Industry 4.0 to 5.0: What it means for Meat Processors and Manufactures

Industry 4.0 to 5.0: What it means for Meat Processors and Manufactures

Feb 8, 2022 | Agri, Article, Data, Decision Intelligence (DI), Explained

Smart Farm: What you need to know

Wondering what Industry 4.0 and 5.0 is all about? We’re here to explain.

Currently, we are living in the 4th industrial revolution – Industry 4.0. This is the age of information technology (IT), machine learning (ML), and artificial intelligence (AI). Industry 4.0 brought about the autonomous exchange of data among smart machines without the need for human intervention. Organisations benefit from the data retrieved and analysed by smart technology and the delivery of actionable insights for better decision-making.

But at the same time, we are already transitioning into Industry 5.0. What changes will this bring? Most importantly, what does your organisation need to do to stay ahead?

Industry 4.0 is here and now

Industry 4.0 is about connectivity to enhance efficiency and productivity. It has given us AI and ML, along with cloud-based computing and the Internet of Things (IoT). These technologies have created networks of smart sensors that communicate with each other rapidly and feed data back to us. It has allowed for the development of smart robots to take over menial tasks previously done by humans, freeing up human intelligence to focus on more advanced tasks.

What Industry 4.0 has in turn created is big data – large amounts of up-to-date data that is available at our fingertips, and growing every day due to continuing advances in ML and AI. This massive influx of data requires more advanced analytics capabilities than ever before. We touched on this topic in our article on Smart Farms and how this influx can create new challenges to overcome. 

This is where Business Intelligence (BI) systems come in. Thanks to BI, we can receive all of this advanced data via automated, real-time reporting. BI is the driving technology that organises and analyses large amounts of data, delivering actionable insights that simplify the decision-making process for business leaders.  

What this all means is that in Industry 4.0 we have the ability to harness the technology that drives data-driven decision-making for any organisation’s growth and advancement.

Organisations go through what we call a data maturity curve, where they move from working manually with Excel reports at the base level, all the way through to a Decision Intelligence solution. Each phase drastically improves upon the next, and it is critical to progress through the phases consecutively to build on the previous foundations.

Smart Farm: What you need to know

Industry 5.0 balances tech with human input

What Industry 5.0 introduces is a greater collaboration between humans and machines. 

Industry 4.0 is currently giving us the technology and machine power to make incredible advancements in meat processing and manufacturing. We can improve our workflow processes and maximise productivity and efficiency. ML and AI have freed up more time for humans to focus on the bigger picture by automating menial tasks. 

Industry 5.0 is the next step forward, with greater human interaction with machines in order to apply human creativity and critical thinking to machine output. It’s 4.0 with a human touch, perfectly balancing modern tech with human input. 

Some fear that machines will replace humans as workers, but that is the opposite of what Industry 5.0 is about. It is about a synergistic relationship that utilises the efficiency of machines but relies on humans to oversee and make critical decisions. Machines cannot replicate human judgment and empathy, nor the ability to shift from short-term to long-term thinking.

Machines plus human workers provide endless opportunities for businesses that take advantage of the advances. Robots will become “cobots” (“co” for collaboration), safely working alongside humans while intelligently learning about their environment to continually adapt. Manufacturing and Meat Production constantly become smarter processes. 

Even Elon Musk admitted that excessive automation at Tesla was a mistake, and that “humans are underrated.” The speed and consistency of robots increase productivity, but the human skills of creativity and critical thinking are necessary components of a collaborative manufacturing relationship to maximise productivity. 

So are BI systems ready to keep pace with Industry 5.0? BI itself is undergoing a concurrent evolution as Business Intelligence evolves into Decision Intelligence (DI).

Smart Farm: What you need to know

How can your business adapt?

What exactly is DI? Much as the evolution from Industry 4.0 to 5.0 involves greater collaboration between humans and machines, the evolution of BI to DI combines human decision making with Business Intelligence and Machine Learning.

DI relies on AI and ML to learn and improve upon decision-making models to optimise decision-making. This enables some decisions to become automated while providing humans with precise insights to make higher quality, faster decisions for those that require human input. DI provides the technology necessary for humans to utilise the mountain of available data effectively to drive better decision-making and thus better business outcomes.

In short, DI is the link between human decision-makers and machine learning. It makes sense of all of the data provided from a BI system, giving your organisation actionable insights gathered from AI- and ML-generated data.

Decision Intelligence is critical to Industry 5.0

If this is all overwhelming, let us put your mind at ease. The beauty of DI is that you don’t have to understand how any of it works.

A DI system provides your organisation with all of the technological tools needed to help you achieve the best outcomes. DI assesses data along with the chain of cause and effects of decisions for you. You can then implement the right decisions at the right time to enhance productivity and efficiency while decreasing costs. 

