Enterprise Operating System (EOS)

Streamlining global and regional company processes and operations is crucial for success. Enterprises utilize Enterprise Resource Planning (ERP) and surrounding systems, but the selection and integration of these systems vary, creating a unique Enterprise Operating System (EOS). Our role is to aid in enterprise orchestration and optimization.

Enterprise software often requires specialists for the installation, configuration and implementation, whether it's an enterprise-wide solution or a local one. Across a company's entire process, various specialized systems are in place. Analytics play a crucial role in comprehending the overall process. Alexicon steps in to aid with company processes, system analysis, data, and analytics in the current state (As Is), working towards the desired To Be EOS.

This involves designing company processes with business and digital systems, formalizing data and models, preparing focused interfaces and analytics for users, and providing best practice work instructions.

Process

Manual, Systemized and Automated

Enterprise Applications

Business and Digital

Analytics

EDW Table Source (low frontend and middle code)

Data Management

Enterprise, Local and External Data (EDW and Data Lake)

Data Science

EDW, Planning, Forecasting, Simulate and Generative AI

Process: The way a Company operates (steps in selling, buying, making, staffing and more). There are manual, systemized and automated processes.
Enterprise Applications: There are many for most companies (e.g., ERP, CRM, MES | Digital, SCM and HR). Changes require Assessments and Planning, Team Formation, Data Migration, Customization and Configuration, Integration, Testing, Training, Go-Live, Hypercare and Continuous Improvement.
Analytics: Accesses EDW tables for contrasting and comparing data. Planning areas create data (forecasts, allocations and more).
Data Management: Integrates and formalizes EDW tables for Analytic use.
Data Science: Used in overall Company processes, Enterprise Applications and in Data Management to formalize tables for use in Analytics (Enterprise Users).

Smart Enterprise

Similar to our personal smartphones, companies possess applications, processing power (compute), and memory (storage). Transitioning between phones or altering hardware and software necessitates swift data migration. While a company might not actively monitor aggregated enterprise compute and storage metrics, the analogy holds true on a larger scale within both local and cloud landscapes, encompassing considerations of switching costs, operating expenses, and overall performance.

“IT Cloud Migrations” Area has many sub areas to consider including Cost Savings (e.g., it has seven key areas), Time to value (TTV), Scalability, Flexibility, Accessibility, Processing Power (Compute), Memory (Storage), Automatic Updates, Disaster Recovery and Improved Collaboration. Also, Security Concerns, Downtime, Data Privacy, Migration Challenges and Vendor Lock-In. All are considered in comprehensive migration strategies.

Enterprises revolve around two crucial temporal dimensions: 1) "Realtime," where connected systems collaborate, execute processes, and log Date Timestamps during operations. 2) "History," housing the recorded Date Timestamps. The Enterprise Data Warehouse (EDW) capitalizes on these timestamped events from Enterprise Applications and supporting systems to unify data based on shared enterprise time, master data, and other essential dimensions. Through this integration, the EDW transforms into a multidimensional data source, serving as a cornerstone for data provisioning and enterprise analytics.

Below is an example for a manufacturing company with three key Enterprise Applications:

A significant portion of data integration occurs during off-hours, although there is a transition towards increased Near Real-Time and Real-Time data processing.

Enterprise Software Applications (ESA) and User Landscape

Top Enterprise Application areas.

Enterprise Metadata (other Users) >

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.

Enterprise Operating System (EOS)

Enterprise Resource Planning (ERP) and surrounding systems: Customer Relationship Management (CRM), Supply Chain Management (SCM), Manufacturing Execution System (MES | Digital), 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.

Best Practice process focused Work Instructions.

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