Technology solutions for cyber asset management are important for the enterprise, but there’s a whole part of the equation that goes beyond just the tooling. It has to do with the data-driven culture and interpretive skills that business users in the enterprise need to have in order to make the most of their new cyber asset management systems.
A data-driven workforce culture is a mindset, one where stakeholders across the enterprise relentlessly tie data to business goals and outcomes. For digital native companies and start-ups whose workforces are already steeped in technology, this mindset may already be familiar, almost second nature.
But there are countless other companies, including established brands that have decades of business history, where new multi-cloud investments are underway. These well-known companies are wanting to adopt the latest technologies for competitive gain and efficiencies that enable new business processes as part of a transformation. And that’s now prompting a need for the workforce to change its way of thinking and get more familiar with data to drive business operations and decision making.
New Levels of Visibility Require New Ways of Thinking
Once an advanced solution for cyber asset management gets deployed – say, for instance, an agentless discovery solution that dynamically scans for assets and maps dependencies across your extended enterprise architecture – you begin to see floods of new information showing up on dashboards and visualization tools. This can be both enlightening and jarring for business users.
That’s because the thrill of these sudden, newly granular levels of visibility may be accompanied by a sense of trepidation of what all this new data means. “What exactly should we do with all this new visibility?”
CloudSphere understands this, and it’s a familiar scenario we’ve helped many clients work their way through. A recent engagement with a global luxury brand comes to mind. The company sought our help with discovery across their multi-cloud environment – which includes both AWS and Azure hosting, as well as on-prem systems. They had previously relied on limited, agent-based discovery and we were helping them deploy a powerful agentless discovery solution for the first time.
Within minutes of turning on the system, they were getting new data they weren’t getting before. Within days, they were introduced to comprehensive dependency maps for decision support. And on an ongoing basis, they were getting more variety and accuracy of data around both assets and their behaviors. But our job was far from over!
Evolving Both Technology and Workforce Skills with Data
At CloudSphere, we pride ourselves not just on the technical product capabilities we bring to customers, but also our hands-on customer support that includes consultation, education and demonstration around everything we deliver.
For this luxury brand, that meant helping technical and business managers understand the new asset and dependency data they were seeing, including the operational context around that data. With such an understanding, better and more strategic decisions around move groups, workload placement, provisioning and more could be made.
Furthermore, we helped these analysts and users make the business case for data-driven decisions to senior management. Collateral for this included economic assessments, technical planning documents, readiness assessments and cost comparisons to guide IT financial management strategies and decisions.
Ultimately, we were able to help the client take what would have been a three or four month discovery process and accelerate it to the point where 80% of assets and dependencies were mapped in less than two weeks. It was a fantastic outcome, but one that wouldn’t have been possible without the data-intensive workforce skills to go along with the sheer technological innovation for the enterprise.
