Understand your business objectivesÂ
Whatever happens, the main purpose of the team is to help achieve the overall business objectives by having succinct priorities. This should also achieve the team objectives, which need to be created to align with the business objectives. By having strongly aligned business and data objectives, data teams and the wider organisation will continue to grow while maintaining high retention, quality, and satisfaction. A strong alignment will pay dividends when it comes to implementing budgets effectively. Â
Data leaders need to examine, scrutinise, and break down the existing business and department objectives to be able to assess a hierarchy of priorities. One of the hardest parts of being a leader is knowing when to kill your darlings, and low priority items need to be ready to be sacrificed if needed. One DataIQ member mentioned that their organisation faces more than 150 budget requests each year, and not all of them will receive support. Â
For example, generative AI (genAI) has been high on the agenda for many businesses in 2024 and numerous teams have now implemented their own genAI tools. Going forward, however, there are growing costs associated with running and maintaining genAI tools including training and cloud costs. If business leaders insist on the continuation of genAI use, then they must appreciate the additional costs that will need to be shouldered by the data team and compensate accordingly. If they are unable to accommodate this, then the use of genAI must decline to keep costs down, which is why project prioritisation is so important.Â
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Implement flexibility for prioritiesÂ
In the real world, sometimes plans must change, and this is also true of budgets. If, for example, the first quarter of 2025 provides unexpected financial challenges that are outside the control of the organisation – international trading turmoil, war, climate change – data budgets need to be ready to adapt and evolve accordingly. Â
Many data teams operate in businesses where the income has reduced for one reason or another. The twist of irony here is that data teams are needed to improve income, while likely being on the chopping block for budget restrictions. Therefore, data teams need to implement a level of flexibility to be able to easily cut back on certain projects, focus on one area, or even be deployed into other business teams to help drive success. Â
When it comes to flexibility with projects and priorities, it is worth examining if there are any projects that overlap. If it does come to the situation where the lowest priority project needs to be cancelled, perhaps there is a way that some of the funding for that project can easily be transferred to the continuing project. Just because one project needs to be ended does not mean that another cannot benefit from the situation. Â
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Evolve each yearÂ
Seldom are there two years with the same priorities, and if data-driven change is being followed it should be the case that the next year will be different to the year before. This means data leaders need to realise they cannot rely on the same financial strategy and priorities year-on-year. Â
In the same way that data leaders need to urge others to become data literate, data leaders need to become financially literate, and this must be a priority. By honing financial skills, data leaders can become more adept at predicting the costs of projects at different stages of development. DataIQ members have mentioned that their teams frequently find themselves fighting an uphill battle against costs and financial metrics when trying to implement new systems or seeking investment, so it is an extra string to the bow to become financially savvy to help ease the discussions.Â
There will undoubtedly be a contest between different departments for the last remnants of available budgets. By being financially literate, data leaders can avoid being influenced by framing and the highlighted agenda of other departments and ensure the financial framing of the data department is robust and can withstand inevitable scrutiny. Data leaders need to continuously evolve their financial abilities to cement their role as a leader and improve the standing of the data team within the wider organisation. Â
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