How we help you
Production monitoring tools and other Industry 4.0 systems help make your business smarter, more effective and profitable. We help you implement these tools and use them to get a clearer understanding of what’s happening during your production process and how you can make it more efficient.
Implement production monitoring and Industry 4.0 tools
Gain insights into your production process
Find new efficiencies and avoid losses or leakage
Strengthen your profitability and cash flow
Get an Industry 4.0 advisor to streamline your production processes
We don’t just give you the tools to make your production processes more efficient — we help you integrate them into your business. Our experienced technology advisors understand manufacturing, Industry 4.0 and how to use technology to improve your operational performance.
Explore our production monitoring services
Wipfli’s guided implementations help ensure timely, accurate configurations and enhance management and operator confidence. We support your business with:
- Configuration: Our process-based approach helps us better configure solutions to align with your processes and objectives.
- User training: We support your staff education efforts to help ensure that end users can use the full potential of your new solution.
- Adoption: We help you leverage the data from your solution and incorporate new strategies for performance review into daily management. With our adoption support, you can see greater value from your investment and scale it over time.
Wipfli’s performance analysis support helps you identify more ways to use the data from your real-time production monitoring system.
As part of our remote support we:
- Help increase data literacy across your business through intentional performance analysis.
- Provide regular checkups of your environment and analyze any data trends.
- Provide coaching over your data so that you understand how to apply it to improve performance.
We provide in-person support to help you use real-time data from production monitoring tools to drive operational and process improvements.
As part of our in-person support, we:
- Work closely with your shop floor team to leverage data to drive shop-level improvement.
- Facilitate the changes that need to happen based on the data from your solutions.
- Leverage data to make smarter decisions about operational changes.
- Augment staff where needed to help ensure you have skilled talent in critical areas such as operations, sales or finance.
Wipfli is committed to helping you simplify production data with Intouch, an affordable production monitoring solution that can modernize your factory without a legacy system overhaul.
We’ve been a trusted Intouch implementation partner since 2022, with a track record of delivering productivity insights in days, not weeks or months. Our specialists can help you connect discrete manufacturing equipment to dashboards that measure efficiency, quality and profitability around the clock.
Here is what you can expect from Intouch with the support of Wipfli’s implementation consultants:
- Results: Intouch and Wipfli’s custom dashboard and reporting support help you see data down to the machine, part and shift level, so that you can identify inefficiencies, react faster to downtime events and know exactly how to improve utilization.
- Automation: We help you seamlessly integrate Intouch’s Manufacturing Equipment System with your ERP, enabling you to automate data exchange, eliminate double entries and base decisions on a single source of truth.
- Value: With nearly a century of experience in serving manufacturers, we understand your operations and how to take Intouch beyond hardware to give you full control over your production strategy. We also offer comprehensive services to support successful implementation, from onboarding and leadership training to continuous maintenance.
Insights and resources
ARTICLE
Manufacturing investments that drive operational efficiency
Manufacturers are operating in an environment of labor shortages, rising costs and economic uncertainty. They are also dealing with the rapid emergence of AI and automation. Businesses must invest in technology that improves efficiency to remain competitive. But questions about which investments are worth the cost can be overwhelming. Keep reading to learn which technology investments manufacturers should prioritize to overcome current business challenges and make long-term gains in improving operational efficiency. The efficiency challenges facing manufacturers today The manufacturing industry has made significant progress since the disruptions of the COVID era. But post-pandemic, significant challenges still remain. Labor shortages remain a long-term issue Hiring qualified production employees remains difficult across much of the manufacturing sector. Even when positions can be filled, turnover remains high, making it difficult to maintain consistent production schedules. Insufficient staffing can prevent equipment from operating at the levels required to meet customer demand. Automation has become more expensive Automated solutions are seen as an answer to labor shortages. But automation projects require greater upfront investment than they did several years ago. Inflation, lingering supply chain issues and tariffs on imported equipment and parts have increased the cost of robotics, machinery and automation technologies. AI decision paralysis AI is top of mind for many people in the manufacturing industry right now. Many organizations hesitate to invest in proven automation technologies because they’re