It is no news that data represents a key asset for companies, today even more important in supporting digital transformation and data-driven innovation. The innovation of processes, products, and ways in which companies can grow in new markets has as allies new tools for doing data analysis, processing big data, and usefully applying artificial intelligence and machine learning algorithms (AI/ML ). The ability of modern companies to adapt quickly to new needs, identify new customers, and proceed on a path of continuous improvement depends on the appropriate use of technologies and data through data-driven innovation.
Table of Contents
From data-driven enterprise to data-driven innovation
Compared to the classic data-driven business concepts in which the company’s ability to optimize current processes and activities using data is at stake, data-driven innovation refers to the use of data analytics to guide the evolution of strategies, products, and corporate organization over time. Data-driven innovation feeds on the most varied datasets, both internal to the company and external ( open data and private sources). Depending on the type of business, it can be important historical data, big data, geospatial information, real-time updated data from IoT sensors, or user interaction with online services. While the information needed to improve existing products and services is obtained from the analysis of internal data, it is above all from external data sources that it is possible to identify new businesses and exploit company capabilities in new markets.
Data-driven innovation: the necessary steps
Data-driven innovation takes advantage of the availability of data from different sources, made usable through integration, cleaning, and anonymization (in the case of sensitive data relating to people). Therefore, the ability to make information relevant through advanced analytics and AI/ML algorithms is paramount. This is possible with new-generation systems, high-performance computing (HPC), and cloud services that can be exploited in an as-a-service logic for the most advanced processing. As an HPE partner, the skills of our specialists allow us to follow projects concerning data integration and security, data storage, recovery/backup, and data center refresh. Experience with these technologies and skills in cloud services ( Microsoft Azure and Microsoft 365) to ensure data availability and performance.
How data-driven innovation is realized
Data-driven innovation requires strategic vision, the ability to benchmark potential markets, and an understanding of how to exploit data sources to exploit them. Therefore, an action plan is needed that sets priorities according to the obtainable benefits and makes the entire project economically sustainable. Finally, it is necessary to redefine organizational models and introduce new skills, technologies, and algorithms for starting POCs.
Examples of data-driven innovation
In some cases, data-driven innovation that brings new profitability concerns the ability to transform existing company data into a product to be sold or new digital services accessible via API. This is the case, for example, of mobile phone companies that sell (anonymized) cell data to third parties who use it to find out how many people frequent public places, shopping malls, or what the billboard audience is. In other cases, innovation is functional to the launch of collateral businesses, for example, in predictive maintenance by exploiting data from IoT sensors and AI/ML algorithms. In general, data-driven innovation is a hot topic for R&D departments today of companies, for the teams responsible for optimizing production and delivery as well as in the marketing departments solicited to create tailor-made proposals for the customer.
The right partner for your data-driven enterprise
As Netmind, we have experience in managing complex projects to support medium and large Italian companies in various sectors. Throughout our history, we have carried out strategic IT consultancy activities, infrastructural renovations capable of enabling digital transformation, promoted the adoption of digital collaboration and workplace tools and developed portals and software integrations to meet the needs of digital transformation and data-driven innovation of our customers.