This graphic shows the different sources of data and information that can come together to make strong contextual data.

Why Contextual Data on the Plant Floor is a Must-Have.

Why Contextual Data is a Necessity for the Plant Floor of the Future

Yes, Contextual data is a requirement for the plant floor of the future, most definitely not just the icing on the cake. Further on that point, we may be talking about the not-so-distant future. Or even right now, today.

Before we get into it, here is the definition of contextual data: information or a set of circumstances that form the setting for an event or idea for a thing in terms that it can be fully understood and assessed.

Throughout the remaining parts of this article, I will explain to you why contextual data is absolutely a requirement. Also, why you should get started now before you get left behind.

The State of the Manufacturing Industry Today

The majority of manufacturers today are aware that we are exiting the 3rd industrial revolution, and Industry 4.0 is making its grand entrance. Let’s quickly recap why this is so important that I felt it was necessary to make this the first major point in this article.

Industry 3.0

Machine automation. Cool, right? Yes, machine automation has been huge for the manufacturing industry and is of course still extremely relevant and valuable today. However, there’s another level to it now, now we can automate much more than just machines on the plant floor.

Industry 4.0

Business process automation. This is the next step. Industry 4.0 does not completely reinvent the modern-day physical factory. Factories actually look extremely similar to Industry 3.0. What it does do, is reinvent the way we approach processes and unlocks the “hidden factory.” The hidden factory is all of the data and information that has been trapped inside of machines from Industry 3.0 that simply could not be extracted or used before. Industry 4.0 ties the whole company together to, once again, automate business processes. You have the back office, the plant floor, and everything in between- Industry 4.0 brings the capability to fluently make these departments or sections of the company work together for better business.

Don’t forget Your other Half

The back office portion of manufacturing companies has already been revolutionized Industry 4.0 style with ERP systems. One problem is that many people believe that ERP systems can act as an MES or IIoT system. ERP systems aren’t built for this, and they are simply incapable. ERP systems are for the back office, they do a great job at what they do, but that job does not take place on the plant floor.

You need contextual data in the back office and the plant floor.

What you need, is the plant floor version of an ERP- a system that can collect and analyze data + communicate effectively with other systems (such as your ERP system). This is called an MES (manufacturing execution system). ERP systems came along and they made a huge impact, they’re standard today. Now, MES is next. MES bridges the gap between the back office and the plant floor.

Why is this Important?

MES and IIoT (Industrial Internet of Things) systems provide contextual data from the plant floor. These systems complete the circle that allows each section of the company to gather, analyze, and share contextual data to automate business decisions. Contextual data drives business decisions. This is what Industry 4.0 is all about, and this is the (not so distant) future of manufacturing.

Enough explaining why this information is so important to manufacturing companies- Let’s get into the how, and some examples.

Machine Data + Contextual Data

Machine data on its own is okay. Getting dates and times detailing when a machine was down is helpful information. What if you knew why the machine was down, what caused the downtime, the symptoms, and reason codes. Would this information be helpful? Would it assist you in making a decision to improve productivity and your process? Absolutely!

Combine machine data + contextual data to vastly improve production on the plant floor.

Having basic data to analyze the most common causes for downtime code by occurrence and duration goes a long way in helping you solve downtime issues for your machine. But think about all of the other data in your company and the data surrounding that machine. Name of the operator, job or part being run on the machine, the shift, the level of training of that operator, and a host of other data points. When looking at the downtime of the machine would it be helpful to not only know why the machine was down but also what part was being produced, who the operator was, etc? Again, of course!

How You Can Gain Access to Contextual Data

So, how do we connect the contextual data with the machine data to get extreme value? Answer: Through thoughtful planning, an open mind to new ideas, use of best practices, and open nonproprietary technology.

As an example, we have two different approaches to this challenge. The first is to use a product like-


SensrTrx is a single system into which a lot of machine and contextual data can easily be combined, analyzed, and displayed.

For More Complex and Challenging Scenarios:

We implement architectures that use MQTT data brokers, the unified namespace, and open technology tools. The data broker and a unified namespace are two key pieces of the puzzle that enable us to combine the machine data with many layers of contextual data from the rest of the plant. We have multiple videos on our YouTube channel which describe how these architectures work and how quickly they can be put in place.

Don’t be part of the 92%

11 out of 12 companies fail industrial transitions and end up either 1. Going out of business or  2. Getting bought out. Historically, this has happened throughout the first 3 industrial revolutions. Now, as the 4th industrial revolution has begun, it’s important to be adaptable. Adjust to the changes in the manufacturing landscape, and fall in line with that 8% of companies that successfully make the transition.

In order to remain competitive and stay in business today, you need to take the next step, create a data-driven company culture, and be proactive.

If you have any questions at all, don’t hesitate to leave us a message here. We have decades of experience in the industry and we could talk about data-driven manufacturing, contextual data, Industry 4.0, and similar topics all day long.

Industry 4.0 graphic.

Industry 4.0 in the Simplest Terms Possible

Industry 4.0 in the Simplest Terms Possible

The manufacturing industry has been progressing towards the 4th industrial revolution. Industry 1.0 brought mechanized production with steam engines. Industry 2.0 brought mass production with assembly lines and electricity. Industry 3.0 brought automation, production without direct human intervention. What does Industry 4.0 bring? There is no revolutionary new style of machines, no upgrade from the use of electricity, and we already have machine automation in industry 3.0. 

The simplest definition of Industry 4.0: Industry 4.0 is extracting and leveraging data pulled from existing equipment to automate business processes. 

That’s it, I promised you the simplest definition possible. When you break Industry 4.0 down, data and what you can do with the data is what you are left with. There is no new style of manufacturing, an industry 4.0 factory physically looks very similar to an Industry 3.0 factory. The key difference causing it to become a revolution is the addition of deep real-time data that has never been available before. This data can be used to enable valuable, real-time decision-making- and that is what changes everything.
Each industrial revolution graphic, all the way up to modern day Industry 4.0.

Industry 3.0 Automates Equipment, Industry 4.0 Automates Business Processes

It’s a common misconception that Industry 4.0 is all about automation and computerization. But, we already have automation and computerized machines, which is industry 3.0, nothing new. Though, of course, that’s not to say manufacturers aren’t continuing to add more automation to the plant floor. Manufacturing equipment has had automation ability for decades. These automated machines were a big deal and still are for the manufacturing industry. However, machine automation is not the point of emphasis in industry 4.0, not at all. 

Industry 4.0 is the automation of business processes with the help of accurate real-time data. Real-time data that is trapped inside of these Industry 3.0 machines. Industry 4.0 provides manufacturers with the ability to unlock these machines, unleashing their true potential. With this data, you can track metrics and processes that you couldn’t beforegain detailed insight into every part of your business from the plant floor to the sales team, and everything and everyone can have access to deep real-time data to base decisions on and make improvements. It bridges the gap between the back office and the plant floor

The 1 Thing that every Industry 4.0 tool revolves around


Industry 3.0 was missing the data, the substance to make informed business decisions. This causes manufacturers to leave a lot on the table. They don’t have real-time visibility into what’s going on on the factory floor. They don’t know where to focus when trying to improve inefficiencies, why machines are going down, why they have so much scrap, why they struggle with on-time delivery. Many decisions made today are subjective.

If they do have some data, some visibility, it is often basic, manually recorded data. The problem here is that, again, the data is basic, is less accurate, and likely outdated by the time it gets delivered and used. That is if it ever gets delivered in the first place. 

