Our world today is all about data: we build our company strategies and go-to-markets on it. But while it feels like 'the more, the better', we know simply collecting data isn’t enough. For privacy and cybersecurity in particular, companies need qualitative data, with solid governance for all the information flowing in.
In this session, we heard from seasoned experts about best practices to ensure organisations can see the data forest for the trees, and avoid getting lost in a tangle of information.
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Data quality at Allianz
Setting the scene for this session was Tom Van Wint, IT Service Management at Allianz. He sees three different data governance perspectives:
In the effort to streamline processes, data often gets polluted, he warned. For example: people generally choose the path of the least resistance, such as finding workarounds for potential bugs or anomalies. But this can compromise the data.
Another warning: guard your interface logic and make sure your operator is duly trained - otherwise your process or application will only be used for a fragment of what it's meant to do, impacting output. And in terms of managing data, Tom sees a few valuable angles (slide 4).
Embrace the help of a Data Quality Manager, especially to define the data you need, he emphasised. Have a true scientist analyse your data and graphs, and make conclusions on what is sensible.
Data & information management: cracking the code
Next, Jeroen Vergauwe, Partner – Data Analytics at Deloitte, took the floor. Data, he stated, is a key resource to realise your strategy for a digital world. Take a broad view on your world and translate it to your data strategy. Ensure you have a clear plan and a regularly reviewed roadmap.
Many different people have varied accountability and roles regarding data, influencing its quantity and quality. Define these roles and map who is accountable for what - and don't forget to include all parties in the chain, including your contractors. And last, but not least, recruit people through a focus on your strategy, not just people with capabilities for today's operations.
The graph on slide 5 shows that more analytics means less human input. You need to adapt your business process accordingly. Decreased human input increases the need for change management. First mature your data and information management, then change your business processes and provide proper change management, Jeroen advised.
In a digital enterprise, solid and trustworthy data finds its purpose in proven technologies like automation, cloud, IoT and analytics, and also in newer technologies like 'Mixed Reality' and Blockchain. This can reshape the heart of the business, Jeroen concluded (slide 7).
To close the session, the attendees exchanged experiences with each other, with an interactive discussion on their concerns and pitfalls.
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