Govt v s Deloitte, which is better

Innovation excellence

Data Innovation Services

Data Driven Innovation are innovative projects that arise from trends or correlation with data. The impact can lead to new economic opportunities and greater efficiency. The use of a wide variety of data sources can also show an understanding of dependencies and present company processes more transparently and thus support the decision-making process.

Whenever a product is created, one thinks about solving a problem, changing the perception of a brand or even an entire industry. Disruptive innovations such as the Uber or Netflix business model are also part of it. Whatever the reason, the goal is always innovation. Using data does not have to involve complex data science methods. Product innovations can already be produced with a simple data analysis such as A / B testing, open innovation and the like.

 

Avoid data silos through collaboration

In practice, it is often the case that data, product, marketing & innovation departments keep data and insights to themselves instead of exchanging them. A complete overview can only be achieved if all relevant data can be consolidated and analyzed. On average, data is lying around in 17 different silos and is not linked to other data sources. So often this situation arises here:

 

Data can create added value

  • Map and measure business performance
  • Provide a better basis for decision-making
  • Segment customers and create personalized products and experiences
  • Drive product development
  • Bring about innovations

In every industry

  • Health care: Health data to improve clinical tests, provide individual medicine and better analyze disease patterns
  • Public sector: Reduce administrative costs, open data / open government for better transparency of political and social aspects, better allocation for funding programs
  • Finance and Insurance: Improved customer service, fraud detection, more efficient operational processes, identify risk potential and proactive management, personalized customer care
  • Media and Telecom: effective discovery and delivery of media content that enables users to interact with dynamic channels across all channels, value creation with inclusive personal location data that enables smart, personal content
  • Trade: for interactions between retailers and consumers. Productivity and efficiency increase, impact on cross-selling activities, location-based marketing, analysis of in-store buying behavior, customer sentiment analysis, optimization of the multi-channel consumer experience, supply chain optimization, etc.
  • Productions: Smart factories - product optimization, Industry 4.0 with increased efficiency in production and quality, as well as distribution, predictive maintenance for new business models
  • Energy and Transport Sector: Monitoring and optimization of the logistics and transport network by consolidating various data sources, optimizing the supply and demand side of energy networks.

Data value chain

We help you to fully exploit your data potential. The basic requirement is that your internal company structures and processes enable data-based value creation. For this purpose, for example, ERP data, CRM data, web tracking and transaction data should be available integrated, which serve to increase the customer experience or bring about innovations.

Then we apply a process mining methodology. Here we look at internal company processes and visualize them. This enables us to evaluate data together with your processes in the next step. This results in potentials and fields of action that are adapted to the customer experience of your personas.

Together with you, we create a data innovation strategy that is based on processes and data points in the value chain. Through this we stabilize company processes, close data gaps and create new products, services and business models together with you. In the last step, we look together at how your data can be used strategically in data ecosystems in order to exploit the market potential here as well.