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Category Archives: Digitisation

Unleashing the Potential: Harnessing MongoDB AI for Enterprise Applications

By | Allgemein, Digitisation, Trends | No Comments

In today’s rapidly evolving digital landscape, enterprises face a myriad of challenges in managing and analyzing vast amounts of data efficiently and effectively. Traditional approaches often struggle to keep pace with the volume, variety, and velocity of data generated in modern business environments. However, with the advent of Artificial Intelligence (AI) technologies, a new era of data management and analytics has emerged, offering unprecedented opportunities for enterprises to derive valuable insights and drive innovation.

Among the leading players in this space is MongoDB, a pioneer in modern, flexible, and scalable database solutions. MongoDB’s innovative AI capabilities are empowering enterprises to unlock the full potential of their data and revolutionize the way they build, deploy, and manage applications. By seamlessly integrating AI into its platform, MongoDB is enabling organizations to leverage advanced analytics, machine learning, and natural language processing to extract actionable insights and drive intelligent decision-making across various business functions.

One of the key strengths of MongoDB AI lies in its ability to handle complex and unstructured data with ease. Traditional relational databases often struggle to accommodate diverse data types and schemas, leading to inefficiencies in data management and analysis. MongoDB’s flexible document model allows enterprises to store and manipulate data in its natural format, enabling them to capture, store, and process diverse data sources seamlessly. This flexibility is particularly valuable in enterprise applications where data formats may vary widely, such as customer interactions, product catalogs, or sensor data from IoT devices.

Moreover, MongoDB AI offers powerful capabilities for real-time analytics and predictive modeling, enabling enterprises to uncover hidden patterns, trends, and correlations in their data. By harnessing machine learning algorithms and predictive analytics, organizations can anticipate customer behavior, optimize business processes, and identify new opportunities for growth. Whether it’s predicting customer churn, optimizing supply chain operations, or personalizing marketing campaigns, MongoDB AI empowers enterprises to stay ahead of the curve and drive competitive advantage in today’s fast-paced business environment.

Another compelling aspect of MongoDB AI is its ability to democratize data science and AI within the enterprise. Traditionally, data science and AI initiatives have been confined to specialized teams with expertise in statistical modeling, programming, and data engineering. However, MongoDB’s intuitive interface and developer-friendly tools enable users across the organization to leverage AI capabilities without extensive technical knowledge. From data analysts and business users to software developers and IT professionals, MongoDB AI empowers a diverse range of stakeholders to explore, analyze, and derive insights from data, driving innovation and collaboration across the enterprise.

In addition to its advanced analytics and machine learning capabilities, MongoDB AI offers robust security and governance features to ensure the privacy, integrity, and compliance of enterprise data. With built-in encryption, access controls, and audit logging, MongoDB provides enterprises with the confidence to deploy AI-powered applications in mission-critical environments while adhering to regulatory requirements and industry standards.

As enterprises continue to embrace digital transformation and strive for competitive advantage, the role of AI in driving innovation and value creation has never been more critical. With MongoDB AI, organizations can harness the power of AI to unlock the full potential of their data, gain actionable insights, and accelerate their journey towards becoming truly data-driven enterprises. By leveraging MongoDB’s flexible and scalable platform, enterprises can build intelligent applications that anticipate customer needs, optimize operations, and drive sustainable growth in today’s dynamic business landscape.

How we apply the SIT Method

By | Allgemein, Digitisation | No Comments

Driving Innovation in digitalisation projects can be tremendously complex. Digitalisation in companies crosses traditional organisational borders and derails traditional responsibilities and processes. In order to guid a digitalisation project and enable to manage the change processes we use a reliable framework of thinking.

To drive inventive thinking in our customer projects we apply a distinct Method: SIT. SIT stands for Systematic Inventive Thinking and applies a Method of Thinking and structure for the Process to drive continuous Innovation and Inventive progress. It applies via the Ripple Model. Below you’ll find a description of the ripple model.

The method can be seen as consisting of five layers:

Thinking Tools:
At the heart of SIT’s method is one crucial idea: that inventive solutions share common patterns. Focusing not on what makes inventive solutions different, but on what, if anything, they might have in common, led to the development of the five Thinking Tools that form its core.

Thinking Tools:

  • Subtraction
  • Multiplication
  • Task Unification
  • Division
  • Attribute Dependency
  • Principles:
    The tools can only work if they are used properly, and in order for this to happen, the tools are accompanied by several principles which allow you to use the tools optimally and reap the benefits.


  • Function Follows Form
  • Path of Most Resistance
  • Closed World
  • Cognitive Fixedness
  • Virtual Product
  • Existing Situation
  • Facilitation Skills:
    Since most SIT programs are conducted not for individuals, but for teams of participants, a range of facilitation skills are needed to complement the content. Some of these are the sort of skills any good facilitator would need, but many are specific to the setting of an SIT innovation workshop.

    Facilitation Skills:

  • Reflection
  • Idea Collection
  • Practice
  • Meta-Cognition
  • Bingo vs. Judo
  • Documentation
  • Puzzles, examples, stories…
  • Project Management:
    This level leads you in the direction of smooth implementation processes for the newly developed ideas. The ability to come up with new ideas is crucial for the process of innovation. However, new ideas are merely the first step in a rigorous process of managing true innovation, since few are the ideas that make it all the way through to the end of the process.

    Project Management:

  • Action Items
  • Idea List Processing
  • Innovation Mapping
  • Convergence
  • Commitment to Deliverables
  • Project Teams
  • Organizational Innovation
    Innovation projects are important, and no single innovation can deliver lasting advantages. In order to grow organically, a company must encourage innovation and creative thinking systematically and continously. Click here and read more.

    Organizational Innovation:

  • Cross Organizational Training
  • Innovation Management
  • Predictable and Measurable
  • Common Language
  • Sustainable Creativity
  • If you are looking for more information on how to manage inventive and innovation thinking in your organisation or if you face challenges in digitisation projects feel free to talk to us.