What companies should pay attention to in business intelligence projects

(Estimated reading time: 3 - 6 minutes)

Better decisions, more transparent corporate management, more efficient processes through automation: the introduction of a business intelligence solution is an integral part of the digitization strategy of many companies. However, in order for a business intelligence project to actually be a success, there are a few points to consider. In this article we report from practice.

There is no question: the desire for up-to-date key figures in order to make strategic and operational decisions on the basis of a reliable database is present practically everywhere. A lot of information can already be found in the ERP system or in the online shop. There is nothing wrong with first working with the evaluations and analysis functions that these systems provide. However, if time-consuming and manual evaluations are automated, if several data sources are linked in addition to the ERP, if data is to be compressed and enriched, it is time for companies to think about introducing a business intelligence solution. KUMAVISION is based on this Microsoft Power BI. The business intelligence application is part of the Microsoft technology platform, which means that interaction with ERP and CRM solutions based on Microsoft Dynamics 365 is extremely simplified. However, a pure software introduction is rarely enough, as the following practical examples show.

Measure correctly, plan better

Will business intelligence solutions, like Microsoft Power BI, linked to the ERP software, provide users with a wide range of evaluation and analysis options. On the way to becoming a data-driven company, however, there is always the danger of turning in the wrong direction and putting the reins on the horse from behind. The problem: Only the existing data is used prematurely, without asking which data is actually required to achieve the intended goals. At the beginning of every business intelligence project, it should therefore be compared which data should support decision-making in the future, which data is missing and where and how it can be collected and processed if necessary. Another mistake that is quickly made in the initial euphoria is the excessive collection of key figures. Reports with dozens of metrics overwhelm users. But even if the selection of key figures is set, pitfalls lurk. Because key figures in themselves are not very meaningful at first: They have to be related to goals in order to make a target/actual comparison possible in the first place. While the number-based achievement of goals in company areas such as sales or purchasing is already part of everyday life, other areas such as marketing or HR have a harder time with it. But here, too, Business Intelligence offers added value, to critically question one's own work and to continuously develop potential for improvement.

No business intelligence without change management

A cleanly modeled data model, well-maintained master data and attractive reports with the right key figures are indispensable for the success of a business intelligence project, but they are not the only decisive factor. Technology is usually the smallest hurdle when it comes to business intelligence. Much more important is the willingness to actually implement changes in the company based on the insights gained with business intelligence. With Microsoft Power BI it is possible, for example, to automate the creation of up-to-date evaluations and to incorporate different data sources. However, if no concrete action steps can be derived from the evaluations, valuable potential will be wasted. Business intelligence is incorruptible and in some cases also uncovers unpleasant truths such as declining sales figures or declining quality. It is all the more important to convey to employees as part of a change management process that business intelligence actively supports them in their tasks in order to create acceptance for changes. Because otherwise – as experience has also shown – reports and evaluations remain unused in the virtual drawer.

Data quality problem

An obvious, but often unpleasant finding: if the data quality is not right, the business intelligence analysis based on it cannot be right either. Companies should therefore think in advance about which data is required for which analysis and the quality of the data available in the company. A typical example: If incoming orders are to be broken down by article groups, a corresponding segmentation of the master data is essential. At one point or another, this can mean additional work in data maintenance. This makes it all the more important to involve employees at an early stage and to convey the benefits of the additional data collected for them and the company. Experience shows that an investment in high data quality pays off in multiple ways. Because in addition to reliable business intelligence evaluations, high data quality forms the basis for automated workflows and smooth interaction with other solutions, such as between ERP and CRM.

Fast with SmartStart

A case that often occurs in practice: A company wants to introduce a business intelligence solution, but does not know how and where to start. The result: You get bogged down in technological issues instead of working meaningfully with data. KUMAVISION therefore has for companies that use Business Central as ERP software, SmartStart packages for Microsoft Power BI developed. SmartStart packages are available for different industries and contain ready-made best-practice solutions: data models for various business areas such as warehousing, finance or production as well as industry-specific key figures and evaluations. Customers do not have to start from scratch, but can build on solutions that have been tried and tested in practice and quickly become productive Power BI work. Of course, the SmartStart solutions can be adapted and expanded to meet customer-specific requirements.

Self-service instead of programming

Microsoft Power BI is a self-service solution. The term "self-service" should not be misunderstood here. Tech-savvy users are quite capable of carrying out many tasks themselves, such as adapting or creating data models and evaluations. The respective specialist department can thus approach the topic of business intelligence in a more agile manner, while at the same time the IT department is relieved. However, it is advisable to involve an experienced external business intelligence partner or IT for modeling the data model and integrating other data sources. Often hidden: Self-service is not only limited to the creation of data models and evaluations, but also includes access to them and their integration. Reports can be automatically published on portals, where employees can access them independently. In addition, companies have all the possibilities of workflow automation with the Microsoft technology platform. The automatic posting of reports in Teams channels is also possible, as is the notification of superiors by e-mail if certain values ​​are exceeded or not reached. This means that decentralized teams can also be provided with the necessary data at any time.

New insights, new opportunities

The digital transformation ensures that data is generated in many business areas that did not exist before. Business Intelligence enables companies to use this data profitably. Whether to establish new business models, to increase efficiency in production and logistics, to transparently control sales, to relieve employees in the long term, or simply to no longer leave decisions to gut feelings alone: ​​With business intelligence, you gain new insights into your company. We are happy to help

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