You're transitioning to a new ERP system. How can you ensure data integrity during the migration process?

Some strategies to maintain data accuracy, completeness, and consistency: 1.Data Validation: Before migrating data, thoroughly validate its quality. Identify inconsistencies, duplicates, and errors to address them proactively 2.Error Management: Continuously monitor data during migration. If any issues arise, promptly identify and correct them to prevent data discrepancies 3.Methodical Approach: Inspect, extract, cleanse, and transform data from various sources before importing it into the ERP system's database 4.Stakeholder Support: Involve relevant teams in the migration process. Dedicate a team to analyze, migrate, and validate the data 5. Start Early: Begin the migration process early to avoid delays in ERP deployment.

É importante fazer um mapeamento detalhado de todos os processos existentes. Isso ajudará a entender quais deles deverão migrar para o novo sistema e quais são desnecessários. Este mapeamento ofertará visibilidade sobre quais dados serão relevantes para receberem a tratativa de limpeza. Também permitirá o entendimento dos recursos necessários durante a migração e pós.

The 3 big buckets of data have to be cleaned and the attributes mapped. 1) master data - objects such as customer, vendor,bom etc. - preferably use MDM 2) transaction data - preferable to only load open/current transactions only 3) documents in the data base - pdf, engineering documents etc Ideally there should be a SME for each object and added to the master plan Also; the newer ERP systems usually have a discrete objects and schema compared to legacy so the object and attribute mapping is critical from architecture perspective.

This point cannot be stressed enough, you can't just move or migrate data - you MUST CLEAN it first. Otherwise, you'll be in a garbage in-garbage out scenario. Companies spend so much money on ETL Tools without Investing in their DATA FIRST. To me, and I know it sounds biased, but its the reason why I left my comfy job to do what I do now - because Data Integrity is KEY. Without Clean Data, you won't get any good outcome or ROI on your future investment in AI, Automation, or RPA. Good AI, needs GOOD Data. Good Migration can only be good if the data was cleansed and organized to meet your business requirements and needs.

The data validation ensures to get rid of duplicated data and inaccuracy while guaranteeing uniformity. Moreover, standardization is carried out by putting similar data formats and terms that match new ERP system. Also, you are tasked to cleanse up any undesired repeated entries which may impede proper management of organizational information from records. Data validation guarantees the removal of duplicated data, accuracy correction as well as consistency maintenance. Data Validation: By deleting duplicates, correcting inaccuracies and ensuring uniformity in it. Standardization: Aligning with the new ERP system requires standardizing formats and terminologies in data

This will be achieved by careful planning and understanding which data is to be migrated. Open items or not. Use this as an opportunity to deep clean your data, decide on the cleanse criteria and cut deep. Set out your success criteria by setting up a process of reconciliation from old to new.

Garbage in garbage out. Based on experience, make sure to have a task breakdown for data cleansing, monitor regularly the progress and make sure client is validating every step, from pre-migration to post-migration. Client reconciliation must be conducted and sign off must be secured before continuing the project.

Of course, testing is an ongoing process in the migration journey, not a one-time event. To ensure a seamless transition and preserve data integrity in the new ERP system, a comprehensive testing plan is crucial. This plan should encompass various stages of the migration, enabling prompt identification and resolution of any issues that may arise.

Indeed relying on a small sample is a recipe for disaster. Test early, test often and utilise large and varied data samples and ‘listen’ to the results they provide. If you come up with little or no errors, your sample isn’t large enough. Don’t attempt to cut corners with problematic data, if you do you’ll run into trouble ahead. Data cleansing is hard but necessary work.

In my history I've run several mocks ... and as many as 10, 11 ... Successful go-live and post mortem proved and supports this practice. Why add or more importantly introduce needless risk.

Test and monitor (reconciliations). Repeat as necessary. Do not get lured into tempting shortcuts because in the long run they rarely pay dividends.

It is critical (practically mandatory) to have a separate test environment where testing can be conducted without affecting the target environment. This allows multiple tests to be run without affecting production performance and protects against errors in the extraction and transformation of the source data affecting the target ERP environment.

1. Enabling audit logging within the ERP system to keep track of all data migration activities. This includes who initiated the migration, what data was migrated, when it was migrated, and any changes made to the data. If an issue arises, the audit trail provides a detailed record to help trace the problem back to its source. 2. After the migration, conducting regular reviews of the migrated data to ensure it remains accurate and consistent. This can involve comparing a sample of migrated data against the original data to check for discrepancies. For instance, if financial data was migrated, a post-migration review could involve reconciling account balances and transaction histories between the old and new systems.

