Over the past twenty years, our experts have found that whether you’re moving to a new data center, migrating to the cloud, planning & testing a disaster recovery plan, or any other digital transformation project, the two biggest challenges for IT organizations are:
Whatever type of change you’re planning, you need to start with a solid foundation of actionable data – data that is aggregated, normalized, current, and accurate. Most organizations have data stored in – and duplicated across – multiple systems. Users have access to different systems, and no single user has access to all the data. There are also file systems, databases known only to those who created them, and tribal knowledge that is lost whenever people leave the organization.
Without easy access to a consolidated source of data, decision making becomes difficult and risky. And, IT teams often lack insight into critical business facts. Instead of working across silos, business units are often territorial about their data, sharing only what they think IT may need. Making decisions using data that is pieced together through a combination of spreadsheets, data exports, and email messages doesn’t provide project teams with a comprehensive understanding of compliance, security and other business requirements.
That’s why TDS enhanced its rules engine, making it easy to write simple scripts that apply business rules to data, ensuring that the results will be aligned with business goals.
During the data discovery phase, the rules engine helps teams ensure they have a comprehensive set of data by prioritizing sources, normalizing data and standardizing the nomenclature used. Rules can evaluate data quality and remediate any gaps.
During planning and analysis, teams can consider many options for planning migrations by rapidly iterating through different scenarios. For example, it may be helpful to evaluate if the cost savings realized by moving out of a data center and into a colocation facility outweigh moving a different set of applications to the cloud first. And, teams will need to consider many factors, including vacation schedules for staffing levels, peak business periods, and other events. The rules engine makes it easy to rapidly iterate and evaluate custom criteria – before moving forward with a plan.
When IT teams are involved early during a merger & acquisition or a divestiture or carve-out, the rules engine can provide the project team with insight into the potential synergy – or the lack thereof – between the two organizations’ technology and infrastructure, or where there may be gaps left when decoupling assets.
A TDS partner recently shared that the ability to automate affinity grouping, wave planning, and the creation of an end-to-end migration schedule saved an enormous amount of time for many project stakeholders, and simplified one of the most complex steps in the planning of any transformation process. By evaluating asset dependencies, staffing levels, and windows of availability – among other custom criteria – the rules engine eliminates hours and weeks of difficult planning. And, because scripts can be rerun, edited, and updated, if your business criteria changes, reapplying the rules to the updated data is all that is needed to generate a new plan.
TDS practitioners have experienced the same challenges as IT organizations, and we provide our solutions to these challenges with TransitionManager, the platform that we continue to evolve to help us, and you, solve complex transformation challenges.