Big Data

Manufacturing and Production Industry is Fighting a 41% Increase in Ransomware Attacks over Four Years

By Sandra Lee, Managing Director of Southeast Asia and Korea, Sophos Wrapping up the first half of 2024, the Asia-Pacific region (APAC) is set to be the fastest growing region of the world economy1. It accounted for more than half of global GDP growth with the manufacturing industry becoming one of the key drivers over the years2, paving the way for APAC to be the world’s manufacturing and production hub. However, the industry is claiming a sad record in Sophos’ latest report with the highest growth in the percentage of organisations hit by ransomware in 2023, emphasizing the potential risk to the global production chain. Compared to all other industries that recorded a decrease in attacks last year, the manufacturing and production industry is one of the only three sectors with an increased attack rate of 9% other than healthcare (+7%) and financial services (+1%). A concerning percentage (65%) of organisations reported they were hit by ransomware last year, which was a notable increase from the previous years since 2020 (i.e. 24% in 2020). A majority (93%) of manufacturing organisations hit by ransomware in the past year claimed that cybercriminals attempted to compromise their backups during the attack. Of them, 53% of backup compromise attempts were successful. Additionally, three out of four ransomware attacks on manufacturing organizations (74%) resulted in data encryption, hitting the highest encryption rate for the sector in the last five years and the cross-sector average of 70% in 2024. Although most organisations hit by ransomware were able to identify the root cause of the attack, which exploited vulnerabilities and compromised credentials — malicious e-mails were identified as the root cause. Some organizations are still failing to implement key security measures that can demonstrably reduce their overall risk profile, resulting in a higher attack recovery cost. In […]

Energy Experts on AI Tools for Building’s Sustainability:“Triple Win for Businesses, People, and Planet”

Donatas Karčiauskas, CEO of Exergio Research studies continue to highlight that aside from environmental benefits, AI-based platforms in building energy management deliver economic savings and improve occupant well-being. Energy experts provide real-case examples for these tools. Vilnius, Lithuania. Numerous studies delve into the potential of AI for buildings and their energy efficiency. While such AI-based platforms are often seen as primarily environmentally focused, the latest research showcases that they also deliver economic and social advantages. “Latest AI platforms that focus on energy performance also provide other benefits such as cost-efficiency and even better quality of work for energy-efficient building occupants, creating a triple win for businesses, people, and the planet,” said Donatas Karčiauskas, CEO of Exergio, a company that provides AI-based solutions for buildings’ energy performance. Energy performance experts provide insights on 3 key areas that benefit from such tools – environmental, economic, and social impact. AI Tools are Needed to Reach Net-Zero Goals The key aspect of implementing AI-for-energy tools in buildings is to reduce energy waste. It is particularly important in commercial buildings, where environmental impact is the highest due to energy consumption. By managing energy systems in real time, AI helps lower carbon emissions by ensuring sustainable use of resources. Unlike traditional systems that react to changes, AI can predict energy needs and adjust operations accordingly, leading to more sustainable building management. “With AI tools, we can fine-tune every aspect of a building’s energy use, squeezing out efficiencies that add to environmental gains. We have implemented such tools in office buildings and malls, where payback of deep renovations could take up to 10 years. It’s already too late to retrofit all the old build stock if we want to reach net-zero goals by 2050,” Karčiauskas explained. “AI, on the other hand, is capable of integrating thousands of […]

Fighting data noise in industrial production – with fully configurable digital twin

Genius Core, provides industrial manufacturers and process-focused industries with a fully configurable digital twin of their facilities, giving complete, real-time visibility over maintenance needs, safety, and operational efficiency from anywhere in the world. Process Genius says Genius Core tackles the critical issue of digital noise in industrial processes, where hundreds of systems and sensors combine, making it extremely difficult to keep track of deviations in processes, maintenance, safety alerts, and malfunctions. The platform centralises all data from equipment in a 3D visualisation on both overview and facility levels, and all critical information can be accessed in real-time. Operators can also set up their digital twin without external help from external consultants. Data noise is one of the critical obstacles to industrial efficiency. A single facility produces thousands of data points to multiple systems from equipment every minute, which is often only accessible in one of the systems in use or Excel spreadsheets. As such, facility managers and process engineers waste significant amounts of time looking for the data they need or, in the worst case, overlook critical failures or maintenance needs because they are not made aware of critical information. When operating multiple facilities, this problem increases substantially. Genius Core removes these hurdles that cause decision-making delays. The modern industry operator doesn’t lack data. Industry 4.0 has seen a vast array of sensors and software that has made available any data imaginable from each piece of equipment in the facility. Their issue now is how to put this data to good use. With hundreds of systems and thousands of data points, the challenge is understanding the data and making the right decisions. With Genius Core, they can finally stop doing unnecessary and time-consuming detective work and focus on making those decisions. Industrial production largely depends on consistent facility uptime, and […]

