Make data-based decisions & maximize profits
The use of business analytics is considered a promising means of making data-driven, profitable decisions for the company. Find out more here:
- In which industries and areas of activity the use of business analytics makes sense
- Which business analytics pitfalls you should be aware of (and how to overcome them with flying colors)
- How your company can best benefit from the use of business analytics
Why business analytics?
Almost every company generates huge amounts of data every hour. Information that companies can benefit from, for example to reduce costs or optimize processes.
By definition, business analytics can help you use this information to find out what is going well and what can be improved - in order to make informed, data-driven decisions.
The aim is to identify trends and patterns and proactively drive strategic business planning.
For many companies, business analytics in conjunction with data science is already considered an indispensable tool for gaining a competitive advantage in the fast-moving business world.
However, most companies are still leaving a great deal of potential untapped because they are either not yet working with business analytics at all or only superficially.
The possible applications of business analytics are quite diverse and range from controlling and process optimization in production to the optimization of marketing campaigns.
The use of modern BI tools, databases and statistical software is essential.
Data-based for optimal recommendations for action
In an increasingly data-driven business world, it is no longer just about analyzing the past or predicting future trends. Companies are faced with the challenge of not only gaining insights from the multitude of available data, but also deriving concrete measures from it that create real added value. The next step in setting yourself apart from the competition and achieving sustainable competitive advantages is therefore the crucial question: What should I do next? This is precisely where prescriptive analytics comes into play - it goes beyond pure analysis and not only shows what could happen, but also provides well-founded recommendations for action.
Our technologies
nedyx®
nedyx® is a low-code platform that enables business apps without programming knowledge. With a drag-and-drop interface and Office-like operation, it offers individual dashboards, chatbots and cloud integration. nedyx® supports flexible planning, operational control and adapts to different business requirements.
Microsoft Power BI
Microsoft Power BI is a data visualization platform that helps companies connect and analyze data from multiple sources. It offers interactive dashboards, real-time analysis, AI-supported functions and is easy to use. Power BI is scalable and secure, ideal for small and large companies.
Microsoft Fabric
Microsoft Fabric is an integrated data platform that supports companies in analyzing and using their data. It enables centralized data management, fast analysis and informed decision-making. With functions for real-time analysis and AI-supported insights, Fabric optimizes the data strategy and increases efficiency.
OBIEE (Oracle)
Oracle Business Intelligence Enterprise Edition (OBIEE) is a comprehensive BI solution that enables companies to create interactive dashboards, reports and ad-hoc analyses. It centralizes data management, integrates seamlessly with Oracle and third-party tools and supports data-based decisions.
FluenceXL/AnaplanXL
The use of FluenceXL/AnaplanXL offers maximum productivity in the implementation of company-specific requirements in the areas of analysis and reporting. Another advantage: IT focuses on the operation of the data platform rather than on the realization of ad hoc business reporting requirements.
Your expert for business analytics
Do you have questions about the technologies used or would you like to discuss your project? Our expert Adrian Liebetrau has years of experience in digitalization projects and will be happy to talk to you without obligation.
Contact us nowThe advantages of business analytics and Intelligence
- Informed decision-making: Decisions are based on data rather than intuition, leading to greater accuracy and reliability.
- Opportunities for process optimization: Identify inefficiencies and bottlenecks to improve workflows and resource utilization.
- New ways to save costs: Reduce unnecessary expenses and optimize your budgets and investments.
- Create competitive advantages: Recognize market trends earlier and identify promising opportunities to adapt your strategy before your competitors.
- Better customer understanding: Gain deeper insights into your customers' behavior. In this way, you can optimize your sales strategy and improve customer satisfaction.
- Proactive risk prevention: Identify potential risks earlier and initiate proactive measures to minimize risks promptly.
- Increase profitability: Make the right decisions for your company that ultimately lead to cost reductions, sales increases and profit maximization.
What are the challenges
are there with business analytics?
- Poor data quality: Incomplete, outdated or incorrect data leads to inaccurate analyses and incorrect decisions. It is better to implement strict data cleansing processes and regular data checks before you start with business analytics.
- Unclear objectives: Vaguely defined objectives or KPIs can lead to inefficient use of resources and a lack of focus in the analyses. You should therefore define in advance what you specifically want to achieve through the use of business analytics. You should stick to the SMART formula, according to which goals should be specific, measurable, achievable, relevant and time-bound.
- Excessive data complexity: Many companies make the mistake of wanting too much at the beginning. As a result, excessive amounts of data flow into the analysis and you get bogged down. It is better to focus on the most important data for you and your goals at the beginning and thus simplify the data structure.
