Consumer-goods (CG) companies have already started to apply digital solutions to their manufacturing processes. The new pandemic measures and globalization added further difficulties to all supply chain parts and product life cycles.
With little margin for error, CG companies are looking into new ways to improve their products and processes. In order to provide the best service and customer experience, while keeping the costs low, many CG companies are turning towards agile or lean manufacturing.
Industry 4.0 brings the digitization of the entire manufacturing chain where Big Data, Cloud and IoT technologies help manufacturers to get an overview of the entire value chain.
Some companies are not sure what parts of the manufacturing process can benefit the most from digitization and what they should plan next.
So let’s see how companies can apply technology and use advanced analytics to optimize their manufacturing processes.
Lean transformation is the process of ‘introducing changes into an organization to maximize the flow of value produced for the customer.’ The result is removal of wasteful activities for optimized operational processes.
The best way for a company is to centralize data and assets into a cloud-based hub. Such a hub can contain different suites of tools to support daily lean operations (performance tracking, management system, platform for sharing information and real time collaboration etc.).
Such an organization enables key people to access company information (via dashboards, graphs etc.), enabling them to detect any performance gaps and compare metrics by custom filters. A cloud-based hub can automate data collection and exporting, tracking of key performance indicators (KPIs) and generating email reports, thus significantly reducing the amount of administrative workload.
Sharing data quickly enables more productive collaboration between different sectors in the company and more efficient communication where your employees can more likely discover issues in real time.
Preventing small problems to become major disruptions is crucial while scaling up.
When companies succeed in deploying digital tools to business quickly with minimal resources, it may improve overall equipment effectiveness (OEE) by up to 20% within a few months.
Advanced analytics have had a massive effect within particular sectors like Quality Control, Predictive Maintenance and Supply Chain Optimization.
Assets in many consumer-goods companies are difficult to keep optimized due to uncertain conditions. This can prevent the company from achieving the quality targets.
Depending on your area of operation, manufacturers can exploit the data collected by sensors or other devices in order to improve their quality control.
For example, if you produce and distribute polymer solutions (or any other product), you can adjust your warehouse process using customized algorithms to analyze sensor data and deliver productivity increase. Usage of sensors can significantly reduce the time necessary for employees to complete the tasks (scanning the labels, monitoring the storage facility etc.). Quicker inputs and more efficient communication reduces administrative workload.
CG companies should always analyze their own data for the entire manufacturing process/facility to improve the quality of their products/services.
All manufacturing companies gather data whether manually or automatically. Even when you collect data on a regular basis, you should always strive for MORE data.
Theory says that increased data collection will ensure your facility to prevent release of improper products, avoid injuries, increase efficiency, and more.
But to put theory into practice, DO NOT focus on the amount of data, but on the quality of data and its proper analysis. The data you gather must be meaningful in order to provide you with insights.
To make a greater impact, you should try to identify the worst-performing stages in the production or storage process. Then adjust and use the analytics to determine your facility’s shortcomings. Such an approach will provide you with insights into operations while identifying areas for improvement.
A proactive approach can always help you to quickly begin reducing costs and deficiencies.
Predictive analytics is already in use by some consumer-goods companies for maintenance activities resulting in possible maintenance cost reduction from 10-40%.
Consumer companies can deploy sensors to collect data and later use for analysis (or comparative analysis) via custom algorithms and determine the optimal time for a certain action (replacement of a machine parts, product processing stages etc.). Such precision predictions based on thorough analysis can increase your product quality and lower inventory or other costs.
Vehicle sensor information can also be used for predictive maintenance – maximizing the lifetime of company equipment (vehicles, forklifts, trucks etc.) with preventive maintenance based on the overall data.
Supply Chain Optimization
Consumer goods companies are putting all their efforts to reduce costs and optimize most of the supply processes.
Some companies use analytics software solutions to determine the best distribution plans per area considering storage capacity or local demand. Such analytics enable companies to increase profits with little or no change in production capacity.
These analytics solutions include Big Data for warehouse management and data inputs from bar codes, RFID, GPS etc. They can obtain traffic sensor data, road network and vehicle data in real time enabling logistics teams to optimize transportation or delivery processes. Moreover, they can react to unforeseen events (accidents, blockage) more effectively; track cargo or vehicles in real time and provide customers with real-time updates.
When talking ‘Big’, the common practice should be to implement Big Data first into individual departments in the supply chain and only then repeat the success across other departments. Such an approach will help managers to mitigate internal resistance and review the strategic business goals driving the specific operational unit.
