Data-related offers provide companies with the opportunity to develop new, future-oriented business areas. Companies must create new business models and consolidate their databases for this to work – a time-consuming and cost-intensive task. Promotional banks provide financial support.
Data form the basis for promising business models. This is shown by a study by the Lisbon Council in 2019. According to this, the “data economy” could reach a volume of between $600 and $1 trillion in 2025, depending on the scenario. The data economy is based on value creation models based on technologies such as the Internet of Things, machine learning, and data analysis using big data and analytics.
Data as an opportunity in coordination
The topic of data is relevant for companies from all industries: retail, mechanical and plant engineering, the tourism industry, and many others. Sometimes data is even the basis for a new business idea. Here, a machine learning-based system helps to reduce empty runs. Customers can leave information about their freight on the platform, and the algorithm calculates how it can be optimally divided among one or different transport companies – and at what price. This is how companies and the environment benefit.
Data also play an essential role in ensuring that vehicles can drive autonomously in the future. The basis is formed by sensor and camera data from test vehicles, which are evaluated by algorithms. In this way, the software learns how road traffic works.
Data economy is still with obstacles
Beyond these examples, the data economy is a promising field for medium-sized companies to position themselves for the future. However, for data-based business models to work, it is not only necessary to have a corresponding budget. Instead, companies need both technical and organizational knowledge of data.
Many companies find it challenging to use data profitably. According to a study, 84% of companies are “beginners.” This refers to companies that rarely store central business data digitally and hardly systematically evaluate or process them. The importance of data for their processes and products is often not yet evident for these companies. One reason for this is the lack of resources and the lack of the necessary skills.
To make matters worse, the amount of data in companies is increasing, while at the same time, there is a lack of specialists who can view, process, and analyze such information, such as data scientists.
Start with the business model
Given these challenges, preceding data orientation is not an option with a view to the future. Instead of reacting hastily, it is helpful in the first step to identify potential and develop clear goals for a data-oriented business model. In some cases, customers can function as whistleblowers themselves. According to a report, 74% of companies stated that they had developed their data-oriented business models at customers’ suggestion.
The next step is to view and prepare the databases that are to serve as the basis. An essential criterion for success is to ensure the high quality of the data.
This is done based on criteria such as completeness, consistency, and timeliness of the information.
In addition, it often makes sense to combine the data from different “silos” such as CRM (Customer Relationship Management), ERP (Enterprise Resource Planning), and MES (Manufacturing Execution System) on a central data platform. From the combination of customer information (CRM), data from sales and inventory management (ERP), and production information from the manufacturing level (MES), a company can gain exciting insights to develop data-based services or to make them available to partners and other interested parties.
Financial support
However, collecting, consolidating, and summarizing data on a data platform is complex. In addition to challenges such as legal security when dealing with data, the company also often incurs costs. According to the study of data-driven business models, around 42% of US companies would like financial support to implement complementary products and services.
Such support is provided, for example, by government-sponsored loans. Medium-sized companies can finance the infrastructure development to analyze substantial amounts of data, the development of data-based services, and many other digital projects.
With these loans, companies also can bridge liquidity shortages at short notice. This means that You can use the opportunities of the data economy even in challenging times.
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