Basically, you don’t have to worry about the process. The end results are delivered to you so that you can make higher quality, faster decisions with less effort.

Summary: We make it easy for you

To sum up, Industry 4.0 looks to connect and centralise all the data sources within the manufacturing process for improved analytic decision-making, and Industry 5.0 creates a coexisting relationship between humans and machinery to further improve the capabilities of the organisation.

DI is the key to unlock these capabilities. The team at Toustone are experts in DI and ready to bring your organisation up to speed with Industry 4.0 and prepare you for Industry 5.0, no matter where you are at currently. We are passionate about leveraging DI to improve the processes of any size business no matter how large or small.

You don’t have to be a data scientist – that’s what we are here for. Contact our team today to see how a DI system can help your manufacturing business access data-driven insights to make better business decisions.

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Smart Farms: What you need to know

Smart Farms: What you need to know

Dec 21, 2021 | Agri, Article, Decision Intelligence (DI), Explained

Smart Farm: What you need to know

The future of Australia’s agriculture is in smart farms.

Australia is the second-largest agricultural area in the world, after China. We have over 85,000 farms using 372 million hectares of land and 9.2 million megalitres of water. In FY 2018-2019, the gross value of Australian agriculture was more than $62 billion. The National Farmers’ Federation has set a daunting vision for that number to reach $100 billion in 2030.

As we’ve seen in the past, mother nature will always throw curveballs. But by connecting the physical world with the digital, you can develop a better understanding of your farm operations to improve efficiencies, drive better decisions, and predict what’s coming next. It is the piece of the puzzle required to move Australia into the future of agriculture while reducing the environmental impact.

If you’re curious about how smart farms and Decision Intelligence will pave the way for growth in agriculture, read on.

What Is A Smart Farm?

Smart farms use the latest technology and data analytics to optimise agricultural practices. Sensors, drones, autonomous vehicles, machinery data and Artificial Intelligence (AI) combine to enhance the overall understanding of operations and identify areas to reduce costs, improve yield and quality, and forecast what’s to come.

One critical tool for smart farms is the Internet of Things (IoT). IoT refers to all of the sensors on the farm that communicate with each other wirelessly via the internet. Using internet connections means farms can be remotely monitored. Equipment, water management, weather events, crop diseases, soil requirements – all of it can be tracked in a dashboard and viewed from any device, anywhere at any time.

Using IoT technology enables automation and more autonomous activities in day-to-day operations. For example, soil sensors track moisture levels and soil health to predict diseases. Drones diagnose crop diseases and measure water and nitrogen levels. Livestock sensors monitor health and fertility. According to KPMG, every farm should be connected to the IoT by 2030. This technology enables total oversight of daily operations, improving operational efficiency without having to be at the physical location or even in the same country! 

Lack of internet access is the biggest obstacle for Australia’s agriculture industry to go digital, and the future of farm telecommunications is changing to improve farm connectivity.

“Getting these devices to talk to each other and provide real-time information in a central dashboard at the farmer’s home or office will require connectivity on a scale never seen before, and will undoubtedly involve different interfaces, methods and systems that are not always seamlessly compatible,” says Sami Makelainen, Technology Insights Manager, CTO Strategic Planning and Foresight, Telstra. “The benefits though, once successfully done, will be game changing for Australian farmers.”

Smart Farms + Decision Intelligence = Maximum Impact

Introducing IoT devices into your farm allows you better visibility and management of your operations. With this new technology comes vast volumes of data which, when utilised correctly, can provide additional benefits and insights to your farm operations and profitability. The challenge lies with how to manage these large volumes of data, also referred to as big data. Without a strategy in place, this big data becomes siloed across the different devices with no data relationships and correlation being identified and exploited for their value. 

This is where a Decision Intelligence (DI) solution comes in to connect, automate and analyse the data to provide you with actionable insights without being a data scientist. Forget organising and reading reports. Smart farms can operate from one DI dashboard that connects and presents all of the information and insights you need to make the best decisions. The beauty of DI coupled with smart farming is that it removes that risk of building silos of data across your farm which ensures you are always working with the right information on hand.

“Data delivered by digital technology coupled with advanced analytics are a game-changer for Australian farmers to push the boundaries of performance.”
KPMG & National Farmer Federation,
Talking 2030 (2018)

Using IoT technology puts a lot of data at your fingertips, but you also need DI to know what to do with it. Manual handling of data is time-consuming and jeopardises the integrity and reliability of your data. It is too easy to accidentally copy and paste a number incorrectly, throwing off all of your results. DI eliminates the risk of these errors and delivers data-driven insights instead of just data.