This is the business challenge that can be solved, and the solution revolves around accurate real-time data. The tools of industry 4.0 all revolve around data.

A number of definitions of Industry 4.0 focus on 9 technologies to advance manufacturing. There are indeed many tools equipped with industry 4.0 capabilities that you can use to help you achieve your specific business goals. Illustrated in the graphic are the numerous data sources and tools. Data sources such as the cloud, and big data are of course, reliant on data. However, the tools such as IoT (Internet of Things) and AR (Augmented Reality), are also completely based on the power of data. It is true that IoT helps connect machines, devices, equipment, and people together, but the connected network is just one aspect of Industry 4.0. The real power comes from the contextualized and accurate data that is created by this network of people and equipment. The omnipresence of data and the value companies can derive from it causes the slightly different definition of Industry 4.0. 

The True Power of Real-Time Data

The addition of real-time data changes everything. Industry 4.0 brought the ability to collect real-time data from everywhere, process it, learn from it, and make processes better in real-time. This unlocks numerous possibilities on the plant floor and throughout the entire company. Here are a few areas within manufacturing companies that can be substantially improved with the help of Industry 4.0 data- 

  • Reduced machine downtime and improved machine availability
  • Reduced scrap and waste
  • Improved lead times
  • Smarter more informed employees enabled by data
  • Accountability
  • Improved productivity
  • Increase production output
  • Increase revenue and profits
  • Do More With What You Already Have

Industry 4.0 data is a major key to improvement in manufacturing today, the answer is not buying more machines to make up for the lack of production from current equipment. 

Reducing machine downtime, scrap, and waste can all be improved by picking up on tendencies you see in the data, and machine learning. You will start to see why a machine is going down, symptoms and causes. You can see where scrap is coming from, and use this information to make adjustments and improve plant floor efficiency. Quicker, more efficient production means more parts produced in less time, and this leads to better on-time deliveryoutput, and revenue. Employees will start to see what’s happening inside the machines in real-time, enabling them to make data-driven decisions to improve their process and instantly see the results. 

The Future of Manufacturing

It’s clear that Industry 4.0 is the future of manufacturing. Companies like Amazon, Tesla, and Facebook have been extremely data-centric, and these companies are leading the digital transformation charge. Companies such as these are leveraging data and applying industry 4.0 principles to make data-driven decisions. They are constantly growing, constantly innovating, constantly analyzing, and improving their current processes to drive better business. It has become apparent that these are the types of companies that will thrive today and in the future. Following in their footsteps and applying the same principles can put you on the right path to set yourself apart from the competition, give yourself the edge, and “future-proof” your business. 

This graphic shows a few different data sets. It also illustrates the vast amount of different data you can acquire with an efficient factory floor data collection process.

How “Current” is Your Factory Floor Data Collection Process?

Your Factory Floor Data Collection Process is More Important than You Might Think

How “Current” is Your Factory Floor Data Collection Process? Data runs our world today. Some of the largest and most successful companies that we see rely on enormous amounts of data to drive their business decisions. They base everything on data. Companies such as Facebook thrive off of gathering, analyzing, and acting on data they acquire from users. They know everything about the people using their platform- Where they live, where they’re from, where they worked, who their friends are, their interests, and they leverage this data for their advantage very successfully.

The same goes for the manufacturing industry. Just like how data runs our world, data runs the manufacturing industry. In recent years many companies have started to realize this. On the other hand, many companies have also deemed that modern systems that provide better and faster factory floor data are excessive, expensive, and unnecessary.

What do you think? And, what is your current process?

If You Aren’t Moving Forward, You’re Moving Backward

This quote applies to business especially. There is no treading water in business- you’re either going up or you’re going down. Furthermore, there is always (emphasis here) going to be someone willing to put in the effort to be better than you, do your job better, produce more products faster, do your job cheaper, and so on.

Competition is only growing, and if you want to get ahead or stay ahead, you have to keep innovating and keep moving forward.

The point that I am making, is that manual factory floor data collection is not cutting it anymore. Manual data entry sets you back, it’s outdated, and it consumes too much valuable time without providing sufficient value.

If you aren't moving forward, you're moving backward.

Manual Factory Floor Data Collection is like Carrying Around a Phonebook in Your Pocket

If you are still doing this today, sorry for calling you out. But chances are if I see you pulling out a phonebook to dial a phone number in public- you’re either A) really old, or B) That’s all I can think of, honestly there’s just no reason for this. Why? because it’s extremely inefficient, and there is a much better, widely available solution today. Even the most basic phones have a digital contact list that you can scroll through and make a call within a few seconds. Phone book.

The question is, why would it be any different within the manufacturing industry? Why would manual data entry be an acceptable solution? I understand that you have to start somewhere and that investing in a real-time data solution such as an MES is a larger investment than a basic $100 phone. However, if you are innovating and trying to compete, this should at the least be a goal that your company is working towards. Start small, think big, but you have to start.

Work towards modernizing your system, strive to be ahead of the curve. The old ways of manufacturing and manual data entry might seem to be okay for right now today. With that being said, in the coming years when it’s standard to have a higher level of factory floor data collection and more efficient processes, it will be detrimental to the ones who choose to ignore.

What is Your Current Factory Floor Data Collection process?

Prepare yourself for a lot of questions here.

Where would you put yourself today? How do you currently collect data from the factory floor? Do you collect manually with pen and paper? Maybe a whiteboard reporting system? A starter kit that records some basic factory floor data for you? Or, are you more advanced, recording data with an IIoT or MES solution?

For whichever factory floor data collection process you are currently using, what are you doing to progress to the next step? Where does your data end up once it’s collected? Are you acting on the data you gather?

Are you content with your current process? Should you be content with your current process?

Here are some questions that you can ask yourself to help determine how efficient and detailed your current factory floor data collection process is:

  • How long does your process take? Starting from gathering data, to making an adjustment, to determining whether that adjustment improved efficiency, did nothing, or decreased efficiency.
  • Are you aware of your own biggest inefficiencies?
  • Can you accurately determine where your downtime is coming from, and how much downtime you encounter in a period of time?
  • Do you know your own biggest downtime reasons?
  • How efficient or inefficient are your change-overs? (for products and people)
  • Are your maintenance schedules optimal? How do you know?
  • Does your factory produce excessive scrap and waste? Do you know how much?
  • Is your data validated and accurate? Do you completely trust your own data?

Based on your answers to these questions, evaluate where you are today, and determine what your plan for the future should be.

The Best thing that You Can Do to Improve Your Companies Factory Floor Operations

I’ve previously mentioned that you should always be working towards improvement. A goal for factory floor data collection should be to end up with a solution that provides real-time visibility into the plant floor, with all of the data coming from one source, one version of the truth. The data should also be readily available to consume for each person within the organization.

With that being said, that is the goal for the technology. To keep moving forward, you have to equip yourself with the right tools. However the ultimate goal is more sales, and more revenue, right (You should be saying yes)? To advance in these areas you need to focus on your business challenge FIRST. Business challenge first, and leverage solving the technology challenge to be the catalyst to help you achieve your ultimate goal. 

Establish a proactive data-driven culture among the people in your company. Encourage your employees to act on the data they see, use it to make real improvements, and use it again to gauge results.

