New technology and Enterprise Asset Management

Over the past 20 years, the technology landscape has undergone significant transformations, driven by advancements in data processing, connectivity, and computational power. Here's a summary of the key trends that have shaped the technolgy industry:

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1. Big Data: The explosion of data generation from various sources such as social media, online transactions, and sensors has led to the rise of Big Data. This trend has necessitated the development of new technologies and frameworks for storage, processing, and analysis of large volumes of data. Hadoop, Spark, and NoSQL databases are examples of technologies that have emerged to handle Big Data. Questions were “How to capture data” and “What data should we capture”, but we forgot a bit the “why…”

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2. Internet of Things (IoT): The proliferation of connected devices has given rise to the IoT, where everyday objects are embedded with sensors and network connectivity to collect and exchange data. This has led to smart homes, cities, and industries, with applications ranging from home automation to industrial automation and smart grids. Here, some data collected may not be relevant without an use case and applications. Similarly to RCM, focus should be on critical assets and data captured may not need to be “real time” to capture possible failure patterns.

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3. Predictive Analytics: With the availability of large datasets, predictive analytics has become increasingly important. This involves using statistical algorithms and machine learning techniques to analyze current and historical data to make predictions about future events. Predictive analytics is used in various sectors, including asset management (Predictive Maintenance) finance, healthcare, and retail, to forecast trends, optimize operations, and personalize services. Often customers try to make a “leap frog” from XLS spreadsheets to predictive.. again it takes some time to define a strategy, the what / how and why and start identify relevant predictive results.

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4. Machine Learning: A subset of artificial intelligence, machine learning has seen tremendous growth. It involves the development of algorithms that can learn from and make predictions or decisions based on data. Machine learning has been applied to a wide range of problems, from image and speech recognition to natural language processing and autonomous vehicles. Sometimes we are confused between data analytics, BI, trends, modelisation and actual machine learning. Computing power required can add to cost so again without a strategy and ressources to deploy this strategy, one needs to be wary.

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5. Artificial Intelligence (AI): AI has been a central theme in technology trends, with significant progress in areas such as deep learning, neural networks, and natural language processing. AI technologies are being integrated into various applications, from virtual assistants and chatbots to advanced robotics and autonomous systems. We can finally see actual results and great applications from AI, although there are still challenging to insure results are correct.

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6. Cloud Computing: The shift to cloud computing has been a defining trend, with businesses and individuals increasingly relying on remote servers for storage, processing, and software delivery. This has led to the rise of major cloud service providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. However sometimes hybrid is advocated, or Cloud is not also perfect (recent event with Crowdstrike etc). Again, each organisation needs to assess its particular needs and resources (time, money, people, materials etc) to deploy Cloud.

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7. Mobile Technology: The widespread adoption of smartphones and mobile internet has transformed how we access information, communicate, and conduct business. Mobile technology has also enabled the growth of other trends, such as IoT and location-based services. In the asset management domain, on/off line applications are helpful for fields technicians to access assets information on the spot, and save time to carry on work order and preventive maintenance, while reducing manual entry errors thanks to pre configured list of values for instance.

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8. Cybersecurity: As technology has become more integrated into every aspect of life, cybersecurity has become a critical concern. The past two decades have seen an escalation in cyber threats and a corresponding increase in the sophistication of security measures, including encryption, multi-factor authentication, and advanced threat detection systems. As per Cloud’s comments, example with Crowdstrikc has shown how dependent many services (airport etc) depend on technology.

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9. Blockchain: Initially introduced as the technology underpinning cryptocurrencies like Bitcoin, blockchain has evolved to offer secure and transparent ways to record transactions and manage data across various industries, including finance, supply chain, and healthcare. Perhaps for asset management will be more useful for fixed / financials assets in case of tranfers.

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10. Quantum Computing: Although still in its early stages, quantum computing has the potential to revolutionize computing by solving complex problems that are currently intractable for classical computers. Research in this area has accelerated, with tech giants and startups investing in quantum technology. This power will definitely help AI.

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11. Augmented Reality (AR) and Virtual Reality (VR): AR and VR technologies have matured, offering immersive experiences in gaming, education, training, and design. These technologies are also being explored for remote collaboration and virtual meetings. For Asset management field, we see this as a support for field technicians, contractors, new employees, for remote location/ assets etc..

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12. 5G Technology: The rollout of 5G networks has begun, promising faster data speeds, reduced latency, and the ability to connect a large number of devices. This will further enable the growth of IoT, smart cities, and high-bandwidth applications like streaming and cloud gaming. As discussed for mobile with off line capacities, expansion of network will reduce the white areas and enable technicians and engineers to perform maintenance work anywhere with access to relevant data.

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These trends have not only reshaped industries but also influenced societal norms and behaviors. As we move forward, the convergence of these technologies will likely lead to new innovations and challenges, with continued emphasis on data, connectivity, and intelligence. Enterprise Asset Management will continue to benefits to this development in technology.

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