Many organisations are starting to notice the immense potentials with Artificial Intelligence, Internet of Things, Machine Vision, Machine learning, and other technologies.
A large number of organisations want to deploy these technologies and tend to start with the end result, i.e. hiring AI, IoT, MV or ML specialists or a set of data scientists without necessarily taking into account the readiness of their data.
Yes, of course, organisations don’t have to wait with innovative projects or their digital transformation until they reach a particular level of “data maturity.” However, it is a crucial “must-have” to take up the management from the start in order to avoid the cases of high investments with little rewards.
… Communication and Organisational Buy-in is the Key.
Still, even with clear data principles, an understanding of the gaps, and a burning platform, it’s not easy to convey to business people so that they can start doing something with data or understanding that some of their business challenges are in fact (hidden) data challenges.
That’s why we created visual storylines, making sure anyone in the organisation could understand how data management could solve some of their problems as well.
“With great power comes great responsibility” — Peter Parker.
Data can enable innovation, digital transformation, operational excellence, etc., but comes with great power and responsibility as well. Just think about GDPR and wrong decision-making based on incorrect data and higher costs.
In order to make sure data became part of the organisations’ DNA, we immediately started with defining (and assigning) data stewardship roles and informing/training and coaching people into their new roles.
This helped the assigned people to be more confident, as well as effective in their new roles, while also making sure everyone in the organisation had go-to persons to discuss their (data) challenges.
Having these people assigned in the organisation made sure we could accelerate not only data governance but also the organisation’s data maturity while better overcoming the data management gaps.
Even though it’s crucial these days to get to deliverable fast and continuously innovate, it’s also important to make sure you take the right steps with your data journey and ensure that your data has the right level of readiness and correctness.
Many companies invest in innovative technologies and find out (after 1 or 2 years) that their investments ultimately delivered too little business value.
This unique step-by-step approach led to much wider adoption of data management in the organisation and much better focus on the required data capabilities and priorities in terms of innovation and digital transformation.
Taking the right approach won’t stop an organisation from innovating, but will make sure the outcome is the right and sustainable one for the organisation in the long run.