Navigating technology trends

“Did you see the article about blockchain on the paper’s home page? I think we need blockchain, too.” “We should give all our IT to an offshore system integrator—that will save a lot of money. Our competitors are doing the same thing.” “We need to do something about generative AI right away!” Many who work in IT have heard variations of these statements from well-meaning senior colleagues. And given how much technology underpins so many trends, as well as the increasing pace of innovation, IT leaders can expect to hear more of them and feel pressure to act on them. Sometimes it makes a lot of sense to act quickly on a trend. Innovation, after all, is a hallmark of successful companies. But not all trends are created equal. The annals of many IT organisations are littered with bold initiatives in trends that created a lot of excitement but not much value. Moving quickly to chase a trend often bogs an organisation down, leads to wasted spend, and takes attention away from important priorities. For this reason, the ability to evaluate trends quickly and communicate their relevance to the business is becoming a critical capability for the modern CIO. In practice, it is rarely as simple as saying “yes” or “no” to investment in a particular trend. Trends are unpredictable, change with time, and their relevance to a given business often waxes or wanes. Instead, CIOs need a clear set of parameters to rely on both for evaluating trends and for determining which posture to take for engagement with them: first mover, fast follower, slow adopter, or sometimes non-partaker. Four guides for determining a trend’s relevance Disruptive business value: The trend can result in measurable value to the business. Independence: The trend allows the organisation to work in smaller, more independent units. Connectivity: The […]

The Interview: Marcelo Tarkieltaub, Regional Director, Southeast Asia, Rockwell Automation

Focusing on Rockwell Automation’s Industry Outlook, the growth of industrial automation & smart manufacturing in Asia Pacific, highlighting both the benefits and gaps that businesses must navigate in this growing market. Tell me about Rockwell Automation’s Industry Outlook for the manufacturing sector in Asia Pacific Rockwell Automation’s Industry Outlook for the manufacturing sector in Asia Pacific showcases a promising landscape. Manufacturing is one of the most significant contributors to the Asia-Pacific economy and is undergoing rapid transformation. Some key factors that are influencing the manufacturing sector include: Technological Advancements: The integration of cutting-edge manufacturing technologies, including automation and IoT, is transforming the manufacturing sector, leading to enhanced efficiency. According to our State of Smart Manufacturing Report, close to half (44%) of APAC manufacturers plan to adopt smart manufacturing within the next year; out of this, China (80%), Australia (60%) and India (59%) are already using some components of smart manufacturing. Sustainability and Environmental Regulations: An increasing emphasis on sustainability and environmental regulations is driving changes in manufacturing practices and product requirements. Again, our State of Smart Manufacturing report cites that for the 94% of APAC manufacturers who have formal or informal environmental, social and governance (ESG) policies in place, close to half (48%) cite “a competitive differentiator” as the top driving factor for pursuing ESG initiatives. Economic Growth: The overall economic growth and stability of countries in the Asia Pacific region can have a significant impact on manufacturing. Rapidly growing economies drive increased demand for manufactured goods. How is smart manufacturing growing in Asia Pacific? Smart manufacturing is growing in the region driven by a combination of factors including technological advancements, government support, and the region’s strong manufacturing base. APAC is home to some of the world’s leading technology companies and has a strong presence in industries such as electronics, […]

Who is Sam Altman?

On Friday, OpenAI’s high-flying chief executive Sam Altman was unexpectedly fired by the company’s board. Co-founder and chief technology officer Greg Brockman was also removed as the board president, after which he promptly resigned. Now it looks like Sam Altman has ended up at Microsoft. In an unexpected twist, talks began about potentially reinstating Altman in some capacity following an outpouring of industry and investor support for him and several OpenAI researchers who quit their jobs in solidarity. OpenAI’s board found a new CEO –Emmett Shear – in record time. Shear, the former CEO of Twitch, will now take over from Murati as interim CEO. It has been an epic backstabbing scene worthy of the HBO drama Succession. While many have speculated about why the board may have forced Altman out, details remain scarce. What we can say is the decision to fire Altman will likely put a dent in OpenAI’s commercial progress. An unusual company structure OpenAI is the hottest company in tech today, having released the ChatGPT chatbot and DALL-E image generator onto a largely unsuspecting public. The company’s mission is simple: to develop artificial general intelligence (AGI) – that is, an AI which is as smart or smarter than a human – and to do so for the public good. Many were starting to believe OpenAI could succeed at this goal. But developing AGI isn’t just a technical challenge. It’s a major management and economic nightmare. How can you ensure the vast power and wealth generated by AGI doesn’t subvert the company’s goal to seek the public good? Many individuals within OpenAI and the wider tech community worry AI is progressing too fast. A global race in AI development is underway and the commercial pressure to succeed is immense. Following its launch, ChatGPT quickly became the fastest-growing app […]

Working with AI: Real Stories of Human-Machine Collaboration

Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.

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