A recent white paper published at sapinsider, does a nice job of surfacing many of the challenges Blazent’s customers face. This blog will expand on the 5 reasons listed in the white paper, which focus on data quality implementations in the context of IT asset and service management. The top five reasons are:
- Minimize critical business interruptions: Manually entered and unverified data uploads create discrepancies that hinder effective decision-making. Even the simplest task, such as a vendor’s name being entered in different ways, can create confusion that must be resolved before well-informed decisions can be made. If a business is lacking the tools to automate the normalization of such data conflicts, the business will be forced to rely on slow and error-prone manual reconciliations.
- Keep pace with business change: Businesses are constantly changing. Accurate asset inventories are needed to support migrations to cloud applications, expansion through acquisition, and organic growth. Large enterprises onboard and retire hundreds of assets per month, and every one must be procured, supported and, eventually retired.
- Confidently manage risk and compliance: Compliance audits can happen at short notice. Unless an organization proactively maintains accurate records of software licenses in use, it can be forced to accept the vendor’s word for how much the organization owes or that there is a breach of the software agreement which has incurred penalties. Data quality is also a paramount concern when considering the risk of not having 100% anti-virus coverage and awareness of any unauthorized equipment such as a wireless router.
- Expand or consolidate systems: System expansions and consolidations are very data-intensive operations. If the data is not normalized in advance of migration, then rationalizing multiple data sources becomes very painful. Conversely, having a high-quality baseline of existing systems can form the foundation of a graceful expansion effort. By ensuring uniformity of data, IT can drive meaningful reporting across the old and new systems.
- Prepare for continuous data governance: All the preceding points refer to activities that are not one-time events. It pays to institute a continuous data governance approach by regularly refreshing a trusted source with normalized, accurate and timely data. Most organizations use a Configuration Management Database (CMDB) to maintain such an authoritative source of application and asset dependency information.
Unmanaged data quality can have a significant impact on business performance. In his November 30th webinar, Carlos Casanova, an industry-leading expert in IOT Service Management, will detail how poor data quality can cost businesses as much as 30% of their revenues. Understanding what functions and processes have problems enables the identification areas to be investigated for potential savings opportunities through the application of data quality management. You can register for the live event here.