Symbol

US / Header

CaddiMenuBar

Core:Section

US / Footer

Explore our latest insights and strategies for procurement success. Visit now to stay ahead with valuable industry knowledge and actionable tips!

Resources

US / Resources

Explorer cover graphic for Saving Money in Manufacturing: Frequently Asked Questions, with the tagline Find opportunities to mitigate costs over a green rising arrow on a hundred-dollar bill.

Saving Money in Manufacturing

Explorer cover graphic for Cloud ERP, Procurement 101, with a stock photo of hands typing on a laptop overlaid with an ERP dashboard and analytics charts

The shift towards cloud-based solutions is driven by compelling advantages that directly impact the bottom line and operational agility of businesses:<ul><li>Improved Agility: For growing companies, agility is more than a buzzword; it’s a survival strategy. Cloud ERP endows businesses with the flexibility to scale operations, diversify product lines, and enter new markets with ease​​. Introducing sub-ERP systems to group subsidiaries or overseas branches is overwhelmingly easier with cloud ERP.</li><li>Enhanced Cash Flow Transparency: A vital aspect for any business, especially midsize ones, is the visibility into financial operations. Cloud ERP integrates accounting processes with business operations, ensuring a clear view of cash flow and profitability​​.</li><li>Ease of Integration: In today’s fast-paced environment, businesses require systems that can seamlessly integrate with other applications. Cloud ERP stands out by offering straightforward integration with a wide array of business tools, thereby reducing complexity and costs​​.</li></ul>

<h3>Common Failure Cases</h3>When it comes to delays or failures in ERP implementation and migration, the following scenarios are emblematic:<ul><li>Inability to finalize requirements due to failure in reaching an agreement with business users on additional development projects.</li><li>The scope of necessary development exceeds expectations, leading to never-ending development phases.</li><li>Data migration issues, with an overwhelming number of errors emerging during testing phases, preventing completion.</li><li>Business users express concerns about the usability being worse compared to the old system, leading to a refusal to use the new system, citing that it impedes their work processes.</li></ul>Key reasons for these challenges include:<h3>1. Lack of Executive Commitment</h3>Often, leadership does not fully commit to the project, resulting in a lack of control (the objectives and policies are not effectively communicated and enforced across the organization). ERP implementation is a comprehensive overhaul of core business processes (such as production, procurement, sales, accounting, HR, etc.), involving numerous stakeholders.Balancing their interests is far from straightforward. Ideally, top management should oversee the coordination of these diverse interests. However, it’s common for executives, particularly those who have never engaged with the system directly and assume it’s sufficient to delegate responsibilities to the IT department post-budget approval, to only receive reports.This not only reflects a gap in the executives’ approach but also highlights the information systems department’s failure to convey the project’s complexities. Engaging with top management from the outset and ensuring their active involvement is crucial.It’s essential for the leadership to perceive the project as their own concern and to be actively involved. Here, “executive” refers not only to the officers in charge of the system but also to those leading business or back-office functions. While securing the CEO’s commitment is ideal, it’s practical for department heads to commit to the project’s direction.<h3>2. Ambiguous Role Distribution between Business and IT Departments</h3>There’s a common misconception among business units that ERP systems are primarily for the IT department’s benefit, leading to a lack of ownership on their part. Complaints from business users about the system not meeting their operational needs or being different from what they envisioned are not uncommon. This can lead to an increase in additional development, necessitating further revisions and potentially delaying or even halting system implementation.The root of the issue lies in the unclear division of responsibilities. Core systems should primarily serve the operational departments, requiring them to take ownership and commit to decision-making within the project (e.g., deciding between additional development or abandoning certain features in light of various project constraints). The IT department should assume responsibility for the system’s technical aspects and requirements not covered by business users.The absence of agreed-upon roles and responsibilities before the project commences, along with a lack of awareness and proper framework to support these roles, often leads to such scenarios. Consequently, the IT department may bear the brunt of the blame, impacting the project’s success.<h3>3. Over-reliance on Vendors</h3>Similar to the previous point, but it’s worth noting that many organizations have historically left the operation of core systems entirely to vendors. This habit extends to replacement or overhaul projects, resulting in a lack of ownership. For instance, deciding on requirements and additional development targets is the responsibility of the implementing company, yet delays occur when decisions cannot be made promptly upon vendor requests.It’s crucial to remember that the primary incentive to stay within budget and ensure smooth system operation lies with the company’s personnel, not the vendors. As additional development increases, so does the vendor’s workload and profit. Although vendors are partners in system implementation and refresh projects, companies must approach these projects with the mindset that they are in charge, keeping the business structure in mind.

Next, we want to discuss how to tackle the above challenges.<h3>1. Consensus Building with Management</h3>It’s essential to explain the project’s complexity to the management team and communicate your expectations regarding their role in adjusting stakeholder interests and resource allocation, as well as decision-making. Given the multitude of stakeholders involved, successful coordination necessitates commitment from the management. The likelihood of failure is high without their involvement. In transitioning from a custom system to an ERP package, certain functionalities available previously may no longer be feasible due to budget constraints, necessitating some tough decisions about which features to forego.It might be challenging for management to grasp the full extent without firsthand experience, but it’s crucial to raise these issues. If working with external consultants, incorporating case studies from other companies can underscore the importance of management involvement. Simply conveying expectations won’t suffice; a structured approach to ensure project success will be outlined in point 3.<h3>2. Clarification and Agreement on Departmental Roles</h3>It’s vital to define the roles of business units and the IT department clearly. For example, the business unit should determine the necessity of additional development functionalities from an operational perspective, while the IT department supports by providing system-related insights and defining system-required functionalities.The goal is to ensure business units take ownership of the system, which is designed to support their operations, not just serve the IT department. Given budget limitations, decisions on what to develop or forgo prior to operation must also come from the business side to avoid blaming the IT department for any issues that arise later (though complaints may still occur).<h3>3. Creating a Framework for Execution</h3>With management’s commitment secured and the project’s objectives and policies defined, the next step is to establish a structure capable of realizing these goals. This includes scheduling meetings with management at critical project phases and regular progress review sessions involving project leaders and department heads to address any issues.During the requirements definition phase, it’s crucial to reach an agreement, including management, on the extent of additional development allowed. Decisions should be based on project policies, such as compliance with legal requirements, business customs, and factors contributing to competitive advantage, while adhering to a predetermined budget cap. Leaders and management should be tasked with decision-making, and key departmental figures informed of the policies and outcomes.<h3>4. Accurately Assess Total Cost of Ownership (TCO)</h3>Begin with a comprehensive evaluation of all costs associated with both on-premise and cloud ERP solutions, including hidden and ongoing expenses. This assessment helps in making an informed decision that aligns with your financial objectives​​.The <a href="https://caddi.com/en-us/resources/insights/total-cost-ownership/" rel="noopener noreferrer" target="_blank">TCO</a> includes a variety of costs that extend beyond the initial price tag:<ul><li>Software Licensing Fees: For on-premise solutions, this can be a substantial upfront cost, whereas cloud ERP solutions typically operate on a subscription model, spreading the cost over time.</li><li>Implementation and Customization Costs: Both on-premise and cloud ERP systems may require significant investment in customization and implementation services to align the solution with business processes.</li><li>Operating Expenses: These include the costs of running data centers for on-premise solutions, such as electricity, cooling, and IT staff salaries. For cloud ERP, operating expenses might cover subscription fees, which generally include maintenance and support.</li><li>Training Costs: Ensuring your team can effectively use the ERP system involves training, which can vary widely in cost depending on the complexity of the system and the method of delivery (e.g., in-person, online, etc.).</li><li>Infrastructure Costs: On-premise ERP solutions require substantial investment in IT infrastructure, while cloud ERP reduces the need for physical servers and hardware but might necessitate investments in secure, high-speed internet connections.</li><li>Upgrades and Maintenance: On-premise systems often require manual updates and maintenance, which can be both costly and disruptive. Cloud ERP providers typically handle updates and maintenance, but the subscription cost may reflect these services.</li></ul><h3>5. Adopt a “Small Start” Implementation Strategy (Optional)</h3>Additionally, adopting a “small start” strategy, where implementation begins in a specific department and gradually expands, can indeed be a viable option.Begin with a department or function that can significantly benefit from cloud ERP capabilities. This allows for manageable initial implementation, providing valuable insights and adjustments before wider roll-out. This phased approach not only mitigates risk but also facilitates smoother change management and system customization as you scale.This phased approach allows organizations to manage risks more effectively, learn from initial deployments, and build internal expertise before rolling out the system more broadly.