waiting to see what new AI tools emerge on the market. While AI will continue to transform manufacturing, delaying practical investments can leave companies operating with outdated processes while competitors continue to improve efficiency. What automation investments have the highest ROI in manufacturing? Not every automation investment delivers the same return. Manufacturers often achieve the strongest results by investing in technologies that eliminate repetitive, non-value-added work while remaining flexible enough to support multiple products or production lines. Examples include: Packaging automation Packaging frequently requires significant labor while adding little customer value. Automated packaging solutions can reduce repetitive labor requirements and improve consistency and throughput. They can operate across multiple product configurations when properly designed. Machine monitoring systems Machine monitoring technologies are becoming increasingly valuable because they provide real-time visibility into: Machine uptime Downtime causes Production rates Equipment performance Process consistency This data can be used to respond to issues on the production floor faster and to develop strategies to maximize productivity. Beyond helping manufacturers identify bottlenecks, machine monitoring systems create the data foundation needed for future AI applications. The organizations that collect and organize operational data today will be better positioned to deploy advanced analytics and AI capabilities tomorrow. Process control technologies Investments that improve machine consistency and process repeatability often generate substantial returns. Better process control reduces variability, improves quality and minimizes the need for downstream human inspection and correction. Reducing overhead in the back office When manufacturers think about improving efficiency, they often start with the production floor. However, some of the best opportunities to reduce overhead exist in the back office. SG&A tasks frequently involve manual data entry, repetitive transaction processing and labor-intensive reporting that can be automated. Here are some examples: Accounts payable and accounts receivable processes: AI and automation can streamline invoice processing, payment matching and collections tracking by reducing manual data entry and accelerating transaction workflows. This helps improve accuracy, shorten processing times and free finance staff to focus on higher-value activities. Sales order entry and management: Automated order processing tools can capture orders from emails, portals and customer documents, populate ERP systems and flag exceptions for review. This reduces administrative workload, minimizes errors and speeds order fulfillment. Financial reporting activities: AI-powered reporting tools can automatically consolidate data from multiple systems, generate standard reports and identify anomalies or trends. This reduces the time spent on manual report preparation while improving reporting consistency and insight generation. Customer communication workflows: Automation platforms can handle routine customer inquiries, order status updates, payment reminders and service notifications through email, chat or self-service portals. This improves response times while reducing the labor required for repetitive communications. Internal reporting and data analysis: AI can quickly analyze large volumes of operational and financial data, generate dashboards and identify patterns that might otherwise go unnoticed. By automating data collection and analysis, manufacturers can reduce reporting overhead and enable faster, data-driven decision-making. How data can reduce management overhead Advanced data can streamline mid-level supervisory functions. Modern dashboards, automated reporting and AI-powered alerts can deliver operational insights directly to managers instead of requiring manual data collection and analysis For example, data from your production floor can power AI agents that deliver real-time insights into production. Floor supervisors can look at that data and quickly identify which machines or units were producing at expected rates and which weren’t. That data, combined with the supervisor’s knowledge of part or machine history, enables more targeted investigations and faster solutions to production slowdowns. Let data drive inventory decisions Supply chain uncertainty continues to make inventory management a difficult balancing act. While some manufacturers respond by increasing inventory levels, simply carrying more stock is rarely the most effective solution. The goal isn’t maximizing inventory. It is maximizing visibility. To make informed inventory decisions, manufacturers should combine customer forecasts with historical demand patterns, supplier lead times and market intelligence. Analyzing historical data can improve planning accuracy when customer forecasts are imperfect. Collaboration plays a role in inventory management Rather than carrying inventory risk alone, manufacturers should work closely with both customers and suppliers to establish realistic expectations regarding demand, lead times, inventory levels and forecast accuracy. Open communication across the supply chain often results in better inventory decisions than independently managing uncertainty with larger inventory buffers. Don’t start with AI — start with your data When manufacturers consider new automation or AI investments, it’s natural to focus on the tools or systems. But it’s important to first evaluate the quality of your organization’s