Using Real-Time Data to Win New Business

Bottom Line: Manufacturers are achieving only 40% of their potential because they’re spending too much valuable time manually updating inventory control, production reporting, and pricing reports when their competitors using real-time data to get the data they need to win deals and plan next-generation real-time factories

Manual Reporting Creates Mediocre Results

Relying only on manually-produced reports, manufacturers are able to use at best 40% of their production capacity based on interviews and plant visits completed in the last six months. The pace of sales cycles, competitors, and pricing decisions, all driven by buyer’s compressed timeframes for making purchasing decisions, is a primary factor. A second factor is the volume of data a typical manufacturer produces in a given day of operations. Relying entirely on manual updates to reports, spreadsheets and schedules aren’t fast enough to capture and capitalize on all relevant data and opportunities.

The truth is manually-based manufacturers who are slow to respond to quotes (if they ever respond at all), slow to move on pricing or make production decisions aren’t considered by buyers anyone. They’re left out of opportunities because buyers don’t consider them in the first place. Here are a few examples of how manual reporting creates mediocre results every day:

• It takes 6 months or longer to onboard new production engineers & planners due to the number of systems and data sources they need to do their jobs at a specialty products manufacturer.
• Production scheduling teams spend the majority of the time acquiring, cleaning, and preparing data prior to data analysis and rarely if ever, have time to optimize schedules.
• An industrial equipment manufacturer relies on swivel-chair integration or having their engineers swivel from one screen to the next to update production schedules form a homegrown MRP system to Excel spreadsheets.
• A plastics contract manufacturer at 40% capacity is struggling to get more business because production engineering is too busy doing reports to respond to quotes.

Lack of Trust Is Locking Manufacturers Out Of Real-time Opportunities To Improve   

Data gaps create distrust, and poorly implemented enterprise systems fuel it. That’s why so many manufacturers reject the idea of implementing new production systems. Sales cycles keep accelerating, and pricing keeps getting more volatile, buyers’ timeframes keep getting shorter, making real-time data necessary to survive today. Manually-based businesses I’ve spoken with are the most confident about two things: their product quality, and customers repurchasing from them next year. Manufacturers who only rely on manually-based reporting are deluding themselves if they think they can hold onto customers in a real-time world. When their competitors are retrofitting existing plants, building smart factories or both, it’s time for the over-reliance on manual reporting to end.

Choosing to compete in real-time opens up opportunities to improve plant-wide, starting with the following:

• Convert more sales quotes, pricing requests, and proposals into orders by being able to respond faster and more accurately. Doing quotes, pricing and proposals manually put any business at an immediate selling disadvantage, because it’s often the competitor who provides the first quote who wins the deal. When a manual reporting mindset dominates a manufacturer, the lack of quote, pricing and proposal wins quantifies the dollar loss from lack of speed. Automating configuration, pricing and quoting (CPQ) is where manufacturers need to start.
• More accurate cost control and visibility down to the unit level. The majority of manufacturers are suppliers to tier-1 OEMs and brands in their industries, where deals are won or lost on per unit pricing, delivery, and quality accuracy. Real-time monitoring helps to find where and how per-unit costs can be reduced and quality improved.
•  Troubleshoot process and batch-based product quality problems using data from real-time monitoring. Real-time data is proving indispensable in troubleshooting the root cause of process and batch-based product quality problems, with Statistical Process Control (SPC) techniques commonplace. Real-time data is creating the foundation of smart factories today, starting with product quality.
• Improving cycle times and reducing scrapped parts by using real-time data to better troubleshoot and solve process, batch, and machinery-related problems. A plastics manufacturer I recently visited adopted real-time monitoring to troubleshoot why they were getting 36% yield rates from an extrusion process and machine. Real-time monitoring pinpointed a specific mold and plastics combination that once fixed improved yield rates to over 99%.
• Improve production plan performance by attaining greater schedule accuracy. Operators and entire production teams don’t trust their planning and shop floor systems because the data are inaccurate and out of date. Troubleshooting why planning and shop floor systems are providing inaccurate results needs to start with real-time data that helps to more accurately benchmark true work center productivity levels and machinery utilization rates.
• Prolonging the life of equipment, machinery, and tools using real-time data to predict when maintenance, repair, and overhaul need to take place. Real-time monitoring is providing an entirely new series of insights into how manufacturing equipment and machinery lifespans can be improved. By combining real-time data with predictive analytics and machine learning, it’s possible to determine when a given machine will need repair. Best of all, long-standing assumptions regarding preventative maintenance are changing due to greater insights gained from real-time data.

Conclusion

Manufacturers who continue to rely on manual reporting are missing out on the opportunities to improve their business and gain new customers that real-time data brings. The data gaps many see in their homegrown, legacy, and third-party systems create distrust. Shutting down all initiatives to improve using an enterprise production system is not the answer, however. Configure, Price and Quote (CPQ) strategies are a great place to start with a real-time data pilot, as improvements in this selling process are measurable in improved revenue and reduced selling costs, and shortened sales cycles.