As discussed, the key to a successful ERP implementation and migration can be considered a form of Change Management. It’s crucial to instill in business users the notion that the system is their own, to reform the mindset of the management layer to ensure roles are executed effectively, and to design detailed operations aimed at achieving the ideal business processes.In essence, there is no silver bullet. The complexity of the task is high. But, precisely for this reason, the value of successfully implementing cloud ERP is immeasurable.Although not addressed here, the choice of which cloud ERP to select is, of course, also of paramount importance. Depending on your company profile, business issues, and the department or business function you start with, the choice of cloud model (public, private, or hybrid) might vary. In another article – <a href="https://caddi.com/en-us/resources/insights/cloud-erp-software-2024/" rel="noopener noreferrer" target="_blank">“Cloud ERP Software 2024 – Comparison and the future,”</a> we have provided a classification and list of major cloud ERPs and introduced software to support ERP utilization for your reference.

Procurement 101: Common Failures in Cloud ERP Implementation and How to Avoid Them

Explorer graphic titled What is manufacturing intelligence exactly? with the tagline Make MI work for you, showing a worker in a hard hat holding a tablet in front of shipping containers with glowing data network and chart overlays

The first step required to build manufacturing intelligence in your business is to gather the necessary data. There’s a lot of potential useful information that your shop is continually producing, and you need to harness it.‍It can be helpful to think of this data in three primary categories:<h3>Manufacturing process data</h3>This is the data generated as you complete the actual work of manufacturing products. You likely have computer-integrated machinery on your production line. You can have these machines report on their output rates, their current settings, etc. These reports can be logged in a central database.‍More advanced machines can use technology like computer vision to gather more information about their process. They can visually assess their outputs and judge their quality, thus generating data around defect rates.‍This data can be used to estimate the time and quality of future work, and what machine settings are most applicable to each job. This is an essential part of manufacturing intelligence: enhancing the productivity of your process through strategic analysis.<h3>Engineering data</h3>Perhaps the largest amount of data falls into the category of engineering data. This is everything required to begin production of a product: the design, drawings, material information, process information, estimated costs and timelines.‍After the work is done, engineering data also comprises a lot of information you can gather about the work in aggregate: how much in total was produced, what the defect rate was, how long each stage took, and more.‍This is data that you likely already produce using computer software and thus is stored digitally somewhere automatically. However, the way this data is stored may not be conducive to manufacturing intelligence. Keep in mind that just because data exists somewhere, doesn’t mean that it’s a useful or actionable asset.<h3>Logistics data</h3>Logistics data comprises everything that connects your overall business operations with the specifics of your manufacturing process. This includes the storage and transportation of your products, the human resources of people who make production happen, the overall financials of your business, and much more.‍This is likely information you already have well-organized and managed. It’s data that inherently paints a big picture of the highest level inputs and outputs of your business. However, to create manufacturing intelligence around it, it should be connected to the particulars of every deal and process.<h3>Building data lakes for manufacturing intelligence</h3>In order to craft all of this data into something you can use as manufacturing intelligence, the best way is to gather it all in one place. A system that can consolidate data from many sources and contextualize it with each other is known as a <a href="https://us.caddi.com/knowledge-base/data-lake" rel="noopener noreferrer" target="_blank">data lake</a>.‍The benefit of a data lake is that it can pull in data from many different sources without requiring manual reprocessing or oversight. It’s the only way to keep pace with the amount of data your shop generates every day.‍A data lake also allows you to uncover strategic insights across all sorts of categories of data and stages of the production process.‍For example, you may have data indicating that certain parts have abnormally high defect rates. But this likely is just a mapping of quality data and specific part IDs. To find the common factor, you’d need to link this logistics data with engineering data, looking at the drawings for these parts and looking for elements they all share. Then you can look at the process data for that element to diagnose exactly what’s going wrong.‍Making that connection from the highest to lowest level to answer a specific question can be a lengthy, difficult process involving a lot of manual cross-referencing and searching. A data lake makes it automatic and easy, by linking each piece of data with the central design, and connecting similar designs together. The quality data that instigated the question contains its own answer by linking these other pieces of data, connected using design elements themselves.

Now that you’ve got the data needed for manufacturing intelligence into one place, you can start putting it to strategic use.&nbsp;<h3>Manufacturing intelligence for strategic initiatives</h3>A good way to approach this is from the top down. Make overarching strategic goals for your business. Here are some examples of the level you can work with:‍<ul><li>Reducing costs for product storage by some percent</li><li>Consolidating suppliers down to some number</li><li>Decreasing the production time of the longest production processes</li><li>Reworking the production processes of the products with the highest defect rate</li><li>Improving the speed and consistency of responding to RFQs</li></ul>‍For each of these questions, the answers lie in your manufacturing intelligence. Break down the information you’d need to answer the questions into more and more discrete chunks.‍For example, when consolidating suppliers, first you’d need to make a list of all current suppliers. Then you’d want to know which parts you order from each supplier. Then you’d look at the types of parts that each supplier provides. Are there areas where one supplier could handle similar parts currently sourced from another supplier? Who’s offering the best deals for each type of part? Who provides the highest quality for each type of part?‍Using your data lake, you can have all of this data laid out for you plainly. Which suppliers are most ideal for each type of part you require will become obvious. This is the true realization of manufacturing intelligence.‍As the world’s supply chains and labour markets become increasingly unstable, intelligence is the only way to remain flexible and agile. Rapidly pivoting to plan Bs or even Cs could be necessary on any given day. You need a way to quickly understand and evaluate your options.<h3>Manufacturing intelligence for day-to-day consistency</h3>The other important benefit of manufacturing intelligence is from the bottom up. Manufacturing intelligence means continual monitoring of your shop’s outputs on the most detailed level: every part coming out of every machine.‍What this allows is the earliest possible detection system for anomalies and problematic trends. You can be alerted immediately if anything goes wrong. Then, using the manufacturing intelligence setup you’ve built, you can immediately contextualize the issue with your business as a whole.‍For example, if a machine’s output is slowing gradually due to wear and tear making it less effective, it may be hard to know when to repair it. Repairing costs money and temporarily reduces output to zero. On the other hand, decreased production slowly eats into your profits.‍With manufacturing intelligence, you can follow the ramifications of this slowdown up the chain. You can see exactly how the production slowdown impacts your bottom line and determine when investing in the repair makes most sense.

CADDi is an AI data platform for manufacturing that serves as a powerful data lake and enables manufacturing intelligence. Our patented similarity search automatically collects drawings with similar design elements. Then it links each drawing with all of the contextual information, from the revisions of its design, to the suppliers of its component parts, to the defect rates when it was put into production.This gives you the detailed big picture perspective necessary to use manufacturing intelligence strategically. See it all in action by <a href="https://us.caddi.com/demo-request?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Demo&amp;utm_campaign=&amp;utm_term=blog" rel="noopener noreferrer" target="_blank">checking out a free demo</a> or <a href="https://us.caddi.com/product-tour?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Blog&amp;utm_campaign=&amp;utm_term=" rel="noopener noreferrer" target="_blank">walking through our product tour</a>.

What is manufacturing intelligence exactly?

Explorer cover graphic for The Reshoring Reality Check, with an aerial view of a crowded beach and coastal city skyline, subtitled Reshore and offshore dynamically

For decades, U.S. manufacturing witnessed a decline as companies pursued lower labor costs overseas. This trend is now reversing, with reshoring and nearshoring reaching record highs in 2022 and 2023, driven by a profound rethinking of supply chain strategy. The allure of bringing production closer to home is multifaceted:<ul><li>Increased Control and Visibility: Reshoring offers manufacturers more direct control over their supply chains, reducing reliance on volatile international factors and enhancing transparency.</li><li>Reduced Shipping Costs and Lead Times: Localizing production minimizes exposure to fluctuating international freight costs and shortens delivery times, allowing for quicker responses to market demands.</li><li>Improved ESG (Environmental, Social, and Governance): Producing domestically can reduce carbon emissions from transportation and allow for greater oversight of labor and environmental risks, aligning with growing consumer and regulatory values.</li><li>Economic Growth and Job Creation: Reshoring is projected to add millions of jobs and contribute significantly to GDP, stimulating the domestic economy.</li><li>Supply Chain Resilience: Past global shocks have highlighted the vulnerabilities of distant, lean supply chains, making resilience and redundancy as valued as efficiency. This means moving away from single-source dependencies and diversifying supply bases.</li></ul>

