In today’s increasingly globalised and digitised business environment many organisations are finding that they have outgrown their existing ERP solutions are no longer going to be supported or are just becoming too slow and are failing to deliver what they need to keep pace with their competitors. This is now driving rapid growth in the instances of companies that have begun the daunting process of upgrading or replacing their ERP systems, which in many cases could have been in place for decades.
Choosing to move to a new Enterprise Resource Planning (ERP) platform is not an easy decision for any organisation that has investment and resource implications for every aspect of the day to day business operations including financial management, supply chain, manufacturing and HR. It follows that it is crucial to the success of the project that a detailed plan is put in place at the outset that breaks down the process into manageable tasks with clearly defined roles and responsibilities allocated across the organisation. Rather like the question How do you eat an elephant? The answer is – slowly and in small pieces!
Most important of the tasks is data migration. This is critical to ensuring that only accurate, complete and relevant data is transferred to the new ERP system. Well-planned data migration will not only help to keep the entire ERP implementation project on time and on budget, it’s also an opportunity to remove inaccurate or duplicate data from legacy systems that could undermine the successful roll out of the project.
As such, Data Migration cannot start too early in the ERP upgrade process, a point that the global business analysts, Gartner emphasise in their paper on the subject -Don’t Let Data Be the Achilles’ Heel of Your ERP Project “Many enterprises plan and execute data migration too late in their implementation projects and often struggle with data quality issues, impacting business benefits. ERP leaders should develop and execute a data migration strategy and start planning early to mitigate data migration challenges.”
Whilst starting data migration early is crucial it is also important not to underestimate the complexity of the task and the many things that can go wrong that no business can afford to get wrong. This means taking time to ensure that your data migration strategy is appropriate for your specific business needs. There are several ways of approaching this task but regardless of which way you decide to proceed there are some best practices you should bear in mind.
Incremental or “Big Bang” Approach
When it comes to data migration there are two basic methodologies. All at once (Big Bang) or in incremental steps. Whilst the big bang approach might appear to be the optimum choice from a time perspective, this can turn out to be a false economy when post-production issues start to arise. Adopting an incremental approach where the old and new systems run in parallel means that the legacy system is only turned off when everything is working as planned.
Back up the data before executing.
It is easy for data to get corrupted or lost during migration. Making sure that you have backup resources provides peace of mind that you have a plan B if the worst should happen.
Stick to your guns
Accepting that the migration process can be complicated from the outset is important so you can prepare for the times when things almost inevitably don’t go according to plan and help resist the temptation to change the strategy mid-stream.
Test, test, test.
The importance of testing the system at every stage of the migration process, including deployment and maintenance, cannot be over-stated to mitigate the potential damage and delay that can result from a simple error being missed at crucial early phase of the implementation.
Go it Alone or Expert Support?
As a highly specialised skill very few organisations are likely to have the necessary in-house expertise and resources to tackle the data migration process without some external consultancy support. Getting expert help at the start of the project will ensure informed decision making across all aspects of the implementation process, keeping the project on time and on budget, enabling a seamless transition from the old to the new and minimising the risk of missing the fundamental business objectives driving the decision to migrate.
Download our Data Quality Checklist to help prepare for your data projects
As data quality can be complex and time-consuming, it’s often difficult to know where to start. We’ve put together this helpful checklist to point you in the right direction.
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