Recently, Lawrence Harvey hosted the first in our “What I wish I’d known…” Series, with the inaugural evening involving a discussion on Data Management.
3 panelists, all experts within the field of Data Management, shared their successes, failures and horror stories within this area.
Below are my 4 key takeaways from the night:
What is data management?
The general consensus is that Data Management is made up of several different disciplines, which are well explained by the DAMA-DMBOK wheel (https://dama.org/content/dmbok). However, it does mis-lead people into thinking Data Management and Data Governance are interchangeable, and it could potentially also use new additions like data ethics and remediation.
Businesses need to also consider and investigate how they are fixing their data. This, along with the other spokes of the DAMA-DMBOK wheel, can be particularly challenging for many different organisations. Often, to be successful, data management needs to be aligned with Group Data Strategy, keeping in line with external factors such as regulatory changes.
The wheel provides a good basis but remember to consider your own staff’s experiences, as well as factors specific to your organisation.
Challenges within Data Management?
One of the biggest problems that businesses face is getting people from all levels on board. Education and awareness of data management needs to be addressed from all sides, and the DNA of a company needs to be changed to incorporate this. With enough backing, it can be made into a higher profile problem to bring to the board. Data ownership should be encouraged at all levels of the business, this way full buy in can be achieved right from the ground level to the C-Suite.
Employ both a carrot and a stick approach.
How to best engage the business in Data Management
Getting the business to take ownership of Data Management is a widespread issue, and attempting to run it from an ivory tower has generally been found to be ineffective. The real wins are found when the benefits are sold to the people on the ground, getting everyone on board. Formalising the process and making it a “proper” best practice activity. When people are bought into an idea then they will make sure it’s implemented.
Ownership & Sponsorship – approach from both a senior and ground-level angle.
Implementing new technology
There is a use for technologies such as machine learning, robotic process automation and AI within Data Management, however a certain level of caution should be applied. For example, a major problem with the utilisation of the above is that issues like interpretation error can cause machines to misread data.
There are huge opportunities to streamline and improve Data Management processes, and also to further engage the business in Data Management. The improvement of data quality and the removal of human error are just two of many opportunities.
There is more new technology on the horizon, too, with concepts such as 5G having the potential to change the landscape substantially.
There is opportunity, but due caution must be exercised.
In conlusion, it was a very enlightening evening, with plenty of engagement from the audience and some common themes addressed around both the challenges that people are facing, and the opportunities that are presented by doing Data Management in the right way.
Look out for the video clips from the evening which are being released soon and get in touch to find out more about our next 'What I wish i'd known...' event, coming soon!