Learning from data democratization pioneers
Opendatasoft
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Data democratization benefits organizations across all sectors. By sharing data more widely internally and externally companies and public sector bodies improve productivity, increase collaboration, drive greater efficiency and enable innovation.
Data-driven organizations are more agile, make better decisions and are more transparent to their stakeholders.
However, turning data democratization strategies into practice is not always easy. It requires organizations to align people, processes and technology, changing culture and ensuring that data is high-quality, accessible and shared across the organization and beyond.?
To help organizations accelerate their data democratization programs, Opendatasoft recently brought together 5 pioneers from the private and public sectors:
They shared their experiences and best practice, focused on 4 key factors you need to put in place for success.
Create a data culture in your organization to support data democratization?
Traditional organizations have grown up in departmental silos, such as sales, finance and customer service. This structure limits data democratization, trapping information within departments and leading to a culture that prevents data sharing. In many cases there is no common language around data, with different departments using different terms for the same concepts.?
Experts agreed that creating a culture that supports data democratization is a major change project, requiring organizations to go back to common values and provide effective training.
“We are built on several key values: creating connections, sharing to progress and working for quality. The notion of usefulness is therefore very strongly anchored in our DNA. Our architecture and governance around data have been set up in alignment with these principles. Each dataset has a meaning, a use, which has been previously thought out collectively. We do not want to “make data for data’s sake”, but we want it to have a strong use. We therefore systematically identified high value-added data sources in order to create uses and take action. We are moving from the world of opinion to a more enlightened and factual world.”
“Transformation spans several axes. It’s talent, it’s data, it’s tech, it’s the environment. We need to have a 360 degree vision to cover this, backed by a medium-long-term investment that can drive a radical change in practices and culture. Businesses that do not know how to use data have not been supported so that they can benefit from it. When we give people data now, they are not used to it, so this has to change.”
?? Learn more about creating a data culture in our blog .
Structure your organization and governance to increase data democratization
Creating a data culture relies on providing access to the right datasets for all. Achieving this at scale can be difficult. Data is being produced by all parts of the organization and needs to be managed consistently. Centralizing this data management and governance solely within one team can create bottlenecks - to overcome these Schneider Electric has adopted a hybrid approach.
“Setting up consistent data management between very different activities – industry, services, software – is an extremely complex task. We have therefore based ourselves on common repositories so that the systems set up from Paris transform all the Group’s geographic operations too. We use a hybrid model. So we have a central data office that I manage with my team. We take care of the overall data strategy of the company, the definition of the model, and ways of working. And then, we leave the local implementation of these common repositories and common languages to individual businesses. This combines a strong top-down corporate push and a local bottom-up approach.”
? Read more about Schneider Electric’s approach to data democratization in our blog .
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?? Read more about different approaches to structuring your data democratization team in our blog .
Improve data quality to enable data sharing
Often, it is only when data is shared that issues around quality become obvious. Gaps might be found in datasets or they lack descriptive metadata that helps non-specialists to reuse them with confidence. Effective data democratization therefore relies on standardizing data and ensuring that it is high-quality when it is shared internally and externally.?
“Overall the issue of data quality quickly became apparent when we put increasing demands on our data. For example, when we digitized our archives from 1901, we came up against problems as some department numbers have changed geographical area in 60 years. It was therefore necessary to carry out a lot of work on quality, which also influenced the recruitments and skills we brought on board. We now recruit people dedicated to data and trained in agile methods. We have also invested in a standards center and are involved in a number of international standards to help with wider sharing and usage creation.”
“Standardization is essential. To consume data, it must first be created. To create it and to be sure that it is usable throughout the company and for all business models, it must be standardized by adopting common classifications. Then, once it is standardized, it is ingested. This is where technology comes in: it allows us to integrate data and consume it. To ensure the proper functioning of these processes, we have defined certain transversal working rules. My colleagues manage their business priorities, and we work together to structure the data. We are now well structured and we have all the necessary resources to be data-centric.”
?? Find out about the importance of quality and governance to data democratization in our blog .
Create value for your ecosystem through data democratization
Above all, the key reason for embarking on a data democratization is to create value for the organization and its ecosystem. Whether this is to become more open and transparent, to make more informed, faster decisions or to increase collaboration with partners and stakeholders, data democratization will ultimately fail if it does not deliver business benefits.
“One of our key objectives is to do everything possible to ensure that 60% of children can survive cancer by 2030. Data is an essential lever in this fight because it allows us to create virtuous ecosystems to connect health professionals and parents. We have heard a lot about data “at the service of meaning”. I put it at the service of impact. You have to collaborate together to be able to create ecosystems based on relationships of trust. We need to work with data from ministries of health in the countries in which we are present, and we need to work with scientific organizations. This requirement to work jointly with public and private actors is very innovative for highly regulated organizations, such as pharmaceutical companies. So we need to break down silos and work collaboratively to establish this trust-based philanthropy. In terms of our platform on childhood cancer, the idea is that doctors take ownership of it and that, in fact, they can contact the parents and the patients, themselves. Transparent ecosystems are essential to advancing the key causes we are working on.”
?? Learn more about the business benefits of data democratization in our blog .?
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