2.0 Business Process

Capture the business process that the application supports . This can be describe through a process diagram or a business capability model.

Old Situation:

MS ACCESS was required to generate different lists based on the PRS data. Those lists were manually sent by mail by General Counsel to different recipients (till end 2023) and most recently it was part of reverse TSA tasks which has been stopped end of June 2024.

Reports were sent to different stakeholders for different departments:

• Sustainability (ESG reports)
• Legal
• Industrial Function
• Internal audit
• Risk Insurance.

Today this task has been transferred to GBS Finance SL. But exist some issues to transfer this process such as:

• MS ACCESS licenses is not provided today to users from FSL
• No Knowledge about MS ACCESS and how to generate the required queries
• Current process not fitting with the simplification objective of the group.

So it was requested to create one single report containing all required information from PRS and available for all the different stakeholders. This would replace the manual work to generate different export to excel + sharing by mail and reduce the  dependency of the availability of persons doing the extraction (self-service like). In terms of landscape, it will avoid users to also have to request the Microsoft Access which is not included in our standard working tool (licenses).

Also it's an opportunity to have one "single source of truth" list.

2.1 Challenge/Opportunities

Clearly articulate the specific problem or opportunity that the application is addressing within the business by leveraging from data. This should be a concise and well-defined statement that captures the essence of the challenge or opportunity that the application is trying to solve by providing insight from the data. 

3.0 Application Feature Overview

Information about the existent features in the application.

4.0 Business Objects

This section should contain a table with the business objects used in the reports with links to the business object definition in LeanIX.  The purpose is to ensure that all DA&AI Products adhere to a centrally maintained list of business objects and definitions to allow us to achieve our digital ambitions.  For any questions about business objects and LeanIX, contact Data Governance or the Enterprise Information Architect.

5.0 Functional Specification

5.1 Dashboard 

if already existed put the link to the wiki page of the user documentation 

5.2 Data Input

1. Data Sources (including the nature of the data and what is it needed for)
1. Business data (actuals, facts, customer data, transactions…)
2. Reference data (hierarchies, lookup tables… )
2. Transformation Rules (for each of the data source in the previous point)
1. Extraction rules and filters
2. Exception handling rules (how do we handle when data does not come in the format we need) 
3. Enrichments (normally joins) 
4. Aggregation rules

5.3 KPI's Definitions 

5.4 Visualization

• Additional Information

For this report we have the following worbook available:

4.0 Business Objects

TFor this application we have all the fields in this mapping file:

5.0 Functional Specification

5.1 General Data/Calculations 

For these reports, it’s important to understand some concepts which will allow the user to work with the reports and analyze the data.

5.2 Process Detail 

5.2.1.  Report/Process Definition 

SAP BW High level view 

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6.0 Non-functional Descriptions 

6.1 Usability

The solution prioritizes usability to ensure that users can easily navigate and interact with the workbook, making it intuitive to learn and use effectively. Key functionalities, like filtering and data extraction, are designed for simplicity and ease of recall. 

6.2 Regulatory Compliance

The Maintenance Dashboard complies with Solvay’s regulatory standards, including GDPR and other relevant data protection regulations, to prevent unauthorized access and misuse of customer data. Access is strictly granted to authorized users only, ensuring that compliance requirements are met for data confidentiality and integrity.

6.3 Security

To maintain security across the solution, data encryption is implemented to safeguard against unauthorized access and malware threats. Only authorized administrative users can create and manage user access privileges, ensuring secure data handling and restricted access based on user roles. Maintenance data is split between SCO and ECO, and users have access only to data pertaining to their assigned entity.

6.4 Performance

The solution is designed for high performance, ensuring swift response times during user interactions. Background processes, such as data transfers and backups, are optimized to occur seamlessly, with minimal impact on the user experience. The dashboard and workbook data loads are configured to handle the current user base effectively, providing a fast and efficient experience even during peak usage.

6.5 Reliability

Reliability is essential for consistent operation, and the system is designed to function without interruptions under standard conditions. In cases of refresh delays or failures we can have some alerts but normally is managed by ticket.

6.6 Scalability

The solution is built to be scalable, able to accommodate growth in users, transactions, and data volume. It can handle several users per month.

6.7 Compatibility

Compatibility with other systems is ensured through seamless integration with external data sources and applications.

6.8 Availability

To support continuous business operations, the system maintains high availability with a Service Level Agreement (SLA) of 99% uptime on weekdays, between 09:00 and 18:30 CET. This schedule aligns with business hours, ensuring that the system is accessible when users need it most, with regular maintenance scheduled outside these hours to minimize disruptions.

6.9 Refresh of the Data

The loads of the report are daily at XXX confirm with the technical colleague.

5.1 Advanced Analytics

if already existed put the link to the wiki page of the user documentation 

5.2 Data Input

• Data Sources (including the nature of the data and what is it needed for)
  • Business data (actuals, facts, customer data, transactions…)
  • Reference data (hierarchies, lookup tables… )
• Transformation Rules (for each of the data source in the previous point)
  • Extraction rules and filters
  • Exception handling rules (how do we handle when data does not come in the format we need) 
  • Enrichments (normally joins) 
  • Aggregation rules

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• If data is sourced from the data ocean, the Multidimensional modeling of the data at conceptual level including fact and dimension tables to be captured or the link to the documentation of the corresponding data mart to be provided. 

