Specialist article
Project management
BI projects are often accompanied by special requirements and therefore require a special approach. In this article, we reveal how you can adequately take these into account in project management and master them using our success factors.
Like so many IT projects, BI projects also fail for often avoidable reasons. For example, Gartner analyst Nick Heudecker1 estimates that around 85% of all big data projects, as an example of modern BI projects, fail. To join the successful 15%, we have developed success factors for BI projects based on our experience, which are often underestimated.
Where do we get our experience from?
29FORWARD has already successfully completed a large number of BI projects worldwide in the banking, insurance, retail and aviation sectors. As a result, we have built up wide-ranging expertise in BI project management and are familiar with the special dynamics of such projects.
Data quality and technical significance of KPIs (Key Performance Indicators)
While some companies already regard the importance of data and data quality as a strategic element, others still lack a clearly defined concept for this. An important component here is responsibility, the quality of individual data and the definition of the content of KPIs. The higher the data quality, the more meaningful the KPIs that are calculated using this data. Reliable decisions can only be made on this basis if the underlying data is of good quality (completeness, consistency, origin).
Success factors:
- A clear definition of responsibilities for data and data changes is necessary. It is important for your project team to transparently delineate the responsibilities and interests between the various stakeholders. This also includes the involvement of the line organisation, which requires close cooperation with bodies such as data stewards or a BICC (Business Intelligence Competency Center).
- Provide the relevant department with tools to measure and improve data quality. You can define your own metrics for data quality, e.g. consistency of a data set, completeness of a data set, redundancy (no duplicates).
- Ensure that your documentation is up-to-date and complete. Always keep the documentation of your KPIs and data streams up to date and ensure a transparent and standardised understanding within the project team. In this way, you avoid a heterogeneous interpretation of key figures and provide a single point of truth for the relevant company key figures.
- Motto “Trash in – Trash Out!” – If possible, rectify data quality problems in the supplying systems in the source system to avoid time-consuming data corrections in the subsequent BI system. The golden rule applies: A BI system is only as good as the quality of the data provided in the sources.
Test management
As BI projects are data-driven projects, the creation of test data is particularly important in test management in addition to test execution. The complexity of the latter is often underestimated at the start of a project.
Regulatory requirements
In principle, regulatory requirements (GDPR, critical infrastructures, MaRisk, BAIT, etc.) naturally apply to all types of IT projects. However, due to the processing and analysis of often sensitive or confidential data, data protection plays a special role in BI projects.
Regulatory bodies such as auditors or data protection officers are often perceived as “impeding innovation”. Project management urgently needs to avoid such a working environment. It is important to mediate between the various stakeholders in order to constructively bring together the requirements of all parties.
Success factors:
- Actively involve important roles from the areas of data protection, IT governance and compliance in the project organisation and communication right from the start of the project. Clarify the underlying regulatory requirements at an early stage, taking into account the IT infrastructure, and establish clear premises for realisation during the implementation phase. The jointly developed objectives should be clearly recognisable in the implementation concepts for the affected work packages. You can have these checked and validated by responsible stakeholders as part of an official acceptance procedure. This creates planning security for your project and avoids conflicts and costly workarounds in later project phases.
- Analyse the BI solution and the data budget for risky and sensitive data and functions. Based on the results, an authorisation concept should be provided for each system component of the solution design in accordance with the requirements of the GDPR and MaRisk in cooperation with the key stakeholders from governance and IT infrastructure. As part of an official approval process, the concepts are checked and approved by the responsible key stakeholders before implementation.
- Establish clear definitions and documentation procedures, for example for anonymisation and pseudonymisation processes. The authorisations must be adapted to a variety of regulatory requirements, the information needs of the specialist departments and risk management. In addition, all information and requirements should be available at an early stage when designing the system and architecture. For this reason, plan bindingly and with foresight so that you have sufficient time to coordinate all authorisations with the stakeholders.
Our conclusion on the recipe for success
There is great potential in every BI project, taking into account the success factors mentioned above. Always bear in mind that it is the responsibility of project management in particular to develop the joint concept in close cooperation with the responsible company roles in order to avoid conflicts and unnecessary additional work. You should also involve test management, regulatory affairs and data quality in the conceptualisation phase at an early stage. Using an iterative or even agile approach, BI solutions can be developed step by step. Experience has shown that this is particularly suitable for BI projects in order to best apply our success factors in practice. The content and success factors in this article are based on the extensive experience gained from 29FORWARD projects. If you are further interested, 29FORWARD is also available to you as a trustworthy partner for the realisation of your BI projects.
