by Sue Dunnell
It’s often said these days that every organization is, at some level, a technology company. Regardless of the industry or the role individuals play across an enterprise, all are increasingly dependent upon IT to innovate and deliver on the promise of digital transformation.
However, before any change is made, good decisions must be made, and good decisions require good data, which must be relevant and aligned with business facts and priorities.
One article I recently read proposes a systematic approach to redesign a CMDB by focusing on vital business functions. This seems like an ideal way to build a foundation toward better decision making: work across the enterprise. And as the author noted, building a CMDB is “a management project that needs to be tied to the business.”
There are plenty of solutions specifically built to address these needs.
First, there are many sources of data – CMDBs, DCIMs, files, databases, spreadsheets. And then there are collaboration tools used across the enterprise – Slack, Asana, email, and messaging. We all know there are a multitude of documents for business strategy, policies, regulatory requirements and SLAs stored across departments.
All of these tools work well, but they don’t work together. And users have different levels of access to specific data sources, but no single person has access to all data.
We recently worked with the team at a global financial services organization that was struggling to move forward with their cloud migration plans. They lacked a central system of access for all relevant data. And, frankly, were in spreadsheet hell as they tried to gather facts and data. This meant they were making decisions in the dark, and realized that this was putting them in a very risky situation. They knew they needed to get a complete and actionable view of their environment before they could go any further. You can read the full case study here.
From our experience with this team and with countless others, we often beat the same drum: If organizations are to succeed in their efforts to innovate, they need their disparate data sources and tools to work together as a toolchain, first to aggregate and normalize data, then to consolidate it with critical business data.
Decision making is best done when all stakeholders have access to the same data, ideally in a visual and easy to map format. If you need your organization to move together to make innovation happen — and ensure that your technology is an enabler rather than a roadblock to progress, check out our Jump Start Offerings.
The methodology and tools you choose for your migration journey will directly impact your goals and measure of success. Download our Data Center Migration Survival Guide now to kick off your journey.
Follow these key cloud migration best practices for successful cloud adoption in your organization.
When executing a cloud strategy it takes time to understand how your apps work, identify those most critical to business, which are best fit for the cloud, and which require modernization before migrating. What if you could accelerate this process by automating your toolchain?
Transitional Data Services (TDS), a global leader in cloud and data center migrations, and modernization, today announces the availability of TransitionManager 6.2. The new release provides further enhancements to improve performance and streamline migration tasks. Additionally, release 6.2 allows customers to execute digital transformation strategies with confidence, addressing critical business areas such as disaster preparedness and cloud adoption.
IT organizations need a platform built specifically for planning, managing, and executing migrations, recovery events, M&As and other transformation projects, end-to-end.
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.