In 2023, more and more large manufacturing companies start to take advantage of technology in order to optimise production and find smarter ways to use resources. 

That’s the fancy way of saying that industrial companies are trying to stop bleeding money because of inefficiencies in their daily operations—at least that’s the simple truth at the end of the day. 

However, you feel like you can’t exactly put your finger on the inefficiencies and you can’t link them directly to losses in resources (money, man-hours, materials etc). To get a bit poetic, they’re like little hidden trolls that multiply and compound over time, lurking around the plant floor, silently working under the radar, and eating money. Some plant managers have a hunch the trolls are there, but can’t be sure without… data. 

Data is the light you shine upon them to expose them, and your SCADA system is the one making sure it happens. 

Wait, why would you care about SCADA? 

The straightforward answer is that you probably really don’t care about SCADA itself. And honestly, as an executive, especially in charge of the budget, you shouldn’t—I certainly wouldn’t. 

What you should and do care about is the ROI from a project like that. You understand that the tech part is cool for your colleagues, but if this thing goes south, you’re the one that approved thousands of euros on it, and it wouldn’t feel good. You’re the guardian of the business, and business means money. Naturally, you ask “ok, guys, do we really need this? And if we do, how do we make sure we’re spending this significant budget wisely to actually get some results in the form of either reduced costs or increased income?”

That’s the question I’m going to answer today. As a business owner myself for over 16 years, I can 100% empathise with the feeling and provide some insights that are relevant to the business/finance side of things. 

What even is SCADA? 

SCADA is an acronym for “Supervision, Control, And Data Acquisition”. 

In a nutshell: 

Supervision = you supervise/overview your processes and equipment. You can:

• overview process values,
• monitor alarms,
• follow the production in real time,
• ‌see what’s going on, right now in real time.
  

Control = you can interact with the process 

• by changing settings,
• start and stop processes.

Note: Supervision is information flowing from the process to you and Control is the other way.

Data Acquisition = collect data. 

• get real-time information about the processes – for example, set KPIs and stay informed about them.
• historical data for data analysis.
• data to track and trace your products. 
• all data is available to everybody at the same time in a unified format and contextualised (explained below)
• Work Order Management 
  

Let me explain and exemplify a few things here. 

Get real-time information about the processes

For example, set KPIs and stay informed about them.

We can talk here about an OEE (Overall Equipment Effectiveness) dashboard. Several KPIs on such a dashboard can be relevant for executives. I’ll just give one example: scrap rate. 

The scrap rate represents the percentage of defective or rejected products compared to the total number of products produced. A high scrap rate leads to increased material waste and higher production costs, affecting the company’s profitability.

Short storytime: 

Recently, we built a simple quality control solution in Ignition for a manufacturing company.

Before, their scrap rate was over 50%. Yes, more than 50% of their resources were essentially wasted. 

Today, thanks to the data from the quality control process, their scrap rate is less than 5%. The financial implications of this are more than impressive. 

All data is available to everybody at the same time

… in a unified format and contextualised,

As I will explain below, all data from different sources comes in one place: the Ignition platform. Thanks to its features, we can provide different levels of access and permissions to different roles, but if two roles with the same access/permissions need to view the same kind of data at one point in time, they will both see exactly the same set of data. 

The data is “in a unified format”, which means the data structure is standardised. The SCADA system is designed to get data from various sensors, devices, PLCs throughout the manufacturing process, so these data sources may have different formats and communication protocols. The data is diverse, which means there has to be a common model or a structure that all data can be translated into. 

From a financial point of view, this is necessary for at least 2 reasons: 

• It removes a lot of headaches and resource-consuming activities when it comes to adding new devices to the process (it makes it scalable) because they will be integrated much more easily. 

• If the data is unified and the data structure is clear, you can compare, for example, the data from line A to the data from line B, thus potentially identifying differences or other types of insights. 

Moreover, the data point is not just a number – it is contextualised. 

What does “contextualised” mean? 

Short storytime: 

We were in a large utility company some years back, visiting the plant floor. There was an automation engineer present, showing us around. At some point, we stopped to view a display. On it, there was the value “70.5”. 

