For businesses, three years is a long time.
If you think back over the last 36 months for your business, how much has changed? Even excluding the global pandemic and the turbulence it brought with it, we’re willing to bet that your business has faced unforeseen challenges and grasped unexpected opportunities in that time, that have placed new demands on your data and the way you manage it. The plans you had for your data back in 2019 (and your definitions of ‘good data’) probably look very different to the reality of your data strategy today. And three years from now, they will have changed again.
Yet so many data quality projects are still delivered via traditional waterfall methods that take two to three years to deliver your data vision. That’s two to three years without any tangible return – and no opportunity to change or adapt the project during the process. While your business plans – and data quality needs – are evolving and developing in line with industry challenges, customer demands and new opportunities, your data quality project isn’t.
The result? A data quality system that’s out of date before you’ve even started using it – and data that is out of touch with the realities of your business.
However, having a vision for your data and what you want to achieve with it at the start of a data project is crucial to delivering results. Without a goal, any data initiative is doomed to fail: you can’t measure results if you don’t really know what you’re trying to achieve.
So what’s the alternative? How can you work towards a data vision while maintaining your flexibility with data?
By bringing agile methods into your data project delivery, businesses can be guided by a more holistic data vision. While agile projects still bring direction to your data quality strategy, they allow you to adapt data processes and technologies to respond to fluctuating demands, opportunities and problems as they arise.
The waterfall framework: working towards a data vision
Traditional waterfall – or sequential – data quality delivery takes your data vision and delivers it in one package, usually around two to three years from project launch. Your data goal is achieved by building the solution one step after another: through planning, design, build and testing. Once one phase is complete, the next begins.
The problem, as mentioned above, is that during that time you can’t deviate from that goal. Once the project is underway, there’s little you can do to change it without huge disruption and significant costs. The data quality classifications you establish at the start of the project will be exactly the same at the end of the three years as they were at the start – despite how your use or expectations of that data might have changed in the meantime.
In short, your data quality stagnates, while your competitors’ keeps moving.
Agile delivery: making your data vision a reality
Agile delivery methods still maintain a long-term vision, but break delivery into smaller, faster sprints that take around two weeks. Each sprint includes its own build, test and delivery, providing data quality improvements at every leg of the journey. Agile delivery methods are also client-focussed, keeping your team involved and maintaining visibility of the project, avoiding any nasty surprises – for instance, data quality that’s not really fit for the purpose you intended – upon completion.
With agile delivery, you don’t lose that ‘vision’ for your data, but you do gain a flexibility that keeps your end data quality goal in line with your commercial business objectives as they change. It’s a delivery method that works with the fast-changing nature of data, instead of against it.
Should you stick with waterfall, or twist to Agile?
In our latest guide, we take an in-depth look at agile vs traditional waterfall delivery, and the key differences that agility can bring to your data vision: from faster results to easier adaptation along the way. To find out more download Stick or Twist: An agile guide to choosing fast, more flexible data solutions or contact the Agile team for advice on your next project.