The concept of digital divide has accompanied entire generations taking on various nuances of meaning with respect to the context and technologies of reference. Today the question of whether or not access to interconnected systems is not only about the Internet or the use of a particular technology, it has much more to do with the ability to learn, analyze, integrate information to improve one’s condition, both as individuals and as citizens or companies.
We have moved from the concept of Digital Divide (ability to access or not to certain technologies) to that of Analytics Divide, understood as the ability to develop meaningful analyses able to have a strong impact on the business of the companies.
The Corporate Analytics Divide
In a business context, Analytics Divide measures the ability to leverage Big Data through AI and ML tools in a strategic data-driven vision, thus becoming the key factor in determining a company’s ability to stand on the market.
The Analytics Divide gap, understood as a gap in analytical competence, is therefore linked to many different aspects:
- Cultural: data-driven culture is a necessary prerequisite, a mental and business management model that must pervade every business area.
- Technology: implement digitalized processes in the company, with appropriate Business Intelligence tools and software to treat information transforming data into important business insights.
- Strategic:s, software, and processes must follow, support, and improve business strategy at every level, both management and operations.
- Skills: research and retain in the company those figures able to apply analysis models to more or less complex issues (from the data scientist to data engineer, etc.).
The issue therefore brings with it a number of other complexities, such as the ability to develop effective Business Intelligence and Analytics systems, with positive impacts on user adoption, within sustainable budgets, involving adequate and competent resources, adopting tailored technologies that generate a positive impact on ROI.
Impact of Divide Analytics for Businesses
Companies that adopt Advanced Analytics systems have many competitive advantages over those who lag behind:
- Process transformation and optimization is a continuous process of continuous improvement. Thanks to AI systems and ML techniques that allow to extract value from elementary, even unstructured data.
- The management and analysis of Big Data allows you to create scenarios and identify new paths. The pandemic from Covid-19 showed how companies that have adopted predictive and prescriptive analysis models have been able to react promptly transforming adverse events into new opportunities.
All this translates into valuable insights for cost containment, penetration of new markets, optimization of productivity and supply chain management, up to the maximization of marketing activities, increase in ROI, revenue and sales.
In short, the companies that will be the first to equip themselves with effective Advanced Analytics systems, are the ones that will first have a great competitive advantage: they can look at new scenarios and predict future events, taking timely and successful opportunities that other companies do not even see.
A paradigm shift based on the ability to have access or not to information of great strategic value, which must be built and to which not everyone has access.
Italian companies and Business Analysis
According to a study conducted by Osservatorio Big Data & Business Analytics of Politecnico di Milano at the beginning of the pandemic, we have moved from a phase in which the competitive advantage was represented by the application of Business Intelligence in the company, to a phase in which the centrality was covered by the ability to access and manage Big Data, to end up today in a context where the competitive advantage is in the hands of those who hold tools and skills of Strategic Data Science.
In short, the ability to do analysis, to act promptly by understanding and anticipating trends and to grab and train competent resources within the company team, are characteristics present in extremely different percentages among medium-sized companiesSMEs and large companies.
While the big brands and dominant players have already invested in Advanced Analytics systems ahead of their time and boasting today a difficult advantage to fill for competitors, SMEs are still for the majority at the beginning of these evolutionary processes.
The majority of Italian SMEs are still in a phase of “immaturity” compared to the adoption of data-driven processes on which to develop Advanced Analysis projects. This means that they are in a condition of “traditional” business model, or that they have just landed in a state of awareness and are taking their first steps.
How to Bridge the Analytics Divide Gap
For these companies, the challenges to face are very demanding, but the road is already marked by those who have travelled before them:
- Dealing with “enabling investments”: the initial step that allows the company to introduce Big Data governance and analysis technologies.
- Implement data analytic models in a data-driven optic.
- Adopt Advanced Analysis tools, both predictive and prescriptive, to generate reliable scenarios and make reliable future forecasts, also being able to automate certain actions in response to specific events/situations.