On Generative AI Investments. Q&A with René Haag

Q1. You published recently a study developed with HFS Research to help organizations understand the value they can derive from their generative AI (GenAI) investments. What are the main take aways from this study?

Like all new technologies or business processes, the Clients need to make sure to put the right foundations in place. With AI – as stated in the Study- the adage “garbage in, garbage out” never becomes truer as with this technology. AI learns and evolves from data input and uses this to build the outcomes. So one of the key takeaways from this study is the importance of Data for a successful AI Implementation and furthermore, the expected outcome of AI driven processes will only appear with the right Data Foundation.

Q2. One-third of executives in this study believe less than half of their organization’s data is actually consumable. What does this mean in practice? 

The good news here is that the value of data has become a key role in the executive’s mindset and is part of the planning for a successful business. In practice it means that companies who are considering data as part of their value chain, gain more and better out codes of their business results. When it comes to digital transformation and of course the implementation of AI, there is still a way to go for the companies but as stated in the study, with the right approach and the change in mindset on all levels, it will bring a lot of value.

Q3. What is your definition of a proper data foundation that can help real-world business to generate good data quality outputs?

Understand your data! At Syniti we have a simple approach behind our successful data initiatives with our Clients. “Let the data tell the story”. As every other project, you first of all need to understand where you are in your journey. After that, using the right tools, like our Syniti platform, and more importantly a change management initiative to understand and focus on data, will generate the output required to support business transformation.  .

Q3. Is Syniti able to help overcoming the challenge of data bias? If so, how?

Absolutely. That’s part of what we do on a long term basis for our clients. It all starts with the definition of a common understanding of data on a global basis. For example salutations: Given the diversity in our society, we need to define rules on how we want to interact with employees, clients, vendors…. This rule needs to be defined and executed on the data level, so that the AI process (for example, a Chatbot can use the right salutation based on different data inputs). Of course we can add local requirements to that but the principles behind need to be defined and enforced.

Q4. Syniti’s CEO is advocating a Data-First Approach To Digital Transformation. What does this mean in practice? Why does it matter?

Usually, the legacy data will be touched the first time, when it comes to the Data Migration. At this point in time the companies have already gone through a lot of effort and decisionmaking regarding the new Template & Processes. Very often the companies need to invest additional time and effort as soon as they try to transform the legacy data into the new standard, one key reason for project delays and overrun of budgets. With Data First, we include the legacy Data from Day one and can reduce effort, ease decision making and secure the transformation within Time & Budget.

Q5. To quote Syniti’s CEO: “Digital transformation requires data transformation.” Can you explain why?

First of all I would like to clarify the term Transformation. As already mentioned, the lift and shift approach is in our view not a transformation. It is a technical approach to move the legacy World into the new digital World. This approach will bring only very little improvements to the business, as the processes and the Data will stay nearly the same. If the aim of the company is to transform their Business, improve their business processes and improve their business outcome, this -in our view- is a Transformation. And to secure the expected outcome of new Business processes and gain the improvements of a Digital Transformation (and of course of AI), it is required to transform your Data to a “Business Ready” state, which requires Data Quality, Data Harmonization and more.

Q6. Can you give a short explanation of Syniti’s silo-free enterprise data management approach?

The Syniti Knowledge Platform (SKP) or maybe better known in the Region as SAP Advanced Data Migration & Management (ADMM), is a single Platform to support the whole Data Lifecycle. It contains Solutions like Data Rightsizing, Data Assessment, Data Migration, Master Data Management and more, just in a single Platform. Each part can be used in a modular approach but all modules are integrated. That means, wherever our clients are in their Data Journey, we can support their actual initiatives and re-use the knowledge for each upcoming step in the Data Journey. We call it Knowledge Capture & re-use. One reason why we can improve and streamline Data Initiatives and Transformation Projects at any scale.

Q7. Anything else you wish to add?

It doesn’t matter if you consider Transformations, AI Implementation, Reporting, Business Process Improvements or any kind of Business Initiatives. All of these topics come back to Data. Only if the Data foundation is ready to support these, the companies will receive the expected outcomes. Data First, will help to design and improve these initiatives, reduce the efforts to implement and most important, will secure the outcomes.

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René Haag is VP of Sales MEE (Central and Eastern Europe) at Syniti. His focus is on data migration, data integration and data governance. Before joining Syniti, Haag was an independent consultant in the SAP environment and held management positions at Qlik, Magnitude Software and CDQ in Switzerland, among others.