We all stood there, wondering: 70.5… of what? Celsius? Liters? Pressure measurement? 

That’s what we mean by contextualised data. Numbers on the screen are just that – numbers on the screen. Data has to mean information. 

Work order management

The primary goal of work order management is to streamline and optimise the workflow for executing work orders, which are requests for specific tasks or activities to be performed. These tasks can range from routine maintenance and inspections to repair work, equipment installations, and other planned activities.

Here are several ways SCADA can help with work order management:

1. Real-time data collection: SCADA systems continuously gather real-time data from various sensors and equipment throughout the industrial process. This data includes equipment status, performance metrics, and operating conditions. By having access to this real-time data, work order managers can make more informed decisions about when and where to schedule maintenance tasks based on the actual condition of the assets.

2. Condition-based maintenance: SCADA systems can implement condition-based maintenance strategies, which means that work orders are generated automatically when specific predefined conditions are met. For example, if a pump’s vibration levels exceed a threshold, a work order for maintenance can be automatically triggered. This approach helps to detect potential issues early, reducing downtime and increasing asset reliability.

3. Resource allocation and planning: SCADA data can help optimise resource allocation by providing insights into asset performance and historical maintenance data. Work order managers can efficiently allocate technicians, tools, and materials to specific tasks based on asset conditions and historical maintenance requirements.

4. Historical data: SCADA systems store historical data, including past work orders and maintenance activities. By analysing this data, work order managers can identify patterns and trends in equipment performance, enabling them to fine-tune maintenance strategies.

5. Reporting and documentation: SCADA systems can automatically generate detailed reports and documentation related to work orders, maintenance tasks performed, and associated costs. This documentation helps with compliance reporting, auditing, and regulatory requirements.

Why can’t we just use what we already have? 

Because what you have now may include these problems that are drilling holes in your budget: 

Siloed data

This links back to the above topic of “all data available to everybody”. Let me start with the short story this time to illustrate the benefit of integrating your data sources.

Let’s take a major manufacturing company as an example. A lot of departments, a lot of sites, a lot of people, right?

There’s a person in the Sales Department, let’s call him John. John gets a call from a potential customer. The customer would like to make a huge order of a specific product. 

This is a good opportunity for the company, and he’s excited about it.

But he just got a major obstacle in his way: he has no idea how the production of that product is going currently. He has no data and information from the plant floor – can he even put in that huge of an order? How long would it take? 

So, John puts the important customer on hold and begins a very tedious, long process of phone calls to get information from the plant floor.

If he’s lucky enough, the customer will still be on the phone to talk more about it. 

If not, John just lost an opportunity. And it could’ve been avoided if he had easy access to the relevant data he needed.

That’s why you should aim for an infrastructure that shares data across the company. Here’s what that looks like: 

The aim must be to have a good overview of your data from the plant floor to the enterprise level. That means that you need to connect your systems in order to have a single source of truth and a seamless flow of data throughout the organisation.

It may sound complex and hard. Well, it’s definitely not “easy”, but if you go with our proven way of starting small, it’s more than achievable. 

You want your data integrated because you want to make decisions based on it, right? The right tools and processes turn data into valuable insights that benefit everybody. All organisations focus on knowledge sharing and getting people to engage. Data turned into insights is the ultimate democratisation of knowledge sharing. 

It reminds me of a statement from one of my previous bosses: “Is this something we know or something we think we know?” It’s a great question, and with the appropriate data, we can move more in the direction of something we know. 

To sum up: everybody should have access to data because it is the ultimate form of knowledge sharing. And because everybody makes decisions, large and small, every single day. 

Last but not least, it promotes transparency, but more on that later. 

Note: it’s important to say that there’s a right and wrong approach to this. The right approach is bottom-up. Start with the plant floor (connect machines, devices, processes etc), then work your way up to the ERP and other enterprise systems. It reduces risks, shows ROI faster, and can remain adaptable to changes. 

Ok, wait, we were talking about SCADA, and now you’re mentioning ERP. What’s up with that? 

