In Part 2 of this series we continue our discussion on Failed CMDB Initiatives, the reasons they fail and how to avoid them.
Avoiding the Pitfalls
Solution Definition and Organizational Scope
The introduction of the term Configuration Management Systen (CMS) to replace CMDB took steps towards more clearly describing the balance of technology and process necessary to succeed, but it is still not widely used by everyone. It introduced the concept of federation whereby technology becomes a core component in the solution to aggregate data from various sources, whereby the CMDB is often viewed as the solution on its own.
Be clear and precise when defining the objectives and scope of the initiative. Objectives can be open to misinterpretation, so pay extra attention to minimizing areas where any misunderstanding might occur.
Stakeholders need to easily recognize a successful CMDB/CMS implementation and articulate its value. Below are some key elements that need to be considered when developing your solution definition.
Describe and document what success looks like. Do this in both SACM/IT terminology and in terms your business partners can understand and relate to. Establish a plan that not only communicates what you’re doing, but also leverages and attracts advocates throughout the organization.
Focus on improvements in performance and uptime that correlate to having the CMDB in place to describe the value being delivered. If your stakeholders don’t share a common vision for what the solution looks like, work with them to define it and make sure to guide solutions that meet their needs.
Understand what you’re implementing and the difference between creating just another data store versus and a CMDB/CMS. They are not the same even though some of the data they contain overlap. If you find yourself expanding scope to include more runtime and operational type data simply because it exists, you are losing focus and not working more towards a CMDB.
Thoroughly assess the capabilities of your technology. Identify what can be automated. This will minimize how much you need to do manually. Adjust your scope and timeframes accordingly because automation will directly impact the depth and breadth of your scope.
Prioritize and incorporate high value items with short term milestones. The deeper levels of granularity of data and/or more departments, requires more support and resources to participate. Taking small steps can ensure progress is always demonstrated.
Data Quality & Availability
Lack of data is rarely a concern for CMDB initiatives. Lack of qualified and reliable data, however, is what needs to be avoided. Data considered to be of sufficient quality at the team level might not be able to be maintained when scaled to the enterprise. Intimate knowledge of the data usage and relationships at the lower levels breaks down and disappears at the enterprise level.
When venturing into a CMDB initiative, it’s important to take the following into account as it relates to Data Quality and Availability:
Analyze all data sources you come across and look past the surface, rationalize them against other sources for quality comparisons and make decisions based on whether they can enable business value in the short term, long term or never.
Utilize technology to assist in the enhancement of data quality and move it up the Data-Information-Knowledge-Wisdom hierarchy of value. IT environments are far too complex and dynamic these days to deploy a CMDB and require a technology component that automates the aggregation and normalization of your data from across the enterprise.
Assess what, if any, audit and controls are in place on the data source. Avoid sources that are solely manually controlled with no structure or procedure. They will not scale and will discredit all of your other data.
Define what good data looks like and what thresholds are acceptable for inclusion and exclude the rest. Poor quality data in the CMDB will cause users to lose confidence in it.
3. Lack of Governance
Implementing a formal governance model will be challenging, but is essential to success. The SACM Governance model enables intelligent decisions and improved business outcomes. Without it, data quality suffers and undermines the entire effort.
4. Expected Business Value of Return
Great capabilities that go unused are not valuable to the business. Enable growth and competitive advantage with the data you make available. Speak with your business partners and those funding the effort in business terms in which they can see value. Mitigate risks of failure associated with expected business value of return from CMDB initiatives by looking for and understanding better how you might engage your business partners and help them see the value of return you are providing:
Be sure that everyone has the same understanding. Initiatives can easily proceed with the belief that all parties are in unison on what is to be delivered only to find out upon delivery that the capabilities do not meet the needs of the business.
Clearly define your scope in accordance with the expectations and stick to it. If you do change your scope, be sure to reset all expectations and communicate them out often. Changing scope to include an additional data source or technology platform in the solution is fine, but make sure your business partner is aware of it and agrees that it will deliver value.
Demonstrate improved outcomes in business terms. Show how sales growth was partly enabled due to improved server uptime metrics. Demonstrate the ability improve buying power and price reductions by using reliability metrics of devices. Always translate the technical metrics into correlated business values that they understand.
Conclusion
As a leader in data quality management, Blazent helps organizations leverage large amounts of data more effectively and efficiently by solving the ‘garbage in – garbage out’ problem with which all organizations struggle. We do this by providing an accurate and complete view of aggregated, reconciled and remediated data from across the broadest range of data sources in the industry. Thus, enabling operations, finance and technology infrastructure teams to validate and transform data into actionable intelligence to make better business decisions to significantly improve business outcomes.
The Blazent data quality management platform can significantly reduce time and effort on challenging infrastructure initiatives such as ITSM tool migrations, Initial CMDB stand ups and the automation and maintaining of the CMDB with validated and accurate data.
For more information, visit Blazent.com or email us at sales@Blazent.com.