The Future of Farming is Now

Smart farms use IoTs to connect every aspect of farming, from soil and crop health to best animal farming practices and weather conditions. Decision Intelligence connects all those IoT devices with any other relevant data sources into one secure location, then analyses and presents that information into an easy to use dashboard.

Farmers don’t have to waste their time analysing reports or stress about whether they are making the right decisions. A DI solution makes it easy by presenting actionable insights for the farmer to make data-driven decisions. The time and resources saved along with continual efficiency enhancements drive higher yields at lower costs.

Smart farming resources are available and are being used now. Toustone has developed a ready-to-implement Agri DI solution to connect all of your data points without the need to change any of your current platforms or devices. If you’re ready to implement smart farming on your farm, get in touch with the team at Toustone today.

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Using Data to Increase Productivity

Using Data to Increase Productivity

Jan 14, 2021 | Agri, Article, Data, Decision Intelligence (DI)

Smart Farm: What you need to know

A key driver of productivity in any organisation is recognising where your business is succeeding and where it is preventing you from succeeding. Gathering insights from your data can give you an understanding of where your business sits, and using the compounding effect of data will make clear what actions you can take to increase productivity in all areas.

Productivity in the Australian Meat Industry

The Australian Meat Industry runs at high cost compared to international competitors. Cattle prices have increased throughout 2020 so that Australia is home to some of the most expensive cattle in the world. Increasing productivity to use less labour and energy would drive these costs down. Some traditional ways of enhancing productivity are through improving the pasture, refining the genetics of the stock, and using new technology or upgraded equipment.

But one thing is critical to increasing productivity now and in the future: Data. Applying the compounding effect of data to this high-cost industry shows us just how important data is to the future of the industry.

The compounding effects of data

As a recent article discussed, the three compounding effects of data are:

  1. Hindsight
  2. Insight
  3. Foresight

Applying hindsight, past data can be analyzed to assess what has happened. Knowing what happened positions you to make better decisions in future. This is the basic level of Decision Intelligence (DI). Regarding high costs in the meat industry, hindsight analytics would show how each component contributed historically to the total cost and reveal areas that could be improved to increase productivity.

With insight, we go a step further to understand why it happened. Now we have an understanding of the big picture – what, when, and why. The data tells the irrefutable story, removing emotion or gut feelings from the decision-making process and pointing the way to desirable outcomes. For instance, food safety and biosecurity are major points of contention in today’s global environment and Australian processors have the advantage of solid, trustworthy systems. While it may increase the cost, it is highly desirable in the current times and therefore may be a selling point worthwhile to buyers even at a cost higher than the competition’s. Using insight to understand why justifies this aspect of productivity.

Foresight uses predictive and prescriptive analytics to then help us understand what will happen – and what we can do to make sure it happens. It points you to the actions that need to be taken. Each of the components affecting productivity, whether it be genetics of the stock or management strategies, are assessed. This level of analysis allows you to take preemptive action to prevent undesirable outcomes and encourage desirable ones.

Utilizing the compounding effect of data ensures greater insight and foresight to improve efficiency and therefore lead to increased productivity. This is the bases of Decision Intelligence.

Data is the future of the Meat Industry

As technology advances and industries increasingly rely on data, it is critical for the meat industry to maximise gains utilising their data. Not only is it important in order to efficiently increase productivity, but the quality and transparency of the data is important in order for genetic research and advanced technology to invest in the meat industry.

The data is already there, it is simply a matter of analysing and using it. With the compounding effect of data, each stage builds on the previous one. Starting with the right data foundation that allows you to use hindsight gives you the ability to generate insights and make the next logical step to foresight. If you would like to learn more about DI in Agriculture, click here.

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Predicting Absenteeism with Data

Predicting Absenteeism with Data

Jan 7, 2021 | Agri, Article, Data, Decision Intelligence (DI), Technology

Meat Processing

Absenteeism affects every business operation. If someone isn’t there to do their job, the tasks are either delayed or another person has to be found to fill in. Direct costs include the expense of paying out sick leave plus replacement staff. Indirect costs are seen in delays of work and the effect of the absence on coworkers or supervisors. Costs begin to add up and affect the bottom line. In Australia, the annual cost of absenteeism to the Australian economy is estimated at $44 billion per year.

But, through the use of existing data, absenteeism can be predicted and potentially prevented.

In our last article, we went over the compounding effect of data and it’s three components: hindsight, insight and foresight. To sum up, as the use of your data is optimised, you move from assessing what happened and why to predicting what will happen. You are able to see what actions you can take to ensure a favourable outcome. Your existing data is optimised and gives you the ability to make better decisions and better decisions lead to better business.

Absenteeism is one key area that we can assess with the compounding effect of data to better understand why it happens and prevent it from happening in future, resulting in a significant reduction in cost.

