworks, we believe in connecting people, places and communities through innovative and responsible infrastructure. Through our expertise, we harness innovative ideas and approaches that enable us to safely and responsibly design and deliver resilient infrastructure.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
The Independent
3 days ago
- The Independent
The hidden cost of tech complexity – and what you can do about it
Freshworks is a Business Reporter client Most tech solutions promise simplicity but deliver chaos, costing time, decisions and connection – it's time for change. As companies grow, they often move fast. New markets, new customers, new demands. But growth tends to bring a flood of quick tech purchases – each solving a specific problem, each adding another layer. Before long, the very tools meant to enable speed begin to slow everything down. It's a familiar trap: complexity creeps in quietly. A duplicate process here, a siloed system there, and suddenly teams are misaligned, data is fragmented and performance suffers. Complexity is the enemy of scale As a tech leader with experience across the sector, I've seen this pattern repeat across industries and continents. Businesses of all sizes end up fighting the same invisible force: fragmentation. Teams operate from conflicting versions of the truth. Manual handoffs and makeshift integrations clog up workflows. And tech investments stall before delivering value. And it's not just operational. Fragmented systems slow down operations and obscure visibility. When your support desk, product analytics, customer database and financial systems can't communicate effectively, you're essentially making decisions without real insight. Take customer retention. If your support platform can't surface relevant in-app behaviour or billing anomalies, your team can't intervene at critical moments. That's not just a missed support ticket – it's a lost customer. Worse, it may signal dozens more if warning signs aren't shared across departments. Good intentions, bad outcomes Ironically, fragmentation often stems from good intentions. Departments adopt specialised tools to solve local challenges. But without a coherent architecture or integration strategy, organisations end up with tech stacks that resemble patchwork quilts and intelligent automation falls flat. It's what Stanford researchers Bob Sutton and Huggy Rao, authors of The Friction Project, call 'addition bias' – the instinct to add features, tools or steps instead of removing them. In their study of global brands, this tendency increased friction and slowed performance. Simplifiers, they found, often faced resistance, while adders, those who added complexity, were rewarded – even when performance suffered. Too often, organisations are sold bloated platforms packed with unused features, marketed as 'added value' but delivering the opposite. Implementations drag on for months, results take years, and the very tools meant to empower teams end up complicating their work. Meanwhile, the real cost is paid by employees, who now spend their time navigating systems rather than solving problems. AI only works if it's connected Artificial intelligence has enormous potential to accelerate business. But that promise breaks down fast without integration. Disconnected systems can't fuel automation and half-built workflows create more work – not less. But when applied strategically, AI delivers real results. Finance teams can analyse costs and optimise spending in real time. Support teams can use AI-powered agents to handle routine support tasks. Engineering can automate troubleshooting. HR can screen candidates more efficiently. And the payoff is clear: 98 per cent of employees are already getting time back in their workday thanks to AI – reinvesting it in higher-value efforts such as boosting productivity (71 per cent), coaching others (67 per cent) and tackling more creative or complex challenges (66 per cent). When AI is properly integrated across functions, it doesn't just streamline operations. It empowers people. Escape the cycle: a strategic path to uncomplicating systems The good news? It's possible to break the cycle. Here's how forward-thinking organisations are simplifying by design: Inventory everything. Map every tool across departments. You can't fix what you can't see. Use workflow automation to identify data gaps, redundancies and ownership. Prioritise integration. Evaluate platforms for open APIs and native integrations. Tools that don't integrate easily should raise red flags. Unify your data. Create a single source of truth for customer information – whether via a centralised platform or a modern data unification layer. Ensure every team works from shared insights. Designate integration leaders. Empower individuals or teams to connect departments, break silos and ensure systems integrate strategically, not reactively. Collaboration tools help align efforts. Think in platforms, not point solutions. Consolidate where it makes sense. Choose platforms that support multiple workflows – not only for current needs but also for future direction. Simplicity as a competitive edge Customer experiences are powered by the systems employees use every day. That's why tech leaders must focus on alignment, not just implementation. Sustainable speed doesn't come from scattered bursts of progress. It comes from unified momentum. In any context – business, productivity or daily operations – complexity breeds inefficiency, higher costs and slower decisions. Simplicity unlocks focus, clarity and results. For teams, unnecessary complexity causes stress and burnout. Simplicity fuels effectiveness. So the question leaders should be asking isn't whether they can afford to simplify. It's whether they can afford not to. At Freshworks, we believe simplicity isn't a sacrifice. It's a competitive edge. It's time to uncomplicate and get maximum value from your tech stack.
