Data Analytics: How to turn mass into class

It sounds almost too good to be true: Based on comprehensive facts, a company recognizes what customers and business partners want in the future, what quality they prefer and what quantities are needed. The concrete price expectations are also known in advance, even the planned date of purchase. The big data development company learns all this in accordance with all regulatory requirements. If a parameter changes later, the determined data reflects this in real time. In short, all relevant business decisions can be made on a basis that is more resilient than ever before.

What seemed like a distant vision a decade ago is now a reality. Linking statistics with computer science enables big data analytics organizations to process, understand, visualize huge amounts of relevant data – and to get the most out of all this!

What makes big data analytics irreplaceable

A specific algorithmic process is used for the IT, method- and system-based analysis of the raw data from many different sources, which is often available in data warehouses. The aim is to find patterns and connections in the information with so-called data mining that allow conclusions to be drawn about different options for action. Thus, the analysis of correlations in data sets enables entrepreneurial decisions that are based less than ever on assumptions, but all the more on verifiable knowledge. Theories and models can also be verified or refuted in this way.

Fields of application for data analytics in the company

In general, a data analytics consulting company offers solutions for almost all areas of the business. This includes methods, new approaches and tools for controlling the company, as well as providing solutions in business planning, pricing and volume planning, supplier evaluation, auditing and increasing the performance of business processes.

Finance and accounting

Finance Analytics supports predictive action and accelerates processes. It helps:

• identify risks in good time;
• interpret performance deviations;
• open up new potential;
• design processes;
• identify tax risks.

Regulation

Risk & Regulatory Analytics optimizes risk management and improves the visibility. You:

• identify deviations from internal and external regulations;
• support accounting through journal entry testing and statistical testing;
• enable internal control system as well as fraud detection and prevention by means of ad hoc analysis and continuous monitoring;
• enable the use of antitrust and data privacy applications;
• support analyses of business processes in terms of effectiveness, efficiency and compliance.

Customer relationships

Customer analytics enables sales maximization through differentiated customer relationship management (CRM). That includes:

• identifying potential sales opportunities;
• efficiently analyzing customer behavior and customer relationships;
• identifying the risks of customer churn in good timeInitiate targeted marketing campaigns for customer loyalty and new customer acquisition;
• improving products and optimizing pricing.

Personnel management

Workforce Analytics supports human resources strategies by:

• processes in personnel management can be optimized;
• the recruitment and retention of talent is promoted;
• data-driven decision-making processes (for example, employee safety) can be supported.

Sales control

Supply chain analytics allows predictions with regard to demand planning, procurement processes, production and distribution processes. This includes:

• insight into the entire supply chain: from demand to all aspects of sales;
• cost savings in purchasing;
• the early detection of potential disturbances;
• well-founded demand forecasts;
• optimizing logistics.