We are launching a miniseries of three articles dealing with ‘Data Democracy’. First and foremost a cultural subject in full swing, it deserves to be experimented within companies of all sectors and sizes.
Behind the rights of Data Democracy, we address what employees should expect from their company in regard to engaging in data or digital transformation.
In the short to medium term, this may not be a problem, but in a more engaging way, and in the long term, a committed employee wants some form of recognition. A ROI is not only financial, it is human.
Some companies are investing in the deployment of data streams through functions. Employees wishing to play a role in data can embark on a job that has value for the whole organisation as it is recognised by human resources, in addition to the managerial lines.
Without this, there is no point in building objectives on the margins of responsibility with an employee if he or she gains nothing but glory. What happens to a Data Manager or Data Steward after a few years of loyal service?
These are all challenges that organisations and their human resources need to address or they will struggle to attract talent and struggle to retain the talent they have built.
Before playing a role, or even taking on a function, mastering the level of commitment is essential. This commitment can be assessed through the capacity or bandwidth of an employee, depending on the challenges of their new responsibilities.
With little hindsight, it is difficult to define the workload of a Data Quality Manager or a Data Owner.
The team and the organisation in which an employee is working must be able to allow for the experience and test the time necessary for the position to function properly. Agility is a good lever to implement these principles. A Data Steward could start their activity on a small part-time (⅖) basis and, with the resulting KPIs, measure the added value. Then the Data Steward and their team could comfortably move on.
A data steward is often a cross-functional position, even if they work in a silo. Indeed, it will depend on their business and IT. So, depending on the context, the workload may change depending on the urgency. These include data quality issues associated with regulatory, financial or customer risks.
This recognition and capacity is not necessarily congruent with the issues of the employee’s line manager. The example of the data steward is also relevant here, as they are often in an operational team on the business side. Their manager is therefore the leader of this team. However, the objectives of the Data Steward rather more feed the challenges of the CDO.
For relevant and mutually beneficial commitment, reporting should be managed through two channels: the operational manager and the CDO channel.
‘The challenge of skills transformation is particularly relevant for knowledge workers. And it seems obvious to me that today’s managers will not be competing with AIs… but with managers who know how to use AI. And this will happen very quickly.’
This is why the communication effort is twofold. Top-down communication across the entire data community, represented by the roles and functions played by many employees, so that the data community has a continuous grasp of the company’s strategy. And a bottom-up communication so as to show the efficiency of the strategy and operational data engaged to meet the challenges of the business strategy.
Feedback is then given at all levels of the organisation. From the bottom up, from the top down, or transversally, feedback is the key to the successful deployment of a data driven culture. This will be the strength of a living data community.
In a large and complex organisation, the fact that Data Quality Managers can meet to share practices and problems in a co-development logic brings value to the whole company: risk reduction, ideas for innovation, consolidation and optimisation of processes, etc. Data is an ingredient that can solve many things.
From the above points, it is fairly clear what the objectives and constraints of an organisation are. But this is still not enough.
To guarantee the operability and efficiency of its data community, a company must think about support and training for these new roles and professions. While an organisation can rely on the initial training of a young employee, it must make efforts to develop the skills of experienced employees. Professional, in-house or external, training courses on the data professions are developing in a rapidly expanding market.
Another strategy, even more effective, is to rely on the natural rise in competence of the data community, which will grow in a concentric manner. The company can then simply (but even more rigorously) form its first circle so that it can form the next, and so on. But beware, this practice must absolutely be accompanied by an approach to its KPIs.
Finally, as good tools make a good craftsman, either the limit of human capacity or the need to industrialise is reached quite quickly. A strong data community will be able to support IT in providing tools which, in a UX/Design Thinking approach, will meet the needs of the business and data strategy.
They’ve been talking about it for some time
Fierce Healthcare – on Google, Fitbit and access to personal data
‘[…] “Google could also use Fitbit’s data to establish a dominant position in the digital health or related markets, thereby depriving its competitors of the ability to compete effectively. This would reduce consumer welfare, including by degrading data privacy options, limit innovation and increase prices,” the consumer groups said.
Regulators must assume that Google will in practice use Fitbit’s unique and highly sensitive data set in combination with its own, especially since it could increase its profits, or regulators should impose strict and enforceable limits on data use, the groups said. ”
Original source: https://www.fiercehealthcare.com
Justine Morin, Business Leader
‘For me, data democracy is a model, or a movement, that makes it possible to raise the awareness of all the players in an organisation, whether they know or not, in order to involve them in the definition of a roadmap and a data culture in the broad sense.’
Simon Grimaud, Business Leader
‘In my opinion, Data Democracy represents a dynamic system in which data is shared and accessible by all. A body is responsible for governing all this data, in order to ensure its quality and availability. Each individual within an organisation is then responsible for his or her own data and can interact with the data of others in order to continuously improve its quality.’