Artificial Intelligence (AI) Policy

We follow ethical Business and Data Science practices. Artificial Intelligence (AI) is a subset of Data Science. AI assists people with automation and data intelligence. We assist Companies with "Enterprise Operations" to improve efficiency and effectiveness. AI provides businesses new insights, automation and methods. Assisting Management, Associates, Customers, Suppliers and Communities.

Currently, Large Language Models (LLMs) are popular. Alexicon first tested Natural Language Processing (NLP) software in the late 2000’s. The goal was to upload bulk text data to get an "Executive Summary" of everything or search. LLMs today have achieved the goals needed then. They are quick to consolidate and display concise information, in an Executive Summary format, based on loaded data.

We focus on business benefits to organize text, dates, time and numerics for systems, data models and analytics using available Data Science areas. For Human Machine Interfaces (HMIs), Operational Technology (OT) and the Industrial Internet of Things (IIoT), we use the same policy. Assisting with Data Science and advancing Management and Associate skills.

Data Science >

Enterprise. Orchestrated.

Enterprise Operating System (EOS)

Enterprise Resource Planning (ERP) and surrounding systems: Customer Relationship Management (CRM), Supply Chain Management (SCM), Human Resources Management System (HRMS), Information Technology Service Management (ITSM), other COTS and In-house Built Applications.

Integrated Applications and Analytics.

In-house and Cloud Planning, Migrations and System Operations.

Process focused Work Instructions.

Leverage a Data Dictionary and "Metadata" for the Enterprise to assist with planning software applications and the data landscape.

Enterprise Metadata >

Process

Enterprise Business Processes and Technical Processes for Systems and Data.

Align key processes across the Enterprise to achieve optimal performance. Sync Enterprise Applications and Analytics.

Time intelligence speeds operations and provides clear communication with Associates, Customers, Partners and Suppliers.

Formal Lean Six Sigma or streamlined methods and techniques.

Define, Measure, Analyze, Improve and Control

Statistical Process Control (SPC): Run Charts, Control Charts and Design of Experiments

Gain the process advantage and include learning in the EDW and Data Lake.

Analytics

Enterprise Visualizations, Dashboards and Reports.

Data Science

Leverage Desktop Excel, SQL, R, Python and Scala code. Hyperscale activities.

Integrate Data Science activities in the EDW for Enterprise-wide computations.

Data Mgmt.

Enterprise Applications, Other Data, EDW and Data Lake.

Data Roadmap >

Enterprise Operating System (EOS)

Process

Analytics

Data Science

Data Mgmt.

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