Three Ways Leading Businesses Ensure Data Transformation Projects Succeed

In a previous blog, we discussed the risks of relying on ETL/Excel to execute an enterprise data migration. Now, to help provide some practical, go-forward advice, I’ve compiled three recommendations on how to ensure your enterprise executes a successful digital transformation. Let’s get right into it.

1. Plan Effectively 

It’s the obvious place to start, but it really shouldn’t be underappreciated or hurried as part of a transformation process. The objective of migration planning is to leverage automation to quickly assess your data and systems landscape, build upon those insights to develop a preferred project approach, define risks, understand resource requirements, and build a business case and budget.

With assessments and planning, it’s always best to start with analyzing your application, data, data quality, and custom code landscapes before initiating a transition. Leveraging automated assessment technology (like Syniti’s Data Assessment Express technology) can rapidly provide an overview of your current situation and provide a framework for moving forward. This visibility should help you understand what work needs doing, where risks exist, what areas of your business could unlock the most value the fastest, and what project approach will align with your organizational goals.

Understand data quality challenges

To truly understand the state of data quality, you need to understand the data construction, the rules, and the current governance workflows operating in the enterprise. Automating this step through technology to get the answers faster puts you in a position to accelerate your migration project with increased confidence. By conducting a comprehensive scan of all your diverse data sources you’ll be able to assess where data quality is at its best and worst, but it also helps identify trends of poor data quality, and crucially for the business, where this poor data quality is negatively impacting the enterprise’s bottom-line. When done effectively, this effort leads to insights on where to find savings and P&L improvements, which could help to offset overall migration project costs. 

Understand source-to-target challenges

It’s also important to assess both source systems and the ultimate target to get a vision of how the current dataset will need to be transformed to achieve project goals and deliver rapid time-to-value. For many complex enterprise data migration projects, it’s rarely just one source and one target involved. It could be tens or hundreds of different source applications each with its own individual wiring and utilization culture that needs to be understood before moving data to the target. Most ETL/Excel solutions struggle with this volume and diversity of source systems. Be sure to look for a solution that provides out-of-the-box compatibility with hundreds of SAP and NON-SAP source and target systems.

Understand custom code remediation

Another important focus in migration planning is custom code remediation, particularly in the case of ERP migrations. Most enterprises have made significant customizations to their legacy ERPs and applications. Without a clear understanding of the current situation and the desired future state, this code can act as a blocker toward landscape standardization, transformation, and modernization. During the assessment, it’s important to examine custom code across the entire enterprise landscape and develop a plan for which code would be best to retire and which should be transformed to the new target. With automated refactoring and migration of code, the likelihood of a successful migration increases significantly.

2. Leverage Smart Technology to Minimize Potential Points of Failure

There are few worse feelings in life than knowing you’re not in control. In the world of complex data migrations, that is especially true. One way to gather more control is to take advantage of technology that is proven to deliver accuracy (and accelerate the project as a bonus).

Load Early, Load Often

For successful migration projects, it’s important to repeat the mantra of “load early, load often.” This agile best practice leads to successful migration projects, as it is critical to test, fix, and test again, especially with real data. Many companies look to test components of the migration with test data, hoping it acts as a sufficient analog when moving towards a migration go-live. A consistent sandbox-style approach to data migration, leveraging real data, will provide clarity into the status of every aspect of the migration and dramatically increase the likelihood of a Boring Go-Live with a target system that works smoothly and delivers immediate value

Auto-code generation and no-code capability

For enterprise migrations, it is not uncommon to have thousands of data mappings, and one-off, manual migration code snippets in Excel spreadsheets distributed throughout the company. This is far from a best practice. One way to reduce risk while accelerating migration projects is to leverage a platform that delivers automated code generation for mappings and data harmonization. Autogenerated code that is created using best practices garnered from thousands of projects can significantly reduce the potential points of project failure and lower risk. When you come across unusual and unique situations that need to be harmonized between source and target systems, look for a solution that offers centralized no-code development capabilities to address the issue quickly and easily.

Built-in best practices and proven methodology

Leveraging a platform that embodies proven best practices and the experiences of thousands of projects can go a long way towards success. For example, a solution that delivers pre-defined data mappings from SAP ECC to SAP S/4HANA out-of-the-box can significantly accelerate project timelines. Look for smart systems that deliver best-practice-driven data quality rules and policies, and provide proven and pre-vetted data quality reports and dashboards. This type of automation can rapidly identify potential issues, minimize missteps, reduce resource requirements, and lower project costs.

3. Pull Together, Not Apart

Many enterprise migration projects experience the challenge of “Excel sprawl,” the consequence of having multiple versions of critical data spreadsheets out in the ether, each telling a different story of project status and data accuracy. To avoid this risk, here are three areas of focus you should consider.

Every stakeholder in one system

When your entire team works together in a single system, you can crowdsource project and data excellence. It’s easy to assign roles to your technical team, line-of-business experts, executives, and system integrator partners. You determine the responsibilities, workflow, and dashboards that fit the requirements of each role and with every team member working in the same system, project visibility goes through the roof and the risk of project failure goes down significantly.

Automated project orchestration

Working in a centralized migration solution also allows for the orchestration of efforts across the entire migration project. This provides project leaders with visibility into each migration sprint, the status of data quality improvement efforts and workflows, and automated updating of dashboards that provide real-time visibility into project status and how it relates to program objectives. It also allows project personnel to work collaboratively in the cloud ensuring any remediation or coding work is updated in one spot, in real-time.

Executive leadership buy-in

A single platform is also the way to go to enable smooth collaboration with executives. Realtime executive-ready dashboards to help visualize project status and data quality will go a long way to ensure project buy-in and support. This helps drive realistic and accurate business and project decision-making and keeps projects on-time, on-budget and on-expectation.

Is a frictionless data migration possible?

While delivering a frictionless data migration isn’t easy, it’s certainly possible with the right tooling, experience, and best practices fuelling your approach. All these points listed above dramatically reduces the risk of having a big-bang go-live fail AND positions the company to achieve faster time-to-value. But it’s not solely about driving value. Because after all, isn't it really about sleeping easy the night before a Boring Go-Live.