The Independent
3 days ago
- The Independent
The AI transformation in construction risk management
CMiC is a Business Reporter client How AI-powered predictive analytics are bringing enhanced cost control, safety and quality and proactive decision-making to supply chains. Construction has always been an industry fraught with uncertainties. From fluctuating costs and delayed materials to safety incidents and quality concerns, risk management in this industry has traditionally relied on experience, intuition and reactive problem-solving. But while these approaches have proved adequate in the past, today's construction projects face unprecedented challenges: tighter profit margins, compressed timelines and increasingly stringent regulations. In this high-pressure environment, artificial intelligence (AI) has emerged as a transformative force, shifting the industry from reactive problem-solving to proactive risk prevention. By leveraging advanced algorithms, machine learning and real-time data analysis, AI is revolutionising how construction firms identify, assess and mitigate risks across multiple fronts. Predictive analytics: foreseeing cost and scheduling risks Cost overruns and schedule delays have long affected construction projects. Traditional forecasting methods – relying on historical trends and manual calculations – often lack precision, leading to budget miscalculations and unforeseen disruptions. AI-driven predictive analytics offers a more accurate alternative. By processing historical project data, supplier reliability metrics, labour productivity rates and environmental variables, machine learning models can identify risk patterns that signal potential delays. Supply chain bottlenecks, labour shortages and weather disruptions become predictable, allowing project managers to implement preventative measures before setbacks occur. The adaptive nature of AI further enhances its predictive capabilities. As new data flows in, algorithms continuously refine their predictions, creating a dynamic risk management system that evolves throughout the project lifecycle. Resource planning receives a significant boost from AI's real-time data analysis capabilities. Construction sites generate vast quantities of information through equipment sensors, workforce tracking systems and material logs. AI processes this data stream to optimise resource allocation, preventing shortages and minimising downtime. Smart scheduling tools dynamically adjust project timelines, ensuring isolated delays don't cascade through the entire construction sequence. Financial oversight also benefits from AI integration. Algorithms scan procurement records, subcontractor bids and invoices for inconsistencies, flagging discrepancies before they escalate into budget overruns. When combined with real-time financial tracking, these tools provide construction firms with unprecedented visibility into spending trends. AI-driven safety: preventing accidents before they happen Safety concerns remain paramount in construction. Traditional safety measures – training programs, manual inspections and compliance checks – help mitigate hazards but often fail to prevent incidents proactively. AI introduces a transformative approach to safety management through real-time risk detection and predictive threat assessment. AI-powered cameras analyse live video feeds from job sites, identifying unsafe behaviours. When these systems detect a risk, they trigger automated alerts to safety managers, enabling immediate intervention. Wearable technology amplifies AI's safety impact. Smart helmets and vests equipped with biometric sensors monitor worker fatigue, heart rate and environmental exposure. AI analyses these signals to detect signs of exhaustion or hazardous conditions, alerting supervisors when predetermined risk thresholds are crossed, thereby reducing accidents caused by human error. Predictive safety analytics adds another protective layer. By analysing historical incident reports, weather patterns and project schedules, AI models identify when and where safety risks are most likely to emerge. This allows site managers to proactively adjust work schedules, reinforce training or implement additional protective measures in high-risk areas. Compliance management also benefits from AI automation. Natural language processing tools review safety documentation and incident reports, ensuring regulatory standards are met while reducing manual paperwork burdens. Quality control: minimising defects and failures Construction defects lead to costly rework, project delays and potential structural failures. Traditional quality control methods – manual inspections, material testing and compliance checks – are effective but limited by human oversight constraints. AI strengthens quality assurance through automated inspection processes and early inconsistency detection. Computer vision and deep learning algorithms analyse images and video from job sites, with AI-powered drones and robots scanning buildings for defects often invisible to the human eye. These systems detect cracks, misalignments and improper installations early, reducing expensive corrections later. Material performance assessment improves through machine learning models that analyse supplier records, environmental conditions and past project outcomes. If materials show failure likelihood, AI flags them before installation, ensuring only specification-compliant materials enter the construction process. Building information modelling (BIM) integration further enhances quality control. AI-enabled BIM platforms compare design blueprints with actual construction progress, triggering alerts for any deviations and allowing timely corrections. AI simulations also test structural resilience under various stress scenarios, ensuring compliance with engineering standards before material placement. Supply chain and labour risk management Supply chain disruptions and workforce shortages pose significant project risks. Traditional planning methods often fail to anticipate these challenges, relying on historical data and reactive decision-making. AI-driven procurement systems analyse market trends, supplier performance and geopolitical factors to predict material shortages and price volatility. These systems recommend alternative suppliers, optimise order timing and adjust procurement strategies before disruptions occur, helping firms minimise supply chain-related delays. Material tracking improves through AI-powered logistics platforms using RFID sensors and IoT devices to provide real-time shipment visibility. Automated scheduling tools adjust deliveries based on project timelines, preventing material shortages and excess inventory. Labour shortage risks decrease through AI-enhanced workforce analytics that assess skill availability, predict labour gaps and recommend hiring or training strategies. These systems optimise workforce distribution by matching assignments with workers based on skill level and availability. Automation further mitigates labour risks, with AI-powered robotics handling repetitive tasks such as excavation and bricklaying, allowing human workers to focus on higher-value responsibilities. The human-AI partnership Despite AI's transformative potential, human expertise remains essential in construction risk management. The most effective frameworks integrate AI capabilities with institutional knowledge, ensuring that algorithmic insights align with on-site realities. Successful firms combine AI risk assessments with superintendent evaluations, continuously validate models with field data and maintain transparent accountability structures across all stakeholders. This balanced approach leverages AI's data processing power while preserving the irreplaceable value of human judgment and experience. As construction firms increasingly adopt these technologies, they will not merely reduce project risks – they will fundamentally redefine how projects are planned, executed and completed. In an industry where margins are tight and expectations are high, AI-powered risk management represents not just an advantage but a necessity for future success.
