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Here we share our unique perspective with the world. All things data, process optimization and AI, but always from the perspective of the employee and customer experience.

Latest Articles from Our Blog

How Predictive AI Improves OTIF Scores

Predictive AI models can significantly improve your OTIF scores in several ways:
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What data is captured for OTIF Scoring?

Yes, I'm sure you're already accounting for OTIF, but are you factoring in everything?
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(OTIF)On-Time In-Full FAQ

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Why On-Time In-Full (OTIF) is Your Key to Success in 2024

As we warmly welcome 2024, the logistics industry is poised for a significant transition – the shift towards stricter On-Time In-Full (OTIF) standards. If you're a CIO, this shift ...
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The Shift from Time to Quality in Process Optimization

In the past decade, the focus on productivity and process optimization has become paramount across various industries. As professionals, we strive to make the most of our time and ...
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Case Study

OTIF Scoring: Putting it all together

Combining a Unified Data Platform, Robotic Process Automation (RPA), and Artificial Intelligence (AI) to improve On-Time, In-Full (OTIF) scoring can be seen in the case of a company that used a bot-building platform to overcome challenges related to data consolidation across production, inventory, and sales.

 

JasperArt Jan 25 (4)

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Definitions and general information

Overview of concepts and industry jargon.  

Integrated Data Platform

An Integrated Data Platform is a comprehensive solution that combines various data sources and tools into a single unified system. It enables businesses to efficiently manage, analyze, and derive insights from their data. By integrating different data sets, such as structured and unstructured data, it provides a holistic view for informed decision-making.

Semantic Model

A Semantic Model is a representation of data that captures the meaning and relationships between different elements. It provides a structured framework for organizing and understanding data, enabling more effective analysis and interpretation.

Information Architecture

Information Architecture is the practice of structuring and organizing information to make it easily accessible, intuitive, and user-friendly. It involves designing navigation systems, categorizing content, and creating clear hierarchies to optimize the way users interact with information and navigate digital interfaces.

Process Discovery

Process discovery is a systematic approach to understanding and documenting existing workflows within an organization. It involves analyzing data, interviewing stakeholders, and mapping out activities to identify inefficiencies, bottlenecks, and opportunities for improvement in order to streamline operations and enhance productivity.

Process Mining

Process mining is a data-driven approach that extracts knowledge from event logs to visualize and analyze real-time processes within an organization. It enables identifying inefficiencies, bottlenecks, and opportunities for optimization to enhance operational performance and drive continuous improvement.

Task Mining

Task mining is a data-driven approach that captures user interactions and analyzes them to understand how people perform tasks on their digital devices. It enables organizations to identify inefficiencies, streamline processes, and improve user experiences through actionable insights gained from the analysis of task-level data.

Intelligent Automation

Intelligent automation, also known as Hyperautomation by Gartner, is a disciplined approach where organizations rapidly identify, assess, and automate business and IT processes using advanced technologies like AI and machine learning. It aims to streamline operations and enhance productivity.

Augmented Automation

Augmented automation combines artificial intelligence and advanced automation technologies to enhance and optimize business processes. It leverages AI algorithms, robotics, and machine learning to streamline operations, increase efficiency, and improve decision-making, ultimately driving digital transformation and organizational growth.

Applied AI

Applied AI refers to the practical implementation of artificial intelligence technologies in real-world scenarios, where algorithms and machine learning models are used to solve specific problems and enhance decision-making processes across various industries and sectors.

Generative AI

Generative AI is an advanced technology that uses machine learning models, such as Language Models (LLM), to create original content, such as text, images, or even music, by analyzing and learning patterns from existing data. It enables the generation of new and creative outputs based on the learned knowledge.

Data and AI Governance

Data and AI governance refers to the framework and practices that ensure responsible, ethical, and secure management of data and artificial intelligence technologies. It involves creating policies, procedures, and safeguards to protect privacy, mitigate bias, ensure transparency, and promote accountability in data-driven decision-making.

Responsible AI

Responsible AI entails the ethical development and deployment of artificial intelligence systems, prioritizing transparency, fairness, accountability, and privacy. It involves mitigating bias, ensuring safety, and promoting the positive impact of AI on society.

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