Data is a valuable raw material for companies when it is correctly processed and evaluated. In these times of big data and digital transformation, the flood of data in varying formats and from different sources poses enormous challenges for companies, their business models and processes.
For data to generate operational as well as strategic added value for companies, it is necessary to capture, integrate, analyze, visualize and manage it properly. A combination of professional understanding and technological know-how is a key success factor. With our Data & Analytics services, we support companies in closing the gap between business and IT, enabling them to benefit from their data.
The use of new methods and technologies is essential to master the many challenges efficiently and effectively associated with the provision, processing and evaluation of large amounts of data. On the business as well as the IT side, structures, processes and components must be tailored and designed for Data & Analytics. For the required technological components, data memory must be flexibly scalable so that analyses and results can be interpreted and easily stored using measures ; visualizations can also be presented in an understandable and appealing way. In terms of organization, it requires agile and data-driven processes, dynamic structures and cultural change. Ultimately, enterprises that digitally transform their organization and business model and derive knowledge from their data enhance their competitiveness.
As Data & Analytics increases in importance for the long-term success of a company, IT managers expect a substantial amount of future investment budgets of German companies will be associated with analytics. While successful companies already benefit from their data and analyses to a certain extent, current studies show that modern analytics strategies have become part of almost all business initiatives. Indeed, 51% of C-level executives of large companies in North America and Europe say that analytics is imperative to maintain and increase market share over the next two years.
Large amounts of structured and unstructured data are generated by various systems, processes and actions within and outside of companies on a daily basis. Technologies such as the Internet of Things, mobile applications, social media, smart homes and connected cars can uncover previously unknown relationships, patterns and correlations and create real added value from existing data. In all business divisions and across all industries, there is a multitude of Data & Analytics use cases for cost reduction, root cause analysis, risk identification, and planning and trend forecasting. The insights gained from data analytics significantly change not only everyday decision-making, but also company organization and business models.
The BearingPoint Data & Analytics team, with its broad, cross-industry understanding of business processes and technological expertise, advises companies at all organization levels and in different business areas on IT-architecture, data management, advanced data analytics and data visualization. We empower our clients to leverage the full potential of modern technologies to develop customized Data & Analytics solutions and generate operational and strategic added value.
BearingPoint looks at Data & Analytics from three different perspectives to provide optimal support for companies to overcome digital challenges.
Together with our clients, we define and implement customized data strategies and suitable organizational structures to enable firm-wide, data-driven decision-making. We support clients in the conception and integration of Analytics and Business Intelligence centers, whereby Data & Analytics processes are firmly embedded within the existing company structure and decision-making is based on insights from data analyses. Aspects such as cultural change, the use of modern technologies, and agile development are taken into account so that these findings and resulting actions create sustainable added value.
Using advanced data analytics, we help companies gain valuable insights. Modern analytical methods such as machine learning, statistical modelling and neural networks are used to identify untapped potential in various applications. Based on the results of the data analysis, unstructured data (“big data”) achieves structured results, leading to lean processes, increased productivity and effectiveness, reduced costs and enhanced customer satisfaction.
Besides developing innovative business models and advanced analytics solutions, we accompany and support the digital transformation process of our clients through the implementation of state-of-the-art technologies. IT architectures not only function as a storage medium but form the basis for leveraging the full potential of data and advanced analyses. By building modern, scalable technologies such as cloud storage and a serverless framework, we ensure our clients’ competitiveness in the digital age.
Our Data & Analytics performance portfolio covers the entire data value chain, ranging from the implementation of IT architectures to data visualization for business users. By pursuing a holistic approach, we coordinate business and IT goals to guarantee a long-term benefit of Data & Analytics initiatives. Our four services include Business Adaptation, Data Engineering, Advanced Analytics and Business Insights.
How and where can data and analyses be used in the company? Together with our clients, we address this question and find solutions for any associated challenges. We identify customer-specific business scenarios for the use of data analyses and define Data & Analytics use cases taking into consideration existing processes and structures.
Data governance guarantees long-term benefits from Data & Analytics projects and is a decisive success factor. However, it is too often underestimated. We holistically define aspects of data governance for processes, metadata management, auditing, data policy as well as compliance with regulatory requirements, such as GDPR.
Successful utilization and budgeting of data is founded on a data and IT architecture that is adapted to users and their requirements. To obtain a broad acceptance and utilization of the embedded technology, these requirements are defined and implemented in close collaboration with IT and other business departments. In addition to data warehousing and cloud computing, our Data Engineering services include data quality management, data gathering and processing, data architecture and data modelling.
We apply advanced data analytics methods that go well beyond traditional business intelligence and performance management to provide our clients with new insights about their data. We follow an agile approach with established data-driven processes that enable early problem identification, direct implementation of lessons learned and ongoing optimization of data analytics.
The use cases of advanced analytics within a company may vary. Certain use cases can be applied across industries while others are only industry-specific or even customer-specific. Our advanced analytics service portfolio is divided into seven categories: predictive maintenance, finance analytics, risk management, marketing analytics, sales performance, quality management and operational analytics.
Data analyses and results become less relevant if they are not easy to understand and correctly translated into the necessary measures. For data-driven decision-making, information must be delivered to the right people at the right time in the right form. By applying our business insights service, complex data structures and relationships become understandable and the results of the data analyses are usable for end users.
We define ourselves as a vendor-independent consultancy: we cooperate with a large network of technology partners, from market leaders to specialist providers, to deliver the best solutions to our clients. We utilize a variety of state-of-the-art data technologies, cloud computing applications, advanced analytics tools and state-of-the-art visualization capabilities.
Tailored to the specific business needs of our clients, we provide technology-enabled data science services along the entire data value chain and deliver powerful applications by either working with and improving existing tools or recommending the right technology to address a specific business problem.