Why SMEs should leverage digital data

Data is a rich and complex source of information. It often has significant economic potential for companies.

Three people talking in front of pictograms of statistical data.

Analyzing customer behavior, improving productivity, reducing risk: the utilization of IT data has many strategic and operational benefits for companies. "SMEs have every reason to take an interest in these issues because numerous new technologies have the potential to fundamentally change the way they create value and the rules of the game that apply in the markets," explains Petra Kugler, Professor of Strategy and Management at the Institute of Business Administration at the University of Applied Sciences of Eastern Switzerland (ISM-OST).

This disruptive potential applies in particular to "big data," the extraction, storage processing and analysis of very large amounts of data. "Companies risk missing out on competitive advantages if they ignore these new technologies. New technologies are therefore of great interest from a strategic point of view, but they also lead to fundamental changes in the functioning and environment of companies", continues the expert.

Find your own way of managing data

However, Petra Kugler emphasizes that it is not a question of companies becoming like Google or Amazon, but of finding their own way to manage data. "SMEs need to understand the changes and effects brought about by data, data science and artificial intelligence, and the implications for their own business, for potential or current competitors, or for collaboration with other companies."

There are three main types of data that are useful to businesses. Operational data is used to improve efficiency and reduce costs. Strategic data drives innovation and business development. Finally, data that would not otherwise be used can be sold to generate additional revenue (monetizable data). "Swiss companies currently focus mainly on efficiency benefits from data. This means that there is still considerable potential in using data for the other two types of purposes."

Use of data by all employees

The use and understanding of data should not be limited to the highest levels of a company, says Dominic Schweizer, co-head of the Digital Sustainability Lab of the Public Sector Transformation Institute at the Bern University of Applied Sciences (BFH G): "Each employee should familiarize themselves with this subject because data mining has tangible benefits across multiple day-to-day functions."

The fact remains that data mining often requires a significant initial investment in human or financial resources, without being certain when and to what extent it can generate revenue. "In this respect, there are many courses or tutorials, either on video platforms or specialized sites such as Kaggle, which can be helpful for launching an initial small project for very low investment", underlines Dominic Schweizer.

Resource Sharing

Pooling resources with other companies can also be a promising approach for SMEs. Earlybyte, a Winterthur-based company that develops and creates data platforms, for example for the industrial cleaning robot manufacturers such as Cleanfix and Kemaro, is one such company. For Cleanfix, a manufacturer of water-based cleaning robots, Earlybyte was able to develop a manufacturer-specific platform. The start-up Kemaro focuses on sweeping robots and is a customer of Earlybyte's second platform called "Swarm". Swarm was designed as a multi-vendor platform that will, over time, evolve into an ecosystem for the administration and management of distributed devices and robots for different manufacturers.

"During their operation, the two robots generate information such as duration, area and type of cleaning, battery charge status or errors that occurred during their intervention," explains Remo Höppli, co-founder of Earlybyte. "Once processed, this data is made available to our customers in the form of a cleaning report and can be used in quality assurance, for example."

When addressing the topic of data analysis, it is essential to set clear objectives, says Dominic Schweizer. Another piece of advice from the expert: don't hesitate to turn away from Excel spreadsheets in favor of programming languages such as JavaScript or Python, which make it much easier to solve certain problems. "It is also important to be curious, and not to get discouraged if the first results obtained are bad or unusable, even if it means looking for another way. Remember that while data analysis holds a lot of promise, it is not a magic bullet."


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Creating a data culture

"Our research shows that companies that want to work intensively with data need a change of logic in order to make it more central to value creation," explains Petra Kugler, Professor of Strategy and Management at the Institute of Business Administration at the University of Applied Sciences Eastern Switzerland (ISM-OST). The first steps towards the realization of such a data culture are to raise awareness of the subject within the company, launch the first projects, gather knowledge and develop or strengthen the necessary competencies. "It is also possible to designate a central person who acts as an ambassador in the company and drives the project forward."

Last modification 04.01.2023

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