DATA DEMOCRATISATION: IN ORDER TO REMAIN COMPETITIVE, A SOLID DATA CULTURE MUST BE BUILT, WHICH IS NOT SIMPLY AN OPPORTUNITY TO ACCESS INFORMATION. IT STARTS FROM A NEW GOVERNANCE DESIGN AND TARGETED DATA LITERACY STRATEGIES AND EMPOWERS ALL THE ACTORS IN THE COMPANY
The various definitions of data democratisation have in common the theme of free, fast and easy access to data and the goal of enabling all teams, regardless of their technical know-how, to use critical business information to make informed decisions independently. Data then becomes an asset available to everyone, and no longer just the traditional custodians such as managers, analysts or marketing managers. A model that increases analytical maturity and business intelligence capability in a scenario where more than 99% of companies invest in Big Data (Forbes) but 72% have not yet created a data-driven culture (CF0, 2019).
While 72% of global decision-makers on the topic of data analytics report that their company is implementing self-service reporting and analysis (Forrester’s Data And Analytics Survey, 2022), the efforts being made are still limited: only 26% of the same global decision-makers believe that making more informed business decisions is a key benefit for their organisation or company. A data culture based on the acquisition, democratisation and circulation of data, where every actor can make use of the acquired information to apply the data to their business activities, can radically transform the way companies function. Already 100% of senior analysis decision-makers at advanced level and 93% at intermediate level became aware of the need to invest in the culture of data. If we look at smaller companies, the figure drops significantly (only 58% of respondents at less advanced companies* intend to initiate or have already taken such actions).
Culture, because democratising data does not mean merely accessing data: it is a continuous process, requiring a real cultural change, at all levels of the organisation. Part of this process isData Literacy, defined by Gartner as the ability to read, write and communicate data in a given context, to understand the sources and methods of applied analysis techniques, to describe use cases, applications and the resulting values. By 2023, data literacy will become an essential component in driving business value, as evidenced by its inclusion by decision-makers in more than 80% of data and analytics strategies and change management programmes. An indispensable manoeuvre for digital companies, which are destined not to be able to compete or even to go bankrupt by 2025 if they do not adopt a new approach to data governance and analysis. Modernisation of technology stacks and migration to the cloud, without a data-driven culture, will not be enough.
How to create the culture of data democratisation?
First of all,access: even non-specialists within a company or organisation must be able to refer to the data, a process that can be made easier with analysis tools such as Data Catalogues, Data Virtualisation, Data Visualisation, CRM.
Secondly,interpretation: the aim is not only to provide teams with access to certain data, but also to enable them to understand which resources could really be useful for planning their activities. The type of data required by each team reflects the essential needs: while product teams need to evaluate data to create successful features and functions, support teams require data that can enable the faster resolution of tasks and incidents; the marketing department needs to create engaging content by identifying those with a better conversion rate; sales teams benefit from data that identifies promising potential markets, loyal customers and those to be acquired. Data democratisation cannot therefore simply mean making data available: it must encourage the way in which the available data become comprehensible and usable even to those not skilled in analysis, to the point of making them autonomous and confident in using them on a daily basis.
Third point, governance: for CFOs, the challenge is to maintain a balance between the management of confidential information and a decisive shift away from a traditional ‘closed access’ attitude, in a process that allows the secure use of data by all actors. The security aspect includes the implementation of lean but robust policies appropriate to the various forms of data sharing.
The main challenge to overcome the limitations of outdated corporate governance strategies is to reacha level of maturity whereby data governance becomes not only an organisational, but also a cultural scenario.
Data confidentiality, compliance with regulatory requirements and ethical principles must be combined with advanced software solutions and services that help manage and evaluate the policies and protocols used to access and value metrics.
According to Forrester‘s definition, data governance must therefore include tools for defining data quality, controlling compliance, and assessing security risk management: data governance as a process that deals with the end-to-end lifecycle of data, all the more so if access is facilitated to all actors in the company.
Data democratisation: the actions and good practices to be implemented
For the Alteryx study, the paradox is clear: out of the more than 99% of the companies that invest in Big Data and AI, only 24% of these are data-driven (source: Forbes). So what actions can be implemented to build a democratic data culture in the company?
Adopting data governance solutions supported by technologies such as AI can pave the way for better use of data in companies, improve employee literacy levels, foster collaboration and increase the empowerment of individuals with respect to proper information management.
Data democratisation can only arise from a data-driven, value-creating culture.
According to Forrester, the market for data governance solutions is evolving along with the concrete needs of businesses: whereas traditionally governance was conceived as a set of pure operational actions, with the spread of privacy and data protection laws, such as the GDPR in Europe, today the scope of data governance has expanded to include privacy and sovereignty, and it has become a factor that affects the company’s relationship not only with privacy regulators: from an operational issue to one that also includes the issue of trust.
The scenario widens further with the democratisation of data and its use for improving the business decision-making process.
To begin with, the process can comprise 4 stages:
awareness-raising, with the assessment of the company’s level of maturity and the engagement practices of all stakeholders on the subject of data democratisation; preparation – a time when the vision and strategy are defined and the challenges with the greatest impact on the company are identified – execution and support, with the monitoring of the results achieved and the maintenance of the initial enthusiasm and momentum.
The best practices to be implemented include:
- the adoption of software solutions with simple and intuitive user interfaces to improve data storage and detectability and allow everyone to handle data with confidence;
- the choice of flexible tools that can evolve according to the level of literacy achieved and the advancement of the technology and the infrastructures;
- stimulation of the collection of use cases, administration of surveys on the usefulness of data for certain activities
- training sessions, lectures, TED Talks, events and conferences on the impact of digital transformation, automation and analytics to improve everyone’s skills;
- employee involvement in the process, with gamification activities such as hackathon challenges and moments that help stimulate interest in the topic of data culture.
The benefits of democratising data
Data democratisation therefore means accelerating innovation within the company and improving the decision-making processes by all figures, not just the board of directors. The advantages that can be observed include:
- a more complete view of customers’ and partners’ needs; clarity and transparency on data shared by different departments can help anticipate challenges and new needs,
- less bureaucracy and simplified flows, improved performance and ROI,
- improved real-time decision-making,
- more transparent and satisfying customer relationships: sharing data on certain services can also help customers make decisions and increase mutual trust,
- increasing the attractiveness of the company and developing an environment that evolves with the pace of the tech market,
- engagement of the employees, who become more autonomous, more secure and more satisfied, and
- the parallel development of a culture of data governance and security inside and outside the company.