Start Small, Think Big

Easier said than done, it’s an investment to move towards a real-time data solution. It should be carefully thought about and planned out before jumping to conclusions. With that being said, data is the future. An efficient process and solution for data collection can be extremely valuable for companies who utilize it correctly.

Start with a pilot project. Connect to just 1 or 2 machines. Start with gathering real-time data on 1 or 2 manufacturing processes on the plant floor, and go from there.

At Ectobox, we have been through this process numerous times, and we recommend that companies start out small with this type of project.  To keep it very, very simple for this post, here is the process-

  • Define the Business Challenge
  • Start with a Small Project
  • Prove the Value
  • Scale when Appropriate

You don’t have to make a huge upfront investment, what is important though, is that you get started with proper and efficient data collection and take advantage of the technology available today. In doing so, you are preparing yourself for the future and ensuring that you don’t fall behind.

This image illustrates the question, "What is real time visibility?"

What is Real-Time Visibility? And Why it Changes Everything

What is Real-Time Visibility?

What is real-time visibility? It’s all in the name, it’s getting visibility, data, and insight into a process as that process takes place. No delay, no gathering of information. Real-time data solutions automate the process of gathering data manually and deliver it to you to analyze and make quick data-driven decisions. This is basic, you know what real-time data is. You’re here to find out how much of a difference real-time visibility can make for your company.

There’s a lot of value in real-time visibility, much more than just saving a couple of minutes that you would have spent writing down that information. In the following parts of this article, we will further establish- What is real-time visibility? What’s the value of real-time visibility? And how does real-time visibility change the way manufacturers operate?

Real-Time Visibility is a Game-Changer for Manufacturers

You can create value with real-time data in numerous ways, but there’s something that you have to keep in mind and apply. No matter what data you gather, if you aren’t making quick decisions and acting on those decisions, real-time data will do you no good. It sounds obvious when you put it that way, but establishing a proactive data-driven company mindset is absolutely essential. View MES, IIoT, Manufacturing analytics, and other real-time data solutions as an overall strategy, rather than just one project.

With that being said, let’s get into how real-time visibility will add value to your manufacturing company.

Improves Production Efficiency

You’ve heard this before, that IIoT and real-time data will improve efficiency on the plant floor, but how? When you gather data in any way, you can improve production efficiency. First, you gather the data, analyze it, make a decision, carry out that decision, and then hopefully that adjustment actually improved production.

How long would a process similar to this take when manually recording data? Here’s an example- an employee records basic data on paper, and that data gets delivered and analyzed by a decision-maker within 24 hours. Let’s say that the decision-maker made a decision, communicated that decision to the operator, and the adjustment was carried out that same day. Now, you wait at least one more day to get the next set of data to determine whether that was a good adjustment or not.

We’re looking at 3 days here, minimum, and that is with a pretty efficient process for manual data collection.

This process can be expedited, and that is the value in real-time data. This 3-day process could start and finish over the course of a few minutes. Systems equipped with real-time visibility gather, contextualize, and deliver information to everyone in an easy-to-understand way to make quick decisions and keep moving.

The manual process may have worked in the past, but it is completely outdated. This aspect of real-time visibility alone makes it worth the investment. The time savings and quick turnaround for making and seeing results on adjustments can provide a large ROI quickly.

This is a CNC machine that could have improved production if equipped with real-time visibility for accurate and quick data.

Lean Manufacturing

What gets tracked, gets improved. Simple as that. Better tracking and better, more accurate, and consistent data will assist in your lean manufacturing efforts. The ultimate goal in lean manufacturing is to continually improve and create the most highly efficient environment possible. Eliminate waste in all ways- eliminate scrap material, and eliminate wasted/inefficient human motion. By gaining access to extensive data on machines, schedules, and people with a modern MES/real-time data solution your lean efforts will be greatly benefitted.

Big Data

Big data is deep, detailed sets of data that are so extensive that it is not possible to manually record. Simply, there’s nowhere near enough time for somebody to manually gather and record this amount of information. Big data provides another level of insight into your machine and processes on the plant floor. With data sets numbering into the millions and even billions of rows, you can benefit from real-time data, as well as historic data to pick up on trends and tendencies. With this information, you can be better equipped to prevent unplanned downtime, and optimize your maintenance schedules with predictive maintenance.

Data-Driven Manufacturing

Becoming a data-driven manufacturer is essential in modern times. Equipping yourself with a real-time data solution is the best thing you can do to drive this effort. However, keep in mind that data-driven manufacturing is a strategy, not just a physical solution. Let data drive your decisions and take action.

A Centralized Solution

A proper MES/IIoT solution will be a centralized solution. How does this add value? Well, this means that all data is coming from one source and will be available for everyone to consume. No separate silos of data- the sales team receives the same data from the same source as the people working on the plant floor and vise versa. This creates one version of the truth that everyone can benefit from.

How Does Real-Time Visibility Change the Way Manufacturers Operate Daily?

We answered the question, “what is real-time visibility?” and defined the value. Now, I will tell you why real-time visibility completely changes the way manufacturers will operate on a daily basis.

  • Your manufacturing process will be different
  • The data will be different
  • The way in which you gather data will be different
  • The metrics you track will be different
  • The way you approach a problem will be different
  • organization of data, people, and schedules will be different
  • Focus and mindset on the plant floor will be adjusted

Instead of just focusing on the literal production, there will be an emphasis on the data and monitoring machines and processes to make quick decisions and adjustments on the plant floor. Manufacturing becomes more than just ensuring that a machine is turned on and running and products are coming out. It becomes a continually improving process with a continuous stream of real-time data that you will need to act on. Acting on this data will create value time and time again.

If you don’t act on the data, it does you no good, you get zero ROI, and you get stuck in the old ways of manufacturing. Don’t position yourself to get left behind and surpassed by the competition.

That is exactly how real-time visibility changes everything. It opens the door to making real improvements on a consistent basis for manufacturers who are willing to put in the effort.

The actual factory will look identical. The process, the information, the data, and the mindset are what will be completely different. That is what Industry 4.0 is, and that is what revolutionizes operations on the plant floor today.


Are you considering getting real-time visibility into the plant floor? Contact us- We are happy to answer any questions.

    This factory floor could have improved efficiency with a real-time data solution. Which solution would be best? MES vs IoT?

    MES vs IoT: What’s the Difference?

    MES vs IoT: What’s the Difference?

    MES vs IoT. Two manufacturing solutions that are equipped with the ability to greatly increase plant floor production, and eliminate inefficiencies. Each of these two types of solutions are great at what they do. However, they are not exactly interchangeable. There are many key functions that differentiate these two solutions. So, what makes them different? How are they the same? Which is the more complete solution? Which is best for manufacturers today?

    Throughout the following parts of this article, we will dive deeper into this topic and answer each of these questions.

    IoT / IIoT

    First off, let’s define the difference between IoT and IIoT. Keeping it simple, IoT stands for “Internet of Things” and IIoT stands for “Industrial Internet of Things.” Generally, these two are the same thing, and the two acronyms are interchanged frequently. The difference between the two is just that IIoT is used in a more specific (industrial) setting. Consequently, IIoT will also generally put a stronger emphasis on security standards.

    IIoT creates a connected factory. An IIoT solution uses sensors to create a network within the machines on the plant floor. This creates a platform for machines and operators to seamlessly communicate real-time data between each other. IIoT streamlines the process of gathering, analyzing, and sharing machine data.

