Many argue that by bringing IA tools and decision-making closer to the ground floor, businesses can access a wealth of benefits and create a more agile framework. However, there is never a one-size-fits-all solution and for some businesses a more centralized approach is necessary. The issue is that many businesses may continue to operate in a centralized model when in fact this is holding back their transformation from achieving true scalability. Could a decentralized approach to automation accelerate your transformation agenda by unlocking more tailored and insightful solutions, boosting employee engagement with change and driving innovation? Or is it just not right for you?

Join this fiery panel in debating the value and efficacy of decentralized automation:

• How do we balance the by-product of the flexibility of centralisation vs new approaches that facilitate domain driven environments?
• Scaling transformation by decentralising automation – does bringing automation decisions closer to the ground floor drive continuous improvement, innovation and agility?
• Identify the benefits and risks of citizen developers and data scientists
• Engage employees and drive your transformation agenda by involving the right people in your transformation
• Unlock the potential of your centralization model by assessing which tools businesses can leverage to optimize their model
• Find the right model for your business by assessing the effectiveness of decentralisation across different sectors – which sectors succeed and why?

David Castro-Gavino

Head of Data & Customer Analytics, Transport
Booking.com

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Join a leading data scientist in delving into this case study to illuminate how to deliver real-world value with your company’s data. Through the example of how he overhauled and optimised this pharma company’s operations, attendees will learn how to translate these successes across all industries and business models.

Join this talk to hear:

• Advanced techniques for modelling and forecasting demand
• Optimal operational design, sites/countries selection given costs & time constraints
• Data-driven re-projection and optimal adjustment of demand to increase probability to meet target
• Centralized statistical monitoring and detecting unusual data patterns
• Predicting events in event-driven trials
• Forecasting further operational characteristics