data. Before investing in advanced AI tools, you should answer these questions: What data are we currently collecting? Which business metrics truly matter? What information are we not capturing today? How accurate, consistent and accessible is our data? Can our systems share information effectively? The value of any AI or automation system depends largely on the quality of the information available to it. Manufacturers that establish strong data management practices before implementation will be able to extract more value from their technology investments. How can manufacturers measure the ROI of their technology investments? AI and automation investments are made to increase productivity. Here are some metrics you can analyze to determine if you’re getting your money’s worth: Throughput Throughput measures how much value the business creates relative to its workforce. This metric evaluates how efficiently the organization converts purchased materials into customer value using its available labor. Higher throughput generally indicates a leaner, more productive operation. Earned labor Investments in automation and AI tools need to increase earned labor metrics. Earned labor compares the amount of labor that should have been required to produce a given level of output with the labor actually used. For example, if production standards indicate a certain output should require eight labor hours to manufacture, but actual production required 10 labor hours, the operation underperformed expectations. If that same amount of product is produced with seven labor hours, you outperformed labor expectations, and your earned labor metric increased. Back-office productivity Administrative efficiency should also be measured. Evaluate improvements by examining cash collection, sales activity, customer service performance or accounting productivity relative to staffing levels. AI should increase the amount of work each employee can accomplish rather than simply reducing headcount. What technology investments should be prioritized in the near-term? The manufacturers that remain competitive over the next several years will likely focus on investments that are adaptable, scalable, and capable of supporting long-term business goals. Priority areas include: Flexible automation Flexibility allows manufacturers to adapt as customer demand changes. To be ready for fluctuating demands, prioritize scalable technology that can be used for multiple products, processes or production lines. AI-powered knowledge transfer As experienced workers retire, manufacturers risk losing decades of operational knowledge. AI tools that capture expertise, troubleshooting methods, best practices and institutional knowledge can help organizations preserve the experience of long-tenured employees. These tools can accelerate the development of new employees and potentially reduce training costs. Workforce enablement tools Future investments should account for ongoing labor constraints. Technologies that help employees become more productive, make more informed decisions and manage larger workloads will likely generate significant value. Also, prioritize tools that reduce dependence on difficult-to-fill positions. Align investments with long-term business strategy Every business has different technologies needs based on its goals and roadmap. There is no off-the-shelf solution that is right for everyone. Manufacturers should first determine what they want their business to look like three to five years from now and then invest in technologies that support that vision. The goal is not simply to buy new technology but to build a future operating model that remains competitive despite workforce challenges, changing markets and evolving customer expectations. Read more We asked 456 manufacturers about the state of the industry. Here’s what they said. How manufacturers can pursue IEEPA tariff refunds How to build a sales strategy for today’s manufacturing environment
ARTICLE
Move from bottlenecks to innovation breakthroughs with supply chain speed
Increasingly complex supply chains and persistent disruption are making speed a prerequisite for innovation, not just efficiency. As supply networks grow denser and more global, delays are rarely caused by a single failure but by hidden bottlenecks that compound across tiers, slowing production and constraining innovation. When manufacturers can’t see and act across the full end‑to‑end supply chain, even the best ideas stall before they reach the plant floor. Here are some practical ways automotive manufacturers can increase supply chain speed and enable greater innovation : Increasing speed starts with increasing visibility Visibility is the foundation for faster decision-making and operations. When leaders can clearly see what’s happening across their supplier network, they’re better positioned to understand where time, cost and risk are accumulating and how complexity and disruption are affecting the pace of innovation. For many automotive manufacturers, delays aren’t caused by a single issue but by a series of small bottlenecks: extended lead times, limited insight into tier two or tier three suppliers or vendor terms that no longer align with production demands. Each bottleneck adds friction that slows new product launches, engineering changes and process improvements. Without clear visibility from the moment an order is placed to the day materials arrive at the dock, it’s difficult to pinpoint where days — or even weeks — can be shaved off the cycle. Additionally, global sourcing , specialized components and just-in-time production