Michael Hart is a Sr. Sales Engineer at Blazent.
IT Asset Data Governance: The Crack in Every Foundation
Managing any IT asset from sourcing to disposition is both challenging and essential. But too often it is also manual, providing multiple opportunities to lose governance not only of the Asset itself, but of key data needed to defend against financial audits. Most organizations today must practice some form of IT Asset Management in order to comply with legal and regulatory requirements. IT Asset Management typically performs two key functions. First, it provides Finance with key data needed to make strategic financial decisions. Second, it must provide governance control through the complete and changing lifecycle of every asset.
The Status Quo: Rinse and Repeat
The marketplace is saturated with companies providing workflow automation platforms in an attempt to use process to control data quality; but the results have been spotty at best, erroneous at worst. Organizations today, after spending billions on workflow automation and purchasing IT asset and software discovery tools, still can’t seem to get the insight they need to match the speed of change in their environment and make time sensitive decisions. Nor can they defend against audits or negotiate with vendors with high confidence. It’s so bad in fact, that they are supplemented by manual wall-to-wall inventory on a regular basis. Automating process alone with workflow tools doesn’t address poor data quality. Workflow tools integrated with discovery tools don’t fix the data quality problem. Throwing people at the manual wall-to-wall inventory doesn’t fix the data quality problem.
So how bad is the data quality problem? Studies today show that, at any moment in time, up to 40% of an organization’s data is missing, erroneous or incomplete. In other words, ‘bad.’
“When there are lots of people with their hands on the data,” says Dianne Ray, state auditor of Colorado, “that’s where we find the biggest problems.”
The Solution
Given the increase in volume and velocity of data, data quality and validation are fast becoming a focal point for CIOs. Only with a disciplined, proven approach to IT Asset Data Governance can organizations attain insight hiding in the data. Rather than starting over and scrapping their previous investments, organizations are looking for a master data management expert that works with and leverages the investments already made in these expensive tools, ensuring that IT Asset data is managed, from end-to-end. The resulting insight is the missing ingredient executives need to confidently prioritize projects. Current, accurate and complete near real-time data, coupled with context and relationships provides insight needed to predict operational problems and prescribe remedies BEFORE problems occur.
The Blazent method eliminates manual reconciliation efforts and data entry errors delivering confident insight near real-time, backed by multiple data sources.
The Blazent method consists of three steps:
- Identify and Analyze IT Asset Lifecycle Process (Manual and Automated) and Data
- IT Sourcing/Purchasing to Asset Management
- Asset Management to Configuration Management
- Configuration to Disposition
- Continuously Consume IT Asset Lifecycle Data Sources
- Sourcing: Ordering System Data/Vendor Data
- Receipt: Asset Management System Data
- Stock: Asset Management Systems Data, Configuration Management Systems Data
- Deployment: Authentication Data, Operational Tool Stack Data, HR Data, Software Discovery Data, Software Licensing Data, Incident Data, Problem/Change Data, Dependency Mapping Data, Location Data
- Disposition: Asset Management Systems Data, Configuration Management Systems Data
- Establish and Maintain Relationships between Asset/Cis and IT Services
- Physical Servers, Virtual Servers, Database Servers, Database Instance, Application, Servers, Racks, PCs, Network gear: Switches, Routers, Hubs, etc.
Summary
Poor data quality can cripple any organization. Adding more data or additional reporting isn’t the answer. It is essential to fix the data at hand, since they form the basis for crucial financial and operational decisions. With so many systems capable of reporting data, it’s basically impossible to spot bad data before it causes a problem. Buying a workflow automation platform and integrating discovery tools doesn’t prevent bad data from entering your systems. Only a focus on IT Asset Data Governance will identify and eliminate manual and automated processes which create bad data. Continuously identifying and correcting bad data before it’s entered is essential, providing confident insight for the strategic CIO and team.