Collecting and storing data will represent a cost alone for companies if they do not organize themselves to start Data Intelligence processes, i.e. that set of practices and tools which allow the right datum to reach the right person at the right time. An IDC survey shows that 80% of the time an organization dedicates to data is spent on management activities, i.e. for research, preparation and protection, while only 20% is dedicated to analytical activities to extract value and information.
This IDC statistic does not contradict those provided by the Milan Polytechnic Observatory which, speaking in particular of SMEs, show that only 7% of companies has begun Big Data Analytics projects, while 4 companies out of 10 declare that they carry out traditional analyses on company data. If you look at the technological awareness and maturity of small and medium-sized enterprises, still based on the Observatory’s data, it emerges that 10% continues to have little or no understanding of what the advantages given by analyzing Big Data could be. If we look at the reasons for this limited approach, we see that around four out of ten companies (42%) do not activate Data Intelligence processes due to a limited vision of the phenomenon or to a lack of resources to carry out technological investments.
“Companies’ business priorities – explains IDC Italia research and consulting manager Diego Pandolfi – are today focused on improving customer experience, developing new products and services, time-to-market and on accelerating the decision-making processes. Data are at the center of these strategies, but they continue to grow exponentially and it becomes increasingly difficult for companies to navigate within this complexity. A correct and efficient management of data can therefore actually influence in a positive (or negative) manner the effective achievement of the corporate objectives. Data Intelligence tools are able to provide support both to business lines and to IT in order to achieve a better knowledge of the data, an effective governance and a correct protection, including through innovative automation, collaboration and machine learning features”.
Why Data Intelligence?
Appropriate Data Intelligence tools and procedures can enhance the company’s ability to find data more easily and to understand their context and properties for an improved use, with the result of “freeing up” more time for the analytical phase. By using Artificial Intelligence and Machine Learning applied to metadata, Data Intelligence could also allow companies to reverse the proportion, allowing 80% of the time for in-depth analysis and investigations, and only 20% for management activities.
Data alone do not make the difference. Transforming data into value requires appropriate technologies, but also a vision of the opportunities which the data can offer, the whole inserted in an architecture able to ensure scalability, speed, protection and flexibility. Therefore, a degree of awareness concerning the power of Big Data Analysis is necessary, and this is not always found among entrepreneurs. The Retail Transformation survey, carried out by the Digital Transformation Institute and the CFMT in collaboration with SWG and Assintel, shows how 41% of companies interviewed declares that Big Data Analytics processes are not applied in their client companies. A situation that changes if looked at with a three-year perspective, where 52% of client companies states they want to invest in this.
“Many companies have approached the Big Data topic starting from technology – explains Grazia Cazzin, head of the Big Data Engineering Competence Center offer -. This has generated data collections with no objective and with an incorrect positioning of the problems: the issues regarding data governance and quality, which always accompany data, increase exponentially when we talk about Big Data, but this awareness is coming a little late. Data Intelligence as a support to these problems is an important element in the value chain of the datum, but only intentionality steered by a business objective allows organizing in cascade the right actions of evaluation and data collection, necessary to produce the factually usable and truly useful information distillate. For this reason, especially at a SME level, it is necessary to work with the business sector towards a culture of discussion, which stimulates value-added scenarios that allow unlocking the information potential of the data, otherwise destined to remain confined to a theme of costs”.
What is required to start Data Intelligence processes?
The IDC report explains that in order to analyze data and transform these into information, in value and therefore into a competitive leverage, it is necessary to know how to store them, how to keep them univocal and integral, how to make them classifiable and extractable, networkable and distributable. In the digital transformation era, almost all organizational roles use data to make informed decisions in everyday corporate processes. Exploiting Data Intelligence to improve the life cycle of data management and analysis means increasing the efficiency and productivity level of many company figures. And even a small margin of improvement by each figure can lead to a significant increase in company performance.
“The IDC research results – explains Stefano Epifani – only confirm two facts: the first is that we often tend to confuse things, in turn the symptom with the cause, the goal with the tools to achieve it, or the process with the result, it doesn’t matter which; the second is that we must never think that technology will get us out of trouble. As regards the first point, in recent years, all too often organizations have concentrated on collecting data in a completely a priori manner, sometimes explicitly declaring they were doing so even without knowing what such data would be used for. In a Big Data Analysis perspective this is not a bad thing in itself, mind you, but sooner or later the time to ask yourself the questions must come, otherwise Big Data or not, there’s no excuse. In other words, if we do not apply any “intelligence” (human or digital) to the data, these inevitably will not produce value. And this intelligence cannot be disconnected from business logic and from those who develop such logics: that is management. As for the second, instead, nothing is more harmful than thinking the company’s problems (whether market, organizational, management) can be solved by shots of technology. If such shots do not correspond to an analogous application (to remain with the metaphor) of a deep reflection on the meaning that these technologies have and will have on the market, organization and management, at best, no positive results will be obtained… at worst, well it is better not to think about the worst”.
Data Intelligence, according to IDC, also improves the set of operations concerning data, allowing for example, an improved application of the company’s access, use and protection policies, or of raising the levels of availability and resilience. Not to mention the activities aimed at improving the quality and integrity of data and at avoiding cases of duplication, inconsistency and inaccuracy.
“There is no value in the datum without correlated intelligence – concludes Epifani -. Sometimes we focus on the value of data without thinking enough about the fact that the true value lies in knowing how to use these. This is why it is essential to promote a true culture of data in all types of organizations. After all, this is why we created Ingenium all those years ago: because how data are used, the algorithm development methods, the impacts that all this produces must be the focus of thought concerning the role of digital transformation!”.