Smart data: how decision-makers turn big data into competitive advantages

Smart data - how decision-makers turn big data into competitive advantages

In today's business world, smart data has become a key term for success. Decision-makers are confronted with enormous amounts of data that need to be utilised in a meaningful way. Smart data makes it possible to process big data in such a way that companies can not only navigate the flood of data, but also gain precise insights and use them to strengthen their competitive position. With this strategic approach, valuable competitive advantages can be derived from pure data volumes.

The importance of smart data for informed decisions

Companies today have access to vast amounts of information from a wide variety of sources - from customer behaviour and market trends to supply chain information. But sheer volume is not enough. The quality and relevance of the data is crucial. This is precisely where smart data comes in: intelligent filter and analysis processes are used to filter out only the truly meaningful data. This creates a database that provides precise support for decision-making.

A retail company, for example, uses smart data to better analyse customer expectations and develop personalised offers. This not only improves customer satisfaction, but also noticeably increases sales. Similarly, production companies use smart data to predict machine maintenance cycles and minimise downtime. Service providers, in turn, optimise their service processes thanks to smart data analyses and respond more quickly to customer concerns.

BEST PRACTICE at the customer (name hidden due to NDA contract) an international insurance group integrated smart data into its claims management: by analysing claims in real time and linking them with external data sources, risks could be better assessed and claims processing times significantly reduced.

Smart data: increased efficiency and process optimisation

Smart data provides clear impetus for process improvement in companies in a wide range of sectors. In logistics, for example, the intelligent use of data helps to keep supply chains transparent and recognise bottlenecks at an early stage. For example, by linking weather data and transport information, route planning can be dynamically adapted to avoid delays.

Small and medium-sized companies also benefit from optimising their warehousing: smart data makes it possible to control stocks precisely and avoid overstocking. In manufacturing, smart data management helps to adapt production processes to current market requirements. Car manufacturers, for example, use sensor data from connected vehicles to detect quality problems at an early stage and minimise rework.

BEST PRACTICE at the customer (name hidden due to NDA contract) A medium-sized mechanical engineering company implemented smart data-supported predictive maintenance: this reduced the number of unplanned downtimes by over 30 per cent, while at the same time cutting maintenance costs.

How smart data makes market trends visible

One of the major advantages of smart data is the ability to recognise trends at an early stage. Companies in the retail sector, for example, use smart data to record consumer behaviour and seasonal fluctuations more precisely. This allows product ranges and marketing campaigns to be targeted more precisely.

Companies in the telecommunications industry also analyse network data in real time in order to optimally manage capacities and proactively prevent network disruptions. This improves service quality and increases customer satisfaction in the long term.

Financial service providers also use smart data analyses to recognise market changes at an early stage and flexibly adapt their investment strategies to current risk situations.

BEST PRACTICE at the customer (name hidden due to NDA contract) An international telecommunications provider uses smart data to analyse data streams from network sensors and plan capacities in line with demand. In this way, network bottlenecks can be avoided and customer satisfaction increased.

Practical tips for getting started with smart data

The transition from big data to smart data can be achieved through targeted steps:

• Determination of the relevant data sources in the company and prioritisation according to business objectives.
• Implementation of intelligent algorithms, e.g. machine learning, for automatic data processing.
• Training employees so that non-technical teams can also interpret and utilise smart data in a meaningful way.
• Continuous review and adjustment of data strategies to take account of changes in the market at an early stage.

This approach enables decision-makers to ensure that smart data is introduced into projects as an important success factor and not just as a one-off solution.

My analysis

Smart data is far more than just a fashion trend. It supports companies in making big data understandable and usable so that decisions can be made in a targeted and well-founded manner. Companies from all sectors gain competitive advantages through the intelligent use of data by optimising processes, understanding customers better and reacting quickly to market changes. Decision-makers should see smart data as an accompanying partner in the digital transformation in order to provide sustainable impetus for their growth.

Further links from the text above:

What is smart data? Definition, application and benefits [HubSpot]

Competitive advantages through the use of big data and smart data [Agile companies]

Smart Data - Glossary and advantages [Forcam-Enisco]

Competitive advantages through the effective use of data [GmbhChef]

Smart Data: How companies make better decisions [Konfuzio]

Data analytics - big data as an opportunity for companies [Deloitte]

Smart Data: Competitive advantages through intelligent data utilisation [Sauldie]

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