- Insufficient data integration: In practice, we often observe that not all data from different sources is integrated, which leads to fragmented analyses. Use reliable data integration tools and platforms to create a uniform database.
- Incorrect interpretation of data: Misinterpretation of correlations or statistical results can lead to wrong decisions. Targeted and regular training for your teams in business analytics skills, data interpretation and the application of statistical methods can help.
- Ignoring the results of analyses: Unfortunately, we see time and time again that insights gained from analyses are not implemented, leading to missed opportunities. Make sure that the necessary resources and skills are available within your teams to implement optimization measures and work with clear, comprehensible action plans.
Definition: What is business analytics?
Business analytics refers to the systematic evaluation of company data with the aim of making well-founded decisions and optimizing business development. Statistical analyses, data visualizations and modern methods such as machine learning are used for this purpose. In contrast to traditional reporting, business analytics goes beyond the mere presentation of historical data: it provides insights into causes (diagnosis), predicts future developments (forecast) and supports data-based recommendations for action (prescriptive). Companies use business analytics to identify trends at an early stage, improve processes, minimize risks and achieve competitive advantages - data-driven, targeted and measurable.What business analytics methods are there?
The business analytics process consists of several sub-areas:
- Descriptive analytics: Describes what has happened. Typical examples are sales reports, customer behavior analyses and dashboards with current KPI data.
- Diagnostic analytics: Analyzes why something happened. Examples include root cause analyses for declining sales, segmentation of customers who have churned or correlations between product sales and advertising measures.
- Predictive analytics: Predicts what is likely to happen. Typical examples are sales forecasts, risk analyses for lending or the prediction of customer churn - where artificial intelligence can play a key role.
- Prescriptive analytics: Gives recommendations on what should be done. Typical examples include the optimization of pricing strategies, recommendations for inventory management and workforce planning in human resources management. The use of AI is also recommended here.
Where can I use business analytics?
There is hardly an industry in which you cannot benefit from business analytics - provided you approach the topic with the necessary depth of detail. Here are some inspirational examples to illustrate the areas in which business analytics can create real added value:
- Marketing (e.g. target group analysis, campaign optimization, analysis of customer behavior on the website, personalization of offers)
- Finance (e.g. risk management, cost analysis, sales forecast)
- Supply chain management (e.g. inventory management, supply chain optimization, demand forecasting, supplier evaluation)
- Human resources (e.g. evaluation of employee turnover, performance evaluation, employee satisfaction analysis)
- Product development (e.g. market analysis, product performance analysis, product life cycle analysis)
- Customer service: (e.g. analysis of customer satisfaction, optimization of service processes, churn analysis)
When does the use of
Business Data Analytics make sense?
The absolute basic prerequisite for the use of business analytics is that data is available for analysis. In plain language: If no or too little data is collected, even the most modern technology cannot perform an analysis.
- When complex decisions have to be made: Especially in large companies with complex structures, filtered information can be a guide to profitable business decisions. If this applies to your company, you can only benefit from the introduction of business analytics.
- If your success depends on meaningful predictions: Whether forecasting, risk management or procurement, all three of these business areas have one thing in common: the more precisely I can predict possible future scenarios, the greater the benefit for the company. An intelligent business analytics system can help you as a business analyst to take a meaningful look into the future - in a moderate amount of time.
- When process optimization is the goal: Only those who have an overview of their data are able to identify weak points, bottlenecks and waste. Business analytics technology shows you the way to lean, efficient processes that conserve resources and keep value creation high.
- If competitive advantages are to be achieved: In many companies, decisions are still made based on gut instinct. The targeted use of data business analytics gives you direct access to hidden potential in your company - the key to outperforming the competition.
- When targeted cost management is required: If you want to reduce costs in the long term and use your resources more efficiently, the introduction of business analytics can become your most important tool, because: In this way, you can reveal cost guzzlers that would have remained hidden without in-depth evaluation.
Business analytics vs. business intelligence
vs. data analytics
Although the terms "business intelligence" (BI), "business analytics" (BA) and "data analytics" (DA) are often used interchangeably, there are clear differences in their meaning and application.
Business Intelligence (BI) concentrates on the collection, processing and presentation of historical data to support decision-making. The focus of BI is on descriptive and diagnostic analysis that answers questions such as "What happened?" and "Why did it happen?". A typical example of BI are dashboards that visualize current KPI data and comprehensive reporting systems that allow decision makers to act on past data. Business intelligence aims to provide valuable insights into your company's past, creating a basis for data-driven decisions.
