Sprint is not a buzzword: it’s a fast, flexible and measurable method of delivering data solutions. Here’s how businesses can makes sure they are signing up for a data sprint, and not a stroll.
An Agile delivery, made up of a number of sprints, should be fast, flexible and measurable. So why are so many ‘sprint’ projects that are offered by data solutions providers the opposite?
In a 100m sprint, you run the race, you record your time, and you set your next goal. The same concept should apply to a data project sprint: a specific, boxed-in workload, they should be short, with a clear finish line to cross and a measurable outcome to record afterwards.
A data migration, for instance, becomes a series of manageable sprints each incorporating extraction, assessment and discovery, process and build, and data governance. With the right team in place to deliver these actions – one who understands the commercial and technical needs of the organisation – the project can quickly sprint to each finish line, measure the results, and move on to the next task.
Yet the term ‘sprint’ has become something of a buzzword within the data solutions industry: a label that can be added to any offering to suggest speed and agility, when in reality the service the client gets is anything but.
Unlike other buzzwords, which are mostly harmless (if a little vague; think Big Data or Machine Learning), these false sprints are actively impairing business’ data outcomes, reducing their flexibility at a time when – thanks to constant digital change and disruption – businesses need to be more agile with their data, and their technology, than ever.
If you want to avoid the data stroll masquerading as a data sprint, you need to understand what a ‘sprint’ should actually look and feel like – and the role they play in developing an agile approach to data across your organisation.
What is a sprint delivery in data solutions?
An agile delivery breaks down a large, complicated project into smaller, more manageable pieces, or sprints, that aren’t dependent on each other for completion.
For instance, the launch of a 360-degree data visualisation platform, with the goal of improving omnichannel e-commerce experience, becomes several smaller data sprints working towards that commercial vision, from data governance and migration to architecture modernisation and system implementation. Each of the sprints is tested with a ‘Test Harness’ that records the percentage of working tests. As all of the sprints come together and the dependencies are bridged, the percentage of working tests increases to 100%.
The term originates from Agile Project Management (APM) methodologies (like Scrum and Kanban) and is a key part of carrying out a flexible, commercial data solutions implementation. At Agile, we’ve created the Agile Information Management (AIM) framework specifically to provide sprint delivery of data solutions.
What are the main benefits of sprint delivery?
Sprints are quick, manageable, measurable, and – above all – agile. By breaking a delivery project down into set objectives and time frames, it enables organisations to pivot their digital strategy with ease. Each ‘sprint’ has a tangible goal, which allows businesses to not only witness the project’s short and long-term progress, but to make informed decisions with data at every stage, reacting to market disruption and business demands as they evolve.
The customer is able to see phases being developed and integrated end-to-end, making progress more visible as each sprint builds up to the end goal. The sooner the customer can see this, the sooner the development team can get feedback and ensure the delivery is satisfying the customers’ requirements.
This is in stark contrast to traditional waterfall delivery, where each stage of a project leads onto the next, flowing towards one large, long-term goal: eg, the implementation of a cloud data lakehouse. When it comes to data solutions – such as data management software development or implementation – a waterfall can take years to deliver, with little to no real-time evidence of progress, and no opportunity to adapt and evolve on that journey (at least, not without serious disruption).
In today’s fast-paced digital climate, the outcome of a waterfall delivery – unless carefully managed – can be disappointing, or even disastrous. A lot can change for a business in two years: if a data project can’t change with it, the projected outcome won’t align with where the business is by the end of it. Cloud implementations in particular need flexible, scalable deliveries of this kind in order to reap results for the customer.
In short, it’s the difference between taking a hair-pin turn with a motorcycle, compared to a 10-tonne hauler.
How long should a sprint take?
Typically, two weeks. It may sometimes be reduced or stretched a little to suit the type of project but the duration has to allow sufficient time for PSIs (potentially shippable increments) to be produced.
In Agile’s AIM framework, we operate sprints of two weeks, no longer.
When is a sprint not a sprint?
When it’s a stroll – or worse, a cross-country marathon. Businesses are unwittingly adopting so-called ‘sprint’ solutions that aren’t technically a sprint at all. Some have timeframes of two or more months, instead of two weeks, while others are tied together as part of an unmoveable workflow: they may be short, but they certainly aren’t flexible and the dependencies are not effectively broken down.
These are essentially long waterfall release methodologies disguised as sprint frameworks that are costing businesses in lost agility, lost time and lost revenue from their data.
Using Agile’s AIM framework for data sprint solutions
Agile’s AIM framework applies sprint methodology to every data solution, be it incorporating management strategies like data governance; implementing data modernisation tools such as upgraded cloud capabilities; or engineering monetisation solutions like real-time data analytics.
The result? A faster, flexible, more measurable approach to data solutions, and a more agile method to manage, modernise and monetise your data.
Ready to stop strolling and start sprinting towards your data goals? Contact Agile Solutions to speak to one of our experienced data consultants.