Set up some dashboards allowing easy and quick data refresh to track the volume of migrated data, this way you can monitor the progress with all the project team and stakeholders. Establish some basic quality checks that can be displayed on the dashboard as well. You're likely to have more detailed specific checks for each data set to validate the transfer, however it's useful to visualise the status, so that you can highlight or escalate the issues during stand ups.

Es wird oft Unterschätzt, welchen Wert der Aufbau eines Datawarehouses in der Migrationsphase besitzt. Damit können in der Regel bereit im Vorfeld der Migration die Daten und Auswertungen verglichen werden und Fehler werden frühzeitig erkannt. Gleichzeitig ist es unter Umständen gar nicht mehr nötig so viele Daten zu migrieren, da sie nur zu historischen Auswertungszwecken gebraucht werden. Dies Übersicht über die Daten kann auch das Datawarehouse bereitstellen.

In my opinion this process it is the justification of a good key user, once He should be connected with Project deliverables and at same time has the perception to act before failure propagate on the ERP.

Implement strict access controls during the migration process to prevent unauthorized changes. Maintain audit trails to track changes and data movements during the migration.

Realize backups completos de todos os dados antes de iniciar a migração. Isso garante que você possa restaurar os dados se algo der errado.

Proteja rigorosamente os dados durante a migração. Use criptografia para transferência e controle rigoroso de acesso às ferramentas de migração. Estabeleça protocolos de autenticação robustos e realize auditorias de segurança regulares. Isso mantém a integridade dos dados, protegendo a privacidade e a confiança de clientes e stakeholders.

Not to be forgotten are: 1. Comprehensive penetration testing to identify potential loop holes and insecure port usages. 2. Audit policies re: the storage of audit trails and log files as this will impact storage requirements and potential system performance.

Review profiles, cleansing deactivevated users, review all roles based on job changing position, password policies, user deactivation for leaves/vacation/fire process.

1. Engage users early in the migration process to ensure they understand the importance of data integrity and their role in maintaining it. 2. Offer hands-on training sessions allowing users to interact with the new system using real or simulated data. 3. Create and distribute user manuals, FAQs, and other support materials to assist users in the transition. 4. Establish channels for users to provide feedback on their experiences with the new system, enabling continuous improvement. 5. Provide ongoing training opportunities to keep users updated on new features and best practices.

Train users on the new system and the migration process to reduce errors. Document the entire migration process, including data mappings, validation checks, and any issues encountered.

É de extrema importância o treinamento não somente dos usuários do novo erp assim como das equipes de sustentação da nova ferramenta...

A Digital Adoption Platform like tts performance suite could be instrumental in ensuring data integrity before and after an ERP migration. But and it’s a big but! There isn’t any point migrating bad data! By offering in-app, role-based training and real-time guidance, a DAP helps users adhere to best practices throughout the data entry process. It provides step-by-step interactive tutorials on data handling, contextual assistance and instant feedback mechanisms to allow users to immediately correct errors, reducing the risk of data inconsistencies

Two Key Points for Training Users on a New ERP System Understanding New Processes and Data Handling: It is essential that users comprehend the changes in data handling and the new processes within the ERP system. This includes how to enter, update, and retrieve data accurately. Comprehensive training should focus on these areas to ensure users can maintain data integrity and leverage the system's full capabilities. Adopting Best Practices: Educate users on best practices for using the ERP system. This includes proper data entry techniques, regular data validation, and adherence to updated data governance policies. By promoting best practices, users are likely to use the system effectively, reducing errors and enhancing overall system.

I certainly recommend the selection of right tool/software to support this overall process of ETL. Today, there are number of specialise tool’s/ software available in the market and to be really successful, the selection of this product is crucial. These tools help the program to implement all considerations of cleansing, transformation, loading, security, training, and testing smoothly and with good speed.

Establish post-migration mechanisms to swiftly address data integrity issues that may arise after the transition. Continuously monitor data integrity within the new ERP system and provide ongoing support to users as needed. Lastly, maintain regular communication with stakeholders to provide updates on the ERP transition's progress.

Strong leadership from top management is essential. The future of the implementation rests on the quality of the data and the potential to damage the business through inaccurate or incomplete data is huge. Strong executive custody is vital.