Predicting absenteeism in the Meat Industry

Labour-intensive operations where consistent staffing is key to keeping up with output are most affected by absenteeism. Australia’s Meat Industry employs over 32,000 people and is a $21 billion-dollar industry. An analysis done by the Australian Meat Processor Corporation found that labour makes up 58% of the operating cost for beef processors. With absenteeism a major issue in the meat industry and labour costs comprising a significant portion of the cost of meat, processors should be particularly motivated to control absenteeism.

By utilising the compounding effects of data, absenteeism can be accurately forecasted and potentially prevented to increase efficiency and reduce cost.

First, by applying Descriptive Analytics to existing data we can extrapolate the rates and costs of absenteeism. This is the hindsight step – looking at what happened. It’s a basic assessment of how often and where absenteeism is occurring and the associated costs.

Then by using Diagnostic Analytics we uncover why it occurred – this is the insight component. Illness or injury, stress, family issues, transport issues and even employee morale can all be reasons for absenteeism. Analysis of data can pinpoint departments, divisions or geographic locations, all creating a picture of the reasons behind the occurrence.

Finally, we head into the foresight component of the compounding effects of data, where we apply Predictive Analytics to predict when absenteeism will occur, based on what we have already learned about the rates and the reasons. The ability to forecast when it occurs means you now have the ability to take action to prevent it from occurring.

Preventing absenteeism has a significant effect on labour cost while increasing production and keeping customers satisfied. Australia’s meat industry would see a major benefit by using their existing data in the most effective way through the application of Decision Intelligence solution.

Meat Processing

Getting started with data

At Toustone, we are dedicated to help businesses make effective use of their existing data in order to grow. Our reporting solution delivers simple, automated dashboard reports identifying trends, costs, and insights, enabling you to make the best decisions without wasting your time on gathering and analyzing data.

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The Compounding Effect of Data

The Compounding Effect of Data

Dec 10, 2020 | Agri, Article, Data, Human Resources, Technology

Smart Farm: What you need to know

Data-driven companies have the advantage of relying on sound data in every aspect of the business. Rather than focusing on continually gathering more data, they take the data they have and use it in novel ways to drive decision-making. The compounding effect of data increases the value of the data you already have and simplifies the process of optimising your data.

The compounding effect has three parts

  1. Hindsight
  2. Insight
  3. Foresight

Hindsight is the stage where you are building your data foundation. It involves looking at descriptive analytics and analysing what has already happened.

Insight is the practice of using diagnostic analytics to understand why it happened.

Foresight takes your data a step further, using predictive and prescriptive analytics to predict what will happen and how you can make it happen.

The result goes beyond using data to understand what happened and why to using your data to create desirable outcomes.

Application to Human Resources

Traditionally, Human Resources (HR) have been seen as a people-oriented industry. They spend a significant amount of time dealing with staff appraisals, recruitment, satisfaction surveys, and management issues. Today, data can transform HR to an area that delivers insights that have a significant impact on an organisation’s overall performance.

Utilising Data in HR can:

  • Forecast and minimise absenteeism
  • Optimise recruitment tactics
  • Identify how best to keep employees happy
  • Understand the employee lifecycle – know when someone is about to leave
  • Track payroll and compensation
  • Enhance employee COVID tracking

When HR is data-driven, it results in making better decisions that add value to the business. Less time is wasted on recruiting and training. The workplace can be optimised for employee satisfaction. The heavy cost of absenteeism can be reduced.

These days, perhaps most importantly: COVID can be tracked to minimise the spread and impact on your workforce.

Smart Farm: What you need to know

Example

It was identified early on that the meat industry was a high-risk area for COVID transmission. In Melbourne, Cedar Meats was closed for six weeks due to an outbreak among staff – a cost no business wants to face. How could HR data help prevent this?

Even when strict COVID protocols are enforced in the workplace, workers are coming into contact on the way to and from work. Within the meat industry, it’s common for staff to carpool to work together as many locations are in remote areas.

Developments in Bluetooth tracking technology mean an alert can be generated when employees come in close proximity. This data can be used to track who may have been in close contact with someone who tests positive for COVID and speed up the isolation and testing procedures.

To manage this data, a well-supported data environment and system are required to assess the data, draw meaning from it and generate reports that can be acted on in real-time. It may be that changes in shift capacity, start and finish times, and break times could decrease employee contact. Automated insights can assess the data as to what has happened and why and predict future occurrences. In this way, data can be a major force for containing COVID outbreaks.

Smart Farm: What you need to know

Are you getting the most out of your data?

The above example is just one of many ways that the use of data can advance your HR practices, but this is not limited to HR, any department can improve their efficiency to help their organisation grow, from HR to sales to operations. Check out some of our other articles that talk about how data can reduce absenteeism and enhance productivity.

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