Today, decision-makers are faced with the challenge of gaining real insights from huge amounts of data. Smart analytics is the key to getting the most out of big data. Intelligent analysis methods not only allow historical developments to be understood, but also future trends to be predicted. Companies in all sectors use these technologies to optimise their processes and make well-founded decisions. Smart analytics helps to translate data into concrete recommendations for action.
Why smart analytics is important for decision-makers
Decision-makers are often faced with the question of how to draw the right conclusions from a flood of information. Smart analytics offers a clear answer here. It is no longer just about collecting data, but analysing it in a targeted manner and converting it into decision-making aids. This enables companies to react more quickly to changes and adapt their strategies.
Example from industry: A manufacturer uses smart analytics to reduce the downtime of its machines. The analysis shows when maintenance work makes the most sense. This increases productivity and reduces costs.
Another example from the healthcare sector: Hospitals are using smart analytics to better predict staff and material requirements. This enables them to avoid bottlenecks and improve care.
In retail, smart analytics helps to understand customer behaviour. Companies recognise which products are particularly popular and adapt their offers accordingly.
Smart analytics in practice: fields of application and examples
Smart analytics in building management
Smart analytics is used in building management to optimise energy consumption and space utilisation. Sensors provide data that is analysed to identify potential savings. This enables operators to make their properties more efficient and sustainable.
A property company uses smart analytics to monitor the occupancy of office space. The analysis shows which spaces are rarely used. These spaces are then repurposed or rented out.
Another example: a hotel uses smart analytics to reduce energy consumption. The analysis shows when it is best to switch on the heating and lighting. This saves the hotel money and protects the environment.
A third example: a hospital uses smart analytics to increase security in the building. The analysis shows where additional monitoring is needed. This helps to prevent accidents and break-ins.
Smart analytics in marketing and sales
In marketing and sales, smart analytics helps to better understand the target group. Companies recognise which campaigns are successful and adapt their strategies accordingly. This increases efficiency and sales.
An online shop uses smart analytics to analyse the purchasing behaviour of its customers. The analysis shows which products are often bought together. Targeted offers are then created.
Another example: An insurance company uses smart analytics to measure the satisfaction of its customers. The analysis shows where improvements are needed. Targeted measures are then taken.
A third example: a telecommunications company uses smart analytics to assess the quality of its mobile network. The analysis shows where improvements are needed. Targeted measures are then taken.
Smart analytics and the role of artificial intelligence
Artificial intelligence plays a central role in smart analytics. It makes it possible to recognise complex data patterns and make predictions. This enables companies to act proactively and capitalise on opportunities.
An example from logistics: a haulage company uses smart analytics with AI to plan the best routes. The analysis takes traffic, weather and other factors into account. This makes deliveries faster and more reliable.
Another example: an energy supplier uses smart analytics with AI to predict electricity demand. The analysis takes into account weather, consumption and other factors. This enables the supplier to plan generation better.
A third example: a financial services provider uses smart analytics with AI to recognise cases of fraud. The analysis recognises suspicious patterns and warns of risks.
My analysis
Smart analytics is an indispensable tool for decision-makers who want to get the most out of big data. It helps to translate data into concrete recommendations for action and make well-founded decisions. Companies in all sectors use these technologies to optimise their processes and strengthen their competitiveness. Smart analytics is not just a trend, but a forward-looking method for generating real added value from data.
Frequent questions from the field show that many companies need support with the introduction and use of smart analytics. transruptions coaching supports projects relating to smart analytics and helps to find the best solutions for individual requirements. Clients often report that smart analytics gives them new impetus for their strategy and enables them to organise their processes more efficiently.
Further links from the text above:
Smart data: How companies make better decisions
What is smart data? Definition, application and advantages
Definition, examples and strategic advantages
Smart Analytics | Customised solutions for companies
Smart data: definition, application and difference to big data
Smart analytics: making numbers fun
Smart data: building intelligence through analytics
Introducing: Smart Analytics with Flexopus
Smart data analytics: How to master KIROI step 3 with
What is smart data and how does it work?
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