    Implementing an IIoT system is a huge step for manufacturers who are still manually recording machine data with pen and paper, or maybe a whiteboard reporting system. IIoT is much more than just a quicker way to gather data, it gives you access to big data– data that is simply not an option when recording manually. It also contextualizes data in an easy-to-read format in real-time to make quick decisions on the plant floor and keep moving.

    Reasons Why Implementing IIoT is Essential for Companies Who are Still Manually Gathering and Reporting Machine Data

    • Real-time contextualized data for quick data-driven decision making on the plant floor
    • Operators can focus on their manufacturing process instead of continuously taking time to record basic data
    • Accurate data pulled directly from the source of truth (the machines) – no room for human error
    • Machine learning – pick up on trends and tendencies to reduce machine downtime and stoppages
    • Big Data – Ability to utilize deep sets of data to improve production efficiency
    • Improved control and monitoring
    • Seamless communication between people and machines
    • Ability to quickly find inefficiencies to reduce scrap and operating costs


    MES stands for manufacturing execution system. Between IoT and MES, IoT is generally the term the majority of people have heard before, and are more aware of. This might come as a surprise because MES has been around for over 30 years at this point, while IIoT has only gained popularity in the last decade or so.

    There are 11 core functions of an MES defined by ISA-95.

    1. Data Acquisition
    2. Scheduling
    3. Personnel Management
    4. Resource Management
    5. Flow of Products and Batches
    6. Product Traceability and Genealogy
    7. Quality Control
    8. Process Management
    9. Performance Analysis
    10. Document Management
    11. Maintenance Management

    You could argue that many of these MES functions could be handled with a different system, maybe a cheaper system. This is true, there are many different products and solutions that can tackle 1 or 2 of these functions. The value of an MES solution is that it’s one central solution that can efficiently fulfill your needs in each of these areas. An MES pulls data from everywhere on the plant floor and communicates information back and forth with an ERP system.

    An MES will track the entire manufacturing process from start to finish. It receives scheduling and order information from the ERP, and starts tracking production from raw material to finished product.

    MES vs IoT: Similaritites

    At this point, you can likely determine what IIoT and MES systems have in common. We could go on and on listing each specific detail shared between these two solutions. MES and IIoT are both modern solutions for better manufacturing. Each of these systems revolve around real-time data to improve plant-floor efficiency throughout the manufacturing process. Both solutions also put a strong emphasis on reducing downtime and unnecessary stoppages.

    Both solutions have the same overall goal, so what makes them so different? Which one is the best option for you?

    MES vs IoT: Differences

    I’m not going to waste any time here, this is what the entire article has been leading up to. IIoT is one aspect of an MES solution. an IIoT system is an extremely efficient solution for monitoring machines on the plant floor, pulling machine data, and making quick adjustments. However, even though the actual machines and equipment are such a large and vital part of the plant floor and manufacturing process, there are many more factors involved aside from these.

    Referring back to the 11 functions I mentioned previously, an IIoT system falls into those functions with data acquisition and performance analysis. Although, a complete MES solution covers many more areas than this- Scheduling, Personnel management, resource management, maintenance management, document management, etc. This is why an MES is a complete solution covering everything within the 4 walls of the plant floor. 

    This graphic shows the differences between two plant floor solutions, mes vs iot.

    The Best Plant Floor Solution for Manufacturers Today

    Manufacturing companies can be broken down into two main sections. Section 1 is the back office. In the back office you have IT, the sales team, it’s where you receive customer orders, schedule them, and send that information down to the plant floor. The ERP system revolutionized the back office. But, how does this information get to the plant floor? Typically, on a traveler- a piece of paper with all of the order information that gets passed around from station to station until the job is complete.

    Section 2 is the plant floor. MES revolutionizes the plant floor. Instead of that piece of paper being passed around, an MES system will track every process, machine, person, and material on the plant floor. A complete solution covering all aspects of the manufacturing process.

    So, what is the final answer? MES vs IoT? The answer is MES, but both with IoT too. IoT tracks and handles a few very important functions, mostly with machines. With that being said, remember that IoT and tracking machine data is just one function that falls into a complete MES solution.

    The best option for manufacturers today is a centralized MES solution. One overall solution that manages every aspect within plant floor operations. The final frontier for improving operational efficiency in the factory from start to finish.

    This image illustrates a factory with smart technology. The image represents the benefits of smart manufacturing.

    3 Vital Benefits of Smart Manufacturing

    3 Vital Benefits of Smart Manufacturing

    There’s an extensive list of smart manufacturing benefits and many ways that smart manufacturing can add value to a company. Today, there is a “smart” everything and manufacturing companies are not getting left behind on this trend. Technology continues to advance at a quick pace in the 21st century. We have smartphones, smart TVs, but that’s old news at this point. Now we have smart lightbulbs, smart toasters, smart dental floss dispensers. Yeah, I’m not kidding, go ahead and look it up yourself.

    10-15 years ago, you didn’t need to have a smartphone. It was cool to have and useful to a lot of people, but you weren’t weird or behind the times if you didn’t have one. Flash forward to today, you are completely lost without a smartphone. Can’t do a quick google search from your pocket-sized computer? Can’t check your email? Get directions anywhere in the world? We can’t live without these things today. Smartphones started as a cool option for people that wanted to spend a little extra money, now nobody can function without them.

    Old phone showing how the world has changed into a "smart" everything.My point being, the world is getting digitized, the world is getting “smart.” The manufacturing sector is no exception. Many manufacturers still choose to ignore the benefits of smart manufacturing, IIoT, and Industry 4.0, and those are ones that will get left behind. Just like that big, bulky Nokia 3310 you used to carry around.

    In this article, I will go over a few key benefits of smart manufacturing that you should be implementing in your factory today so that you can “future proof” your company.

    1. Increased Plant Floor Efficiency with Real-time Data

    Every manufacturer needs to focus on increasing efficiency. Nobody has a completely perfect process, or anywhere near one. There will always be places to squeeze out more throughput, increase capacity, cut back on downtime, etc. Manufacturers need to have a continuous improvement mindset. Be proactive about making improvements on the plant floor, and establish that type of culture among the company.

    • Make Quick Decisions and Take Action

    It’s really hard to make improvements that actually help when you don’t have much substance or information to base your decisions on. Furthermore, it’s tough to measure success without seeing the numbers. How do you really know if the adjustment you made helped or not? If it did help, how much did it help?

    This is where smart manufacturing benefits you and can step in to lend a hand. IIoT and manufacturing analytics systems are smart manufacturing solutions that are equipped with the ability to deliver real-time data. Real-time data gives you the substance to make quick decisions and then act on those decisions to make quick adjustments on the plant floor. Then, measure the success instantly with, again, real-time data.

    • Don’t Get Stuck in the Past

    Don't get stuck in the past, focus on the future.

    Think about how long this process would take as well as the accuracy if you had to have someone manually gather basic data on the plant floor, and deliver that basic, hopefully accurate data to a decision-maker in a somewhat timely manner. Sort of? hopefully? That data is getting there many hours, if not a couple of days later.

    This is one of the major benefits of smart manufacturing, this process can be streamlined. These types of solutions are what the “trendy” manufacturers are turning to. As I said previously, some other manufacturers are willingly choosing to ignore these advancements in technology. Soon, it won’t be “trendy”, it will be the standard. Companies will either have to adapt and change to the new ways of manufacturing, or they will watch competing companies continue to grow past them. There is always someone out there willing to do your job better, cheaper, and faster, and today, the tools are readily available for people to take advantage.

