Can analytics & AI help companies strengthen their resilience in an ever-changing business world? It’s quite possible. There are early indications of this. Discover how early risk detection, predictive maintenance, robust cybersecurity, bias-free recruitment, and creativity-enhancing training are boosted with Analytics & AI solutions.
Where once a 2.0 or 4.0 symbolized innovative change and disruption, today we see an X. Manufacturing X, Industry X, Digital X. There seems to be a universal agreement that the value derived from interconnected data should be leveraged sooner rather than later. Rethinking processes means interlinking them intelligently through data-driven end-to-end solutions, automating them, and making them more efficient. Implementation is to be aided by standards developed and established by entities like the OI4 Alliance.
One reason for the current industry-wide push towards Digital & Data Engineering is the market penetration of Artificial Intelligence, including GenAI, LLMs, Copilots, Machine Learning, Analytics, etc. However, technology itself does not dictate purpose. Far more decisive is the fact that businesses, perhaps more now than ever, need to learn to navigate uncertainties. Global developments, strategic priorities, a volatile technology market, climate change – much remains uncertain and will likely continue to be so for the foreseeable future. Here, we are witnessing a dichotomy: On one hand, business decisions are made with great caution, questioning whether the right projects and partners have been chosen due to fears of hidden costs and misaligned future focuses. On the other hand, especially in high-risk phases, the mantra is to not fear mistakes. It’s better to try and continuously adapt.
To bolster their resilience, economic experts recommend that companies excel in five areas: Anticipation, Endurance, Robustness, Diversity, and Creativity. The pressing question for many is: How can analytics & AI solutions contribute valuable services to these areas? There’s no one-size-fits-all answer, as the applications vary greatly. However, some trends are emerging:
As versatile as the technological potential of analytics and AI solutions is in helping companies solve complex problems more quickly, there’s often a lack of fundamental prerequisites for making meaningful use of data input. Companies must ensure beforehand that data collection is fully digitalized and structured. Additionally, issues like data storage, data integration, data modeling, etc., must be set up in a future-proof manner for analytics solutions to be effectively utilized. Managers in Germany have recently recognized this, as indicated by their increasing willingness to invest in data, analytics, and AI solutions. Microsoft, without a doubt the leader among equals, announced its intention to invest more than 3 billion Euros in data centers, training, and other AI capacities in Germany.
How companies operationalize their data, which technologies and tools they use to derive value for their business, must be determined individually in their own analytics and AI roadmap. Most tech leaders, especially at the beginning of their AI journey, collaborate with external specialists to benefit from their best practices and implementation experience. From the initial Digital & Data Assessment to Architecture & Technology Reviews, all the way through to the complete development and rollout of analytics applications, we at Device Insight offer a wide range of support for our customers and partners.
Where do you stand now? What’s your data strategy? Which approaches do you seek to understand, compare, or test? Where are you encountering challenges? Let’s exchange ideas and insights. We’re eager to collaborate with you.
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