Your Ignition-based SCADA system and ERP system can be very good friends, providing you with fantastic insights into the real costs of production. 

Short storytime: 

For example, if your SCADA and ERP are integrated (as they will be using Ignition as the platform), you can compare the ESTIMATED production costs in the ERP system with the ACTUAL costs using real-time data from the production lines. 

Just as some clever guys in Germany did: they used Ignition to collect more data, and then they used it to actually learn something from that data. 

How? 

They connected some machines on the plant floor and added context to the data they got from them. For example, they could see that a machine was running at 80%, but they needed to know why – that’s why they added context, or “metadata” as it’s called. 

After they had all this, they compared it with the standard data they already had in their ERP system and built a simple OEE dashboard to visualise it all. 

The question was: does the data from the machines match with the data and estimations from the ERP, do we have the right understanding of our production costs?

The answer was “no”. 

The estimations were off because they weren’t anchored in reality. And they couldn’t have known that if they didn’t have the data from the machines. From a financial point of view, that was a problem. Now, their efficiency is improved, and they’re much more informed about the real costs of production. 

Manual tedious tasks

Ah yes, the usual walk to a machine on the plant floor, armed with a USB stick, lots of patience and mental power to witness, once again, the dreaded Excel spreadsheets that nobody really understands being spewed onto the USB stick. 

For real now—this is what an automation engineer from a huge manufacturing company told us. He was triggered every time he had to do that. And we understand. 

This may sound similar to what you have now, and it’s simply not a wise business decision to continue like this. 

For engineers and operators, manual tasks mean annoying and boring work. 

For you as an executive, it means consumed resources that you could’ve otherwise used more wisely in other ways if those tasks were automated. 

Ignition has built-in features such as data analysis and visualisation tools that can help you make better use of your data. These tools can be used to automate data retrieval and analysis, identify patterns and trends, and optimise manufacturing processes.

Essentially, you use Ignition to connect things, bring data to one place, and have fun with it from there. 

Having data in one place opens a box of opportunities: 

• Do you need Ignition to calculate a standard report or KPI (Key Performance Indicator) and email that to someone?

• Do you need Ignition to monitor a specific value and inform you when a limit is reached?

• Do you need a customisable KPI tool that the end user can adapt according to actual needs?

These are just some examples, but, depending on your needs, an Ignition-based SCADA solution can automate tasks like you wouldn’t believe. 

The financial benefits are obvious. Some examples may look like this: 

If the SCADA system automates manual data collection and monitoring tasks that were previously performed by employees, it should result in reduced labor costs. For example, if the SCADA system saves 10 hours of manual data collection per week for three employees, with an average labor cost of €25 per hour, the annual labor cost savings would be: 10 hours/week x 3 employees x €25/hour x 52 weeks = €39,000.

Automation can also mean increased production capacity, right? If the SCADA system optimises production processes and leads to a 5% increase in production output, and the total annual revenue from the line is €2,000,000, the additional revenue would be: 5% x €2,000,000 = €100,000.

Not the mention the saved money from: 

• Reduced errors, 
• Reduced waste, 
• Reduced energy consumption (thanks to better control and monitoring), 
• Reduced downtime
• Avoided regulatory compliance fines (your SCADA will streamline data logging and reporting required for regulatory compliance, thus avoiding fines AND reducing costs of compliance efforts)

(More) practical use cases 

I already wrote several stories, but here are two more stories about how data revealed inefficiencies in two manufacturing companies.  

They did WHAT?!

When you have data, you can compare production (output and costs) across lines, production facilities, and shifts. 

That’s exactly what a production manager did—naturally, he was thinking “hey, I wonder if there are any differences in costs of producing product A in different places or shifts”. 

Without data to tell the truth, the automatic assumption may be that there are no differences – if the lines are the same, why would there be? 

Well… They compared the production of product A on a specific line during the day shift and the night shift. 

The day shift went well, no comments there. 

The data from the night shift, though, told a different story: the machines were working only at 65% of the capacity of the day shift. For no apparent reason. No errors, no machine breakdown, nothing. 