    Just like the smartphone example. Yes if you have a “dumb” phone, you could drive to a gas station, buy a map, and then go find where you are trying to go. Or, with a smartphone, you could type your destination address in and be on your way in 10 seconds. It’s the same concept with smart manufacturing.

    data delivered instantly in real-time, nobody walking around the shop floor handing out information, gathering information, no operators stopping work to write down their data during a shift. Not only is this a slow and inefficient process, but it’s also poor communication, how often does that data get to anybody else on the plant floor? especially in a timely manner for that data to actually be useful.

    2. Seamless Communication

    Our second key smart manufacturing benefit is communication. This is one that not many people really talk about or make a big deal about. However, smart manufacturing revolutionizes the way people communicate with workmates, customers, machines, and data.

    This image illustrates communication, seamless communication is one of the key smart manufacturing benefits.

    Here’s why this is so important. Wasted time and wasted motion = lost production and an efficient process. This goes against lean principles, and every manufacturer should strive to become a lean manufacturer. Strive to eliminate waste and create a highly efficient environment. Smart manufacturing can have a large impact on a variety of different communication scenarios such as:

    Machines to Employees:

    • Machines deliver data in real-time, constantly delivering information to operators and other employees. This information is instantly made available to each person within the company. 

    Employees to Machines:

    • Employees and operators can consume real-time data to make a data-driven decision and make adjustments on the plant floor. 

    Sales team to Customers: 

    • When customers call for an update on their job or a progress update, the sales representative can look at the data in real-time and give the customer an extremely accurate data-based answer with detail on how much is done, how much is left, and when they can expect delivery. With every metric being updated in real-time. 

    The communication benefits of smart manufacturing are tremendous and will undoubtedly save you a headache here and there, create a more knowledgeable staff, and improve customer relationships.

    Before you start tracking these types of processes, you likely don’t realize how much time and money you could be saving. We have come across clients that have told us that they have people in the company that are consistently spending half of their day running around the plant floor trying to find a certain order for a customer. What a waste of valuable time!

    With a smart manufacturing IIoT / Manufacturing analytics solution, you can give customers accurate real-time adjusted numbers instead of giving a rough estimate based on your best judgment, or going to run around the shop floor to deliver an answer a few hours later.

    Efficient processes = more production, more production = more time for more clients, good communication = happy customers, happy customers = return customers, and all of this = more revenue in less time.

    3. Smart Manufacturing Creates more JobsThis picture illustrates the workforce problems in manufacturing.

    Some people will say that automation is going to take over human jobs in manufacturing and that IIoT is going to turn everything into an automated process putting everyone out of work. This is not the case at all. While it is true that there are some jobs that will likely be largely handled by machines, IIoT and smart manufacturing creates more jobs.

    It’s no secret that there is a shortage of skilled employees in the manufacturing sector. The industry is filled with a lot of people closing in on retirement. Furthermore, there isn’t a large number of young people that want to go into the manufacturing industry. What do young people want? Tech jobs (source). There is a lot of young people that want to do something related to tech. That is where everything is headed, technology drives our world today. Correspondingly, what will all of these smart manufacturers need? They will need people to fill these new jobs created by smart manufacturing and smart factories. See where I’m going here?

    Manufacturers will have new needs for people who can work with new technology, software, and data.

    So, no, smart manufacturing and IIoT are not going to take away manufacturing jobs. It is creating new, different jobs, jobs that might be more appealing to the younger generation. These new jobs will help boost up the manufacturing workforce, which desperately needs the help.

    These three benefits of smart manufacturing are huge, and they are shaping the future of the industry. Start implementing them today. Put yourself ahead of the curve and don’t get stuck in the old ways of manufacturing.

    Graphic illustrating proper vs improper production downtime tracking.

    Improper Production Downtime Tracking is Flattening Your Profits

    Improper Production Downtime Tracking is Flattening Your Profits

    How accurate is your production downtime tracking? Are you even tracking production downtime? Do you have a good idea of how much production downtime is costing you each week, month, year?

    Consultants believe 4 out of 5 manufacturers (80%!!) are unable to accurately estimate their downtime (source). This is a crazy number because downtime is a leading cause of lost revenue in manufacturing. What’s even scarier, is when you look at the statistics for how much money production downtime is costing manufacturers on average.

    Over 7  years ago in 2014, the average cost of downtime per hour across all businesses was $164,000 (source). If I was losing $164,000 per hour for any reason, I know for a fact that I would want to know exactly how and why right away. In addition, I would do everything in my power to minimize such a costly event in the future. Now, don’t let that first number sink in. Just two years later in 2016, that number jumped to $260,000 per hour on average across all businesses. That was 5 years ago, I’ll leave it up to you to determine where you think that number might be today in 2021.

    That is a lot of money, there’s no questioning that. But, how many hours of downtime will a company encounter each year on average? 800 hours. Want to know what 800 x $260,000 is? Neither do I, I’ll just say that there are 9 digits in that number, and the first number is not a 1. 800 hours might sound like a lot, but when you break it down, you see how quickly it all adds up.

    Why Aren’t Manufacturers Paying Attention to Production Downtime Tracking?

    If production downtime is so expensive, why don’t most manufacturers have accurate and detailed data regarding their own downtime within their own facility, if any data at all? It’s tough to formulate a clear answer to this question.

    A large number of manufacturers get stuck in their old ways. They have been doing business a certain way for decades successfully and see no reason to make a change now. The problem here is that decades ago, data was not a big part of manufacturing. There really were no tools or technology available to pull a large amount of data from machines and equipment. Consequently, there was not a huge amount of machine optimization or emphasis on increasing the efficiency of current equipment on the plant floor.

    Today, it’s an entirely different story. The entire world has been going through a digital transformation. New technology everywhere, and this produces a lot of data. You need to find a way to access this data that is trapped inside of these devices that are loaded with technology, and just need to be unlocked. Companies like Facebook have thrived off of data. They have grown and scaled their business by gathering data and making informed data-driven decisions based on that information.

    What does this mean for the manufacturing industry, and production downtime tracking? How can you leverage today’s tools and technology to improve the way you do business?

    Leverage Today’s tools for Better Manufacturing and Better Business

    The manufacturing industry is vastly different than what it was some years ago. Today, there are tools and technology that help with production downtime tracking, plant floor efficiency, increased throughput, and many other things. Do you need tools that help in these areas, or are they just icing on the cake?

    The short answer is yes, you do need them if you want to keep growing your company in 2021 and into the future. The manufacturing industry is growing more competitive. It’s a challenge today to find good employees, draw in new clients, and improve your manufacturing process.

    Industry 4.0 has brought new principles to manufacturing. While industry 3.0 focused on machine automation and computerization, industry 4.0 emphasized data and using data to improve business processes. Yes, we know that we can automate machines to take over a lot of the manufacturing work and activities that humans would otherwise have to handle manually. But now, it’s time to start refining and improving these processes. Gather data, and make data-driven decisions to improve operations across the plant floor.

    Along with industry 4.0, came an abundance of industry 4.0 capable tools. IIoT systems are one of those industry 4.0 tools that can assist you in improving your process.

