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Build a data platform that is ready for AI: start your journey with HSO
As Service Line Director Analytics at HSO International, Jasper Hillebrand works closely with customers on complex data issues. A topic that is only becoming more relevant and urgent, given the developments around AI, which is changing the data playing field at lightning speed. If you want to take advantage of available Microsoft AI tech, then accessibility, reliability and quality of your data is essential. According to Jasper, a operational, scalable data platform is therefore not an end point, but a journey. In this Q&A, Jasper explains what a data journey looks like and what it takes to make AI work for you.
Q: Jasper, can you explain why an operational data platform is a prerequisite for successful digital transformation, including AI?
A: "If as a company you want to make digitalization work for you, like optimizing processes, improving productivity or adopting new technology, like (Microsoft) AI, then a well-functioning, operational data platform is a prerequisite. Because the better you are able to manage and control your data, the better the outcomes of any change will be."
Q: And what do you mean with “data is a journey"?
A: "I like to compare the data journey to an expedition, think of climbing Mount Everest. You travel, well prepared and under expert guidance, from basecamp to basecamp. Each basecamp is a plateau, a certain level of maturity and expertise you have reached.
What you should realize is that a well-functioning data platform is never 'finished'. For example, the first basecamp level is that of an operational data platform. This allows you to deliver valid reports to the business, for example. But if you want to stay at this level or climb further, you must have the capabilities to keep your platform operational and to keep delivering.
We help our customers achieve this first level and build knowledge to deliver and grow further. We call the next basecamps governed data and valued data. And the higher up the mountain, the more value your data can add and, the more benefit you can get from AI."
Investing in Microsoft AI requires trust and partnership
Jasper Hillebrand, Service Line Director Analytics at HSO International: "What we want to avoid is that customers’ investments in AI don’t deliver value. This often happens with test projects, non-operationalized or non-scalable applications. We want to get customers to transform and deliver better results, but that involves a certain investment and trust.
Especially when it comes to AI, we cannot precisely define all outcomes and solutions in advance. After all, the world, people, companies and their needs keep changing at a rapid pace. However, we are confident that we can help our customers get started and get actual value from generative Microsoft AI tech."
Q: Many companies struggle with data in all kinds of different applications and systems, on-premise and in the cloud. How do handle that?
A: "What we see is that investments in a database and data platform are often considered as a kind of capstone, for example in the final phase of an ERP project. However, we say: start with your data engine instead. After all, we can solve a lot of complexity, independent of your ERP system or enterprise architecture, in the back-end.
It can make sense to significantly increase the investment in data and your data platform, compared to your ERP and CRM systems, because it simply delivers more value faster. Especially with the generative AI technology now available."
Q: What does the first basecamp entail?
"We operationalize and centralize all the data into a datalake, which we integrate with whatever ERP or business application. We ensure that the interface is an operational copy of the data in the CRM and ERP systems. Thus, we make you independent of the complexity of the enterprise architecture. We call this Data Initiatives."
"The big advantage is that data initiatives no longer start with a complex data request, but become short cyclical. First operationalizing your data makes your organization much more independent on the complexity of your ever changing enterprise architecture."
Q: In which Microsoft AI applications do you see the greatest opportunities?
A: "With our clients, we always strive for continuous development and continuous integration. Often reporting is the first deliverable and after that we work toward more advanced use cases, but all within a controlled framework of governance.
The biggest opportunities I see are in the area of productivity. Think of a sales manager who may have 15 accounts. If he can save 20% of his time, he might be able to manage 18 accounts. Or take Copilot in Github, which our developers use a lot. The research that has been done consistently shows a 50% increase in productivity."
How to increase data maturity?
Q: Still, I can imagine that many companies want to board this train, but are not sufficiently data mature. How can they get started with AI?
A: "It is true that many, even larger companies, are still relatively low on data maturity. From a trusted advisor role, we help our customers realize that first basecamp, including a continuous process of knowledge transfer and building out data capabilities.
Previously, AI was a discipline of going for the maximum achievable, 100% good outcome. This is changing. For example when we look at ChatGPT, we accept a certain margin of error. By and large, the technology, also the AI apps Microsoft launches, is 60 - 80% finished and then it becomes available. What is important to realize, though, is that automatically building that Power BI report with a simple voice command is not always as easy as you sometimes see in the marketing videos.
After all, if your data is hidden in your ERP system and some additional excel files, you can run Power BI with Copilot on that, but it's not going to deliver the desired results. The same goes for Copilot in Dynamics 365 Sales. The 'next best action' that Copilot generates is not going to work if your system contains thirty versions of the same customer."
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