Despite these compelling strategic benefits, the current economic climate is forcing manufacturers to pause and re-evaluate their reshoring ambitions. The very disruptions that make reshoring strategically attractive are simultaneously making it financially and operationally untenable in the short term.<ul><li>High Upfront Costs and Investment Paralysis: Reshoring typically involves significant infrastructure investment requirements. However, trade uncertainty is the single greatest business concern for 77% of American manufacturers, leading to a measurable slowdown in capital investment. Projected capital spending growth has cratered, with a third of manufacturers planning to reduce or delay investments due to the unstable trade environment. Businesses are unwilling to commit billions of dollars to long-term investments in new U.S. manufacturing facilities for policies that might be reversed, perceiving tariffs as temporary and volatile.</li><li><a href="https://us.caddi.com/resources/insights/labor-paradox" rel="noopener noreferrer" target="_blank">The Labor Paradox</a>: While reshoring aims to create jobs, the U.S. manufacturing sector faces a paradox: an acute contraction in employment (the ISM Employment Index plummeted to 43.4% in July, its lowest in five years) is occurring against a chronic, long-term talent and skills shortage. Nearly half of manufacturers estimate it would take one to over three years to fully staff a reshored operation, a timeline difficult to commit to in the current environment.</li><li>Global Supply Chain Inertia: Industrial supply chains are inherently global, and rapidly restructuring them is difficult. Critical components like PLCs, steel, and valving are often sourced internationally. For many products, it can still be more economically feasible to pay tariffs on imports than to undertake the massive investment required for domestic capabilities, especially if no viable American alternative exists.</li><li>Automation's Role in Job Impact: Even if reshoring brings production back, modern manufacturing is highly automated and less labor-intensive. New facilities prioritize efficiency and high-skilled labor, meaning increased domestic output does not necessarily translate into a significant increase in traditional manufacturing jobs.</li></ul>

The alternative of simply continuing to offshore is not without its own complexities. A singular focus on pure cost-efficiency through globalized, single-source models has proven vulnerable to geopolitical tensions, natural disasters, and global health crises. While nearshoring to Mexico has emerged as a popular option, surpassing China as the U.S.'s largest trading partner in 2023, it still involves navigating international dynamics. Mexico offers geopolitical stability, reduced transit times, and cost competitiveness due to lower labor costs and trade agreements like USMCA. However, even with nearshoring, challenges like cultural differences, communication barriers, and ensuring compliance across diverse legal frameworks persist.

The current environment reveals a growing disconnect between long-term strategic goals (like resilience) and short-term operational realities (like preserving cash flow). Neither a rigid reshoring mandate nor a blind continuation of offshoring is a guaranteed path to success. The manufacturing industry is at an inflection point where agility over long-range, static planning is paramount. The ability to make rapid, data-informed decisions on pricing, sourcing, and production scheduling is more valuable than a fixed five-year plan.Manufacturers must bridge this gap by cultivating a mindset of dynamic adaptation, ready to pivot between domestic, nearshore, and international sourcing as market conditions, policy, and costs dictate.

In this volatile environment, manufacturers need practical, data-driven solutions to build resilience and maintain flexibility. CADDi, an AI data platform for manufacturing, provides the tools to manage this complexity, enabling informed decisions regardless of the sourcing strategy.<ul><li>Unified Data and Enhanced Visibility: CADDi functions as a data lake, aggregating and linking information from disparate systems like PLM, ERP, and even unstructured data from drawings and spreadsheets. This creates a "single source of truth," providing granular, real-time visibility into every corner of the enterprise—from supplier lead times and raw material costs to inventory levels. This is crucial for proactively identifying opportunities and risks in any supply chain configuration.</li><li>Strategic Sourcing and Supplier Management: CADDi enhances the ability to identify, vet, and manage suppliers for any sourcing strategy.</li><li style="text-indent: 1em;">For domestic sourcing, it helps digitize and analyze an entire library of part drawings, providing a granular understanding of manufacturing needs to effectively search for and communicate with potential domestic partners. The similarity search can bundle similar parts into larger order packages, making them more attractive to new suppliers and potentially offsetting higher domestic costs.</li><li style="text-indent: 1em;">For global sourcing, it helps overcome data complications by standardizing measurements and ensuring compatibility across parts, making it easier to evaluate international options.</li><li style="text-indent: 1em;">It also allows procurement teams to compare supplier responses against benchmarks and understand price patterns between design features and costs, transforming negotiation into a data-driven science. This is vital for navigating cost fluctuations, whether from tariffs or market dynamics.</li><li>Cost Optimization and Make-or-Buy Decisions: By linking design information with procurement costs, CADDi facilitates value analysis/value engineering (VA/VE) initiatives, identifying opportunities to save costs without sacrificing quality. Its ability to review similar parts and connect procurement, production, and quality data enables informed "make-or-buy" analyses, which are critical in a volatile cost environment.</li><li>Accelerated Decision-Making and Agility: In an era where speed and adaptability are paramount, CADDi significantly reduces the time spent searching for information. Tasks that once took hours or days can be completed in minutes, such as instantly finding similar designs, their cost estimates, and actual ultimate costs for RFQs. This empowers teams to respond quickly to market changes and seize opportunities.</li><li>Mitigating Knowledge Drain: As experienced workers retire, CADDi acts as a "digital brain" for the organization. Its intuitive similarity search, which understands part geometry from a drawing or even a hand-drawn sketch, democratizes institutional knowledge, reducing reliance on a few experienced individuals and accelerating onboarding for new employees.</li></ul>The current "Reshoring Reality Check" underscores that manufacturing success in 2025 and beyond will hinge on strategic foresight, technological innovation, and a renewed commitment to national industrial strength through flexible, data-driven operations. By leveraging advanced AI data platforms like CADDi, manufacturers can transform uncertainty into opportunity, ensuring they are prepared to optimize their supply chains wherever the best opportunities lie, fostering both resilience and competitiveness.Ready to see how CADDi can help you build and execute a reshoring strategy? Explore our <a href="https://us.caddi.com/product-tour?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Blog&amp;utm_campaign=&amp;utm_term=" rel="noopener noreferrer" target="_blank">interactive product tour</a> or <a href="https://us.caddi.com/demo-request?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Demo&amp;utm_campaign=&amp;utm_term=blog" rel="noopener noreferrer" target="_blank">book a personalized demo</a>.

The Reshoring Reality Check: Balancing Strategic Ambition with Economic Volatility

Explorer cover graphic for the article, with the words AI in Procurement over a glowing digital wireframe of a human head containing a globe

The age of artificial intelligence is upon us. AI and automation are transforming industries across the board, and procurement is no exception. In fact, AI has the potential to revolutionize procurement in game-changing ways.According to our recent survey, 78% of procurement leaders believe AI will disrupt the profession within just 3-5 years. For procurement teams, implementing AI is not a matter of if, but when. The organizations that embrace AI early will gain a real competitive advantage. They’ll be able to reduce costs, risks and cycle times while freeing up budget for more strategic initiatives.The message is clear: to remain relevant in the coming years, procurement must prepare now for the AI era. The transformation has already begun. This article explores the coming impact of AI on procurement and provides advice for preparing your team to harness the power of intelligence automation. The future starts today.

Artificial intelligence is transforming businesses across industries, and procurement is no exception. The most common applications include analysis of spend data, contract lifecycle management, supply chain risk assessment, and supplier discovery.&nbsp;While AI adoption in procurement is still in an early stage, its growth has accelerated rapidly in recent years. The IBM survey found AI adoption in procurement jumped from 20% in 2018 to over 50% in 2021. This trend will likely continue as organizations realize the significant cost savings and process efficiencies enabled by AI. For procurement teams, AI promises to automate repetitive tasks, find hidden insights in data, and improve strategic decision making.

AI and automation can provide significant benefits for procurement teams. Some of the key ways AI can improve procurement include:<h3>Leveraged procurement intelligence</h3><ul><li>AI tools can quickly analyze large volumes of spend data and identify patterns, risks, and opportunities that may be difficult to uncover manually. This provides procurement with greater visibility into spending.</li><li>Natural language processing allows AI systems to read contract details, invoices, and other documents to extract key insights. This automates the data collection process.</li><li>Machine learning algorithms can categorize spend, detect anomalies, and highlight areas to target for savings such as maverick spend.</li></ul><a href="https://caddi.com/en-us/resources/insights/procurement-intelligence/" rel="noopener noreferrer" target="_blank">Procurement Intelligence: Leveraging data for smarter sourcing decisions</a><h3>Enhanced contract management</h3><ul><li>AI can speed up contracting by automatically reviewing agreements for errors, risks, and compliance issues. This reduces the manual review burden.</li><li>Systems can match contracts to purchase orders and invoices to ensure proper execution. They can also provide alerts around key deadlines like renewals.</li><li>Automating routine tasks like extracting terms and conditions allows procurement teams to focus their efforts on high-value strategic activities.</li></ul><a href="https://caddi.com/en-us/resources/insights/contract-management/" rel="noopener noreferrer" target="_blank">Transforming Supplier Contract Management: The Power of Digital Technologies</a><h3>Improved supplier development</h3><ul><li>AI tools use advanced market intelligence to identify potential new suppliers that meet sourcing needs, widening the pool beyond existing partners.</li><li>These systems score suppliers on parameters like quality, pricing, delivery reliability and financial health to assess fit, enabling the ability to make more informed decisions.</li><li>Automating supplier onboarding and conducting due diligence processes are faster and reduce administrative tasks for buyers.</li></ul><a href="https://caddi.com/en-us/resources/insights/supplier-development/" rel="noopener noreferrer" target="_blank">Supplier Development – Practical Guide to Leveraging Technology</a>AI automation enhances productivity in key areas of the source-to-contract process, enabling procurement to operate more efficiently.