    IIoT Can Give You the Edge You Need

    These IIoT systems can be implemented into any factory, even on machines 30, 40, 50 years old. These systems pull data directly out of the machines and equipment on the plant floor and deliver that information to operators and decision-makers in real-time. This changes the way we do manufacturing. Instead of having a person walk around the plant floor and recording data on a spreadsheet and then hopefully getting that “accurate” information to the right people at some point, you can receive data instantly and make the adjustments right then and there.

    Imagine the difference it would make to have access to real-time data giving you insight on production downtime tracking, how much scrap you have, how much throughput, predictive maintenance insights, and asset utilization just to name a few areas IIoT can help.

    IIoT delivers information to all decision-makers in a timely manner. You gain the ability to see exactly where you need to improve instantly so that you can make an adjustment, and then see if that adjustment helped or not right away.

    Before systems like this were available, it was much harder to gain real insight into the plant floor. Furthermore, it was near impossible to see how adjustments are affecting production in real-time. Production downtime gets extremely expensive. You need to be doing everything you can to continually, and proactively make improvements to give yourself the competitive edge.

    Final Thoughts on Production Downtime Tracking

    Production downtime is a leading cause of lost revenue for manufacturing companies. Yet, the vast majority of manufacturers struggle to accurately estimate and minimize downtime. Companies are losing millions of dollars from production downtime each year. For an industry with so many moving parts and people, it’s essential to track processes, make improvements, and do everything you can to get the most out of your equipment.

    Set yourself apart, be that 1 out of every 5 manufacturers that are aware, and can accurately estimate downtime. Leverage the tools and technology available today to gather accurate real-time data. Make data-driven decisions to improve business processes, and climb past your competitors.

    Graphic illustrating the development of a digital strategy vs digital transformation. Failing to plan is planning to fail. Develop a solid strategy to complete a successful digital transformation.

    Digital Strategy vs Digital Transformation: Are you Forgetting one?

    Digital Strategy vs Digital Transformation: Are you Forgetting one?

    Digital Strategy vs Digital Transformation. The benefits of a successful digital transformation in manufacturing are near endless. It opens a lot of doors once you have a truly connected factory. If you look around, the entire world has been going through a digital transformation during the last couple of decades. For the most part throughout the world, the change is welcomed, everyone appreciates the benefits they receive. Digital transformation streamlines a lot of processes, saves time, creates easier communication, and makes many day-to-day activities much more convenient. We can order groceries to our doorstep with a few clicks on our phone, we can communicate with anyone in the world in real-time whenever we want, we can receive alerts on our phones when somebody walks up to our front door.

    Why should anything be different within the manufacturing sector? Why do some companies completely reject digital transformation in manufacturing?

    The vast majority of people would likely agree that digital transformation has made life easier, especially in the workplace. So why would some companies in the manufacturing sector, workplaces with lots of people and moving parts, choose not to move from Industry 3.0 with automation of machines but still many manual business processes and data trapped in machines, to Industry 4.0 and automating the business and driving decisions based on data and information? Well, it has a lot to do with strategy, digital strategy vs digital transformation. In this article we will cover why some companies reject digital transformation, and what you need to do to complete a successful digital transformation.

    Why Some Manufacturing Companies Reject Digital Transformation

    There have been a lot of failed digital transformation projects, some by very well-known companies such as GE and Ford. The reasons for failure all have one common theme, they lack some part of the overall strategy. When you are digitizing your company, the overall goal is not to include as much new technology as you can. The technology can help you get there, but it’s a tool to help you, not the complete solution. With that being said, here are some reasons that some companies fail, or choose to reject digital transformation-

    • Unclear Goals
    • Single Project
    • Projects Aren’t Agile
    • Wrong Technology
    • Resistance Within the Company
    • No Culture Change
    • Focusing on the Technology Challenge, not the Business Challenge

    Unclear Goals

    It’s not beneficial to digitize your company just for the sake of digitizing. Many companies fail the digitization process because they fail to set clear goals and expectations. They might have been going through a digital transformation because they thought that was the next step and the future of manufacturing. While this is true, it is important to innovate with new technology to keep a competitive edge, companies need to define clear goals and make sure that everything they are doing is helping them achieve those goals.

    Single Project

    Digital Transformations are not a single, one-time event. As said above, there are a lot of moving parts in a manufacturing company and many people to work with when making the transition. Change takes time. Rome wasn’t built in a day, and neither was the Digital Transformation at GE or Ford or even for Bob’s Precision Metals shop, for that matter.

    Projects Aren’t Agile

    When implementing Digital Transformation projects, as already stated, it will take time to change a whole company and to change the hearts and minds of the people at that manufacturing company. Therefore, change in the company must be incremental, one project at a time.

    Wrong Technology

    All too often companies will see the flashy sales brochures of companies that provide the silver bullet products…the product that will take care of the whole digital transformation. “Just buy our whole stack of products that integrate together seamlessly and your issues will be taken care of.” That is a proprietary approach to a solution. Rest assured there’ll be a very hefty price tag for that full stack of products as well.

    This is one example of the wrong choices that are made in digital transformations around technology. We use 4 rules or tenets to figure out what technology to use (Report by Exception, Edge Driven, Light Weight, and Open Technology). The resulting solution ends up being highly scalable and flexible, at less than half the cost of proprietary solutions.

    Resistance within the Company

    Everyone needs to be on the same page. The whole company needs to be on board with the process, it’s important that employees buy into the ideas presented. For a successful digital transformation, employees need to have the right mindset and adapt to the new way of manufacturing within the company. If there is a division within the company, it complicates the project. This becomes particularly important when we are working with the leadership team of a company to plan and execute the digital transformation. Even at the top levels of an organization, we’ll find resistance. We’ll often have a conversation with the people in the C-suite, the board, or others to recommend the resistors be swapped out for other people to ensure the digital transformation will succeed.

    No Culture Change

    Falling in line with the last reason for failure, culture change is also very important. Digital Strategy is just as important as digital transformation, if not more important. Make sure that everyone knows why the company is making a change, and how it will be beneficial. This is where everyone from the CEO down should know the Digital Strategy and have a part in executing it. Then, as the digital transformation process is well on its way, if employees are doing the same things they were doing before the digital transformation, and not utilizing the tools they have, or understand reasoning, the project will ultimately fail.

    Focusing on the Technology Challenge, not the Business Challenge

    A lot of companies get wrapped up in solving the technology challenge. Once they get started on their digital transformation they become more focused on the technology they can add, rather than the problem that technology is actually solving. They keep adding more technology, more tracking, and more sensors but forget the reasoning for any of the technology being there in the first place. Define your goals, and let that drive your actions to make changes that will actually yield good results.

    These are all leading causes for a failed digital transformation, and it may scare some companies away. The entire world is becoming digitized, it’s getting to the point where it is a requirement for any modern-day organization. So what can you do to ensure that you have a successful digital transformation?

    How you can Avoid Failure, and Complete a Successful Digital Transformation

    The risk of not digitizing your company outweighs the risk of failure. It’s crucial for companies that want to remain competitive to adapt to the new ways of manufacturing. So, here is what you need to do to complete a successful digital transformation-

    1. Have a Clear Digital Strategy

    2. Start Small, Think Big, Get Wins

    3. Establish a Proactive, Data-Driven Company Culture

    4. Always Focus on the Business Challenge

    5. Be Agile

    6. Open Technology

    • Have a Clear Digital Strategy

    Establish clear goals, clear expectations, and stick to them. When you compare your initial digital strategy vs digital transformation, the project should reflect that initial plan. Spend the time to make a good plan, and make sure you keep that plan in the front of your mind. Determine what you really need, what problems digitizing can help you solve, and make sure all of your actions fall in line with your digital strategy.