The ‘Big Data’ approach requires a whole architecture together with hardware, software and internal protocols for collecting, analyzing and storing the data in real time. Such architecture will allow data scientists to search and filter information, generate relevant reports and share actionable plans across the company’s various departments.
The architecture MUST be scalable as the volume of data will grow and it MUST be secured as any consumer privacy data must be protected. It also must communicate with customer relationship management systems providing real time intelligence providing insights to relevant stakeholders.
Supply chain optimization software can generally help manufacturers to connect the entire manufacturing value chain, from procurement to the final production and delivery. Using such software helps you to track, predict and eliminate operational bottlenecks within the supply chain.
Internet of Things (IoT)
The consumer goods industry as a whole has been increasingly embracing IoT technology.
The Internet of Things represents different devices that are connected online or via the Internet. IoT could not be possible without the Internet as well as cloud computing and small sensors which enable more devices to get interconnected quickly.
Some of the benefits of IoT technology in manufacturing are cost reduction, increased efficiency, improved safety and product innovation.
Most companies were enabled to make more informed decisions based on real-time information and coupled with other tech innovations, IoT technology can help manufacturing companies drive more efficient short or long-term goals.
IoT adoption has increased significantly over the past years as manufacturers are realizing its potential and value much more.
Enterprise resource planning (ERP) systems are the basics to keep your company competitive and apply lean methods.
ERP systems automate and optimize the company’s processes using real time information. This helps to reduce operational costs and prevent any bottlenecks through the operational process.
ERP systems provide businesses with real-time access to enterprise data enabling efficient communication from any part of the world. This way, ERP systems facilitate the vital flow of data and support global markets.
Such systems enable companies to efficiently manage warehouse operations, organize and stock inventory as per sale forecasted results,
ERP systems provide quicker communication with vendors or suppliers across the globe while supporting drop ship purchase orders, saving extra expenses and labor.
Coupled with forecasting and predictive analytics, ERP systems can help you not only to improve operational efficiency but also build a better consumer-friendly brand.
Augmented Reality (AR) and Virtual Reality (VR)
Virtual and Augmented Reality have become increasingly utilized in several industries, where consumer goods companies successfully follow the latest trend.
A good example is Walmart, which opened another ‘test store’ in October 2020 for the purpose of implementing AR technology for inventory control. Their application helps employees with inventory control – employees hold up a handheld device which highlights the boxes ready to go to the sales floor, improving the process so they do not have to scan each individual box. This is a great example of AR used for a more streamlined workflow.
An exciting area for VR is marketing – using VR in marketing can boost conversion rates as consumers are more prone to buy a product they interacted with virtually. A compelling example are virtual reality car showrooms – Audi and BMW provide VR experience for their customers to simulate sitting in the genuine car model with all the texture leather and the knobs included.
There are many more examples of AR/VR use cases, where manufacturers and consumer goods companies offer a complete customer-driven experience thus increasing their online presence and building a stronger brand.
Manufacturers in the consumer goods industry have seen a variety of benefits from 3D printing with reduced production costs in the first place. Prototyping with 3D printing is much quicker allowing designers to fine-tune and test the products quickly.
3D printing made it possible to produce prototypes much quicker than with traditional manufacturing methods, like CNC. It speeds up the process of designing concepts and making changes with 3D prototypes – you can produce them overnight and they will be ready for testing the next day.
3D printing enables companies to produce complex features which lead to innovative products, optimized for durability and/or strength.
Customization is another benefit of 3D printing because it does not require expensive tooling changes for individual specifications. As data is transferred to the 3D printer, there is no need for other tools other than the printer itself. Zero tooling means printing a variety of designs at no extra production cost.
Thanks to the use of this technology, the companies can also design and test new machine parts in less time and costs involved.
3D printing allows manufacturers to make products on-demand, meaning that companies can experiment with more designs without needing a large investment. As the printing process is adding layers to produce a part, it can significantly reduce material waste and make the entire manufacturing process more sustainable.
Consumer goods companies are already benefiting from usage of digital tools; however, companies must also undertake an organizational transformation if they want to keep the pace with digitization within consumer goods manufacturing. Such transformation involves each department within the company and requires full commitment of every employee.
Consumer companies should turn to digital transformation and then can hope to reap greater benefits from digital tools.
Implementing digital solutions will leverage the benefits to the company and in the long run, it will start a new era of manufacturing efficiency.