AI is transforming key procurement processes in the following ways:<h3>Spend Analysis</h3>AI can extract data from contracts, invoices, and other documents to map out spending patterns across the organization. Advanced analytics identify opportunities to consolidate purchases, reduce maverick spending, and leverage economies of scale.<h3>Invoice Processing</h3>AI automation tools can extract key data from invoices and cross-check against contracts and purchase orders. This reduces processing costs and ensures compliance with negotiated terms.<h3>Market Intelligence</h3>AI-powered market intelligence tools continuously scan multiple data sources to identify changes in supply markets. This allows procurement teams to spot issues and opportunities early.

Implementing AI in procurement can come with some key challenges that organizations need to be prepared for:<h3>Data Quality</h3>AI systems are only as good as the data they are trained on. Low quality, inconsistent, or insufficient data will result in poor AI performance. Organizations need to invest in improving data infrastructure, collection, and cleaning to ensure high quality input data for AI systems.<h3>Change Management</h3>Transitioning to AI-driven processes requires change management to get buy-in across the organization. There may be cultural resistance, lack of understanding of AI, and concerns about job security that need to be proactively addressed through training, communication, and leadership.<h3>Skills Gap</h3>The specialized skills needed to develop, implement, and manage AI systems are in short supply. Organizations will need to reskill existing procurement teams or acquire new talent with experience in areas like data science, machine learning operations, and AI ethics; building multidisciplinary teams is key.

As with any new technology implementation, having a solid strategy is key to successfully adopting AI in procurement. Here are some tips for building an effective AI strategy:<ul><li>Assess needs and identify use cases – Carefully evaluate your current procurement processes and pain points; look for repetitive tasks and bottlenecks that could benefit from automation. and talk with stakeholders to understand what challenges they face. Next pinpoint realistic use cases where AI could provide value, whether it’s automating invoice processing, analyzing spend, or improving supplier discovery.</li><li>Develop a phased roadmap – Don’t try to implement AI across procurement overnight. Create a multi-year roadmap focused on rolling out AI in phases, starting with pilot projects. Quick wins can build confidence and momentum for more advanced use cases later. Prioritize high-impact areas first.</li><li>Start with narrow AI – Broader artificial general intelligence does not exist yet. Focus your strategy on narrow AI that specializes in specific tasks. Choose vendor solutions tailored for procurement versus general-purpose AI.</li><li>Plan for change management – Adopting AI will require changes in processes, skills, and mindsets. Develop a proactive change management plan. Train procurement staff on using new AI tools. Clearly communicate the benefits of AI to build buy-in across your organization.</li><li>Consider risks – AI can raise valid concerns around transparency, bias, and job loss. Develop an ethical AI approach that monitors for risks and bias in algorithms. Look at AI as an aid, not a replacement for procurement specialists. Focus AI on enhancing workers rather than replacing them.</li></ul>

Getting organizational buy-in and support is critical for a successful AI implementation. When presenting an AI strategy to leadership, focus on clearly communicating the benefits:<ul><li>Cost savings and process efficiencies – Highlight how AI can drive significant cost reductions through increased procurement productivity and process optimization. Show benchmarks and use cases from other organizations.</li><li>Better spending decisions – Emphasize how AI-driven insights, predictions, and recommendations will empower procurement to make more strategic sourcing decisions. Demonstrate how AI can help identify savings opportunities.</li><li>Enhanced supplier relationships – Explain how AI can enable a proactive, collaborative approach with suppliers through real-time visibility, risk monitoring, and joint process improvements. Stress the benefits of optimizing relationships.&nbsp;</li><li>Competitive advantage – Underscore how AI-powered procurement will establish a competitive edge through accelerated velocity, mitigated supply chain risks, and greater resilience to market changes. Connect AI capabilities with key business goals and KPIs.</li><li>Future-proofing – Highlight that AI investments future-proof the function, equipping procurement with cutting-edge capabilities that will soon become a new norm. Proactively adopting AI ensures the function won’t get left behind.</li></ul>To gain buy-in, the business case must resonate with leadership priorities. Emphasize the tangible benefits AI will deliver for savings, productivity, relationships, and competitiveness. With a compelling vision, procurement can secure the sponsorship needed to implement AI successfully.

As you implement AI, you’ll need talent that can build, deploy, and manage AI applications. Consider hiring data scientists and machine learning engineers. They will be key in developing custom AI solutions tailored to your procurement needs.It’s also important to train your current employees on AI. Explain how AI will impact their roles and what new skills they may need to learn. Provide resources and training to upskill employees on working alongside AI. Some areas to focus on include:<ul><li>Basics of AI, machine learning, and data science</li><li>Tools like Python, R, SQL, and visualization software</li><li>Statistical analysis and critical thinking</li><li>Understanding AI model outputs and limitations</li><li>Ethics and responsible use of AI</li></ul>Your procurement team’s deep knowledge of sourcing strategies, supplier markets, and category management is invaluable. Coupling this with the ability to leverage data, run analyses, and interpret AI insights will be a key differentiator. Focus on developing these blended skill sets in your team.Build a culture of learning; sponsor employees to take courses and certifications in AI and data science. Foster internal experts who can share knowledge. Being proactive will ensure a smoother transition when adopting AI in procurement.

To measure the impact of AI in procurement and ensure continuous improvement, focus on tracking these key metrics:<ul><li>Cost savings – Track how much money is saved over time by automating tasks, getting better prices from suppliers, reducing maverick buying, etc. Set goals for cost reduction.</li><li>Contract cycle times – Monitor how long it takes to complete each stage of the contract lifecycle with AI automation versus manually. Faster cycle times increase productivity.</li><li>Supplier performance – Use AI to continually assess supplier quality, delivery times, responsiveness, and pricing against agreements. Quickly identify issues.</li><li>Process efficiency – Calculate processing times for procure-to-pay, quote-to-order, and other workflows. AI should drive increased efficiency over time.</li><li>Maverick spending – Measure the percentage of spending that happens outside of preferred vendors and contracts. AI tools can help identify and reduce maverick spending.</li><li>Forecast accuracy – Compare actual spending to forecasts produced by AI. Continually tune forecast algorithms to improve accuracy.</li><li>User adoption – Monitor usage rates for AI tools. Work to increase adoption across the organization through training and communications.</li></ul>By regularly measuring performance across these metrics, procurement teams can prove the value of AI, fine-tune solutions, and expand deployments to maximize the benefits. Tracking metrics leads to continuous improvement on the AI-enabled journey.

The AI Revolution is Coming: How Procurement Pros Can Prepare

Explorer report cover titled Pressure and Productivity Index, Five Key Opportunities, shown beside a folded printed brochure

Manufacturers are down on the economy. Only 11% of senior manufacturing leaders have a positive short- and medium-term economic outlook. Regardless of what happens with the economy, many manufacturers likely don’t realize that they are overlooking straightforward opportunities to cut costs, drive profitability, and help them thrive in any economic environment.&nbsp;&nbsp;A significant number of procurement professionals (60%) say they’ve sourced parts at higher costs than what they knew was possible because they lacked access to sufficient supplier data for effective negotiation. The same percentage of professionals say they’ve missed the opportunity to consolidate suppliers and/or secure volume discounts for the same reason. Similarly, 71% of sales professionals have quoted or sold unprofitable deals due to not having access to historical engineering and procurement data.&nbsp;Access to historical data and AI can help address these challenges: 68% of procurement professionals said if they had historical data they could better negotiate with suppliers to secure volume discounts. Thirty-six percent said AI would specifically help with finding volume discounts.

Manufacturers are facing a persistent talent shortage. An estimated 1.9 million manufacturing positions could go unfilled by 2033, according to a report by Deloitte and the Manufacturing Institute. Fifty-six percent of manufacturers cite skilled labor access as a top concern of theirs in 2024.&nbsp;&nbsp;The talent shortage puts a strain on current employees who pick up the slack. Equipping these workers to be successful in their roles will not only mitigate the direct impacts of the talent shortage but also help with engaging and retaining existing workers. Direct your attention to solving for inadequate documentation (missing part numbers, dimensions, material properties, etc.) which 73% of procurement teams cite as their biggest frustration. Most sales teams cited long quotation processes due to needing to track down relevant information (67%) for their biggest frustration.&nbsp;

Seventy-three percent of senior manufacturing leaders are preparing to retire in the next decade and 68% of them believe at least half of their institutional knowledge will be lost forever when they do. Even though most leaders (83%) think they’ve properly documented their institutional knowledge and are confident the next generation is prepared to take the reins, critical limitations still exist.&nbsp;Seventy-four percent of manufacturing professionals say they have a searchable database of engineering drawings and relevant parts and supply chain data, but 54% say they can only search by part ID and part name. There is a lot more historical information teams need to effectively design, procure, sell, and collaborate. Make sure that documented knowledge includes historical data by material, surface, treatment, and other metadata and that it can be easily searched and accessed by your team in the moment it’s needed. Your team will be able to keep operations running smoothly and work faster, smarter, and more confidently, long after colleagues retire.