    • Start Small, Think Big, Get Wins

    You don’t need to do everything at once, Start small. When connecting to machines on the plant floor, start with a pilot project. Connect to just one or two machines, gather data, find what works, what didn’t help, and go from there. Once you have established the value and found out what you need to be tracking, then you can scale the project. This way you are staying on task and making it much easier to follow your initial digital strategy. Make adjustments periodically instead of making tons of changes all at once, and not knowing what really made a difference, what did nothing, and even what made production worse.

    • Establish a Proactive, Data-Driven Company Culture

    Everybody within the company needs to be on board with the transformation, furthermore, you need to establish a proactive mindset among the company. The digital transformation will bring lots of new data and new opportunities to improve operational efficiency. It’s very important to enable your employees and machine operators to make data-driven decisions and act on those decisions. A unified and proactive company culture can be what makes or breaks the digital transformation, as well as the overall future success of the company.

    • Always Focus on the Business Challenge

    Earlier I mentioned how companies can get wrapped up in the technology challenge, this can be fatal for a digital transformation project. The technology itself is not going to improve operational efficiency, customer relationships, lead times, or anything. However, you can leverage technology as a tool to help you improve your company in all of these areas. Always remember, solve the business challenge first, and use technology as the tool that helps you get there. Keep this in mind to help you stay on track, and not add meaningless systems to your project that do not actually help solve the business challenge.

    • Be Agile

    Projects need to be agile. The hope is that all projects can be back-to-back to keep the momentum and excitement going. Drive valuable results and keep a good pace. Small, incremental, but still consistent projects will ensure that people do not get overwhelmed but also stay on task continuously.

    • Open Technology

    Don’t get stuck in a proprietary solution. For a successful, scalable, and flexible solution the technology must be open. This keeps the door open to connect to new systems in the future. It will provide a solution that works today, and one that won’t hold you back, keeping your hands tied in the future. Keep in mind these four rules when choosing technology-

    • Open Architecture
    • Report by Exception
    • Edge Driven 
    • Lightweight

    Digital Strategy vs Digital Transformation: Conclusion

    Digital transformation is essential for manufacturing success now and in the future. Many companies have failed in the past because they get off track, lose focus, and do not structure the project correctly. Worse yet, companies that choose to ignore the benefits of a digital transformation won’t be able to compete in the future. It’s becoming more apparent each day that digitizing your manufacturing company is a must, but you have to do it right. Establish a strong digital strategy. Use accurate digital data and information to drive decision-making, quickly, and in real-time, and you can put yourself in prime position for a successful digital transformation.

    Steps to properly using data, creating a proper data-driven culture.

    The 4 Stages to Creating a Data-Driven Culture

    The 4 Stages to Creating a Data-Driven Culture

    What is a data-driven culture, and data-driven manufacturing? It’s simply gathering, analyzing, making decisions, and acting on data. It’s for companies that have the expectation to be more productive than they were the day before. Going from point A to point B, continually improving, continually setting goals, and being proactive about reaching those goals.

    Company success is typically defined in terms of revenue, profits, and evaluation of the company. To improve in these areas, companies need to do more with what they already have. They need to work towards increased efficiency, increased plant floor production, quality control, on-time delivery of products, and they need to meet and exceed customer expectations. To accomplish this you need to be able to find and eliminate inefficiencies, get visibility into the plant floor and understand what’s going on. You need data to understand, and better yet, real-time data.

    Data-Driven Culture Simple Breakdown

    To have success as a manufacturing company, you need to become a data-driven company and establish a strong data-driven culture among the entire company. There are 3 key aspects to a data-driven culture. These aspects are simple to define but can be tougher to truly implement.

    Steps to properly using data, creating a proper data-driven culture.

    • Understand What’s going on

      • You need to develop a deep and detailed understanding of what is happening on the plant floor, inside your machines, and in each department of the company. This is your baseline, your starting point, the initial gathering of data and analysis. Everything starts with what you already have so it is essential to know these things very well.
    • Make Decisions

      • Once you have an understanding of what’s going on, you can start to make decisions based on the data you have. Make sure you are making your decisions based on complete and accurate data.
    • Take Action

      • You have a deep understanding of everything happening within the company, and you have made your data-based decision. Now you need to take action based on the decision. Remember the goal is to find and eliminate inefficiencies to drive revenue and profit. You already have the data to find the inefficiencies, now carry out the decision and make the proper adjustments.

    In doing these 3 things, you are developing a competitive advantage. You are creating data asymmetry between yourself and the competition, giving yourself the edge.

    5 Facets to Creating a Data-Driven Culture

    A graphic showing the 5 facets of creating a data-driven culture.

    1. Single Version of the Truth

      • All data needs to come together into one place that is available and acceptable for everyone to analyze and consume. This creates a centralized solution with one version of the truth. No separate databases for different departments inside the company.

    2. Data and Tools

      • Proper data and tools need to be available for each person within the organization. They should be readily available to any person at any given time.

    3. Broad Data Access

      • Falling right in line with having proper data and tools, the data itself also needs to be widely accessible for everyone. Everyone should be able to benefit from accurate real-time data. It’s important to ensure everyone will have access when creating a data-driven culture.

    4. Data Dictionary

      • There needs to be some definition somewhere of what data is being tracked. It should show each data metric that is being gathered. Some type of literature should be made available so that each person will know and understand what data will be available even though not every person will use every single data metric.

    5. Decision Making

      • People need to understand how to analyze and consume the data, how to review it, and come to a data-based conclusion. Then, be enabled to take action based on that data-driven conclusion.

    These are all great characteristics of a data-driven company and principles that company leaders should consider when trying to establish a data-driven culture. But where should you start? There are 4 stages most companies go through on their journey to creating a data-driven culture.

    4 Stages to Creating a Data-Driven Culture

    The 4 stages most companies go through on their journey to creating a data-driven culture.

    Stage 1. Conjecture

    This is when the company has little to no data available to them. Making adjustments and decisions based on past personal experiences- it might be knowledge from a past job, or just a gut feeling. Generally making quick decisions on what to do without much confidence and no real substance backing the decision. Many times they are not very well thought out or consistent conclusions.

    Stage 2. DIY

    The company is starting to collect data using an excel sheet or similar program. Typically a small database is scattered across the company. You might be recording data manually on paper, or using a whiteboard reporting system. There is a possibility that you are manually sharing data with a handful of people in the company. Many times in this stage, it’s the tech-savvy people who are asked to record, manipulate, and analyze some basic data. Of course, this data will be very limited in detail, accuracy, amount of data, and will often times be old by the time it gets used by a decision-maker.

    Stage 3. Towers of Babel

    First of all, I love this term, it makes perfect sense. This is when companies are further along in their journey of creating a data-driven culture and truly becoming data-driven. What typically happens in this stage, is the company unintentionally ends up creating numerous silos of data. Each separate department has 1 or 2 primary databases for collecting data. The good news is they are collecting more data, better data, and more systematically.

    It’s much easier for the company to get data from these databases as opposed to the DIY stage. Much better for gathering data and getting some basic visualizations. However, it’s a situation of BYOBI (bring your own business intelligence).

    This can work for a while but for a company to continue down the path of maturing, growing, driving more revenue, profits, evaluations, etc. These companies need to keep improving and drive even further towards becoming data-driven companies.

