Business Intelligence from INETUM as a way to build competitiveness

Business Intelligence from INETUM as a way to build competitiveness

Interview with Marek Czachorowski, Head Of Business Intelligence Practice at INETUM.

Interview with Marek Czachorowski, Head Of Business Intelligence Practice at INETUM.

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Business Intelligence is not a new technology. However, how innovative is it in INETUM's proposals?

It is quite commonly assumed that Business Intelligence, abbreviated as BI, is a specific technology. However, it would be more accurate to call BI a process, or even a group of processes aimed at obtaining specific knowledge. BI processes essentially consist in collecting, processing and analyzing various types of data. The objective is to acquire knowledge that will enable the company to achieve greater business efficiency and, consequently, help it build a competitive advantage on the market.

Data analysis techniques change dynamically. First of all, they include simple forms, i.e. data processing by IT teams and providing business with predefined reports. More advanced analytics is conducted using interactive dashboards or self-service platforms. Here, analysts choose the data and how to analyze it themselves. Augmented analytics is the operation of complex and autonomous mechanisms using artificial intelligence.

INETUM follows these changes - implements analytics based on the standards and best practices of the latest analytical solutions available in the cloud or On-premises.

In the past, BI was used under strict conditions. How wide are the possibilities of using BI today?

Access to advanced analytics is now almost universal, and its use is easier than a few years ago. Until recently, the main obstacle in implementing BI was assigning this task to IT departments. Moreover, the threshold for entry into BI was high. The desire to use more advanced analytical technologies meant the need to invest considerable sums in dedicated hardware and software licenses. Now companies have more possibilities to access analytical tools offered in the cloud, which eliminates the need to incur significant expenses on hardware. Also licensing costs can be reduced by access to the so-called open-source solutions - better and better, and the financing model can be solved by paying “in arrears” only for the resources used in the cloud. It is also a good way to test new PoC (proof of concept) ideas.

Today, the scale of BI application is practically unlimited and independent of the company's size. Therefore, small companies and large corporations use advanced analytics - they use it to the extent appropriate to their needs. INETUM supports customers both in terms of the arrangement of the BI process itself, as well as its subsequent implementation, which includes the study of various PoC variants. Our portfolio includes projects implemented for companies from at least 11 different business domains - in the energy, telecommunications, pharmacy, financial, retail and other sectors.

What results from the specific use cases of BI?

The objective is better control over the company's key indicators, which allows to optimize business management, increase market competitiveness or even build an advantage over others. There are many ways to achieve this objective, but the most important ones involve the use of analytics to optimize processes, monitor market factors, e.g. consumer attitudes, actions of competitors and contractors, as well as creating new strategies. For example, if there is an increase in the failure rate of devices in distribution, which worsens the efficiency of operation, the analytics helps to identify bottlenecks and reduce the number of downtimes. In production, the analyst helps to control its quality - when the number of items that do not meet the quality standards begins to increase, BI enables easier and faster equipment diagnosis or reduction of waste or elements for reprocessing. The analysis of the pre-sale areas is conducive to the achievement of the set objectives, and the analysis of the sales itself is the basis for verifying the effectiveness of the strategy - the faster we get a response from the market, the easier it is to correct the actions.

The range of BI systems applications is really large, which results from the transition from predefined systems towards solutions whose operation depends on the needs of specific companies. There is no universal tool that will allow building an analytical platform “out of the box”. In each case of implementation we conduct a thorough analysis of needs with INETUM. We select technologies and design the target architecture of the BI system only on this basis.

In which areas of business BI works best?

Modern business makes decisions based on data analysis. The more data collected and combined, the better. The data comes from various sources - internal systems (ERP, CRM) of customer and web applications, as well as from external systems, such as Google Analytics, Social Media, Web Scraping and many others. Data-driven business organizations become increasingly important. Market strategies and specific business decisions must be justified by data and not rely solely on the intuition or experience of businessmen. Well-designed analytical models are also indispensable help in prediction, i.e. simulating the future market situation.

Analytical systems designed by INETUM operate in many areas of companies, incl. help to optimize production, distribution or formulate conclusions based on data from thousands of sensors in IoT systems, enable the assessment of the condition of machines or indicate the optimal ways of fuel consumption. We help to profile customers and on this basis build personalized marketing campaigns, and then analyze their results. We have implemented solutions for cross-sectional analysis of sales data - from the activity of sales representatives and the achievement of their objectives to related sales results. What an analytical platform can be used for depends primarily on the imagination of people in a given company.

For years, telecommunications and the financial sector have been at the forefront of IT supplier wishlists. And what support from BI can small and medium-sized companies expect?

The most desired by IT service providers are those companies in which many complex IT systems operate, supporting their operational activities and directly responsible for the results of business processes, e.g. systems for transferring data between devices in the telecommunications sector or customer service tools in the financial sector. IT systems are more and more often created on an individual order or as a finished product intended for a narrow range of applications. On the other hand, when it comes to BI, it looks completely different. The analytical tools themselves are universal and can be used in any company, regardless of its size. It is crucial that the design of the appropriate data model (s) enables effective analysis.

Every company is different - it uses and collects data tailored to its business, uses operational tools from many different vendors, and runs only the right, unique business processes. Building an analytical platform that will be effective and will bring measurable benefits requires understanding the meaning of the data at the very beginning, determining how it will be used and, above all, verifying and improving its quality. It happens that it is not enough to collect data in one model to ensure the appropriate quality of data for analysis. It is also necessary to modify the business processes that produce and provide this data, because otherwise its analysis may lead to erroneous conclusions and, consequently, to consider the analytical system worthless.

 

The interview was published on 22 April in Puls Biznesu https://www.pb.pl/business-inteligence-od-inetum-droga-do-budowania-konkurencyjnosci-1148339

INETUM, based on many years of experience in implementing and improving analytical platforms, helps enterprises primarily analyze data in terms of its consistency, quality, access, which is a condition for the effectiveness of the data governance process.

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