Fifty-one percent of manufacturing leaders cite navigating political demands to bring production onshore as a top pressure point. This is likely because making the decision to bring manufacturing back to the U.S. often means absorbing higher labor costs.&nbsp;But manufacturers no longer have to make this difficult decision. They can create new levels of labor productivity by driving efficiencies in how procurement, engineering, and sales teams access and use historical and critical data. This can offset higher U.S. labor costs, ultimately supporting onshoring efforts and contributing to American prosperity.&nbsp;

As manufacturers look to 2025, 23% see increasing speed to market as a top priority. In manufacturing’s fast-paced environment, getting innovative, high-quality products to market quickly is absolutely essential for maintaining a competitive edge.&nbsp;Despite this, 77% of procurement professionals report that, every few projects, they have to find new parts or suppliers because the initial options don’t meet engineering specifications, which is a huge hindrance to their organization’s speed to market.&nbsp;A huge benefit of solving the internal data challenge: smoother interdepartmental collaboration and faster speed to market. Fifty-five percent of procurement professionals say if they had access to historical data, they could collaborate with engineering earlier and more effectively, leading to better and faster product development.&nbsp;

While the pressures on U.S. manufacturers are undeniable, they also present an opportunity for organizations to redefine their operational strategies and become stronger.Download CADDi’s American Manufacturing Pressure and Productivity Index to dive deeper into the pressures facing manufacturers today and turn these challenges into opportunities.

Five Opportunities Awaiting U.S. Manufacturers Based on insights from CADDi's New Research

Is a Recession On the Horizon? Many manufacturing leaders predict it. Weather the storm by being informed. Explorer graphic with a downward arrow made of dollar bills

Across American history, one of the most reliable indicators of economic trends has been the status of manufacturing. For example, take the <a href="https://www.investopedia.com/terms/i/ipi.asp" rel="noopener noreferrer" target="_blank">industrial production index</a>, which measures the real output of the manufacturing, mining, oil, and electrical industries. Tracking this index relative to the general economy, you can see <a href="https://www.advisorperspectives.com/dshort/updates/2024/08/15/recession-indicators-industrial-production-july-202" rel="noopener noreferrer" target="_blank">consistent dips before every recession</a>. It’s not surprising – these industries are the foundation upon which all other industries in America are built. If the raw material and fuels aren’t being produced and processed, every subsequent transaction grinds to a halt.‍What’s even more telling is that this index is still a trailing indicator, reflecting output of the previous month. That means for manufacturing professionals, like the ones we’ve surveyed for our report, the writing on the wall is apparent even earlier. Aware of all the pressures impacting their production, they can anticipate a downturn in their output months in advance.&nbsp;‍All of this is to say: when manufacturing experts agree that a recession is imminent, there’s plenty of reason to believe them.

Understanding the causes of recession is far from a trivial task. In fact, leading economists spend their whole career puzzling out what factors influence what metrics to which extent. However, there’s some events definitely worth tracking to understand the situation as it unfolds.‍The election – as 2024 is an election year, many pressing policies remain open questions. Both candidates have made promises to revitalize middle class jobs, which could lead to stimulus plans for manufacturing. But regardless of who wins, what they’ve promised, and how successful their plans end up being, this uncertainty leads to caution around investments and purchasing in the short term, which leads to slumping across the board.‍The talent crisis – manufacturing is facing a looming crisis of talent. <a href="https://nam.org/2-1-million-manufacturing-jobs-could-go-unfilled-by-2030-13743/" rel="noopener noreferrer" target="_blank">Estimates show</a> over 2.1 million jobs going unfilled by 2030. In our surveying of major pressing concerns for manufacturing leadership, we found that 56% of respondents identified acquiring talent, and 50% identified equipping current employees to take leadership roles, as among their primary challenges. This is all going to be exacerbated by <a href="https://info.siteselectiongroup.com/blog/the-issue-of-the-aging-workforce-in-manufacturing" rel="noopener noreferrer" target="_blank">upcoming waves of retirement</a>, where many of the most experienced and knowledgeable employees are going to disappear. With major shortcomings in talent expected, major shortcomings in productivity, and therefore economic activity, are sure to follow.‍International competition – for manufacturing especially, the global marketplace has been both an obstacle and opportunity for decades. However, in recent years, destabilizing factors have transformed other manufacturing nations, such as China and Mexico, from helpful resources to growing competition. No longer just places to leverage cheaper labor, other nations have emerged as full-fledged markets, operating without American heads but selling to American consumers. Aggressive tariffs on foreign goods and subsidies to reshore manufacturing jobs back home are intended to reclaim chunks of the global market, but these policies can have second-order chilling effects on investment and growth.‍If a recession is indeed coming, these three issues will certainly be factors. However, there are many others: dozens, if not hundreds, of tiny dominoes that could drop. If we could figure them all out, we probably wouldn’t be staring down a recession in the first place. Being knowledgeable is important, but in the face of such a complex challenge, being pragmatic is even better.

A recession is hard, some shortcomings and stressors are inevitable. But they aren’t a death sentence. In fact, these times of hardship often coincide with opportunities to claim a competitive advantage and move ahead of peers. You just need to move strategically, seize options that open up to you, and stop leaving savings on the table.‍As we mentioned, the causal forces of a recession are uncountably many and dizzyingly complex. They’re often wholly out of your control – your company isn’t personally renegotiating trade relationships with China. It’s better not to think about addressing the actual causes of the recession directly. Instead, think about what areas of your business are likely to be impacted, and optimize what things you can control that also affect those areas. It’s sort of like the old adage about accepting what you can’t change, needing courage to change what you can, and knowing how to tell the difference.‍For example, you’ll likely face a talent gap as retirement frequency increases and new hires are unavailable or ill-equipped to step into advanced roles. That’s likely inevitable at this point, and you can’t hope to magically tap into an army of workers undiscovered by competitors. However, what isn’t inevitable is that you’ll suffer from reduced productivity because of that. Investments in new technology can help uplevel new employees to have the strategic insights of former old employees. No matter what crisis is coming, there are steps you can take to stop the ramifications before they hit the bottom line.‍Speaking of the bottom line, these tighter times are also perfect for claiming opportunities for savings. Maybe you won’t have the capital to tackle ambitious new projects due to the recession, but you can build back a leaner and faster foundation for when economic tides shift back. This doesn’t mean headcount reductions – there’s no faster way to cripple productivity than layoffs and overburdening of whoever remains. Instead, look for inefficiencies and unnecessary costs to do more with what you still have.

Whether a recession is around the corner or not, saving time, money, and stress is always a good thing. CADDi can make revolutionary improvements in your productivity by unlocking the power of your past data. Move past reinventing the wheel and into an era of iteration and evolution with our patented drawing searches, while saving money on procurement and responding faster and more accurately to RFQs.‍See it all in action by <a href="https://us.caddi.com/demo-request" rel="noopener noreferrer" target="_blank">booking a demo</a> or checking out our <a href="https://us.caddi.com/product-tour?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Blog&amp;utm_campaign=&amp;utm_term=" rel="noopener noreferrer" target="_blank">interactive product tour</a>.

Is a recession on the horizon, as many professionals predict?

Explorer graphic titled Manufacturing Drawings, asking how to get the most from them, over a blueprint of a flanged housing with a title block

