How Manufacturers Can Use Real-Time Business Intelligence

Manufacturers generate large amounts of data every day. Each production update, stock movement, labour entry, purchase order, quality check and financial transaction reveals something about how the business is operating.

The challenge is turning all that data into information people can actually use.

When figures sit in separate systems and spreadsheets, or only become available in reports produced days or weeks later, it is difficult to spot an emerging issue or respond while there is still time to change the outcome. Business intelligence (BI) brings operational data together and presents it in a clearer, more timely way, helping manufacturers understand performance, identify priorities and act sooner.

We spoke with two Genius ERP customers—Kaleb James, Managing Director of Stafford Engineering, and Mathieu Robert, President & CEO of G.M. Precision—to learn how their companies use business intelligence and key performance indicators (KPIs) to get more value from their data.

What Is Business Intelligence in Manufacturing?

Business intelligence brings together the tools and practices a company uses to collect, organise, analyse and display its data. In a manufacturing business, this information may come from production, stock, purchasing, sales, quality, job costing, finance and other parts of the operation.

BI converts that data into dashboards, reports, metrics and KPIs that make performance easier to understand.

Although business intelligence and analytics are often discussed together, they play slightly different roles. BI gives teams visibility into what is happening across the business. Analytics helps them explore the information further, recognise patterns and find opportunities to improve. Used together, they allow manufacturers to move beyond simply recording activity and start learning from it.

This does not mean displaying every available figure. Effective BI gives each person relevant information that supports the decisions they are responsible for making.

Move From Historical Reporting to Real-Time Manufacturing Data

Many traditional manufacturing KPIs describe results that can no longer be changed. They show what happened during the previous week, month or completed job rather than what is taking place now.

“Most businesses track KPIs that exist in the past—the ‘what has happened’—not ‘what is currently happening,’” says Kaleb. “They tend to be financial ones, such as job costs or gross margins or what you see in your profit and loss or management accounts, a few weeks after you have any chance to influence the outcome.”

Measures such as job costs, margins and financial results remain essential. However, if managers only see them after the work is complete, the information may arrive too late to help them correct the problem that affected the result.

G.M. Precision gained a more accurate view of its performance by collecting live information from production equipment. The data exposed inefficiencies that had been hidden by the company’s earlier method of measuring machining time. 

“By using real-time data collected from our production machines, we realised that our method for validating actual machining time could be skewed due to various factors that delay production. Real-time machine status monitoring software allowed us to determine the actual hourly unit production time, including time losses caused by both planned and unplanned equipment downtime,” says Mathieu.

This clearer view of what was occurring on the shop floor helped G.M. Precision increase efficiency and productivity.

That ability to respond is one of the greatest benefits of real-time BI. A production manager does not have to wait for a completed report to discover that scrap has increased, a bottleneck is developing or a job is slipping behind schedule. The team can investigate while the issue is unfolding, before it leads to further waste, higher costs or a missed delivery date.

Turn Manufacturing Data Into Useful Information

Access to more data does not automatically result in better decisions. The information must also be easy to find, interpret and act upon.

Dashboards can collect the most relevant measures for a particular team, role or individual and display them in a straightforward visual format. This allows users to see what needs attention without working through lengthy reports or manually combining information in spreadsheets.

“Too often data is hard to visualise, hard to get to, or worse yet, locked away so that it’s not readily available,” says Kaleb. “A good BI toolkit will allow you to surface the things that matter to you most. This could be as simple as visualising any materials that have been ordered and are now due or overdue, so procurement can focus on following up suppliers, ensuring the material is ready when the guys doing the work need it, boosting efficiency and throughput.”

“The key here,” emphasises Kaleb, “is that it should always be available and up to date, as opposed to a report that needs to be run and then sorted through.”

Stafford Engineering has made its KPIs difficult to miss by placing screens in carefully chosen locations around the shop floor. The live displays allow employees to see current performance as part of their normal working day. “We have found that the small outlay in some internet-ready large screen TVs displaying KPIs in strategic locations within the business gets this noticed, and the actions follow from there.”

At G.M. Precision, timely information also supports better production planning and more precise communication with customers. “When it comes to updating customers on production progress, we’re now much more targeted with the information we share,” says Mathieu. “It also helps us better plan our production schedule.”

A useful dashboard is not defined by how much data it contains. Its value comes from making the current situation clear and helping the person viewing it understand where action is required.

How Manufacturers Can Use Business Intelligence

BI improves decision-making throughout a manufacturing company. The best place to begin will vary according to the organisation’s priorities, processes and most pressing operational problems.

Monitor Production Performance and Throughput

Production dashboards can provide an up-to-date view of jobs, machines, labour activity, downtime, work centres and other shop-floor conditions.

With this information, managers can compare actual results against production targets and see where work is moving more slowly than expected. Data on machine and work-centre use can also highlight spare capacity or reveal a constraint that is holding back throughput.

Current data gives production leaders a stronger basis for deciding where their attention will have the greatest effect, instead of relying on assumptions or discovering problems once the job is finished.

Improve Production Scheduling and On-Time Delivery

A workable production schedule depends on accurate information about labour and machine capacity, material availability, job progress and changing priorities.

