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  • Jeb Lyne

Using Advanced Technology to Improve Revenue, Cost, and Cashflow: A Short Primer for Small and Medum Manufacturers and BU-Level Plants

Throughout my consulting journey with diverse manufacturing companies - from large, sophisticated corporations to bootstrapped startups - one common thread has emerged: the desire to leverage technology to enhance work quality and efficiency.

However, many companies grapple with identifying the right technology to implement. Often, business leaders focus on familiar functions or popular technologies, which can lead to challenges in developing a compelling business case.

A more effective approach is to focus on the desired outcome and explore ways to achieve it, recognizing that technology is merely a part of the solution. This is particularly crucial for small and medium-sized manufacturers (SMMs) and business unit (BU) level plants. These entities typically have fewer resources than large manufacturers, leaving little room for error.

To assist these businesses, I’ve created a mapping that links revenue, cost, and cash flow outcomes to use-cases leveraging Advanced Technology (AT). This mapping, based on various sources, including my own ideas (see bibliography at the end), is organized by income statement area. As there are more use-cases possible than those listed here, consider this a thought-starter.

I use the term Advanced Technology (AT) to encompass a broad spectrum of emerging technologies such as Quantitative AI, Generative AI, Machine Learning, Digital Twins, Digital Threads, Advanced Analytics, Internet of Things (IoT), 5G, Additive Manufacturing, Rapid Prototyping and Simulation, Augmented Reality (AR), Extended Reality (XR), Robotic Automation, Collaborative Robots (cobots), Computer Vision, and more. These technologies often serve as building blocks to support achieving outcomes and are useful only when coupled with other technologies.

I intentionally avoid the term Digital Transformation (DT) as it has become generic and should be interpreted as technology-enabled performance transformation, a concept leveraged by most performance transformations throughout history.

Below is the use-case to outcome mapping:





•    Use AT to understand market dynamics to systematically align strategic account management.

•    Lever AT-driven market-based pricing and margin floors.

•    Use AT to steer sales teams and customers into standardized products or get premium pricing for custom products.

•    Use AT to visualize solutions to support sales.

•    Use data analytics to identify cross-selling opportunities across the business.

•    Lever AT to streamline quote development and decision-making process.

•    Use AT to reduce engineering burden to support bid and proposal efforts.

•    Automate connection between sales, engineering, procurement, and production for product design and Bill of Material (BOM) development.

•    Use AT to rationalize SKUs and resultant sales complexity (as well as reduce engineering costs to manage SKUs).

•    Lever a AT-driven risk-based approach to customer terms development

•    Use AT to monitor customer payment patterns and publicly available data to get early warning on customers that are at-risk of default

•    Automate collections management.


•    Implement AT-driven dynamic pricing strategies for pricing passthrough on raw materials and freight based on real-time market trends.

•    Utilize predictive analytics to forecast demand and adjust procurement schedules accordingly.

•    Automate supplier selection and negotiation processes to secure the best prices.

•    Employ AT-driven inventory management to minimize holding costs and reduce waste.

•    Use AT to optimize payment terms based on supplier risk profiles.

•    Use AT to monitor supplier delivery performance and publicly available data to get early warning on suppliers that are at risk of disrupting production.

•    Use AT to optimize inventory to support production schedules and upside scenarios at the lowest days on hand.

•    Use AT for demand forecasting to align production with market needs.

•    Optimize payment terms with suppliers using AT to analyze market conditions and supplier performance.

•    Integrate blockchain for transparent and efficient procurement transactions.


•    Optimize production capacity to match financial goals.

•    Increase uptime and resultant effective capacity to fill more demand.

•    Enhance product quality via computer vision and AT-assisted quality control, leading to higher customer satisfaction and repeat business.

•    Deploy AT for training, enabling faster ramp-up times for new product lines.

•    Lever process mining and AT to optimize shop floor, routings, etc. to reduce waste and support implementing lean manufacturing principles.

•    Utilize AT for predictive maintenance, reducing downtime and maintenance costs.

•    Use advanced technology to automate issue identification, escalation, and resolution.

•    Incorporate collaborative robots, automated process steps, and automated material handling to reduce cost and smooth production flow.

•    Accelerate production cycles with real-time monitoring and AT-driven process adjustments.

•    Reduce capital tied up in work-in-progress inventory through just-in-time production strategies.


•    Use AT to optimize route planning and delivery schedules, improving customer service levels.

•    Implement AT-enhanced navigation systems for drivers to improve delivery efficiency.

•    Automate warehouse operations with robotics to lower labor costs.

•    Employ AT for demand forecasting to optimize distribution center locations and inventory levels.

•    Use pick-to-light or other AT to increase picking accuracy and reduce time to pick.

•    Integrate electronic proof of delivery with invoicing systems to speed up receivables.

