What You Don’t Know Is Hurting You – Shop Floor Management Software – JobPack

Connect transparency with results by analyzing the production data you already have.

There’s a lot happening on the shop floor, and every single bit of it can impact your production schedule. As technology evolves and the manufacturing industry undergoes digital transformation, real-time production monitoring is becoming increasingly accessible. And while real-time information is critical for operational agility, there’s even more to be gained from all that data as it collects over time.

Data analytics help you pinpoint opportunities to gain efficiency, reduce waste, shrink cost, and deliver on time. With analytical tools like those that JobPack offers, you can leverage the shop floor data you already have to find and close gaps in your processes, and to build on what you’re already doing well. Moreover, you can learn things about how your factory works that you never knew, and answer questions that you never thought to ask.

Without quality analytics, your shop is flying blind. With them, you can construct a detailed map of where you are—and where you want to go. Here are five ways that missing or underutilized information is hurting your manufacturing business, and how you can harness your production data to turn each of them into opportunities.

1. Reduce missed deadlines

Without analytics, achieving a high on-time delivery rate is a demanding job. You have to either adhere rigidly to a fixed production schedule, or put in strenuous work to adapt to sudden changes—and sometimes, both at once. In cases where there was no obvious inciting incident, finding the root cause of the delay may take days of sifting through production logs, all while trying to maintain productivity on the shop floor as well.

With analytics, you can leverage historical data and real-time capacity information to give clients high-confidence delivery estimates. Using knowledge gained from previous similar jobs, you’ll be able to plan the ideal time to order supplies, raise alerts right away when production falls off the necessary pace, and begin contingency planning as soon as possible.

2. Understand planned vs. actual performance gaps

Without analytics, the difference between planned performance and actual performance becomes a guessing game. Was there a supply chain issue? A staffing hurdle? Is a machine performing less efficiently than it was previously? Issues are rarely attributable to just one cause, and finding the most pressing logjam only compounds the challenge.

With analytics, root cause investigations become dramatically easier. Compare past and present data to pinpoint changes, and trace them to evaluate downstream effects. Gain a high-level view of production workflows and eliminate bottlenecks to boost your efficiency. As you make changes to your production process, you’ll also be able to regularly reevaluate your key performance indicators to ensure that you’re headed in the right direction.

3. Minimize understaffing and overtime costs

Without analytics, finding the right staffing plan is a challenge, and errors are costly. Insufficient staff can mean missed deliveries, long hours of overtime, and stressful juggling of priorities—to say nothing of the effect that last-minute schedule changes can have on employees.

With analytics, you can predict your capacity more accurately, and optimize staffing accordingly (and well in advance), letting you cut down on overtime spending and improve the experience for your employees at the same time. You can even take advantage of historical data to identify seasonal trends and other patterns in demand, and plan to staff up or down to match. That way, you can rise to the occasion while cutting back on unexpected costs.

4. Avoid unplanned downtime

Without analytics, equipment failures can catch you by surprise and upend a tightly planned production schedule. Now, not only are you facing the cost of equipment repair or replacement, but you have to simultaneously realign your schedule around reduced capacity and critical maintenance.

With analytics, you’re able to build predictive models of equipment performance and spot red flags when they arise. If a machine is showing signs of wear, you can find the best window in which to shut it down for maintenance. Analytics allow you to develop a predictive maintenance plan based on past performance, and avoid the disruption of run-to-failure.

5. Capitalize on opportunities you might otherwise miss

So far, we’ve covered a handful of stubborn, but common, challenges that result from underutilizing your production data. But the biggest advantage of robust data analytics might be the ability to spot the previously invisible: the factors impacting your productivity that you hadn’t even anticipated.

With detailed production data monitored over time, you gain new levels of visibility into your shop floor and its processes. Mining that data for insights can turn up undiscovered inefficiencies or delays, and offer you the opportunity to fine-tune your workflows, make better use of your resources, or boost your output. Integrate with a full ERP, and you’ll be able to cross-reference production data with even more business information—and uncover more synergies to build on.

Uncover the insights to grow your business with JobPack’s data analytics.

JobPack is a lightweight, intuitive production scheduler that implements quickly and enables you to make the most of your shop floor. With JobPack, you can organize the production data you already collect and leverage it to optimize your existing processes as well as test new ideas.

JobPack builds on your existing technology environment: whether you’re at the beginning of your digital transformation or you have a mature ERP implementation, JobPack integrates with your current data sources to offer the real-time visibility, robust monitoring, and actionable insights to help your business be its best self. To learn more about how JobPack can elevate your production scheduling, request a demo today.