What do you do if your ERP implementation is facing data migration challenges?

In addressing ERP data migration challenges, analyze the current data migration process suitability for the data volume and cleansing needs. Ensure that the tools used are optimal for these tasks. Assess whether the team has adequate training to handle the migration effectively. Additionally, consider a phased migration approach to troubleshoot issues incrementally and confirm the integrity of data at each stage.

Not having an effective data strategy and trying to take all data from all legacy systems. The transformation program should not be seen as the panacea for all your legacy data issues or even worse to ensure that you are GDPR compliant. Take the minimum amount of data to run the business processes and please don’t ask the business how much data they require as they will always say "everything" so take the lead. Also ensure that you have an effective long term data strategy for the remaining legacy data. This could be to migrate the data into a BI data warehouse, migration in to a SQL server you may even decide to leave the data on the current system as read only BUT have a strategy / plan, even Baldrick from Blackadder had a plan…….

Before migrating data, assessing its quality, volume, and format is critical. Identify and correct errors like duplicates, inconsistencies, or missing values to ensure data integrity. Estimating the volume and migration duration is vital for planning. Moreover, verify the compatibility of your data with the new ERP system to avoid integration issues. Conversions or transformations may be necessary for compatibility. Thorough data assessment aids in effective planning, helping to mitigate risks and prevent complications during the migration process. This preparatory step is essential for a smooth transition.

Before migrating data, assessing its quality, volume, and format is critical. Identify and correct errors like duplicates, inconsistencies, or missing values to ensure data integrity. Estimating the volume and migration duration is vital for planning. Moreover, verify the compatibility of your data with the new ERP system to avoid integration issues. Conversions or transformations may be necessary for compatibility. Thorough data assessment aids in effective planning, helping to mitigate risks and prevent complications during the migration process. This preparatory step is essential for a smooth transition.

Make the data migration a dedicated sub-project and assign an experienced project manager. Make sure to align about the critical path. Which data MUST be there at go-live, which (historical) data can be migrated at a later stage and which data has no use anymore. And don't forget that sometimes it's a good idea to migrate some data manually. That helps in cleaning up.

Avalie as funcionalidades oferecidas pelas ferramentas em termos de extração, transformação, carregamento, validação e monitoramento de dados. Certifique-se de que elas atendam às suas necessidades específicas de migração de dados e ofereçam recursos avançados, como detecção e correção de erros.

Extração: Nesta etapa, você extrai os dados dos sistemas legados de onde serão migrados para o novo sistema ERP. Isso pode envolver a identificação das fontes de dados, a seleção dos dados relevantes e a extração dos mesmos de forma eficiente e segura. Transformação: Após a extração, os dados geralmente precisam passar por transformações para atender aos requisitos do novo sistema ERP. Isso pode incluir limpeza de dados, padronização de formatos, conversão de valores e enriquecimento de dados, entre outros processos. Carregamento: Uma vez que os dados foram extraídos e transformados, eles são carregados no novo sistema ERP.

Make sure that the methodology includes intensive testing & validation. Precisely define the validation types and steps: a) Accuracy: Is the data correct? Use lookup tables or reference data to verify information product codes. b) Completeness: Are all the necessary/mandatory fields populated? c) Consistency: Check for uniformity (for example formatting of phone numbers). Define clear formatting standards for all data elements. d) Uniqueness: Have all records the correct unique identifiers? Identify and eliminate duplicate records. e) Business Logic: Can you transact successfully with the data, and do you get the expected outcome?

Considero muito importante contruir a migração em ambiente DEV (Desenvolvimento) e depois QAS (Qualidade), se ocorrer tudo bem em ambas, é um bom sinal para fazer em Produção, importante mapear pontos de atenção, como saldos financeiros entre contas e quantidade em estoques.

Data consistency, missing values, and duplicate records lead to data quality issues in the targeted system. To overcome these challenges, perform thorough data profiling and analysis before the migration. Identify and clean up any data anomalies, ensure data is accurate, complete, and consistent.

Start very early with the Data Migration efforts. It takes a lot of time to: a) Clean up the data b) Define data extraction and transformation rules c) Validate & test the migrated data