Manufacturing drawings contain a complete representation of the object to be produced, alongside relevant information for the production.In order to show all the angles and faces of a part, the drawing has to depict multiple perspectives simultaneously. This can look like showing both a front view and a side view next to each other.<img src="https://cdn.builder.io/o/assets%2F209ee507cedf4c298e100edae4bba2df%2Fd23cd03292124fc6b6df38c984b892a1?alt=media&amp;token=84bbfe08-dd56-45b6-914e-300b9a8ac61f&amp;apiKey=209ee507cedf4c298e100edae4bba2df" alt="Manufacturing drawing of a flanged hub in two views: a sectioned side view and a front view with an eight-hole bolt circle, annotated with dimensions, tolerances, an M42 x 1.5 thread callout, and GD&amp;T feature control frames.">Other times you may need to also show a top-down view to account for asymmetries. An isometric view can provide additional help in visualizing the final product. <img src="https://cdn.builder.io/o/assets%2F209ee507cedf4c298e100edae4bba2df%2F8945a056860d4196aa03827698cc4838?alt=media&amp;token=fa096523-4435-4728-a646-e88100fd6948&amp;apiKey=209ee507cedf4c298e100edae4bba2df" alt="Multi-view manufacturing drawing of a bracket with a cylindrical boss and mounting holes, showing front, side and top views with dimensions and radii, plus a shaded isometric view."> Sometimes, when vital information about the shape of the part is concealed by the part itself, an exploded view is necessary:<img src="https://cdn.builder.io/o/assets%2F209ee507cedf4c298e100edae4bba2df%2F9d3f2c837b74461ca76324d692f35fbd?alt=media&amp;token=6d596f5f-70dc-4a87-ae13-6fdc131ef72b&amp;apiKey=209ee507cedf4c298e100edae4bba2df" alt="Exploded-view line drawing of a valve assembly with the handle, nut, stem, bonnet plate, body, gaskets, and end flanges separated along their assembly axes">This is used more frequently with products made of several component parts assembled together. Instead of providing instructions for how to manufacture each part, it’s more about how the preexisting parts are assembled together.Depending on the usage of the drawings, they will have different things labeled and highlighted. Common inclusions are the length of each dimension and the specific angles formed. This will allow the machines to create exactly what is depicted on the manufacturing drawing. If the part is based off of existing standards, those standards will likely be referenced in the drawing too. For example, if you produce sheets that are punched by holes of consistent sizing, your drawing may indicate that “hole punch A” should be used for a given hole, and “hole punch B” for another hole. It’s good practice to also include the diameter of these holes too, to ensure consistency and reduce error.On top of the depiction of the part, manufacturing drawings contain other vital information for production in the form of a title box.<img src="https://cdn.builder.io/o/assets%2F209ee507cedf4c298e100edae4bba2df%2F0f02ab2fec0c42a58118b267ae7bf2d8?alt=media&amp;token=97549526-c5e6-4715-a359-29124e7f3a85&amp;apiKey=209ee507cedf4c298e100edae4bba2df" alt="Annotated diagram of a manufacturing drawing title block, with labels pointing to the tolerance block, approval block, dates block, company name and address, list of materials, material block, final protective coating, applications block, quantity per next assembly, scale, sheet number, revision letter, drawing number, and part name or title.">These blocks typically sit on the bottom right corner of your manufacturing drawing. They contain organized information about how to produce the depicted product. This includes:<ul><li>The material the part should be made out of</li><li>The finish it should receive</li><li>The tolerances for how inaccurate the machine can be when producing it</li><li>How large each batch should be in each production</li></ul>The title blocks often also contain information about the drawing itself, such as:<ul><li>The title of the drawing, and the name of the depicted product</li><li>Who created the drawing</li><li>When the drawing was created</li><li>What revisions the drawing had since creation</li><li>When the drawing was approved and by whom</li></ul>Between the title block and the diagram, the manufacturing drawing should give anyone looking at it the necessary information to produce the part. It should also give them the information needed to investigate the history and purpose of the drawing.

In the modern era, manufacturing drawings are often produced by digital tools, known as Computer Assisted Drawing (CAD) software. These tools allow people to create and store drawings on the computer. This makes it easier to make drawings consistent and keep information accurate.You can also scan old paper drawings into the computer for easier access and revisioning. Make sure to give them consistent and helpful names and tags in order to retrieve them easier.However, regardless of how you produce or organize your digital manufacturing drawings, there will always be some shortcomings in their availability.For example, if you’re producing a new drawing and looking for a similar old drawing to reference, your options for finding it may be limited. You may have to remember the specific name or ID number of the previous drawing. Memorizing these is difficult and tedious for experienced team members, and impossible for new hires.Metadata, data attached to the manufacturing drawing to make it easier to find, can help with this process. For example, you can attach tags and labels to a drawing to help you remember where to find it later. However, this has issues too, including:<ul><li>Not remembering the exact wording used in tags</li><li>Wanting to search for a quality of the drawing that wasn’t tagged</li><li>Tags being applied inconsistently or incorrectly or not at all when the drawing is created</li><li>Needing to learn what tags exist in the first place</li><li>Tags being too general, returning thousands of hits that you have to dig through</li></ul>These issues can create <a href="https://us.caddi.com/resources/insights/data-gaps" rel="noopener noreferrer" target="_blank">data gaps</a>. Even if the data is technically somewhere in your system, if people, especially new hires, can’t find it in a reasonable amount of time, it may as well not be there. Keep track of when data gaps occur, and make plans to solve them. This may include more robust tagging, training people on a tagging system, or new organizational structures.

Even if you have good practices around fixing them, resolving data gaps can become an endless game of whack-a-mole. Fortunately, we have a better solution at CADDi.Our revolutionary software automatically indexes all of your manufacturing drawings and makes them searchable and sortable with all the information in them. CADDi parses the very drawing itself, allowing you to search by simply sketching the sort of part you’re looking for, or uploading a similar drawing. We automatically and instantly find all the drawings that overlap in dimensions, features, and more.On top of that, we make the data in your title blocks into true searchable assets. Older drawing digitization software required you to manually enter information in these blocks. CADDi’s OCR technology automatically parses them and makes them into sortable, filterable, and searchable fields.Shave hours off searching for old drawings to make new designs faster and better. Once you find the drawings you need, we conveniently link every related piece of data about each design, from order history to quality rates to sales quotations.See it all in action by trying out our <a href="https://us.caddi.com/product-tour?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Blog&amp;utm_campaign=&amp;utm_term=" rel="noopener noreferrer" target="_blank">interactive demo</a>!

Manufacturing Drawings - What they are and how to get the most from them

Explorer cover graphic with the letters IoT over a photo of an industrial plant overlaid with glowing network, data and connectivity icons

In recent years, the convergence of AI and IoT has been a hot topic in the tech world. According to <a href="https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/iot%20value%20set%20to%20accelerate%20through%202030%20where%20and%20how%20to%20capture%20it/the-internet-of-things-catching-up-to-an-accelerating-opportunity-final.pdf" rel="noopener noreferrer" target="_blank">a McKinsey report</a>, the number of businesses using AI with IoT increased from 19% in 2018 to 27% in 2020, and this trend is expected to continue as more companies recognize the benefits of combining these two technologies.AI is like the brain that processes the vast amounts of data generated by IoT sensors, providing insights and making decisions that optimize manufacturing processes. It’s the conductor that brings all the pieces together, creating a seamless and efficient operation.

One of the key trends in the AI-IoT duet is the rise of edge computing. Instead of sending all the data generated by IoT sensors to the cloud for processing, edge computing allows data to be analyzed and acted upon closer to the source. This reduces latency and improves efficiency, enabling real-time decision-making and automation.Imagine a quality control system that uses machine vision to inspect products on the production line. With edge computing, the AI algorithms can analyze the images in real-time, identifying defects and triggering corrective actions immediately. This prevents defective products from reaching customers and reduces waste, ultimately saving time and money.

Another area where AI is making a significant impact in manufacturing is predictive maintenance. By analyzing data from IoT sensors on machines, AI algorithms can predict when a machine is likely to fail, allowing maintenance to be scheduled before a breakdown occurs.Think of it like a car that tells you when it needs an oil change or when the brakes are wearing out. By addressing these issues proactively, you can avoid costly repairs and extend the life of the vehicle. The same principle applies to manufacturing equipment, where unplanned downtime can be incredibly expensive.

<ul><li>Rolls-Royce uses IoT sensors in its aircraft engines to monitor performance and predict maintenance needs, saving airlines millions of dollars in potential downtime.</li><li>Cisco uses IoT sensors to track the location and condition of its products throughout the supply chain, reducing inventory costs and improving customer satisfaction.</li><li>BMW uses IoT sensors to monitor the quality of its cars as they move through the production line, identifying potential issues before they reach the customer.</li></ul>These are just a few examples of how AI and IoT are delivering value in manufacturing. As the technology matures and standards emerge, we can expect to see even more remarkable results in the years to come.

As the demand for AI and IoT solutions in manufacturing grows, several key players have emerged to help companies harness the power of these technologies. Two notable examples are Samsara and Tulip.Samsara offers a Connected Operations Cloud that enables businesses in industries such as transportation, construction, and manufacturing to harness and analyze IoT data. Their platform collects trillions of data points from sensors, cameras, and other IoT devices, providing real-time visibility and insights across operations.For example, Samsara’s AI Dash Cams can detect distracted driving in real-time, prompting drivers to self-correct and reducing unsafe behavior by up to 50% in just three months. Their platform also enables predictive maintenance, helping companies spot potential issues before they lead to costly downtime.Tulip, on the other hand, focuses on empowering frontline workers with IoT-enabled apps. Their no-code platform allows manufacturers to digitize their operations, connecting workers, machines, and devices in a seamless ecosystem.With Tulip, companies can create digital work instructions, track production in real-time, and analyze performance data to drive continuous improvement. Their IoT-enabled apps have helped manufacturers reduce defects by up to 60%, increase productivity by up to 30%, and cut training time by up to 90%.Both Samsara and Tulip are prime examples of how AI and IoT can be leveraged to transform manufacturing operations. By providing intuitive platforms and actionable insights, these solutions are helping companies unlock new levels of efficiency, quality, and agility.

