Dal dato grezzo alla generazione di “actionable insights”, garantendo sicurezza, governance ed etica
One of the most overused expressions of the last decade initially appeared on an article in The Economist in 2017, Data is the New Oil. This proves the fundamental role that data, and especially information, plays for companies because of their strategic and monetization potential. It is no coincidence that this statement – Data is the New Oil – is countered by the provocative question: but do you have enough resources to refine it?
Many companies today, strongly attracted by the possibility of extracting value from their information assets – through the application of solutions based on artificial intelligence, machine learning, deep learning, etc. – end up losing sight of some aspects that are essential to ensure the fair, equitable and sustainable use of data, such to enable them to achieve:
• Mitigation of compliance risks
• Cost reduction mainly related to storage and processing
• Sustainability in terms of reducing the CO2 footprint
• Quality of data to be used for AI, Analytics and reporting
• Data protection, with respect to content changes, whether accidental and not
It is possible to identify five steps that companies must include to be, for all intents and purposes, data-driven: first of all, they must define a data management strategy that is functional to achieving the company’s business objectives. Subsequently, they must create trust in the data by those who will have to use them, paying attention to quality, availability and documentation of knowledge, as well as ensuring transparency in the use of artificial intelligence applied to data to avoid the black-box effect. The impact of technologies as enablers for the effective exploitation of data should also not be disregarded. Hence, the need to define developmental paths in application and IT and security infrastructure to obtain increasingly high-performance tools to ensure speed of processing, acquisition of increasing volumes of data, and accurate and reliable answers for the business.
These activities are the prerequisite to obtain “actionable insight” or valuable input for business decision-making processes. That of data is for companies a step-by-step ever-changing journey. In other words, companies must establish mechanisms for constant improvement of their data governance and management model.
The most effective levers include:
- the choice of a functional and “non-invasive” Data-Operating Model (roles, responsibilities, experience-sharing mechanisms, etc.);
- the culture of data across all corporate levels and the introduction of an effective Change Model;
- the introduction of data-sharing mechanisms (Data Monetization to obtain revenue from the sale of data, Data Partnership to generate cross-selling opportunities or offer services closer to the needs of Clients, Data Intelligence to produce value-added services for the business, and sector-specific Data Hubs to remove silos and improve data completeness);
- the definition of a developmental path for the data and IT architecture to make it increasingly adequate to pursue business needs and exploit the potential of analytics for operational components as well (see Command Query Responsibility Segregation (CQRS) architectures).
And, ultimately, the ability to reprocess direct or indirect experiences to feed the model through successful case studies (DOs) and mistakes not to be repeated (DON’Ts).
If you wish to learn more about our approach and review our successful case studies contact our experts.