Your Basis for Successful Information Management
An increasing number of companies today are confronted with data-driven demands. These arise in such fields as:
- Master Data Management
- Digital Transformation
- Compliance Directives (e.g. BCBS 239, Solvency II and anti-terrorism regulations)
- Operational Excellence
- Shared Data
- Predictive Analytics
- Big Data
All of these have one thing in common: they need data and information - the most important raw materials for ensuring a company’s competitive advantage, and thus its commercial success. But how can this be achieved?
Data governance is the answer. It requires the creation of responsibilities, processes, standards and metrics for a company wanting to efficiently exploit its data as an important economic asset, and ultimately to achieve its strategic targets. A dynamic data governance strategy ensures that company data is profitably exploited.
Data (and information) is the asset that make any type of digital business strategy possible in the first place, and is the foundation of all business processes. Therefore, its quality level must have high priority within your company, and be appropriately handled and supported by your organisational structures. In other words: high quality levels must be guaranteed throughout the entire data life cycle. And this is made possible with data governance, i.e. responsible and sustainable organisation and control of company data and information. Only reliable data governance will enable a company to transform its data into an operatively exploitable asset. Its correct implementation will result in genuine competitive advantages and a marked increase of company value.
Efficiency in Daily Behaviour with Company Data
Data governance is a joint task of Company Leadership, Company Strategy, as well as specialist departments, such as Customer Services, Sales, Marketing, and IT. To implement it, the knowledge about business processes and user applications systems that lies spread around the company, must all be combined. This means that in the operative field, business rules must be centrally defined, maintained, and continuously evaluated. There is also a strategic and operative perspective: data quality must be anchored in strategic company targets, and the success of all data quality measures introduced must be monitored continuously. Once this is achieved, all processes will operate safely with quality-guaranteed data, and resource information will be optimally exploited. Thus, data governance not only increases efficient daily use of company data, but also enables value creation at a completely new level. This makes clear that data governance is not just a simple, one-off project, but instead, a continuous process involving all parts of a company.
The Uniserv Solution – Long-term Success with High Quality Data
Uniserv data governance solutions enable you to selectively decide whether the quality level of your company’s data exactly fulfils your requirements. These requirements are represented by business rules which describe the importance of data and information within the company context. To comply with these rules, appropriate metrics are defined, which then have to be measured and monitored.
This is particularly important in the field of Compliance – i.e. observance and implementation of legal directives. Also, it is possible to define internal requirements for ensuring the quality of master data and to guarantee operational excellence. For example, marketing campaigns take place only when the quality of the datasets they use is sufficiently high. Or in the field of logistics, where good address quality is essential for efficiently organizing deliveries, and fixed address quality rules are especially beneficial. Regular evaluation ensures that weaknesses are promptly identified, and appropriate countermeasures applied.
Standards and metrics are relevant elsewhere too. For example, Uniserv can help to ascertain whether the data in one or another source system is suitable for subsequent processes, such as a one-off migration project, or a recurring integration process. A typical example here is the transfer of master data and external reference data into a master data management tool, such as Uniserv’s Smart Customer MDM.
Uniserv data governance also provides a whole range of possibilities for rule monitoring. Individual business rules can be stored centrally in a rules repository, and with the aid of a rules engine they continuously monitor company data during operative business. Reports can be created and data quality KPIs shown. Thresholds can be set and alerts sent automatically if any deviation occurs.
But once these questions are answered, what is the next step? Now, a clear decision must be made about what optimization measures are to be introduced, and where. And finally, the success of these measures must be monitored.
Uniserv provides everything necessary for the successful start of your data governance programme, such as Data Quality Profiling; a rules repository, rules engine, Data Quality Monitoring components, dashboards, optimization software, and the necessary expert knowledge. Of course, everything is provided in a precisely tailored version (neither too small nor too large) most suitable for your company, and will ensure long-term competitive advantages and promotion of company growth.
- Sustainable, understandable and secure information quality, as the foundation for successful digital business initiatives and predictive analysis projects.
- An early warning system to register any deterioration in data quality levels
- Possibility of proactive countermeasures to promptly prevent deterioration of data quality
- Time savings by using established standards and definitions
- Control and monitoring of all data quality measures implemented
- An intuitive dashboard that clearly shows all data quality KPIs
- Individual rules for each company department
- Support from experienced consultants when creating data governance concepts and data quality rule sets