Looking ahead, the combination of AI and IoT is poised to transform manufacturing in ways we can only imagine. As IoT devices become more intelligent and interconnected, we can expect to see a rise in autonomous systems, from self-driving forklifts to self-optimizing production lines.AI will enable these systems to make decisions and adapt to changing conditions in real-time, improving efficiency, quality, and safety. It’s like having a team of expert operators working 24/7, never getting tired or making mistakes.

Of course, implementing AI and IoT in manufacturing is not without its challenges. Cybersecurity is a major concern, as the increased connectivity of devices creates more potential entry points for hackers. Manufacturers need to prioritize security and implement robust measures to protect their systems and data.Data quality is another critical factor. AI is only as good as the data it’s trained on, so manufacturers need to ensure that the data collected by IoT sensors is accurate, consistent, and relevant. This requires careful planning and ongoing maintenance of the IoT infrastructure.Finally, there’s the issue of skills and talent. Implementing and maintaining AI and IoT systems requires a new set of skills that may not be readily available in the current workforce. Manufacturers need to invest in training and education to build the necessary expertise in-house or partner with external providers who can fill the gap.

The convergence of AI and IoT is ushering in a new era of smart manufacturing, where machines talk to each other, learn from their experiences, and optimize themselves for maximum efficiency. It’s a world where downtime is minimized, quality is assured, and waste is eliminated.As manufacturers embrace this technology, they unlock new levels of productivity, agility, and competitiveness. The journey may be challenging, but the rewards are immense. With the help of key solutions like Samsara and Tulip, companies can navigate this new landscape with confidence, conducting a symphony of machines and data that will propel them to the forefront of Industry 4.0.

How does AI change the penetration of IoT?

The Challenge: Most tooling shops operate in a "hostage situation" where the keys to the most complex setups live exclusively in the minds of a few senior machinists. This "tribal knowledge" creates an immense "bus factor" risk: if a key employee retires or leaves, the business is paralyzed.Why It Matters Now: The industry is hitting a demographic cliff known as the "Silver Tsunami," with a projected shortfall of 1.9 million workers by 2033. When veteran engineers retire, their undocumented insights into design and production go with them, leading to longer onboarding times and increased error rates for the next generation.How CADDi Helps: <a href="https://caddi.com/en-us/platform/caddi-explorer/" rel="noopener noreferrer" target="_blank">Explorer</a> acts as your organization’s "digital brain," capturing and digitizing decades of fragmented intellectual property (IP), including handwritten notes on legacy 2D drawings. By centralizing this data, the platform allows any team member to access past projects and understand design intent instantly, reducing the time for new hires to become productive by up to 84%. Learn more about this in our report: <a href="https://us.caddi.com/resources/insights/labor-paradox" rel="noopener noreferrer" target="_blank">The Labor Paradox: Navigating Manufacturing's Unsettling Reality</a>.<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2F22d7f188f63c42dbb427d71bda7dcd96?format=webp">

The Challenge: Quoting is frequently a massive administrative time-sink that halts an owner's ability to work on the business. Speed-to-quote is a critical competitive metric, yet many shops rely on legacy spreadsheets and manual searches that can take hours or days to produce a single estimate.Why It Matters Now: In a market defined by the "Amazon Effect," customers expect instant gratification and technical superiority. The first responder to an RFQ often secures the business, but move too fast without accurate data and you risk winning a "race to the bottom" with an unprofitable deal.How CADDi Helps: Using patented similarity search, CADDi Quote allows your team to upload a new RFQ drawing and instantly find every geometrically similar part your company has ever handled. By automatically linking past pricing and actual ultimate costs to these drawings, your sales team can increase quotation capacity by 1.5x and deliver estimates that are both rapid and data-backed. Explore this further in our guide: <a href="https://us.caddi.com/resources/insights/manufacturing-quotation-in-2025" rel="noopener noreferrer" target="_blank">Manufacturing Quotation in 2025 - Challenges and Opportunities</a>.<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2Fe7d74b1c569c4d5ea724246daf34b649?format=webp">

The Challenge: A stark divide exists between shops utilizing data-driven costing and those operating on "gut feel" legacy rates (e.g., a flat $75/hour) that haven't kept pace with labor inflation. This inaccuracy leads to margin erosion and the danger of winning work that effectively loses the company money.Why It Matters Now: The market for skilled labor has reset, with top-tier machinists commanding significantly higher wages than just three years ago. To maintain an EBITDA margin of 15-20%, owners need precise instrumentation to identify exactly which jobs are profitable and which should be "fired".How CADDi Helps: CADDi functions as a System of Insight (SoI), integrating data from your ERP, PLM, and drawings to provide a unified view of your margins. By linking design features to associated financial and quality data, owners can understand price patterns between specific geometries and actual production costs, allowing for logical, fact-based pricing strategies.&nbsp;<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2Fe542deef15134fb0bdcaf54ba4070762?format=webp">

The Challenge: Stringent regulations like CMMC 2.0 and ITAR have moved from administrative headaches to existential filters. Shops that cannot invest the $100,000+ required to secure their digital perimeter risk being exiled from high-margin defense work.Why It Matters Now: Cybersecurity is no longer just an IT issue; it is a strategic moat. As prime contractors tighten their supply chains, they are aggressively seeking compliant partners who can demonstrate "reasonable care" in protecting sensitive technical data.How CADDi Helps: CADDi provides a secure, centralized repository for your most sensitive technical IP. By consolidating drawings from vulnerable local hard drives and email inboxes into a single, access-controlled platform, you reduce your attack surface and satisfy the rigorous documentation requirements of a SOC 2 compliant environment.<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2Fb003353db8b547fd864a184f3575cf60?format=webp">

The Challenge: Tooling leadership is often trapped in a cycle where growth is limited by the number of skilled bodies they can put on the floor. Every time an engineer "reinvents the wheel" because they can't find an existing part, it costs the company thousands in inventory carrying costs and unnecessary tooling.Why It Matters Now: With a zero-sum labor market, every hour of recovered efficiency is equivalent to increasing your headcount capacity. Shops must automate "knowledge work" to free their high-paid talent for innovation rather than administrative drudgery.How CADDi Helps: CADDi’s similarity search directly attacks parts proliferation, reducing drawing search time by 90% and preventing the creation of redundant parts. By enabling design reuse, companies like Dairy Conveyor Corp. have seen a 22% reduction in fabricated part spend, allowing them to scale revenue without adding expensive engineering overhead. See this in action with our <a href="https://us.caddi.com/product-tour?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Blog&amp;utm_campaign=&amp;utm_term=" rel="noopener noreferrer" target="_blank">Explorer Product Tour</a>.<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2Faac2526f8daf487188cb0fc38125ed9c?format=webp">

The American tooling leader of 2025 cannot afford to rely on paper travelers and grease boards. The path forward requires replacing guesswork with data and rigid legacy plans with agile, drawing-centric intelligence. By transforming your dormant drawing archive into a strategic asset, you can secure your margins, bridge the skills gap, and position your shop as a high-value partner in the new industrial era.Ready to see how a drawing-centric AI platform can modernize your operations?<a href="https://us.caddi.com/demo-request?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Demo&amp;utm_campaign=&amp;utm_term=blog" rel="noopener noreferrer" target="_blank">Book a personalized demo today</a> or download our comprehensive guide: <a href="https://us.caddi.com/resources/whitepaper/value-analysis-value-engineering-for-manufacturing" rel="noopener noreferrer" target="_blank">Reduce costs, not quality: Use VA/VE to uncover opportunities for efficiency</a>.

The Owner’s Crucible: 5 Data Strategies to Secure Your Tooling Shop’s Future in 2025

Explorer cover graphic reading "Fastener Consolidation, using AI analysis to achieve results, unlock cost savings and efficiencies," over a blue-tinted close-up of assorted bolts and nuts.