    Stage 4. Nirvana

    In stage 3, companies got their databases to drive data-based decisions with accurate data. So what’s next? Creating a single version of the truth that everyone has access to. The problem with stage 3 is that each department has different data, different data sources. These are all separate solutions, not centralized for everyone. Everyone needs to be on the same page, with the same data. Sales won’t know what marketing is doing, marketing won’t know what operations is doing, operations won’t know what purchasing is doing.

    There needs to be one single, full architecture for data with a single version of the truth. A data architecture where all data is consistent and shared between every person and every department of the company. A Unified namespace. This type of solution allows for flexibility and scalability. It is also the most accurate data when it is from one single location and extracted directly from the equipment itself. One centralized database for everyone to make decisions and drive action.

    Where to Start

    It takes some time and effort to completely transition into becoming a data-driven company. It’s easy to get overwhelmed, and tough to determine where you should start today.

    Studies say that analytics pay back $13.01 for each $1 spent (source). There’s a lot of value in being data-driven, getting started as quickly as possible can be crucial for company success.

    Analytics typically returns $13.01 for every $1 spent visualization.

    A good way to get started on your journey to creating a data-driven culture is to define your own business challenge. Determine where you need the most improvement, and start gathering data. Even if you are just starting with pen and paper. There are stages to becoming a data-driven manufacturer, and you need to start somewhere.


    Let’s say that your specific business challenge is not understanding your asset utilization. Not understanding why your machine line or plant overall is not producing as much as you think it should. This is a perfect opportunity to start gathering some basic data. Start now, and try to develop a good understanding of where you are today. How active are your machines? When are the machines off completely? When are they on, but not running? When are they on and running, actually adding value and producing parts?

    Gather and analyze that data over time to understand what’s going on. Start capturing downtime reasons– not just that the machine broke, capture the cause of downtime and the machine’s symptoms. Gather data, analyze it, make a decision, and take action. You can look at an asset utilization + downtime reason code Pareto chart to understand what’s going on and what the inefficiencies are.


    The above example is a great way to start. The important thing is that you get started, start working towards creating a completely data-driven culture. Use these first small collections of data to help you determine which long-term metrics would benefit you most to keep tracking, and go from there. Start small, think big, and take action.


    Could be using this laptop to analyze common problems in the manufacturing industry.

    3 Common Problems in the Manufacturing Industry that are Holding You Back

    3 Common Problems in the Manufacturing Industry Holding You Back

    There are many common problems in the manufacturing industry. We can all agree that there is no shortage of problems that need to be dealt with. Especially in the industry, there are a lot of people involved and a lot of big machines with many moving parts. Inevitably, with that amount of moving parts and people, there are bound to be issues that come up frequently. These problems go far beyond just the plant floor.

    All of this means that there is a lot of money moving around and changing hands often. Even small errors can equate to a large amount of lost revenue and profits. In this article, we will discuss 3 common problems in the manufacturing industry that could be holding you back. The goal is to help you make your factory as efficient as possible and maximize revenue and profits.

    1. Lack of Skilled Workers

    Let’s not waste any time, and get right to the facts. Manufacturing is a huge industry, employing a lot of people. It’s the fourth largest industry in the united states based on the total number of employed persons (source). This is good, a lot of people working in the industry. Here’s where it starts going downhill- almost one-fourth of the manufacturing workforce is age 55 or older (source). There’s not a lot of young people pursuing a career in manufacturing. This is a growing problem for manufacturers. It’s not a good sign when roughly a quarter of the manufacturing workforce is on the cusp of retiring, along with low numbers of new and young employees entering the field.

    This is forcing manufacturers to come up with a stronger recruiting process, and looking for ways to attract more young people to the sector. This may not be the main problem that you think about on a daily basis, but it is not to be overlooked. The statistics are scary for the future of manufacturing.

    2. Lack of Awareness

    The second common problem in the manufacturing industry to go over is general awareness. There are many different angles you could take here.

    Overall plant floor awareness, downtime awareness, accurate data awareness, digital transformation awareness. At the beginning of this article, I mentioned that there is a lot of moving parts and people in the manufacturing industry. It can be a challenge to keep track of and remain aware of everything happening. On the other hand, it is near impossible to make improvements if you aren’t even aware of what’s really going on. So the first step to improving operational efficiency is to become aware and accurately define where you need to focus or improve.

    Downtime Awareness

    More often than not, manufacturers cannot accurately estimate how much, or where their downtime is coming from. Downtime is a leading cause of lost revenue in manufacturing. That means it should definitely be made a point of emphasis, and that manufacturers should at the very least be aware of where of the amounts and causes of downtime. Sadly, downtime awareness is still a very common problem in the manufacturing industry.

    Accurate Data

    The way in which you gather data changes everything. It doesn’t matter how much data you are attempting to gather if it’s all data that you can’t validate, and you can’t trust. Many times, manufacturers will gather data, see the numbers, and not believe them or disregard them. This makes the initial act and effort in gathering the data completely useless and reinforces the value of using a reliable system for gathering data that you can trust. Manufacturers need to become aware of the validated, trustworthy, and accurate data that they could be extracting from their equipment and benefitting from.

    With IIoT and manufacturing analytics technology becoming more available in recent years, it’s just that much more important to have accurate data if you want to continue to grow, stay competitive, and become a data-driven company.

    3. IIoT and Industry 4.0

    This leads us to our last common problem in the manufacturing industry. You might wonder, how are IIoT and Industry 4.0 common manufacturing problems? The problem is not the technology or the solutions themselves, it’s actually more of a mindset problem. A large number of manufacturers are choosing to ignore the value that IIoT and Industry 4.0 bring.

    While others are open to the ideas, but struggle to become data-driven and use the technology to its fullest capacity. These companies need to focus on solving their business challenge, rather than focusing on the technology challenges. Instead of saying- “How can we equip our factory with the latest and best technology?” Ask yourself- “How will this actually help me?” Or, “What will get improved by gathering, analyzing, and acting on this set of data?”

    A Happy Medium

    There are two extremes here, the best spot is a happy medium in a way. No doubt that there is enormous value in gathering accurate real-time data. IIoT along with Industry 4.0 principles bring this to the table. Becoming a data-driven company is also very important. However, becoming a data-driven company means that you are acting on the data, driving decisions based on this data. Becoming a data-driven company does not mean just extract as much information, data, and generate as many reports as you possibly can. Gather what you need to improve efficiency, and solve your business challenge, any data you aren’t acting on is useless.

    How you can Take Initiative to Solve These Problems

    These are common manufacturing problems, but that doesn’t mean that you have to just live with them. There are things you can do to minimize these issues in your factory.

    The problem with a lack of skilled workers might be a job for the industry as a whole. However, becoming aware of everything happening on your plant floor, with your workers, and inside your machines is something that you can improve. Taking advantage of IIoT and Industry 4.0 can prove to be greatly beneficial. Equip yourself with the right system that meets your needs and solves your business challenge. Adjust your company culture to become a data-driven company. Your operators want to improve their process, they’re smart, allow them to benefit from accurate data. IIoT can deliver real-time data to operators and decision-makers instantly.

    We established that awareness is also a very common problem in the manufacturing industry. Be aware of your specific problems, and use the tools available today to solve those problems. If you actively search for ways to get better and generate a solid plan of action, the results will be rewarding.