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    Home > Technology > It’s time to ban your data team from data
    Technology

    It’s time to ban your data team from data

    It’s time to ban your data team from data

    Published by Jessica Weisman-Pitts

    Posted on June 1, 2022

    Featured image for article about Technology

    By Rob Wadsworth, Director of Enterprise Data at Kin + Carta Europe

    First, it was the data warehouse. Then it was the data lake. Now, if the hype is to be believed, it is the time of the data mesh.

    All in turn have been heralded as the silver bullet to unlock the true value of data in finance. So why hasn’t the true value of data been realised before?

    Too often centralised data teams create bottlenecks within company structure that prevents the business as a whole from taking a democratic and progressive approach to its use of data. The culprits are well-known: siloed thinking, lack of communication between departments/teams and a reactive attitude towards data usage.

    And that’s why it’s time to ban your data team from data – or at the very least alter their relationship with it.

    The benefits of a data-first culture for finance

    The finance sector is awash with data. And this data has the potential to not only solve a plethora of challenges but potentially start a revolution in the sector.

    Take retail banking. A big fear for providers is the commodification of their services. The rise of fintech companies and payment providers such as Clearbank and Revolut have steered legacy operators in the direction of API integration. But this shouldn’t necessarily be seen as a bad thing. Untapped data that can be collected via these APIs could lead to product innovations that allow retail banks to differentiate their services and operate more of a banking as a service (BaaS) model.

    Effective data usage could facilitate hyper-personalisation, enable intelligent experiences through predictive interfaces and more, leading to an enriched user experience. Plus it could also provide an opportunity for more efficient cross-selling – where existing customers are offered products such as loans and credit cards depending on the best fit for their personal circumstances.

    And its not just the retail banks that can benefit from data. Utilising data-as-a-product can also help increase FinTech SaaS ticket prices as well as their ARR.

    So, with all of these options on the table, why isn’t the data team doing more to bring them to fruition? And what role can other teams play in helping them to change this?

    The data bottleneck

    Data teams don’t always believe there are any problems with their current approach to data usage. Central data teams fundamentally exist to build complex transformations that make sense out of data. This means they often focus on ‘is what we’re doing working?’ instead of ‘what could we possibly do?’.

    To the data team, if the data pipelines are working then all is right with the world – because the tech team (the guys building the product from the data provided) hasn’t proactively told them they can provide data in a different way. Within the central data team, there is an acknowledgement that a lot of their role involves cleaning up other people’s mess. Again, this can be solved with proactivity.

    If data teams approached tech teams more readily in order to align languages and formats in the first place, this would allow them to spend less time putting out fires and more time scanning the horizon for potential opportunities.

    Better communication is key to removing the central data team as a bottleneck. Most often, there are several hundred technologists across the entire business who can contribute to finding and unlocking the value of data.

    Getting the tech in order

    The tech team often owns data in the first place, and typically takes a very reactive approach to its implementation. They tend to use the data available to build what they have been told to, rather than helping to inspire people into the broader business to get the best out of their data.

    A product team building something from scratch might lean into the ‘why’ of their data use a bit more – but this needs to be taken further. Tech teams must ask themselves, and most importantly others, which additional departments/areas could benefit from their project if it was treated as a product.

    For instance, the tech team needs to talk to end-users across the organisation and say ‘we’ve got this data – how can we package it in a way that is more useful and provides more value to you’? This is the most important conversation of all, so why is it being missed entirely?

    If the focus is always on asking technology to do something, the result will only ever be as good as the question. If the tech team flips this and is proactive, the sky’s the limit for progress.

    The broader business

    Looking beyond data and tech teams, the broader business also has an important role to play in the decentralisation of data and the cultural shift that must accompany it. This means allocating ownership of different data sets across departments, along with clear communication about how data can be used to help both individuals and the organisation as a whole perform better.

    Getting the broader business to buy into data’s potential can help the tech teams ‘sell’ their data product more effectively. This comes down to an open-minded attitude to data that is embraced company-wide.

    As financial organisations ready themselves for the next stage of the data evolution (whether it eventually takes the form of a data mesh or something new entirely) establishing a dialogue and fostering connections across departments will be key to unlocking its value.

    Ultimately, nobody working within a finance organisation should be banned from data. Everyone should be encouraged to interact with it and use it to improve performance – as long as it is promoted and shared company-wide rather than hoarded under the remit of any one particular team.

    So try this – get your data, business and tech people in a room, ask them to list the top five most valuable data assets in the organisation. Then ask each of them to list five ways in which more value could be unlocked from that data. Now ask them to make those five things a reality.

    You’ll be amazed at the difference it makes.

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