We can make all sorts of assumptions about why the operators on the night shift decided to slow down the production, but one thing is clear: the data revealed the inefficiency and the company stopped losing money during the night shift.

3 hours for a few-minute activity 

In a manufacturing company, the product had to be moved from one facility to a paint cabin and then out of the paint cabin and into the next step in the process. 

In the paint cabin, there was only room for one product, so everything else before that was waiting until the product is moved. 

The catch? The guys from the first facility don’t have data that tells them WHEN the paint cabin is free. So what do they do? They take the product from the first facility, travel with it to the paint cabin, manually check if it’s free or not, and if it’s not… the product is left outside, waiting. Needless to say, depending on the weather and the number of birds flying by, that product may be compromised before going into the paint cabin—even though it was ready. 

And why wouldn’t the product in the cabin be removed when it’s done? Because the responsible people may be out for lunch, in a 1-hour staff meeting, dealing with something else… It may take 3 hours to get a task done that would’ve taken 15 minutes (this is an estimation, I don’t know the exact timeframes, but the essence is the same). No data here to help, so nobody knows exactly what happens and when.

It was a huge bottleneck. Thankfully, thanks to Ignition and to the smart people from the manufacturing company and Enuda, they now have the data they need to drastically reduce the bottleneck. 

4 additional takeaways

1. Transparency. Data revealed the real situation, and it was costing them money. 

2. The plant/production managers know their operation so well that they have a pretty good idea of what can be improved, but they need the data to actually take action. 

3. They know what would make work easier for them and the operators (this can also be translated into more efficiency and productivity), but they need the data to automate processes, create reports, and create automated overviews (i.e. the OEE dashboard) 

4. Your engineers are wired to want to improve things, it’s in their DNA. That’s a huge benefit to your business. Help them get the right tools to do so and let them take care of the rest. You will reap the benefits. 

Frequently asked questions (and short answers)

1. How do we manage the risks like unforeseen challenges, delays, downtime etc? 

• Start on the plant floor, start small by solving specific problems that show results (see the above stories).

• Work with integrators and software that won’t lock you into anything. With an open and non-proprietary platform like Ignition, you don’t depend on recurring fees from a proprietary system. 

• Regarding avoiding downtime, keep the existing systems and processes going, and build the Ignition-based solution in parallel. 

2. How do we optimise the money and time spent on the learning process for the staff? 

Get them involved from the get-go. They learn from the start, and they’re able to take over the solution more quickly. 

3. We tried this before and the ROI was insignificant. How is it different this time?

This time, you prove the value of the solution by solving one critical business need at a time. Either stop after that or move on to the next business need that should be solved. 

Take-home points

Ok, let’s gather our thoughts for a second. A topic like this can get overwhelming even if just trying to explain the business part of it.

The point is: everyone and their dog talks about data, and you’re probably fed up with that. You may think that your company is just embarking on a trend that’s just that – a trend. No real plan to actually use that data in a way that provides ROI. As an executive, you don’t care how the guys and gals on the plant floor connect things to get data, you care about the impact all of it has on your business. Or rather, if it’s worth the investment.

Above, you have several practical stories of real results that the collection and analysis of data have enabled. They prove the benefits: improved efficiency and reduced waste. 

But at the end of the day, the critical aspect of a modern SCADA project is that you will start small. You will NOT embark on a journey you can’t come back from, especially if you work with us. You approve the budget for a pilot project, you see how it goes, and you end it if it’s unsatisfactory. 

There’s a trap humans fall into often, it’s called the “sunk cost fallacy”. Once you start something and you put some resources into it, it feels like you have to keep going to see it through. That’s how millions of euros have been wasted on doomed projects. That’s why we keep preaching about starting small: test things on a pilot line, stop and evaluate, then continue or end it. 

At the core of every fluffy concept (digital transformation, Industry 4.0. etc), there’s truth. In this case, it’s that data (to be read SCADA system) is valuable – not because it’ll turn your operation into a spaceship, but because it will solve dozens of small problems on the plant floor that will either reduce your costs or increase your income. Ideally, both. The above stories, and many others we’ve gathered over the last 7 years, prove it.