Data intelligence as the key to digital transformation
In corporate projects, more and more managers are coming forward with questions about data intelligence. They want to know how they can extract real added value from large volumes of data. The challenge lies in filtering out the data that is actually relevant from a flood of information. Data intelligence helps to organise this flood of information and transform it into valuable insights. This is why KIROI coaching supports teams and managers in implementing their data strategies and developing algorithms that generate intelligent knowledge from data.
The difference between big data and smart data in the context of data intelligence
Companies often come to us wanting to distinguish between big data and smart data, as both terms are used in relation to data intelligence. Big data refers to huge, mostly unstructured volumes of data that are generated continuously. Data intelligence here means not only collecting this data, but also understanding it and using it in a targeted manner. Smart data, on the other hand, is a more focussed version of data intelligence that focuses on data quality and relevance. KIROI projects often show that smart data enables faster and more precise decisions because irrelevant data is filtered out[1][4][7].
In Industry 4.0, for example, machines can produce large amounts of sensor data (big data). With the help of data intelligence and smart data, only those values that indicate maintenance requirements or quality problems are highlighted. This allows production processes to be organised more efficiently and downtime to be avoided.
KIROI BEST PRACTICE at company XYZ (name changed due to NDA contract) A data intelligence solution was integrated in the production area, which only filters out genuinely critical deviations from the operating standards from the extensive sensor data. This allows maintenance staff to react in a more targeted manner and significantly reduces production downtime. Employees report that this accompanying support makes it easier to navigate through the data jungle and provides decision-making certainty.
Data intelligence in marketing and sales: smart data as a success factor
Marketing departments often report that although they have access to large amounts of data on customer behaviour, they struggle to draw actionable insights from it. This is where data intelligence with smart data can help by validating and analysing target group data in real time. This enables marketing to respond more precisely to needs and run personalised campaigns.
Retailers use data intelligence by analysing purchase histories and demographic data. Thanks to smart data, product recommendations can be tailored and stock levels optimised. The transformation from big data to smart data increases sales efficiency and promotes customer loyalty.
KIROI BEST PRACTICE at company XYZ (name changed due to NDA contract) In a retail company, the introduction of a data-intelligent platform meant that marketing and sales teams were continuously supplied with real-time data on customer preferences. This helped to adapt campaigns more quickly and significantly increase sales in key customer segments. The clients report that the coaching project helped them to set up the necessary system landscape in a structured manner.
KIROI's support in the implementation of data intelligence projects
Many companies report that getting started with data intelligence can be challenging. KIROI coaching offers support in identifying relevant data sources, setting up data pipelines and developing algorithms for data analysis. We provide impetus without promising a ready-made solution. We provide support and coaching so that teams can acquire their own skills in dealing with data intelligence and act in an agile manner.
In logistics, for example, we know how data intelligence helps to make supply chains more flexible and transparent. Data on transport times, routes and flows of goods are analysed using smart data in order to identify bottlenecks at an early stage and take countermeasures in good time.
KIROI BEST PRACTICE at company XYZ (name changed due to NDA contract) A logistics service provider used data-intelligent solutions to gain greater visibility of its freight routes. Coaching supported the project team in defining the relevant metrics and selecting the appropriate analysis tools. This enabled the company to react more quickly to disruptions and improve customer satisfaction.
Practical examples and findings on data intelligence in the industry
In the automotive industry, data intelligence enables vehicle data to be monitored in real time. Smart data enables faults to be recognised in good time and maintenance to be planned. This saves costs and improves vehicle availability.
In the energy sector, data-intelligent systems help to analyse consumption patterns and optimise the use of renewable energy. Smart data provides the necessary precision and speed for flexible control.
The importance of data intelligence is also evident in the healthcare sector. Patient data is filtered and analysed in such a way that treatment plans can be better tailored to individual needs. The results help doctors to make informed decisions.
My analysis
Data intelligence realises its potential best when the focus is not just on the quantity of data, but on its quality and usability. The transformation from big data to smart data is an ongoing process for companies, which becomes much easier with support and methodological impulses from coaching contexts such as KIROI. Proven use cases can be seen in various industries that help to reduce complexity and open up new opportunities at the same time. Successful data management means that people, processes and technology work hand in hand to utilise the intelligence of the data.
Further links from the text above:
[1] Big Data vs. Smart Data: Key Insights for Operational Optimisation
[4] Smart Data: definition, challenges and milestones
[7] Big Data vs. Smart Data: Is More Always Better?
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