As companies focus on generating differential experiences for their customers, business models are undergoing profound transformations. Artificial intelligence (HE), el big data, predictive analytics, prescriptive and augmented and other emerging technologies (like cognitive systems) enable us to generate disruptive changes and innovate, not only at the level of services and products, but directly in the ways in which the activity of companies is structured and planned.
Whatever the case, do not be confused: what is at the base of this revolution are not the technologies themselves, but the data. And what really makes the difference is the ability to turn data into intelligence, In other words, in valuable information for decision making.
How to do it?
As raw material with which artificial intelligence algorithms work, data is a critical asset for today's companies. But for them to add value a data optimization procedure must be undertaken, What does it mean to be able to store them?, debug and transform them in such a way that it goes from big data (big data) to smart data that adds real value (smart data ). This is key, since the quality of data and the way it is processed will define the ability of companies to harness the potential of disruptive technologies, both in terms of innovation and operational improvements. Successfully adopting and managing data in all its forms is an essential prerequisite.
According to Forrester's research, truly knowledge-driven institutions are growing at an average of more than 30% annual. These data-driven institutions dominate their industries and create new markets by generating practical insights through data collection and analysis.. In reality: an organization data driven puts data development and analytics front and center of your business strategy.
It may be of interest to you: Artificial intelligence at the service of data management
Stones on the road
A to study recently revealed that progress towards these goals is slower than expected, and that even leading corporations seems to be failing in their efforts to become data-driven companies. This poll discovered that even though the 92% is accelerating your investments in big data, analytics and artificial intelligence, the percentage of companies that identify as supported by data is only 31%.
Another interesting fact emerged from this investigation It is that the main obstacles do not seem to be technological (since only the 7,5% mentioned technology as the central challenge), but cultural: the 93% of respondents identified people and processes as the main obstacles to becoming a data-driven organization.
Data to power
Faced with such a scenario, How to make data truly valuable to the company?
√ The inevitable first step is build a data culture within the organization, that must go from top to bottom and penetrate the business.
√ To make data-driven optimization part of your daily operations, it is imperative to create a data strategy. It's not just about installing the right tools and apps, but to put data and analysis at the base of all business decisions and be adopted at all levels.
√ Improving the data literacy of the workforce is vital to unleashing creative potential and moving towards innovative use of data. 
√ To make better decisions, it is essential that the data is available to everyone within the organization and that the tools to analyze it are also available. Allowing workers from different areas use the right data at the right time, data can enrich and improve decision making and provide substantial competitive advantages.
√ Obviously, the first thing is to start use the data they already have. They should know what data sources are available, both structured (In other words, duly parameterized data) as unstructured (comments in forums or social networks, call recordings, etc.). After, you can also create meaningful collaborations with other institutions to leverage external data.
√ Most often, companies suffer from a certain lack of data integrity. Therefore, it is key to move towards a better data management and governance.
√ Note that data analysis will no longer be a separate instance of daily operation: will be integrated, both at an operational and commercial level. Y, for the analytical advantage that all companies are looking for today, well designed control panels will be needed.
As the digital age advances, the need for institutions to guide their operations and decisions informed by data will become increasingly imperative. In this aspect, investing only in technology is insufficient. As we saw, the process of becoming an organization data driven with the ability to turn data into decision intelligence is challenging and needs to be addressed in depth and strategically.
In your company, Are you taking control of culture change to be a true data-driven company? Then this e-book is for you:
