Strategic planning will: Provide a description of the Business Needs. Summarize next level of digital transformation requirements, impact of digitalization on current and future business models, scenarios and systems. Outline the Proposed strategy and suggested services to achieve your organizational goals. Prepare financial forecasts and review marketing plans. Outlines the organization’s plans and objectives for realizing its transformation.
transformational analysis is a powerful tool that helps organizations identify, analyze and overcome organizational change requirements. The tools are specifically designed to address the rapidly changing organizational structure and tasks in a timely manner. In such a scenario, transformation requirements analysis helps the company make an informed decision regarding their future requirements and it also helps in designing a strategy that provides clear direction for the organizational movement. An effective implementation of ERP will help in improving present results and getting maximum returns on the investment made in the process. Organizations therefore, need to understand and analyze carefully their present scenario and design an ERP architecture that best suits their needs and provide maximum benefits.
Data migration involves changes in existing data structures or interfaces between systems and applications. ERP implementation requires smooth transfer of data from the current structure to the new structure. For transformation requirements analysis, data modeling is an important factor which plays a critical role. Data modeling is the act of creating a data model, a simplified version of the real data which describes the business requirements.
A data transformation process helps to build a standard database which can be used for all future applications. The application of data transformation requirements analysis focuses on requirements that are unique to each organization. This helps in better leveraging of available infrastructure and avoiding redundancy. The primary benefits of using a data transformation process include: Quicker implementation – With fast execution, companies are able to derive maximum benefit from their ERP system. Reduced costs – Using a data transformation tool reduces the cost involved in implementing the ERP system.
Data transformation languages help in migrating data from one source to another. ERP and data transformation tools can easily be combined. However, before starting the migration process, it is important to choose the most appropriate transformation tool for your organization. Common data transformation languages include Java, XML, etc, and PHP. It is best to migrate an organization’s data from current vendor based ERP system to a hosted Microsoft ERP system through a hosted software application.
ERP and data transformation tools include various steps including design of a data model, data transformations, evaluation of these transforms, usage of selected transformations and integration of these transforms into an ERP or EHR architecture. ERP and data transformation tools are divided into different categories according to the nature of work involved in each. While some transformations may require substantial IT investments, other transformations can be performed with minimum IT investments. Some of the common transformations include product development, inventory management, supply chain management, financial activities, human resources, distribution, and manufacturing.
Transformation requirements often depend upon the nature of business. For example, when a large scale company needs to transform its data sources, it would need extensive analysis. However, a medium scale company may only need to transform a part of its data sources. Smaller companies can perform simple transformations like converting email messages into text documents and converting telephone conversations into a database. Transforming business process data sources involves both hardware and software transformation tasks.
Implementing data transformation process needs to involve the whole team comprising all the employees concerned. Implementation should be planned well in advance to ensure successful implementation. Testing of ERP software is also very important to make sure that the ERP software as well as the ERP solution perform well during the entire data transformation process. It is very important for data analysts to understand the business process requirements thoroughly so that they can provide good solutions for customer organizations.