have increased complexity at every tier. When you can’t see through the layers of your supply chain, you can’t adapt quickly to disruptions or opportunities to gain a competitive edge. In this environment, supply chain visibility is a strategic requirement. Clear, timely insight into your supply chain is what enables faster decisions and the agility needed to innovate in an increasingly competitive space. How you can turn visibility into speed Speed is increased when visibility into your operations translates into action. When you can act on supply chain insights, they drive timely, decisive responses rather than sitting in dashboards or reports. Here are three ways you can move toward actionable visibility: 1. Targeted alerts Alerts only drive speed when they’re designed for action. In complex supply chains, signal quality directly affects how quickly innovation and production can move forward. Alerts should be prioritized, real-time and delivered to the people who are accountable for resolving the issue, not broadly distributed or buried in systems. Most importantly, they should be tied to real production risk, not generic variances that create noise rather than clarity. 2. Clear decision rights When an alert is triggered, your organization must know exactly who has the authority to act and how. Clear, scalable decision rights eliminate delays caused by ambiguity, handoffs or unnecessary cross‑functional approval cycles. 3. End‑to‑end control tower behaviors A true supply chain control tower doesn’t simply observe. It orchestrates. Effective control towers should: Connect internal production schedules with external logistics, supplier commitments and real‑time inventory data so every function is working from a single, trusted source. Focus on continuous risk monitoring rather than periodic reviews. Be supported by scenario‑based playbooks for common disruptions — labor shortages, transportation delays, supplier failures — so teams know exactly how to respond without re‑inventing decisions under pressure. Fully embedded so that manufacturers can move from reactive firefighting to proactive coordination. An effective control tower means organizations can activate alternate suppliers or reroute freight before constraints hit. Teams can expedite critical components, adjust build sequences based on parts availability or reallocate inventory to protect high‑priority orders. Just as importantly, these actions happen at the operational level, without teams getting bogged down in reporting issues, escalating every decision to leadership or reacting only after an incident has occurred. The result is faster recovery from disruption, greater production stability and a supply chain that actively supports innovation instead of constraining it. How to build a faster automotive supply chain For automotive manufacturers, improving supply chain speed doesn’t require a full transformation on day one. Agility is built by focusing first on the areas that reduce complexity, sharpen decision‑making and improve responsiveness: Integrated data Digital fragmentation is one of the biggest barriers to supply chain speed. When engineering, procurement, production and logistics data live in separate systems, the handoffs between teams can create delays and increased risk. The ideal state is a single source of truth, where all decisions, dashboards and analytics pull from consistent, integrated data. While achieving full integration can require significant investment, progress doesn’t have to wait. Start by identifying where fragmentation is slowing decisions or creating risk. Focus first on connecting the most critical nodes, such as integrating shop floor data with procurement systems, to deliver immediate gains in responsiveness and ROI, while building toward a more unified data foundation over time. SKU rationalization Complexity is a silent profit killer. Over time, OEM‑specific variants, legacy programs and customer‑driven customization can significantly expand SKU counts and strain operations. Pruning underperforming or redundant SKUs can help manufacturers reduce carrying costs, simplify production planning and improve their ability to reallocate materials during shortages. Fewer SKUs reduce friction across the supply chain, allowing production changes to move faster. Demand planning Speed also depends on moving away from intuitive forecasting toward disciplined, data‑driven demand planning. Purchasing behaviors are too often shaped by convenience rather than strategy, such as ordering materials in large, infrequent batches simply to avoid repeated transactions. Additionally, long vehicle development cycles have historically allowed companies to work through inefficiencies over time. Today’s compressed timelines leave far less margin for error. Developing strong planning habits is essential to navigating faster-moving award programs and sourcing decisions. Effective planning supports operational efficiency today and builds the muscle memory required to compete at higher speeds in the future. How Wipfli can help Faster, more resilient operations are a critical part of enabling innovation at scale. Wipfli helps automotive manufacturers to improve speed and operational agility with services that work across your operations, from technology to strategy to people. Visit our automotive industry page to learn more. See our automotive services Read more Does reshoring make sense for auto parts suppliers? How automotive suppliers can drive profits in a down market Automotive nearshoring: Should auto parts manufacturers consider moving to Mexico?
