written by Marco Belmondo (Chief Marketing Office at Datrix group)
Data Driven Business Strategy: what does it mean? We can try to define it as a series of tactical and strategic choices that lead to transform business decisions in a data-driven perspective, at all levels. Undertaking this transformation involves numerous changes which involve not only the IT and technological functions but the whole company, transversally. Pursuing a data-driven strategy means introducing Data Science into the company. Data science allows to develop advanced analyses and models, in order to extract useful information from data. The aim is not only to monitor the current situation (using a descriptive approach) but also to predict future variables and to address the right choices.
Which aspects should you consider in order to develop a Data Driven Business Strategy? Mainly four, let’s see them together in this article. First of all: data, raw material. The first question to ask is: do I have the data I need? Companies are often overwhelmed by data but often they are not fully aware of it or they have not organized them in the right way. Therefore, it is crucial to a invest in Data Governance, i.e. in all those activities, both technological and organizational, that lead to data integrity and good data quality. Secondly, or even contextually, it is appropriate to invest in Data Integration. This means – as we will see in the next paragraph – having technologies that can support the integration of data coming from different systems and related to different processes (eg. Marketing, Administration, Human Resources).
First of all the raw material. The first question to ask is: do I have the data I need? Companies are often overwhelmed by data but often they are not fully aware of it or they have not organized them in the right way. Therefore, it is crucial to a invest in Data Governance, i.e. in all those activities, both technological and organizational, that lead to data integrity and good data quality. Secondly, or even contextually, it is appropriate to invest in Data Integration. This means – as we will see in the next paragraph – having technologies that can support the integration of data coming from different systems and related to different processes (eg. Marketing, Administration, Human Resources).
Technologies are obviously an essential component to develop a Data Driven Business Strategy. However, it is not easy to choose the right software. It is common knowledge: the ecosystem of data management and analysis technologies is truly diverse and constantly evolving. By the way, the Analytics market is growing by more than 20% – as Italian and international analysts tell us – and, coherently, the technological offer is in continuous innovation.
We cannot go into details in this article, but it is appropriate to highlight three characteristics that a modern technological infrastructure cannot avoid considering:
– Performance: dealing with increasingly important amounts of data, the issue of software performance is extremely relevant, both from the point of view of storage and data processing phase, at different levels.
– Flexibility: one of the hottest technological topics, despite its long life, is Cloud Computing. Cloud services play a primary role in the field of data analytics, as a company can access state-of-the-art software and potentially infinite computing resources, adaptable to use.
– Multiplicity: especially in the specific perimeter of data analysis, there is not a single tool nor a single programming language to use. Data Scientists work with different software and languages, as well as access to data must take place in different ways, depending on the technical skills and needs of the user.
Skills and Organization
Skills can reveal to be the most critical aspect. A few years ago, the Harvard Business Review cited the Data Scientist as the sexiest job of the 21st century. However, it must be said that – particularly in Italy – finding Data Scientists is not easy. Caution! The initial idea should be the creation of a team, in which to identify first of all Data Analysts, less specialized roles in areas such as statistics and Machine Learning. Those figures are easier to be find, and they can manage and develop advanced reporting activities, building dashboards and increasingly complex monitoring dashboards. Secondly, once the traditional Business Intelligence is well established at least in some business processes, it will be possible to start more innovative proof of concept, for example through the support of external consultants.
When the first experiments have already brought good results, it will be appropriate, in the path towards the Data Driven Business Strategy, to structure the company itself at an organizational level, in order to make the most of one’s resources and skills in the Data Science field. In some companies, it is preferable to keep Data Scientists in company functions, so that they can be more domain-specialized, in other cases, companies build Data Science team that offer transversal support, favoring community building and specialization in terms of technical skills.
Technical skills, advanced technologies and data collection and management: all essential elements. However, cultural change issue, or change management, is often underestimated.
To become a data driven company, it is essential to involve as many people as possible in a new approach and language. For what purposes? Greater ability to understand and interpret data, greater habit of using data in making decisions, greater autonomy in seeking the necessary information.
Data Driven Business Strategy: is it worth?
To conclude, let’s recall the main reason why it is important to adopt a data-driven strategy. Making decisions based on increasingly updated and heterogeneous data allows you to acquire a competitive advantage, through reaching new customers or optimizing costs.