Business analytics (BA) goes one step further than BI in that it not only looks at past data, but also attempts to predict future events and make corresponding recommendations for action. BA encompasses descriptive, diagnostic, predictive and prescriptive analyses that go beyond pure data analysis and answer questions such as "What will happen?" and "What should be done?". Application examples include sales forecasting and the optimization of business processes, where BA helps companies to strategically align themselves with the future and secure competitive advantages.
Data analytics (DA) is an overarching term that refers to the processing and analysis of data in a wide variety of contexts. While BI and BA are specific applications of data analytics, data analytics refers to any form of data analysis, regardless of context. It includes both simple and complex analyses that are used in different areas such as science, marketing or the processing of big data. It is about recognizing patterns, correlations and deriving insights that can be used in a wide variety of scenarios.
5 recommendations you should follow to get started successfully with business analytics
- Set clear goals: By definition, the success of business analytics depends on the objectives. So determine in advance what you want to achieve with your business analytics, which areas have priority and which topics should be neglected for the time being.
- Get an overview of the available data and its quality: Check the quality of your data and make sure that it is sufficient for your analyses.
- Prepare your teams: Business analytics does not work without your teams. You should therefore prepare your teams promptly about your plans and get your employees on board for the introduction.
- Evaluate possible business analytics tools and strategies: Weigh up which tools, processes and strategies are already available in your company. We have found that developing customized visual business analytics software is the right decision in many cases, as such a solution brings together the various data sources and interfaces, enables complex analyses at the touch of a button and can be easily connected to external tools such as SAP.
- Get support from professionals: The introduction of business analytics, including software, is a complex process that requires a great deal of methodological, technological and strategic expertise. The best thing to do is to join forces with an experienced team of experts like Partake. If you wish, we can support you from the conception and technical development through to the implementation of your new business analytics solution.
So starten wir gemeinsam
Nach Ihrer Kontaktanfrage nehmen wir persönlich per E-Mail oder Telefon Kontakt zu Ihnen auf und vereinbaren einen gemeinsamen Termin. In einem unverbindlichen Erstgespräch stellen wir Partake Consulting vor – und lernen gleichzeitig Sie und Ihre Anforderungen besser kennen. So schaffen wir die Grundlage für eine Zusammenarbeit auf Augenhöhe und starten anschließend in unser bewährtes 6-Phasen-Modell.
How we develop your individual tool in 6 steps
Phase 3: Technical implementation
Unsere Softwareexperten starten mit der Umsetzung Ihre individuellen Softwarelösung . Dabei gilt: Wir arbeiten eng mit Ihnen zusammen, stimmen uns kontinuierlich ab und sorgen für Transparenz. Auf Wunsch beziehen wir Ihr Team direkt in die Implementierung ein, sodass die Lösung gemeinsam entsteht.
Phase 6: Maintenance & further development
Auch nach der Einführung stehen wir als Partner an Ihrer Seite. Wir entwickeln Ihre Lösung kontinuierlich weiter – mit laufender Wartung, Updates, neuen Features, Prozessanpassungen oder der Integration zusätzlicher Systeme. So stellen wir sicher, dass Ihre Softwarelösung jederzeit optimal zu den Anforderungen Ihres Unternehmens passt.
This is Partake
- Experience since 2007 in the areas of consulting & software development
- Special expertise in the areas of corporate planning, finance, business intelligence & project management
- Experience from over 800 successfully implemented digitization projects
- Professional project management and agile development
- Specialized in digitalization solutions for companies with complex structures
What our customers say
Our projects require a very high degree of customer focus, quality and reliability. This is exactly why we rely on a long-standing partner in Partake. In addition to high flexibility, we value the combination of professional and technical expertise in a very distinctive form.
"For us at DFS Deutsche Flugsicherung, safety and reliability are of the utmost importance. We also have this requirement in the information system and in the digitalization of processes. Our long-standing collaboration with Partake shows us that sound knowledge and IT experience make a decisive contribution to this."
We chose Jochen Brühl (GF) and his team because I was impressed by their expertise from years of collaboration on previous projects. With the help of the low-code platform from their technology partner nedyx®, we can drive our digitalization roadmap forward.
Business analytics: the data-driven path to a successful future
Business analytics can be the key element of a data-driven success strategy for your company - provided the data quality is right and you follow a clear objective.
Are you thinking about introducing business analytics, but are unsure whether your company is ready for this step?
Arrange your free consultation now and we will explain how you too can soon benefit from the advantages of business analytics.
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