BI gives planners a way to monitor these connected factors. When a machine goes down, material is delayed or an operation takes longer than planned, they can see the potential effect on other work and revise the schedule accordingly.

This visibility also helps customer-facing teams provide more reliable updates. Orders that may be at risk can be identified sooner, giving the business more time to take corrective action or communicate a change in delivery expectations.

Connect Stock, Purchasing and Production

Stock figures are far more useful when viewed alongside demand, purchasing activity, current production and the requirements of upcoming jobs.

BI can help teams track raw materials, work in progress and finished goods; find potential shortages; review overdue purchase orders; and see which items production will need next. Purchasing can then focus its supplier follow-ups where they matter most, while planners gain a more realistic understanding of what the shop can complete.

Longer-term analysis can reveal patterns in material usage, supplier lead times and stockholding. Manufacturers can use those findings to make better purchasing decisions, avoid holding more stock than necessary and reduce disruption caused by unavailable materials.

Spot Quality Issues and Reduce Waste

Measures such as scrap, rework, non-conformances and first-pass yield can show where quality is beginning to deteriorate.

Live visibility makes these KPIs especially valuable. If scrap suddenly rises, the production team may be able to stop the process, investigate and correct the cause before additional labour and material are wasted.

Historical data has a different but equally useful role. It allows a manufacturer to find recurring quality problems, compare performance across jobs or processes and judge whether its corrective actions have delivered a lasting improvement.

Use Job Costing Data to Protect Profit Margins

Keeping a job on schedule is only one part of managing its performance. Manufacturers also need to know whether actual labour, material and other costs remain in line with the estimate.

BI can compare estimated and actual job costs, track resource use, monitor margins and highlight changes in expenses or cash flow. When a job begins to exceed its budget, managers can investigate the reason while options may still be available.

Completed-job data strengthens future decisions too. By examining where similar work made or lost money, estimating and sales teams can prepare more accurate quotes, reconsider pricing and plan new jobs using evidence from past performance.

How ERP Supports Manufacturing Business Intelligence

Reliable business intelligence begins with reliable underlying information. Building a clear view of performance is difficult when each department uses different records, spreadsheets or standalone applications.

An ERP system connects core manufacturing activities, including production, stock, purchasing, sales, job costing and finance. Because these areas work from shared data, the ERP provides a strong base for dashboards, reporting and analysis.

Rather than gathering figures manually whenever a new report is required, manufacturers can build KPIs that update as employees record transactions and complete work. Shared records also reduce the risk that departments will base decisions on conflicting versions of the same information.

Manufacturers can create an even more complete view of their operations by combining ERP data with information from other sources, such as machine-monitoring applications, spreadsheets and other business systems. When choosing a BI solution, manufacturers should consider all their important data sources and ensure they can be brought together.

How to Choose the Right Manufacturing KPIs

Tracking more KPIs does not necessarily create greater insight. Too many measures can distract employees from the few that genuinely require attention.

A better starting point is to consider which decisions need to improve and which business problems must be solved. A worthwhile KPI should make performance clearer and help someone decide what to do next.

Common manufacturing KPIs include:

• On-time delivery and job progress
• Production efficiency and throughput
• Machine and work-centre utilisation
• Downtime
• Scrap and rework
• Labour performance
• Stock accuracy
• Overdue purchase orders
• Quotation conversion
• Estimated versus actual job costs
• Job profitability

The right measures will also differ from one role to another. A production manager may need immediate information about job status and machine availability. A purchasing manager is more likely to focus on material requirements and overdue orders. Senior leaders may need a broader view of profitability, capacity, delivery performance and long-term trends.

Dashboards should support these different responsibilities rather than showing every employee the same set of figures.

How to Get Started With Business Intelligence

A manufacturer does not need to design a complete BI programme before it can start benefiting from its data.

Mathieu’s advice is straightforward: “Start with simple indicators that make sense to you—and then improve your KPIs over time.”

Kaleb agrees and adds that it’s important to think about where your data is coming from. “My advice for anyone considering a BI solution is to first consider where your data sources are located and ensure that your BI solution can handle multiple data sources,” he says.  “Often, what you think you want at first evolves along the way as you see the power of good data insights and what they can bring to your business.”

The first dashboard might focus on one urgent concern, such as late jobs, missing materials or excessive scrap. Once employees are comfortable using those measures, the company can refine what it displays, add other data and introduce BI to more areas of the operation.

The requirements are likely to develop as people discover what the information can tell them. Answering one question often raises another or reveals that an additional measure would provide valuable context.

BI should therefore be treated as an evolving decision-making tool, not a finished collection of reports. Its purpose is to help the organisation understand its operations more clearly and keep improving how it responds.

Make Better Decisions With Real-Time Business Intelligence

Real-time business intelligence does more than describe performance. It gives employees the timely, relevant information they need to solve problems, make better use of capacity and improve results.

The experiences of Stafford Engineering and G.M. Precision also show that manufacturers do not need to perfect every dashboard at the outset. Progress begins by making important information visible, giving the right people the ability to respond and refining the approach as the company learns.

Start with the decisions that matter most and select a small number of KPIs that can inform them. Moving from retrospective reporting to live operational insight will put your business in a stronger position to influence performance rather than merely explain it afterwards.