Nine ways smart data improves factory operations

Manufacturers are increasingly turning to smart manufacturing principles, hoping to turn the shop floor into highly efficient, data-driven operations humming with synchronised precision. Unfortunately, line-of-business managers, crew leaders, and shift supervisors—the shop floor heroes—often lack easy access to the ERP system and the relevant data needed to keep production on track.

Deskless workers play a vital role in operational efficiency. Democratising data—making data consumable for a wider population—will give these frontline users valuable decision-making insights. With role-based dashboards and reporting tools, they can drive better performance up and down the production line, from smart use of resources to reduction in rework and scrap.

Countless critical decisions are made on the shop floor every shift. The setting—notoriously noisy and fast moving—isn’t conducive to careful, prolonged pondering of influences. Fast-moving production lines require fast decisions and expedient action. At the same time, errors can be costly, eating away at profitability, wasting resources, and jeopardising as-promised delivery times. Decisions based on guesses, one random exception, or anecdotal stories can send a team into spirals of wasted time, frustrating workers and managers alike.

Empowering front-line users

The answer is to put data in the hands of every decision-maker in the organisation, even those who aren’t advanced data analysts with skills in report writing and applying artificial intelligence (AI) algorithms. Modern digital platforms provide interface tools to help users apply advanced functionality to everyday situations. Featuring low-code and no-code capabilities, the digital platform provides front-line users with role-based dashboards to track relevant key performance indicators (KPIs) and custom reporting to investigate emerging trends. Quickly, dynamic insights are within reach of machine operators, maintenance technicians, and material handling engineers, scheduling clerks, and shift leaders.

Data drives speed and accuracy

Operational-level access to data is especially helpful in preventing gaps in workflows and avoidable delays. Frontline workers can get immediate answers to design questions or specifications on a custom work order. Access to information keeps production lines moving as planned, with minimal interruptions because of questions, disconnects between departments, or stockouts.
Advanced analytics can go even further to keep the shop floor operating smoothly and profitably. Managers can delve into exceptions and tracking influencing variables. They can find opportunities for improvement, such as eliminating quality roadblocks or controlling down time.

Practical applications

As artificial intelligence (AI) and machine learning (ML) have moved into the mainstream, manufacturers are increasingly seeking practical applications for data insights. Proof of concept projects are being replaced by ones which promise a timely, measurable return on investment. The shop floor offers many practical applications for AI-driven insights. Routine processes can be automated, streamlining the need for human interaction. Only anomalies or exceptions need to be routed to supervisors for individual attention. Streamlining the data flow will also help keep various teams apprised of real-time updates and needs. No one is out of the information loop, falling behind on evolving expectations. One data-driven digital thread will connect every stage in shop floor operations.

Here are nine examples of how democratised data helps boost productivity:

1. Custom quotes and bill of materials. Efficiently managing make-to-order, engineer-to-order, and configured products requires an automated system for generating rules-based quotes and matching bills of materials. Once the customer has approved the order, the specifications must flow from sales to operations to ensure the right dimensions, features, and finishes are applied. Access to the customer order helps manager verify details, eliminating reworks or customer returns.
2. Projecting raw resources needed. Synchronising production planning and availability of raw resources requires access to data and AI-driven predictive capabilities to prevent stock-outs. Data helps procurement managers make sure the warehouse is stocked with necessary components. Too much inventory can be just and dangerous, tying up capital and risking obsolescence.
3. Accurate scheduling. Synchronising production runs to fulfill customer orders depends on accurate account data as well as sales, delivery promises, inventory of raw materials, and machine capacity. Working with co-manufacturers or subcontractors also requires access to information. Collaboration portals can help share information while protecting security.
4. Strategic scheduling of the workforce. With data insights, managers can track and understand performance of shifts and crews, identifying essential staffing requirements and tracking expenses. With the acute labor shortage manufacturers face today, careful scheduling of right-skilled workers is especially important.
5. Workflows. Keeping operations running smoothly with no gaps, delays, or roadblocks requires coordination among teams and sharing data on job status, equipment performance, and scheduling. Reporting can help identify trends and analyse variables, allowing managers to delve deeper into influencing factors that can be improved. Decisions can be made, changes executed, results monitored, and further refinements made. Continuous improvement can be part of the system and standardised workflows.
6. Compliance and quality control. Managers need to track, monitor, and evaluate quality standards, with a continuous feedback loop in place. As new products are introduced, specifications need to be easily updated and accessible to relevant teams. Regulation compliance, too, is critical in many industries and demands accurate reporting. Democratised access to data helps keep the details in view when and where they are needed most.
7. Waste reduction. As manufacturers strive to be more sustainable, they place a high priority on reducing waste, including energy, water, and raw resources. Reducing scrap is essential. By improving consistency and quality control, fewer units will need to be scrapped or reworked. Access to data will help crews verify proper machine settings, consult knowledge banks for typical resolutions of issues, and verify proper specifications and variables.
8. The call centre. The aftermarket service operation needs real-time access to account and product details to answer customer questions about deliveries, service agreements, warranty status, and scheduled preventive maintenance. Service dispatch needs to access the location and availability of technicians to dispatch the right person to the right job based on geography, service level agreements, and urgency.
9. First-call resolution. Field technicians at the job site need remote access to details on the unit, as-serviced history, inventory status of parts, and availability of replacement or upgrade units. A technician with the right data is seen as a trusted advisor and can often make sales in the field.

Next steps

Manufacturers considering deploying their first ERP solution or upgrading a legacy solution, often compare various vendors and the functionality of their solutions. A factor that can be overlooked is the usability of the system and how accessible the data is to workers throughout the organisations. Some vendors offer ERP solutions that are cumbersome and difficult to use, meaning many of the features will simply not be used.

In contrast, some solutions offer built-in industry-specific functionality and make usability a top priority. Easy access to data is essential and a characteristic to look for in a smart ERP selection.