Considering that the sea of data is continuously getting deeper, you are probably drowning or already drowned. The list of business data needed to comply is endless. Customer care data, vendor and supplier documents, customer invoices, employee details, and company information – to name a few. So it is always important to migrate your ERP data at a safe place.
Because there is an increase in data volume, businesses should prioritize efficient and timely data processing. The business’ bottom line is being affected when one receives inaccurate or false data. Thus, data integrity is among the crucial aspects of building a good company’s health status.
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When your business is constantly receiving inconsistent and inaccurate data, it can clearly show the ineffective and low performance of your business. If you integrate the ERP system to your business without completing all the needed data, it won’t work, for sure. Aside from failed implementation, this can also lead your business to drop.
Migrate your ERP data
In this post, we are going to provide you with the needed information regarding the best practices you need to adapt to have a successful ERP data migration. So, if you want to learn more, keep on reading.
ERP Data Migration – What are the Best Practices?
Data migration plays an important role in having a successful ERP implementation. The systems used by your organization impacts the data migration. Aside from that, it is also being affected by the regulations impacting your company, the number of users who are part of the data making, the legacy systems, as well as the number of sites that go live frequently. If you deal with your data today, you will not experience any delays, disruptions, and other problems when implementing an ERP system to your company.
The following are the best practices you need to know when you are planning to take the path of ERP data migration.
Analyze and Plan the Data
Before you start your ERP data migration journey, it is important to know your business goal and model to create a plan. This is an important aspect to accumulate effective data migration strategy. Your strategy should include the extraction and segregation of important data, getting rid of the worthless content to improve the processes regarding external partners and customers, sorting the extracted content, and dividing it based on its importance and utilization for business operations in the future.
In this aspect, a business analyst’s help is needed to effectively examine and assess the information and produce accurate content, analysis, and report according to the extracted data. You can also use this to reduce possible risks, streamline operations, and determine relevant insights, which can lead to enhanced outcomes and better and faster decision-making processes.
When planning for the data, it is also crucial to examine and determine how complex the data is, assess the migration resources, and categorize it into historical data, open transactions, and master data. Through this, you will know what you need to eliminate, archive, and what to carry throughout the journey.
Build an Effective Migration Strategy
When it comes to implementing an ERP system for your company, it is important to know the side of your partner. While your partner plays an important role in achieving successful data migration, your organization still need to participate.
Partners must equally distribute upon building a migration strategy and together create a plan and assigning it to the entire team. Every member of the organization must have a role to play, decision-makers, and more. Encourage your team to focus on making well-informed decisions and performing business tasks.
You need to understand how complex and how much is the available data you need to migrate. After that, you need to create an implementable and logical action sequence together with the dues of the set actions. All of these should be performed while accumulating the best possible practice. You and your partner should work equally and systematically. Whenever possible, avoid adapting the Big Bang approach.
Stay and Follow the Data Standards
Despite the number of systems or data sources needed to migrate, storing the data in a unique format is important. Besides that, it is important that every department have a clear pattern for easy classification of data.
It is important that you stay and follow the set data standards to build a data migration design that works uniformly. When defining the data standards, executive management and department managers should work together. If the data is worthless or won’t make any good for the rest of the data migration processes, get rid of it. Aside from that, ensure that you will focus on extracting more complex data and dividing it into easier ones.
Perform Enough Examination
When you are taking the path of data migration, you will encounter numerous types of tests, including batch application, volume, system, and unit. It would be great if you will make sure that all the tests are carried out prior to the confirmation of the ERP data conversion.
Through this, you can prevent storing repetitive data issues. Another significant issue you must keep in mind is data transiency. Considering that frequent changes are always possible in terms of extracting the data, you should perform enough testing and auditing prior to each stage. This will help you to prevent possible decision revisions.
Implementing ERP to your business means you need to keep in mind that data migration is among the top priorities you have to deal with. This is because it is the most time-consuming and crucial part of the whole implementation process. The problem is that a lot of business establishments are still making up mistakes in terms of ERP data migration. In this case, it is crucial that the two teams should have equal coordination and communication.
You need to adapt the four practices we mentioned above to reach success in ERP implementation and data migration. Take note of these practices; analyze and plan the data, build an effective migration strategy, stay and follow the data standards, and perform enough examinations.