Cloud implementations continue rising in popularity and are projected to make on-premise database-driven business solutions obsolete. This trend has been accelerated by the current pandemic and its global impact. Before COVID-19, experts projected the worldwide public cloud services market would jump by 17% this year [2020], reaching $266.4 million. At no other point in history has there been such a need for the instant availability of IT resources and remote collaboration. In response to this global pandemic, over twice as many IT leaders are planning to accelerate their cloud adoption plans than those that are planning to put them on hold. No matter what you or your organization chooses, it is important to not make this decision lightly.
While moving to the cloud has its obvious benefits and can be a very cost-efficient solution, it can also spiral out of control without careful planning and a data-driven approach. Cloud computing reduces or eliminates the need to purchase equipment and build-out and operate data centers. This presents significant savings on hardware, facilities, utilities, and other expenses required for on-premise computing. As an additional incentive, some cloud computing programs and applications, ranging from ERP and CRM solutions, use a subscription-based model. This allows businesses to scale up or down according to their needs and budget. It also eliminates the need for major upfront capital expenditures.
In stark contrast to the benefits and promised cost reductions when moving to the cloud are the risks and costs associated with a delayed, over budget, or unsuccessful implementation. According to Gartner, “83% of all data migration projects either fail outright or cause significant cost overruns and/or implementation delays”. In this case, getting your data loaded into the cloud is only half the picture; the data also needs to be correct, both literally and for the intended business purpose. You can find more about how data migration can fail and the downstream consequences of that failure.
One of the most significant risks in any implementation is data. Data migration often gets underestimated because most think of it as “moving data from point A to point B”, but it is much more complicated. Gartner has recognized the risk inherent to data migration. “Analysis of data migration projects over the years has shown that they meet with mixed results. While mission-critical to the success of the business initiatives they are meant to facilitate, lack of planning structure and attention to risks causes many data migration efforts to fail.” Poorly understood/documented legacy data, dirty data, and constant requirement changes are only some of the reasons migrations often fail.
Lack of preparation is often the leading cause of delayed and over budget projects. No matter the target system, the first part of any successful migration/implementation is a data assessment. Definian’s Enterprise Data Modernization is a short, focused effort that helps organizations prepare for their upcoming initiatives. The list below can be used as a template of questions that must be asked and answered as part of a data assessment effort.
Identify
- Analyze the relevant data across your application landscape
- Generate detailed data statistics and facts for every data element in every relevant legacy table/file
- Report invalid data scenarios
- Summarize unique data patterns in key data elements
- Identify additional data-related anomalies
Assess
- Understand redundant data within an individual application and across multiple disparate applications
- Review and quantify missing, erroneous, and inconsistent data
- Gather metrics summarizing identified data errors
- Compare legacy data against data governance standards
Prepare
- Review detailed findings with the project team and issue recommendations
- Define a data quality strategy that outlines cleansing recommendations for each distinct error/warning
- Provide guidance regarding historical data
- Brief project leadership regarding potential project risks
The only way to plan effectively and create accurate business requirements is to base them on data facts and not assumptions. These facts come from a thorough data assessment effort. Research from IDG found that 41% of IT directors delayed or abandoned some of their 2019 IT modernization initiatives, often due to competing priorities or lack of a clear strategy. A current client, implementing Oracle, was able to meet their originally planned System Integration Testing (SIT) cycle deadlines and conversion metrics, despite not leaving enough time between the initial 3 test cycles to address the complex, dirty, and heavily customized legacy data. The project suffered the heavy additional cost of overtime work for several months. The additional cost would have been unnecessary if a data assessment was performed before the creation of the project timeline because the complexity of the legacy data would have been uncovered and the milestones adjusted accordingly. Other implementation efforts are not so lucky; for example Target Canada. Starting with and committing to a data-driven methodology alongside industry experts, your organization is on the right path to successful cloud implementations and systems for years to come.
If you want to ensure your cloud implementation is a success, have questions, or just want to discuss cloud migration, feel free to contact us.
