Ryan Ramdien, Programme Manager Data Governance at Waterschap Vallei & Veluwe, on Data Governance

Many organisations have run a data quality or data governance project at some point. The number of companies that achieve lasting results, however, is small. That is because rules are often imposed on employees without asking the obvious question: how can I make your work easier? Ryan Ramdien shares advice on how to make your data governance project succeed.

Ryan Ramdien currently works via Data Talents as Programme Manager Data Governance at Waterschap Vallei & Veluwe. The situation he finds there is not unique, he says. "The water authority has enormous amounts of data on pumping stations, locks, water treatment plants, weirs, dams, water levels and so on. It is data from process automation, data captured in Excel, data from all sorts of applications. The systems were never built to exchange data and the organisation is searching for how to facilitate that. They realise it is about measures on the technical side, but first and foremost in the organisation."That is why the water authority brought Ryan in as Programme Manager Data Governance. His task is to play a connecting role. Ryan works at Data Talents and, in addition to the three-day Certified Data Management Professional (CDMP) Fundamentals training at Connected Data Academy, also took the one-day specialist follow-up trainings CDMP Data Quality and CDMP Data Governance.

The importance of a thorough inventory

One of the lessons Ryan took from the trainings at Connected Data Academy is that data governance requires a cultural change. "Projects overrun nine times out of ten because so much time goes into getting the data in order. Many companies then think IT can fix it. They do not realise it is an organisational problem," he says.That is why a good start is half the work. "In practice that means a lot of talking," he laughs. "With managers, with data engineers, but above all with people on the shop floor. The main question I ask everyone is: what do you run into in your daily work? Many problems on the shop floor are caused by bad data, but people do not realise it. You can still make that somewhat clear to office workers. On the shop floor, however, it is very different. A worker on the production floor generally has little affinity with the process automation they work with that generates data you could use, for example, to predict when a system needs maintenance. They also have no idea that the Incident Management System plays a role in this. They use that system only to report major faults they cannot fix themselves; to kick off a work process. Small faults they can fix themselves, they simply fix; why would they report on those? They do know small faults can be a sign of wear. But they do not realise you could use that data to predict when a system needs maintenance."

Raising data awareness

The inventory Ryan made at the water authority led to the realisation that data awareness has to go up across the whole organisation. And you do not achieve that through a general communication campaign. "Because every employee has a different stake in data and therefore a different perception of it. You have to start from the employee's interest: how can data help you make your work easier? The follow-up question you must ask yourself as a data management specialist is: how can we adapt the ways of working, processes and systems so that we make it as easy as possible for that employee to capture data at the source? Because if you simply burden people with a lot of extra work, it will not succeed."He sees in practice at many companies that workarounds emerged years ago and are passed on to new staff. "Such a workaround started, for example, because a certain system was often down. That fault was resolved long ago but the workaround stays and is even passed on to new staff, who do not even know there once was another way to capture that information. Higher up in the organisation nobody knows about it. Until a data project starts and a data engineer sees that certain data is completely missing."Where in practice a data engineer is often inclined to just tweak the model so the missing data is not missed, Ryan stresses the importance of data engineers feeding these gaps back. "But for that you do need a structure, otherwise it does not happen," he warns.

A cultural shift

It must be clear: data governance is above all a cultural shift. It asks something of the entire organisation, at every level and every role. That makes it a stubborn but also a rewarding topic, says Ryan. "Take my current assignment at Waterschap Vallei & Veluwe. There are enormously committed people there who are truly in it for the public interest. They are people who go to great lengths to ensure citizens in their area keep their feet dry and get water from the tap. If I can make sure they do not have to doubt the availability and integrity of the data, then both those colleagues and all citizens and businesses the water authority serves benefit greatly."

Specialist trainings CDMP Data Governance and CDMP Data Quality

Together with several colleagues from Data Talents, Ryan took, in addition to the CDMP Fundamentals training, the specialist trainings CDMP Data Governance and CDMP Data Quality. He is also always present at the periodic catch-up sessions Connected Data Academy organises for Data Talents. "Then Ferry, Erik or Antoine bring us up to date on developments in our field, think of data virtualisation for example. That is much more efficient than having to keep up with all the trade media ourselves and then translate it to the projects we are working on," says Ryan. "Moreover, both the trainings and the catch-up sessions at Connected Data Academy are always two-way: you bring in topics yourself, for example a challenge you run into in your current project. They then translate the theory or a technique to your practice. That makes the conversations enormously valuable."

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