5.3 Pre-processing 

Includes the details of the operations performed on the raw data to the data set that is useable for analytics. Data Cleaning, Data Reduction, Data Transformation, and Data Integration are types of preparation tasks. 

5.4 Modelling 

Analytics type: Identify and list the key features or functionalities that the application offers. These could include recommendation systems, predictive analytics, natural language processing, image recognition, etc. descriptive, prescriptive, predictive,..

End to end pipelines:  Procedures and calculation steps to make the advanced analytics pipelines 

Algorithm: Machin learning algorithms,  data mining techniques, mathematical modeling used for each step (high level). It can include the type of model (e.g., regression, classification, neural network), the algorithm used,

Data flow: Input and output of each step 

5.5 Results 

User flow:

If applicable, use diagrams or flowchart tools to create visual representations of the user flows. Start with a high-level overview of the flow and then drill down into more detailed flows for specific tasks or features.

If applicable, indicate where users provide input to the machine learning model. This could involve uploading data, entering text, making selections, or interacting with visualizations.

If applicable, consider how user feedback or actions can impact the machine learning model or the user flow. For example, if users can provide feedback on model predictions, include this in the flow.

Output:

 Capture where the machine learning model provides outputs or results to users. This might involve displaying recommendations, predictions, insights, or visualizations generated by the model.

6.0 System view (Architecture)

The purpose of this part is to describe the physical components that supports the functionalities of the product. From that point of view, this part should capture and visualizes the physical components of the data products such as backend, front end, data providers, libraries for ML models, etc. 

7.0 Non-functional Descriptions 

7.1 Usability

Usability is about the ease with which a User can learn to start using the solution and the ease with which they can use the system.  In addition to ease of learning and ease of use, usability also includes areas such as ease of recall, error avoidance and handling, accessibility among others e.g., 99% of metadata entry Users who have use the Maintenance Dashboard should be able to change filters, extract etc., when required.  Maintenance data will be centrally stored in the Google Cloud platform, which will be available to other applications e.g., and Dashboards if needed.

7.2 Regulatory Compliance

Software systems must comply with legal and regulatory e.g., GDPR requirements, this can change depending on country, organisation industry and / or region.  The software systems must be secure from unauthorized access.  The Maintenance Dashboard will comply with Solvay’s regulations and compliance e.g., access only granted to authorized Users.

7.3 Security

Security refers to essential aspects that assure a solution and its components will be protected against unauthorized access or malware attacks.  Important considerations related to security aspects of a system are User authentication, User authorization or User access privileges, data theft, malware attacks, data encryption, and maintaining audit trails, e.g., only Users with administrator access shall be able to create new accounts and assign data access privileges to the new accounts e.g.,

• All data will be encrypted in the dashboard
• Only authorised Users / Administrative Users will be able to access data.
• Maintenance data will be split between either SCO or ECO, and Users will only have authority to one Entity data.

7.4 Performance

Performance defines how fast a software system or a particular section of it responds to certain User actions under a certain workload.  In most cases, this metric explains how long a User must wait before the target operation happens e.g., the page renders, a transaction is processed, etc., given the overall number of Users now.  Performance requirements may describe background processes invisible to Users, e.g., backup and speed of data transfers. 

7.5 Reliability

Reliability is the ability of a solution or its component to perform its required functions without failure under predefined conditions for a specified time / period.  Reliability can possibly be specified in terms of average time system runs before failure occurs, percentage of operations completed successfully within a time / period, maximum acceptable failure probability, or number of failures within a period.  Reliability aspects are in reference to (but not limited to) evaluation of the system to be considered as reliable, classification of reliability defining failures vs. regular failures, and the impact of failure on business operations.  The Maintenance Dashboard will display data from the previous refresh of data.   

7.6 Scalability

Scalability refers to the degree to which a solution can evolve to handle increased amounts of work.  The increased amount of work could be in terms of the user base, transactions, data, network traffic, or other factors e.g., the system should be able to handle an additional load of a maximum of 5,000 Users every month for the next 6 months without any noticeable performance impacts.  

7.7 Compatibility

Interoperability is the degree to which the solution is compatible with other components.  It is a measure of how effectively the system interoperates with other software systems and how easily it integrates with external hardware devices.

Interoperability aspects to be discussed during elicitation are in reference to (but not limited to) software systems to be interfaced with along with data / messages to be exchanged and any standard data formats, hardware components to be integrated with, and any standard communication protocols to be followed e.g., Order Management system will push the order file into a secured file transfer protocol server from where it will be loaded into the system through a daily job.  To guarantee between Google Cloud platform and SAP BW Queries e.g., BW_QRY_MVPMOR01_0002, Solvay has introduced a new tool called Xtract (Xtract).

7.8 Availability

Availability is the degree to which the solution is operable and accessible when required. It is a measure of time during which the system is fully operational e.g., available for use and sometimes included as a Service Level Agreement (SLA) considering its criticality to the business, e.g., the system shall be at least 99% available on weekdays between 09:00 to 18:30 Central European Time (CET).

7.9 Refresh of the Data

Frequency, data, and time of the data refresh in the data product.