How Many Spikes Is Too Many?

Spike is fun to say. Spike! For the unfamiliar, the spike is a concept from Agile methodologies that means a time-boxed backlog item where the end result is learning, rather than delivered software.

Mike Cohn from Mountain Goat Software offers this example:

As an example of a spike, suppose a team is trying to decide between competing design approaches. The product owner may decide to use a spike to invest another 40 (or 4 or 400) hours into the investigation. Or the development team may be making a build vs. buy decision involving a new component. Their Scrum Master might suggest that a good first step toward making that decision would be a spike into the different options available for purchase, their features, and their costs.

Because spikes are time-boxed, the investment is fixed. After the predetermined number of hours, a decision is made. But that decision may be to invest more hours in gaining more knowledge.

I've worked on teams where the process was spike-heavy. We'd commonly have backlog items within most sprints that were dedicated to learning about a topic that we knew would be important for future work. We had features we wanted to get into the software, but we didn't have a good idea of how we were going to accomplish that work on a technical level. For teams that put a big emphasis on accurate estimation and minimal to no carry-over of items at the end of sprints, they want to know that a technical foundation for work is understood before its implementation is "promised" within a particular sprint.

I've also worked on a team where spikes were basically not part of the process at all. Backlog items were oriented around features the product owner wanted in the software, but they wouldn't allot an item into a sprint without a "technical approach" filled out on the item first. The "technical approaches" were usually written ahead of time by team leads or architects that did not have "on the board" responsibilities within sprints and would work on these things ahead of the rest of the team, as time allowed. Sometimes senior engineers would also work on technical approaches for future sprints if they finished their assigned items for a sprint with time to spare.

One of the downsides of a spike-heavy process is that you're reducing the amount of "business value" delivered at the end of a sprint. If your entire sprint was consumed by spikes, I don't think the business would be very happy. On the flipside, learning has to happen somewhere. Whether you call it a spike, refinement, technical approaches, or anything else, the learning must happen.

I wouldn't necessarily say that the spike is an anti-pattern, but if it feels they're being leaned on too heavily, it might be time to stop and ask why they're necessary. Is it because we're shifting decision making to the engineers about requirements that a business analyst or product owner should be making? Are we not dedicating enough time to refinement? Is the product owner spread too thin? Is the development team stacked with junior engineers or lacking in engineers that are experienced with the technology at hand?

Learning has to happen somewhere—that's the nature of software engineering. But an over-reliance on spikes for decision making can indicate deeper organizational issues.