ARTICLE
Why speed is the missing link in automotive smart factory ROI
For many U.S. automotive manufacturers, bringing a new model from concept to production still takes three to five years. In a global market where competitors, particularly in China, can compress that timeline dramatically, those cycle times are no longer sustainable. Smart manufacturing is starting to deliver the value and speed manufacturers need, but the challenge is moving from vision to execution. The opportunity is clear: organizations that thoughtfully implement the practices needed for an automotive smart factory can significantly reduce time to market while improving resilience and scalability. Why is speed necessary for smart manufacturing? Smart manufacturing is more than about automation or deploying new technology. It’s about removing the friction that slows production, decision‑making and problem resolution across your operations. Three operational areas where speed has an outsized impact include: Faster line changes: Moving away from manual setups and institutional knowledge toward automated parameters and digital work instructions allows manufacturers to standardize changeovers, reduce downtime and improve throughput. When updates are applied instantly across lines and shifts, production can adjust without sacrificing consistency. Better constraint resolution: Production bottlenecks are inevitable; prolonged bottlenecks are not. Real‑time visibility into production and inventory , combined with the ability to dynamically reroute orders or adjust machine speeds, gives leadership and plant teams earlier warnings, clearer root‑cause insight and faster cross‑functional coordination, including with suppliers. Reduced quality escapes: Immediate alerts when measurements fall out of tolerance, paired with rapid containment actions, help protect customers and brand reputation. Additionally, faster feedback loops between inspection points and production teams reduce the risk of defects multiplying across shifts or lots. How to build your speed stack Achieving meaningful gains in production speed requires building digital capabilities deliberately, layer by layer, with each step reinforcing the next. Manufacturers that want to generate sustainable cycle‑time improvements should focus on three foundational layers of capability: Visibility: Speed starts with visibility. Manufacturers can leverage tools, including production monitoring solutions and standardized dashboards, to provide real-time awareness of their factory floor, reducing blind spots and shortening the time it takes to identify and resolve problems. Predictive insight: Once real‑time visibility is established, manufacturers can begin to shift from reaction to anticipation. The predictive layer uses historical and current production data to forecast equipment failures, anticipate parts shortages and detect quality drift before defects escape. With predictive insights, leadership can improve planning and prioritization so that there’s less firefighting and more proactive responses. Autonomous response: The greatest speed gains come from closing the loop. Autonomous response enables the factory to take predefined actions automatically within clearly defined business rules and controls, helping to remove human bottlenecks. For example, autonomous response could stop a line or isolate suspect builds when quality thresholds are exceeded or resequence schedules in response to labor or material constraints. Visibility provides the data foundation. Predictive capabilities convert that data into foresight. Autonomous response turns insight into immediate action. How you can start increasing production speed today Meaningful speed gains don’t require your organization to reach autonomous response on day one. Instead, focus on building up your foundation in the areas where you can see immediate impact. Here are some practical ways you can see real speed gains sooner: Prepare your processes and data One of the most common missteps among automotive manufacturers is leading with technology instead of the problem. Organizations ask, “How do we implement robotics?” or “Where can we deploy vision inspection?” without first defining their operational challenges. Instead, you need to understand where your production truly slows. Where are your machines failing most often? Where does work-in-progress accumulate? Where do quality issues or material shortages interrupt flow? Introducing new technology into a broken or poorly understood process or without reliable data will only amplify inefficiencies. Start with the outcomes you want to see so you can identify the tools that can deliver a better ROI. Build scalable, repeatable processes Decision‑making that funnels through a single president or leader may work at a small scale, but inevitably becomes a constraint as the organization grows. And tools cannot make decisions, or even support better ones, if the underlying logic isn’t based on documented, repeatable processes. To move faster, manufacturers must establish clear processes, controls and decision rights that empower teams at multiple levels. Support your people through change Speed initiatives can succeed or fail based on adoption. Too often, new tools are introduced without meaningful input from the people who work with them every day — especially on the shop floor. This disconnect can result in solutions that address leadership assumptions rather than real operational challenges. It’s important to involve all stakeholders early in the process. Frontline insight helps validate where bottlenecks occur and contributes to more accurate, actionable data. Seeing increased buy‑in also requires education and training. End users must understand not only how to use new tools, but also how those tools improve their daily work. If teams are not trained to interpret and act on real‑time data, even the most advanced dashboards aren’t going to impact performance. Integrate your systems When data lives in different systems, plans and functions, you’re not getting the clear picture of operations needed to drive decision-making and speed. However, most manufacturers aren’t ready for full, enterprise-wide integration. The goal should be progress, not perfection. Identify the areas where fragmentation is currently creating delays, blind spots or manual workarounds. Prioritizing current challenges for your integration efforts helps deliver near-term gains while setting a foundation for long-term scalability. Read more Top affordability challenges for automotive suppliers in 2026 How smarter inventory management strategies can help you protect margins Cost containment strategies for auto parts suppliers
Reach out to our team
Let’s talk about how we can help you gain deeper insights into your production processes so you can make better use of your capacity, avoid leakage and strengthen profitability. Our manufacturing technology advisors know how to implement production monitoring and other Industry 4.0 systems so you can operate more effectively.
LET'S CONNECT
Discover how Wipfli can help you overcome barriers to profitability and build smarter, leaner operations.
