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Unraveling Digital Transformation: A Pragmatic Approach for Business Success

In a rapidly evolving digital landscape, the practical application of data and the adoption of a pragmatic approach to digital transformation are becoming increasingly vital for organizations. Guido van den Boom, Digital Transformation partner at Xebia, and Rens Dimmendaal, Principal Data Scientist at Xebia, share valuable insights on breaking down digital transformation into manageable pieces and delivering tangible value quickly. This article explores the key themes of data analytics, artificial intelligence, machine learning, and data security, showcasing the expertise of van den Boom and Dimmendaal in navigating the big data landscape and driving sustainable growth and innovation in the digital era.

Van den Boom is quick to set the scene:
“At Xebia, we do not believe in megalomaniac digital transformation programs. These are often too complex to succeed because they simultaneously intervene in every aspect of an organization. Breaking up a transformation into manageable pieces and delivering value quickly has a greater chance of success. For example, in the field of Data.”

Harnessing the Power of Data: The Shift Towards Pragmatic Transformation

Industry events, such as the Data Expo at Jaarbeurs Utrecht, are often centered around themes, such as data analytics, artificial intelligence, machine learning, data security, and the practical application of data across industries. In line with these focus themes, van den Boom emphasizes the significance of 'splitting up' data.

He notes, "Data, particularly with the emergence of GenAI, is a hot topic, especially when combined with scalability and companies' desire to implement data platforms. Consequently, we are witnessing a growing emphasis on data quality, which was previously neglected. Only with proper data management can organizations fully harness the benefits of Business Intelligence (BI) and Artificial Intelligence (AI)."

Generative AI: Opportunities and Caution in the Business Landscape

Rens Dimmendaal, who is responsible for AI at Xebia, discusses the potential of generative AI for organizations.

He explains, "Generative AI complements predictive AI by enabling AI to create text and images, including website and app copy, images, and even videos for recommendations and predictions." Dimmendaal highlights the vast opportunities this presents but also cautions about the associated risks, comparing it to having a new tool that may lead to unrealistic expectations for rapid implementation within organizations.

Concrete Use Case: Smart AI Application for Major Banks

When asked about a concrete use case, Dimmendaal talks about major banks. “The major banks have countless business customers. Account and risk managers want to know what is happening with those customers. These customers are active worldwide and have all kinds of branches.” This makes the flow of information immense, even with subscriptions to specific news services. “A normal person cannot read everything, let alone check it.”

An AI tool can do that. More importantly, such a tool scans, filters, and categorizes what is there to process that information. “We use AI to scan all articles and news. By having AI interpret the content, it is possible to filter what is important for major banks to know. Moreover, we can summarize information into a few lines on which account managers or risk managers can act immediately to mitigate risks,” says Dimmendaal.

Xebia is the builder of such an AI tool, so it is the best point of contact for all the necessary insights. In addition, the company would like to train organizations such as major banks. “We think about where in the organization AI tools add value. And we organize workshops to help customers get through the thinking process more quickly. In many cases, AI makes work cheaper and faster, but is it always better?” Dimmendaal emphasizes that this critical mindset is important to successfully use generative AI, for example. “If it is 100x cheaper, but also 1 to 10% less good, then you want to be very critical of how and where you use it or not.”

Pragmatic Innovation: Xebia’s Approach to Transformations

Both van den Boom and Dimmendaal emphasize the importance of a step-by-step approach focused on concrete use cases such as with major banks.

Van den Boom elaborates on Xebia's approach: "At Xebia, we work on transformations from 6 Service Lines: Transformation, Software Technology, Cloud, Data, Lowcode, and Microsoft. Moreover, many of our consultants also serve as trainers; all trainers are consultants anyway. Knowledge sharing is one of our core values, and that is why we always assist our customers in building their capabilities. We operate with a pragmatic mindset. An increasing number of companies are establishing a data platform to consolidate all their company data. In the past, this typically involved lengthy multi-year projects, such as developing a data warehouse (DWH), followed by initiating business use cases. However, this traditional approach is outdated. Instead, we construct the data platform based on specific use cases, focusing solely on the necessary data objects. This enables us to deliver tangible business value directly into production swiftly."

This approach is demonstrated by the solutions Xebia has developed over the past year to bring GenAI models to production. One example is the GenAI Platform. This MLOps (Machine Learning Operations) platform is tailored to build Gen AI-powered applications, manage the complete model lifecycle models, and integrate the solutions into existing infrastructure. 

Wrapping It Up

As highlighted by experts like Guido van den Boom and Rens Dimmendaal, success in digital transformation lies in adopting a pragmatic, step-by-step approach focused on delivering tangible value. By embracing innovation while remaining critical of its implications, organizations can position themselves at the forefront of the data-driven revolution, driving sustainable growth and innovation in the ever-evolving digital era. If you are interested in learning more about taking GenAI Models into production, please reach out to us. We're happy to explore the opportunities with you.

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