Almost every industry is moving toward a digital business model because they recognize that efficiency and innovation are the only ways to service and thrive in the modern era. Digital business is not about technology supplanting people; it’s about using technology for optimization of processes and supporting users with near-instant access to the information they need to introduce new products and deliver superior customer service.
Big Data, Predictive analytics, and the Internet of Things (IoT) will bring changes to even traditional industries such as paper, packaging and forest products. Here are a few examples.
Big Data analytics sorts through large volumes of disparate data from a variety of sources to quickly pick up patterns and trends that would be impossible to find with traditional BI tools. An In-memory analytics engine can churn through vast quantities of both structured and unstructured data streaming at a rapid pace to create insight into a situation a user might not even have known about.
For example, using upcoming weather reports from around the world as well as historical rainfall records, housing start statistics and employment statistics, a forest products company might discover a higher than normal possibility of fire in a particular area. Armed with this warning insight, the company might choose to move its logging operation into an area to harvest as much product as possible, and then quickly move people and machinery to another area as the warning index gets higher.
Supply Chain Optimization with sensors & predictive analytics
Business is growing faster, but resources and energy are constrained. Companies started sourcing globally, and transportation across oceans is the new normal even for low-margin products. The on-going M&A activity within the paper and packaging industry adds its share of challenges, and in consequence today’s companies need to cope with much more complex supply chains. A solution to this issue could be the timely anticipation of demand, and awareness of storage and transportation capacity – and optimal usage thereof.
Here are some examples: Analyzing crop yields can help packaging companies plan their paper and packaging inventories in advance. Knowing in advance when crops are likely to ripen enables the company to ensure they have the right packaging materials at the right locations on time, without unnecessary inventory.
Another interesting idea was realized by Hagleitner, an Austrian company in hygiene business: As you can image, in a large buildings like a sports stadium with a capacity of ten-thousands of people there is a significant need for paper (towels) in certain areas like washrooms or restaurants. Hagleitner has deployed sensors and collects information about the number of people entering a certain areas of the building. By analyzing this data with SAP HANA the consumption of paper towels be predicted very accurately and it could allow the supplier of those paper goods to react proactively.
Using in-memory analytics, planners have access to information quickly, so they can quickly reroute packaging materials or paper-made goods to the location where it’s needed.
The Internet of things refers to sensors attached to machines that report information about an almost unlimited number of conditions or metrics. This can be particularly helpful in manufacturing processes such as paper production, where factors such as temperature, humidity and the quality of raw materials can affect the finished product quality.
Attaching in line sensors to paper mills is commonly seen in the industry, but real-time processing of huge amounts of sensor data is not. By continuously monitoring energy consumption, thickness, moisture content, and surface evenness, it ensures that the process is running effectively, but only the correlation of this data drives real value. This allows for prediction of machine failures, and, as a German producer of specialty paper just indicated, it will allow them predicting product quality, too.
Attaching sensors to monitor the process in real time and sending the data wirelessly for analysis saves time and money. Having access to information in real time enables the manufacturing team to take corrective action quickly. Using predictive analytics, it may even be possible to make those changes in advance to prevent a process from going out of control. As a result, the company enjoys higher throughput, lower cost, less scrap and higher quality at lower energy consumption.
These are just a few possibilities, but it is obvious that digital business fueled by in-memory analytics has the power to improve efficiency and increase innovation in paper, packaging and forest products.
Interested in more information around these topics? Don’t miss our flagship event – the SAP Forest Products, Paper, and Packaging Forum on October 21-22, 2015, in Frankenthal, Germany. Hear speakers from Sappi, Arauco, Suzano, Koehler Paper, Papyrus, Model Packaging, and Smurfit-Kappa share insights on thriving in the digital world. We expect over 200 attendees from customers, partners and industry professionals. Click here for more information.