The Independent
3 days ago
- The Independent
Retail engagement has evolved – time for your strategy to catch up
Marigold is a Business Reporter client To grow customer lifetime value, today's retailers must master AI-powered, data-driven engagement across every channel. You're a retail or e-commerce marketer focused on what really matters: growing customer lifetime value (LTV). You know that keeping customers engaged is the only way to earn repeat purchases, increase order values and turn one-time buyers into advocates. And you know that AI tools such as predictive product recommendations or audience optimisation can accelerate those goals. But here's the challenge: none of it works if your engagement strategy is stuck in the past. Today's shoppers move fluidly between channels, from app to inbox to store and back again. They expect every interaction to be relevant, respectful and informed by what you already know about them. That means your marketing can't just be cross-channel in theory. It has to be unified in practice. Here are three key plays every forward-thinking retailer should have in their playbook, powered by real consumer data and practical, AI-enabled strategies to help you modernise your engagement and grow LTV in 2025 and beyond. Play #1: Unified data = unified experiences Insight from the Consumer Trends Index: Nearly one-quarter (24 per cent) of consumers say that a consistent digital experience across a brand's website and mobile app is more important than price when making a purchase decision. Shoppers expect your brand to know them, whether they click through from an email, tap on a mobile app or walk into a store. But that level of consistency is impossible without connected systems. When your data lives in silos, your customer experience does too. The Consumer Trends Index shows how varied channel preferences really are. Email continues to lead, with 54 per cent of consumers making a purchase through that channel in the past year. But dig into the age data, and the picture shifts: 57 per cent of 25- to 34-year-olds made a purchase from a social media post. The takeaway? Channel preferences differ by audience. This means it's not enough to just show up across channels. You have to connect them to each individual's preferences. Unified data lets you build real-time profiles and deliver experiences that feel seamless and personal, not disjointed or repetitive. That's the foundation of modern engagement and long-term growth. Key to success: Break down your data silos. Align your teams and tools to deliver one connected experience, no matter where the customer appears. Play #2: Earn trust through privacy-first personalisation Insight from the Consumer Trends Index: 73 per cent of consumers react positively to product recommendations based on past purchases, but 53 per cent find ads based on third-party cookies invasive. This highlights a preference for personalisation based on data that naturally exists within the brand relationship, such as purchase history or interactions on owned channels. Privacy isn't just a compliance checkbox. It should be part of your brand experience. Customers want transparency, control and relevance. When brands design with privacy in mind and personalise based on data, it makes sense for them to earn trust and engagement. With the decline of third-party cookies and stricter regulations, zero- and first-party data are becoming the most reliable, privacy-safe sources of insight. These data types, whether shared intentionally by the customer or captured through direct interaction, help marketers create personalised experiences that feel helpful, not intrusive. Used responsibly, this data creates a virtuous cycle: transparency builds trust, trust encourages sharing and more data leads to more relevant experiences. Key to success: Put privacy at the heart of your personalisation strategy. Be transparent, earn trust and turn every data point into a better customer experience. Insight from the Consumer Trends Index: 79 per cent of consumers say they are likely to engage with personalised emails tailored to their interests. AI is transforming how marketers connect with customers, making every touchpoint smarter and more effective. Predictive modelling helps forecast outcomes such as purchase intent or churn risk, allowing teams to trigger personalised journeys, update segments or adjust spend with greater confidence. It also powers better timing and content decisions. Send-time and subject-line optimisation ensure messages arrive when they're most likely to be opened. At the same time, personalisation engines dynamically surface the right content or product across channels based on behaviour and affinity. Done well, it's the digital version of your best in-store associate: present, helpful and never intrusive. Key to success: Use AI to enhance, not replace, the human element. Let technology power the timing, while your brand voice delivers the message. The future of retail engagement is smarter, not more complex. It's not rocket science, but it does require diligence. You need to do the groundwork and connect your data. Only then can you deliver the meaningful engagement that today's customers expect. That includes personalising with purpose, respecting privacy at every touchpoint and using AI to act with precision. When you connect the dots behind the scenes, you create seamless, relevant experiences that deepen relationships and grow long-term value.
