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The future interplays between design thinking, technology and AI

Paul Hobcraft

This shift has prompted innovation to develop tools and design approaches that support these changes in several critical ways based on four global aspects: Learning from real-time data : Traditional analytics models and past performance data may not be entirely relevant in today’s ever-changing business landscape.

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Recognizing the value of innovative interplays for design thinking impact.

Ecosystems4Innovating

Machine Learning and AI-Driven Insights : Integrating AI and machine learning into the Design Thinking process can provide valuable insights. For example, AI can analyze large datasets of user feedback to identify patterns and trends, guiding designers in making data-informed decisions.

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Barriers to innovation, the cause and effect.

Paul Hobcraft

I am on a personal mission to convince innovation software providers, corporations and innovators to change how they undertake innovation. We do need to recognize innovation carries more risk and uncertainty and should have a much “higher share of voice” in the organization for constant awareness, engagement and being informed.

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Smart Factory 101 A Data, AI, Cloud and Workforce Revolution in the Making

Acuvate

With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Combined with machine learning and advanced analytics, AI allows smart factories to evaluate data, forecast outcomes and failures, control downtimes and maximize output.

Data 52
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Smart Factory 101 A Data, AI, Cloud and Workforce Revolution in the Making

Acuvate

With the help of IoT, equipment, devices, and systems may exchange and monitor data in real time through improved connectivity. Combined with machine learning and advanced analytics, AI allows smart factories to evaluate data, forecast outcomes and failures, control downtimes and maximize output.

Data 52
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Data-Driven Approaches Helping Public Sector with Sustainable Water Management

Acuvate

Industrial IIoT, in particular, in the form of sensors, flow meters, and edge devices, are being used to collect on-field data to create situational awareness and identify leaks, sewer overflows, and faulty equipment before these require costly repairs. No data governance.

Data 78
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Top 10 CPG Industry Trends For 2020

Acuvate

Despite the increase in sales across CPG categories, top CPG brands witnessed a decrease and the cause has been cited due to increased fragmentation of customer preference for private brands. Millennials prefer private labels over national brands due to their cost effectiveness. Using Big Data and Advanced Analytics.

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