•    Apply dynamic discounting for early payments from customers based on AT risk assessment.


•    Offer AT-based customization tools to clients, enabling ability to support multiple revenue streams with a single engineering base.

•    Use AT to accelerate product development and shorten time to market.

•    Streamline R&D processes with AT-driven simulation and testing.

•    Lever AT to enhance Design for Manufacturing (DfM), Design for Cost (DfC), and other “Design for…” (DfX) efforts.

•    Implement AT for automating routine tasks to reduce labor costs.

•    Use AT to maximize use of current engineering library and drive adherence to product platforming strategy.

•    Lever AT to accelerate VA/VE projects and SKU rationalization efforts.

•    Implement project management tools with AT forecasting to improve capital allocation for engineering projects.

•    Enhance patent portfolio management with AT to capitalize on intellectual property more effectively.

•    Use AT for real-time monitoring and management of expenses.

General & Administrative

•    Use AT for financial forecasting to inform strategic decision-making.

•    Deploy AT chatbots for customer service, upselling additional services and products.

•    Automate administrative tasks with AT to reduce overhead costs.

•    Implement AT-enabled training modules for staff, reducing training costs and improving productivity.

•    Use AT to reduce total labor burden on high-cost overhead for tasks such as contract evaluation and regulatory compliance.

•    Utilize AT for financial forecasting, improving budgeting and reducing unnecessary expenditures.

•    Automate payables to optimize cash and take proper advantage of select early payment incentives.

I welcome your thoughts on this list. What did I miss? What’s working well for you? What do you wish more people would consider? Please share your insights in the comments!

Bibliography (note that my retrieval data was 16 April 2024)

  1. Aberdeen. (n.d.). 3 Ways to Boost Revenue in Manufacturing. Retrieved from

  2. ABI Research. (2024, January 4). Generative AI Use Cases in Manufacturing. Retrieved from

  3. Altamira. (n.d.). Cost Reduction Strategies for Manufacturing Industry. Retrieved from

  4. BAutomation. (n.d.). Reduce Manufacturing Costs Using Digital Transformation. Retrieved from

  5. Capgemini. (n.d.). Artificial Intelligence Can Improve Cash Flow for Manufacturers. Retrieved from

  6. Control. (n.d.). Manufacturing Technologies for Increased Productivity and Reduced Costs. Retrieved from

  7. Corporate Tech Decisions. (n.d.). Revenue in Your Factory. Retrieved from

  8. Datapel. (n.d.). Improve Cash Flow in Manufacturing Business. Retrieved from

  9. Deloitte. (n.d.). Manufacturing Industry Outlook. Retrieved from

  10. FinAccountants. (n.d.). Maximising Efficiency: A Guide to Optimizing Cash Flow and Working Capital in the Manufacturing Sector. Retrieved from

  11. Google Cloud. (n.d.). Five Generative AI Use Cases for Manufacturing. Retrieved from

  12. Harvard Business Review. (2023, November). A New Generation of Robots Can Help Small Manufacturers. Retrieved from

  13. Katana MRP. (n.d.). Reduce Manufacturing Costs. Retrieved from

  14. MachineMetrics. (n.d.). Reduce Cost of Production. Retrieved from

  15. McKinsey & Company. (n.d.). Accelerating Revenue Growth Through Tech-Enabled Commercial Excellence. Retrieved from

  16. McKinsey & Company. (n.d.). Digital Twins: The Next Frontier of Factory Optimization. Retrieved from

  17. McKinsey & Company. (n.d.). Harnessing Generative AI in Manufacturing and Supply Chains. Retrieved from

  18. Matterport. (n.d.). Digital Twin: Manufacturing. Retrieved from

  19. MDPI. (n.d.). Article. Retrieved from

  20. NJMEP. (n.d.). 3 Ways Manufacturing Companies Can Improve Cash Flow. Retrieved from

  21. Phocas Software. (n.d.). Improve Cash Flow in Manufacturing. Retrieved from

  22. ScaleUpAlly. (n.d.). Generative AI in Manufacturing. Retrieved from

  23. SME. (2021, May). Assisting Small and Medium-Sized Manufacturers with Industry 4.0/Smart Manufacturing Technology Adoption. Retrieved from

  24. Spiceworks. (n.d.). How Manufacturers Can Cut Costs with Advanced Technologies. Retrieved from

  25. Springer Link. (n.d.). Article. Retrieved from

  26. Stefanini. (n.d.). Applications of Digital Twins in Digital Manufacturing: Use Cases and Benefits. Retrieved from

  27. TechTarget. (n.d.). Unleashing the Power of Recurring Revenue in Manufacturing. Retrieved from

  28. Unity. (n.d.). Digital Twin Applications and Use Cases. Retrieved from

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