Agile project management is a multifaceted topic, and as such, there is far too much information to cover in one article. This article is the first part in a series to go over the benefits, approach and structure of using the agile methodology for analytics projects. For more information on this topic, read Optimizing your agile analytics scrum team.
Author: Christie Vick
Most businesses have vast amounts of company and consumer data; some are unsure of what they have, while others are unable to leverage theirs into strategic insights and take appropriate action. However, there are many that have already engaged in an analytics or data science project to collect, manage and apply such data.
Yet, not all analytics projects are successful in getting that valuable data into business users’ hands. As a business leader, can you imagine some statements you would not want to hear from stakeholders after engaging in such a project? Perhaps they are:
These kinds of reactions can be personally discouraging and even detrimental to such projects and the teams that work on those. So, what can be done to try and avoid this? Leveraging an agile project management methodology that engages users early and often, allowing for changes based on feedback, is a valuable tool in successful analytics project delivery.
What is an agile project management method?
Agile project management takes an iterative approach, relying on and incorporating user feedback in each release cycle. As such, the highest priority in agile is, “to satisfy the customer through early and continuous delivery of valuable software (1).” However, this methodology does not apply solely to software development. The key points of the Agile Manifesto apply directly to delivering analytics to business users (2):
The agile approach
Agile teams work in delivery cycles called sprints. Sprints represent a single development and release cycle, focused on continuous, iterative delivery. The length of sprints is consistent over time, with a common timeframe being two weeks. This allows enough time for the team to build useful functionality and gives the business a quick enough turnaround to ensure ad-hoc requests do not distract the development team. There are several standard ceremonies within a sprint: planning, retrospective, daily scrum and review (3). These activities help drive the desired feedback and cadence:
The benefits of agile analytics
While business models and project goals vary, this approach continues to be successful because of its ability to adapt and pivot to fit current and future business priorities or requirements. Some other significant benefits in utilizing the agile scrum methodology and organizing scrum teams are:
This approach is advantageous because feedback and cadence are prevalent:
Preparing your business for agility
While the benefits of applying agile to analytics project delivery are clear, the transition from other project management methodologies, like waterfall or kan ban, does not happen overnight. There are numerous guides available to help organizations through this change and we can help. Baker Tilly professionals are adept at implementing the agile scrum methodology and organizing teams while keeping your future business goals at the forefront of every decision.