Some of the benefits you can expect to see from achieving fastener consolidation include:<h3>Supplier consolidation and procurement efficiencies</h3>One immediate benefit is that the number of different parts you need to source decreases. Rather than having 80 slightly different screws, you go down to just one. As a result, you’ll order from fewer suppliers. This increases the efficiency of procurement processes, as they’ll need to search for suppliers less often. It also helps you reduce costs per part. You’ll make larger bulk orders from each supplier, allowing for stronger negotiation and rate discounting.<h3>Faster and better designs</h3>Another benefit of fastener consolidation is in the design process. When designing a new part, engineers will know immediately what fastener to use in which situation, instead of having an overwhelming amount of options. Moreover, without fastener consolidation, information on what fasteners have been used before is often scattershot and incomplete. This leads to engineers designing with even more new fasteners, further exacerbating the problem of fastener proliferation. Having a few options, clearly delineated for each case, makes designing new parts much faster and prevents them muddying up your parts catalogue further.<h3>Lower defect and failure rates</h3>Fasteners have a certain failure rate and defect rate, just like any other part. When designing new parts, sourcing component parts, or predicting the failure rate of components in operation, it’s important to know the rates of the fasteners involved. The more different fasteners you’re working with, the less you know about the operation of each of them. Consolidating fasteners allows you to get more testing data for each of them. This allows you to have a more accurate picture of the quality of each product. In turn, this enables designing smarter around this information, leading to higher quality products and lower defect and failure rates.<h3>Better SKU management and reduced organizational costs</h3>As we’ve seen with <a href="https://us.caddi.com/resources/whitepaper/part-proliferation-when-duplicate-and-unnecessary-parts-make-searching-slow-by-clogging-up-your-database" rel="noopener noreferrer" target="_blank">parts proliferation</a>, having your databases stuffed full of unnecessary entries is costly. You have the direct costs of hosting a larger-than-necessary database, and possibly physical inventory. Then you have the costs of having people maintain the accuracy of the database, which scales quickly with the size of the database. Most impactfully is the time sink in actually using the database. The more unnecessary entries you have, the harder it is to find what you need, creating slowdowns in workflows across your shop and massive opportunity costs.‍All of this is just as true for fasteners as any other part. Fastener consolidation can reduce the size of your database, and thus reduce all these associated costs.<h3>Better procurement agility and supply chain management</h3>We live in an uncertain world in terms of the supply chain. Tariffs, other geopolitical conflicts, and shortages can quickly disrupt any procurement strategy and leave teams scrambling to find alternative suppliers. When you’re trying to find an alternative for 800 different types of fasteners, this can be an impossible task. When it’s only 80, it’s a lot more doable. Fastener consolidation allows you to have more options and switch to them more flexibly.

With all of these benefits, it seems like an obvious choice to undertake a fastener consolidation exercise. And the process itself seems straightforward too. In a nutshell, you:‍<ol><li>Track down all the different fasteners currently used across your shop</li><li>Look at each of them and figure out which are redundant</li><li>Categorize them into as few functionally distinct categories as possible</li><li>Figure out which fastener to go with for each category based on price and quality data</li><li>Update designs to use only the chosen fasteners</li></ol>‍It sounds so easy on paper, but when you try to work through this process, you’ll find some stumbling blocks, including:<h3>It takes a long time to do fastener consolidation</h3>The most obvious challenge here is that all of these steps take a very long time when you have lots of fasteners. Tracking down specific designs and reviewing which fasteners are used in each of them is very manual and tedious. It may also require an expert to parse drawings, further bottlenecking your process.<h3>The data you need is likely incomplete or inaccessible</h3>On top of taking a long time, fastener consolidation may also lead you down wild goose chases. You may be digging around for data that exists only on paper, in the memory of other employees, or in gigantic spreadsheets with meaningless ID numbers. You’ll likely have to dive into a variety of tools that each contain their own subset of the story. This isn’t just time-consuming, it’s frustrating, leading many shops to abandon the process.<h3>Cross-referencing contextual data is time-consuming, too</h3>When you’re trying to determine which fasteners are worth keeping, you want to see the big picture on each of them: how much do they cost, which suppliers can we get them from, what are their defect and failure rates, etc. Cross-referencing this data for each part is typically a tedious and manual process, and can also lead to many goose hunts when things are incomplete.‍In all, although fastener consolidation sounds easy on paper, in practice it can be anything but. It’s no wonder that shops often don’t have the resources to tackle this project proactively, even when they understand the benefits. However, there is a modern solution that makes fastener consolidation much faster: AI analysis.

On top of all the other amazing use cases of CADDi, we make fastener consolidation quick and painless. Here’s how:<h3>Connect unstructured data into a data lake</h3>Rather than having to root through a million spreadsheets, tools, and even filing cabinets, CADDi can receive all your data and organize it into one comprehensive <a href="https://us.caddi.com/resources/insights/manufacturing-data-lake" rel="noopener noreferrer" target="_blank">data lake</a>. This way, when you search for fasteners, you can be confident you’re finding them all.<h3>Use AI image search to track down fasteners</h3>Rather than manually looking at each design and trying to find all the fasteners, CADDi uses cutting-edge AI machine vision to “look at” every drawing for you. Upload an example drawing of different types of fasteners – clamps, bolts, etc. – and CADDi will find all the drawings that contain them. You can even start with a hand drawn sketch as your example.‍You can also search for how fasteners are labelled in drawings. CADDi uses best-in-class OCR to find where these labels are written on drawings without needing them to be transcribed into text. Using CADDi searching, you can easily track down every fastener currently used by your shop.<h3>AI image analysis to create categories of fastener</h3>CADDi can go even further, automatically categorizing similar fasteners using our similarity search. Search using any example of a fastener and CADDi will instantly surface the most similar designs. This allows you to quickly identify redundant fasteners without requiring expertise or manual analysis.<h3>Surface contextual data to make strategic choices</h3>When it comes time to decide which fasteners should remain in use, CADDi makes the choice easier by automatically surfacing the relevant contextual data for each fastener. This includes quality reports, pricing history, supplier information, and more. Even new members to your teams can make the necessary strategic analysis to make the correct choice with this information surfaced and highlighted.‍To see CADDi in action and learn how it can help achieve your fastener consolidation goals, <a href="https://us.caddi.com/demo-request?utm_source=Website-Referral&amp;utm_medium=Website&amp;utm_content=Demo&amp;utm_campaign=&amp;utm_term=blog" rel="noopener noreferrer" target="_blank">check out a demo today</a>.

Fastener Consolidation: What it is and how to use AI analysis to achieve it quickly

Explorer cover graphic reading MD&M West, CADDi's Reflections, three key themes for 2026, learn about the next era of MedTech, over a photo of the Anaheim Convention Center with large MD&M West signage

CADDi’s 2026 Manufacturing Outlook Study revealed that <a href="https://us.caddi.com/resources/news/79-of-manufacturing-executives-say-skilled-labor-shortage-is-greatest-challenge-according-to-new-caddi-research" rel="noopener noreferrer" target="_blank">79 percent of more than 200 manufacturing decision makers identified skilled labor shortages as their largest operational challenge</a>. At the booth, the head of Engineering at a MedTech OEM shared, “My lead engineer is retiring in three months. He’s the only one who knows which of our legacy drawings can be repurposed for this new robotic surgical arm. If he leaves, we’re essentially starting from scratch on every ‘new’ part.”CADDi structures and transforms legacy PDFs, even the handwritten ones from 20 years ago. The platform makes those files searchable by geometry so validated design history, tolerance decisions and regulatory context are accessible across the organization.<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2Fa63a57cd90d641d1904859b7ee3fa612?format=webp" alt="Two people talking at a trade show booth, one with a red beard gesturing beside a touchscreen kiosk and the other in a white cap and backpack, with rpk Medical banners and a Sugino sign in the background">

Some manufacturing leaders are dealing with design transfer bottlenecks. An Operations lead at a contract manufacturer shared, “We’re trying to move toward modular automation, but every time a customer sends us a design change for a medical device, the design transfer process stalls. We spend weeks just identifying which existing fixtures or suppliers can handle the new tolerances.”With CADDi’s platform, procurement and production teams can see those design changes in real time and immediately surface every similar part the company has manufactured. Historical tolerance ranges and supplier performance data are surfaced alongside the design so teams can make decisions without extended manual investigation. Structured part history shortens decision cycles.<img src="https://cdn.builder.io/api/v1/image/assets%2F209ee507cedf4c298e100edae4bba2df%2F04b3fdef35ba4ffe8a694ce3fe16b5ec?format=webp" alt="At a CADDi trade show booth, a person in a blazer uses a large touchscreen kiosk showing an engineering drawing while two attendees look on.">

Another key pain point revealed in conversations was global supplier consolidation. During a discussion on reshoring, a Head of Strategic Sourcing explained, “We’re moving 30% of our plastic component sourcing back to North America to avoid tariffs. But honestly? It’s a mess. I have three different buyers unknowingly sourcing almost identical parts from three different suppliers at three different price points.”Similar geometries often exist under different part numbers across business units. CADDi’s AI identifies those identical or similar parts across the entire enterprise dataset, even if the part numbers are completely different. Enterprise-wide part visibility supports standardization and spend control.

Manufacturers are turning to a unified, data-centric operating model to scale and grow their business. Experienced engineers are retiring, and companies risk losing the design knowledge they depend on. Automation programs depend on accessible historical drawings, tolerance data and supplier performance records. Bringing production back to North America adds complexity to sourcing, especially when similar parts exist under different names..Key decision makers at manufacturing companies are assessing how engineering knowledge is captured, structured and reused across design, procurement and production. Interdisciplinary manufacturing leaders evaluate AI technology return on investment by whether it shortens lead times, reduces cost and improves decision making on the shop floorIn 2026 and beyond, organizations who are able to effectively operationalize fragmented engineering data into structured, searchable intelligence strengthen reuse, standardization and cost control across the enterprise.

MD&M West 2026: CADDi Reflections

CADDi leverages AI to digitize drawings and procurement data, making manufacturing insights searchable by shape, text, dimensions and part names.