In the first step, a central data pool, for which the IT department is responsible, was created based on the business requirements. It consists of ten broad data sources from different subject areas and served as a basis for the BI content that would be developed by the specialist department. The emergence of individual data processing was prevented to a large extent by central metadata definitions. Drawing on the requirements of strategic planning and marketing, the central data pool was iteratively expanded according to the needs of other specialist departments.
The descriptions of the provided data sources were compiled in a central catalogue to give analysts an overview of existing data sources, their origin and the data structures they contain. Data sources provided by IT were marked separately to ensure that they are distinguishable from data sources created in relation to the Self-Service. Analysts can thus choose to give preference to the data created by IT, thus ensuring clear accountability. If self-created data sources develop into popular and important building blocks, there is a plan for IT to take these over and stabilise them in order to keep Self
-Service Reporting scalable and stable.
A coordinated SSBI role concept was established for the department and IT, which authorises functionality and data according to duties and responsibilities. The departments began to create the content in close cooperation with IT. This enabled the analysts, who had already been intensively trained in the implemented tool, to further deepen their knowledge of the tool, thus ensuring the semantically correct use of the centrally provided data sources.
Based on the close cooperation with IT, the created content was the direct responsibility of the department. The following rules were established in this regard: For new analytical applications, the responsibility for accuracy lies with the department. If data sources provided by IT are used, IT only assumes responsibility for their availability and accuracy with regard to the interface requirements. The department assigns access to applications and data sources.
Analysts exchange information in their own community at regular intervals. They discuss current problems and ideas for new analyses in these meetings. Problems can often be solved with the experience of another analyst and, when discussing future and currently developing applications and analyses, synergies can be used and knowledge can be pooled.
Die Einführung eines SSBI-Ansatzes in den Fachbereichen bietet für die meisten Unternehmen messbare Vorteile. Mehrwerte werden vor allem in der gewonnenen Flexibilität der Fachabteilungen bei gleichzeitiger Entlastung der IT-Abteilung gesehen:
BI-Content wird losgelöst von IT-Verfügbarkeit und gegebenenfalls vorgegebener Release-Zyklen kurzfristig und selbstständig durch die Fachbereiche erstellt. Dadurch werden auftretende Informationsbedarfe sehr zeitnah gedeckt und die sich ergebenden Freiräume in der IT können zur Fokussierung, zum Beispiel im Rahmen der Datenbereitstellung, genutzt werden.
Ein weiterer wesentlicher Vorteil eines SSBI-Ansatzes liegt in der zwangsläufigen Auseinandersetzung der Fachbereiche mit den Daten, die im Rahmen der fachlich verantworteten Prozesse generiert werden. Die frühe Einbindung des Fachbereichs in die Definition steuerungsrelevanter KPIs und die Konzeption der BI-Anwendung, die sich in vielen BI-Projekten als einer der kritischsten Erfolgsfaktoren gezeigt hat, ist im Rahmen eines SSBI-Ansatzes garantiert. Der Aufbau von tiefem Prozesswissen in der IT kann entfallen. Projektaufwände können reduziert und Kosten gespart werden.
Als Konsequenz führt der richtige SSBI-Ansatz neben Flexibilität und Kostenersparnis zu einer allgemeinen Qualitätssteigerung der Analytik, was wiederum entsprechend positive Effekte auf die
datengetriebene Steuerung der digitalen Prozesse und damit der Gesamtentwicklung des Unternehmens hat.
The amount of BI content grows rapidly due to the increased number of content creators in the departments. Large portions of the created content are working versions and are not finalised. It is no longer possible to recognise which content is correct and which content can or should be used. Also the possibility and responsibility as regards deleting content is not clear. This situation makes the ongoing development of the underlying data management difficult or no longer possible.
Content creators develop their own, non-coordinated derivations of management-relevant KPIs. Comparisons lead to deviations from supposedly identical technical content. This then requires cost intensive re-engineering to determine the existing deviations and the "truth".
The created content is exclusively geared towards specialist content and is not optimally developed with regard to high-performance processing. This causes the load on the underlying reporting systems to increase significantly.
These concern on the one hand the unauthorised opening, editing and use of content, for example between competing departments, as well as the display unauthorised data.
Not every user in the department is immediately suited to the creation of BI content. A lack of knowledge regarding the tools used and the company's internal data architecture can cause misinterpretations of the used KPIs and incorrect process management decisions.
The aforementioned risks can be mitigated with a suitable combination of organisation and tools. If, in particular, underlying organisational conditions are not effectively defined, the SSBI project is destined to fail. Most notably, the properties of cloud analytics can be used to minimise risk here.
Unlike on-premises installations, cloud analytics tools eliminate the need to purchase hardware and install/configure the used tools. The time it takes for the tools to be available to the department and the associated possibility to obtain information is significantly reduced. In addition, the risk of bad investments is minimised, since costs can be reduced to zero in the short term by not renewing with the cloud provider
In contrast to rigid licensing models, flexible pay-per-use models allow costs to be determined by actual usage behaviour. The departments can directly influence the costs incurred via their usage behaviour.
It is not necessary to perform sizing before installation. Cloud usage allows one to flexibly react to increases in resource requirements, both in terms of memory and CPU.
This allows easy integration of additional departments and content creators into the SSBI approach. In addition, it is possible to react to individual requirements of individual departments; for example, if resources are only required at certain times, such as during a month-end closing.
Cloud analytics tools are largely designed for direct use by the department.
Functionalities that are typical for the IT department such as access rights administration can be hidden from the department. Operation is usually possible via the browser. Local installation and malfunctions caused by incompatible release statuses are eliminated.
Cloud analytics products offer a central storage facility for created content. This can be organised according to the individual governance. The cloud provider ensures guaranteed availability of the content. The department and IT do not have to implement backup concepts.
Cloud analytics products provide collaboration options for content creators out-of-the-box, for example by assigning tasks, sharing and reusing content or comment functionality.
In addition to the numerous advantages provided by the cloud, its disadvantages must not be ignored. In particular, it must be decided whether the relevant data may leave the company network or must remain on premise.