[ INSIGHT ] ARTIFICIALINTELLIGENCE
by Sean O’Neill CPTO, Syncron info@syncron.com | +46 8 410 802 00
Unlocking Revenue Growth With AI In the modern service economy, businesses face growing pressure to deliver value-driven customer experiences while maximizing profitability. Yet, many organizations remain tethered to outdated tools and manual processes that hinder operational efficiency and scalability. According to Syncron’s 2024
of supply chain operations. Predictive maintenance and service lifecycle management tools are pivotal in this transition, enabling businesses to extend the life of their products and parts while reducing environmental impact. AI-powered platforms play a critical role here, offering predictive insights into parts usage, inventory needs, and service demands. For instance, by anticipating when a critical component will fail, businesses can proactively allocate resources and reduce costly downtime.
metrics are aligned with overall business priorities. By accurately predicting both planned and unplanned material and labor expenses, these tools empower businesses to maintain margins while delivering transparent, value-driven pricing to customers, and ultimately, driving organizational goals. ENHANCING CUSTOMER SATISFACTION The potential extends to tailored, outcome-based service contracts that can not only drive predictable revenue but also enhance customer satisfaction and loyalty. When businesses can simulate pricing scenarios and adjust in real time to market conditions, they position themselves as agile, customer- centric leaders. Beyond pricing, the transition to a circular economy represents a transformative opportunity for organizations to drive revenue growth while advancing sustainability. Unlike traditional linear models, a circular economy focuses on reducing waste by repairing and reusing materials. For OEMs and service providers, this shift demands a fundamental rethinking
Modernizing the Aftermarket report, 38% of organizations still rely on spreadsheets to manage spare parts inventory – an alarming statistic in an era where AI is transforming industries. This reliance on outdated tools leads to inefficiencies that ripple across supply chain operations. Modernization is no longer optional; it’s a business imperative. Transitioning from manual processes to automated solutions powered by artificial intelligence (AI) and machine learning can streamline operations, enhance decision-making, and deliver actionable insights that drive profitability. One overlooked area of opportunity lies in pricing. Traditionally, pricing strategies have relied on historical data and market averages, often failing to reflect real-time market conditions or actual costs. This gap leaves significant revenue potential on the table, especially as organizations shift toward outcome-based service models. AI-powered solutions offer a new approach to pricing, leveraging machine learning to forecast costs, predict risks, and optimize contract pricing in real time, while also ensuring service
Implementing innovative, data- driven solutions not only ensures
accurate tracking of demand trends for minimizing waste and reducing carbon emissions but also enables manufacturers or distributors to gain end-to-end visibility and control over their service lifecycle. It makes it easier for companies to adopt and scale powerful new aftermarket strategies and high-margin business models, such as servitization and equipment-as-a-service, supporting them to differentiate themselves in the market and drive long-term growth. The convergence of AI, advanced pricing strategies, and circular economy principles marks a turning point for the service economy. By embracing cutting-edge solutions, businesses can unlock significant revenue growth while positioning themselves as sustainability and innovation leaders. n
22 Inbound Logistics • June 2025
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