Balancing Precision And Agility: When To Use Story Points Vs. Hours
Why Precision and Agility Matter
Software estimation seeks to balance the precision of predicting required effort and cost with the agility to adapt to changing requirements. Underestimating stories leads to cost overruns, schedule slips, technical debt, and team burnout. Overestimating causes excessive padding, wasted capacity, and reduced business agility. Agile teams need enough precision to plan iterations and releases while retaining the flexibility to handle new user stories.
The costs of over and underestimation
When teams underestimate, they sign up for more work than can be delivered sustainably. By undercounting the expected workload, velocity projections become skewed, making planning unreliable. Underestimation causes death marches, technical debt, and employee churn. If teams chronically underestimate, stakeholders lose trust in delivery capabilities.
Conversely, teams that habitually overestimate reduce productivity and responsiveness. Excessive padding leads to partial allocations and makes optimizing workflows difficult. With overestimation, capacity sits unused, new opportunities get missed, and projects stretch out. Estimation accuracy helps match capability with feature scope while allowing adaptation.
Being adaptable to change
Software development inherently involves discovery about complex domains and emergent user needs. Even with excellent analysis upfront, new information arises requiring adaptation. Teams must balance reasonable precision for planning with agility to handle requirement and priority changes.
Agile methodologies encompass an empirical approach accepting that complete knowledge is impossible at the outset. By embracing change through short iterative cycles, teams can incrementally refine plans and estimates. Estimation supports planning and risk reduction while agility enables adjusting for new learnings.
When to Use Story Points
Story points provide relative units of measure for expressing the overall size of user stories. They enable estimation and planning without needing precise task breakdowns upfront. Story points are useful when comparing large backlogs of stories and breaking down initiatives into manageable iterations.
For relative sizing and planning
Without specifying details prematurely, product owners can size backlogs by story points to forecast release plans. By grouping stories into small, medium, and large buckets, the development team gains insight into the relative complexity and business value across initiatives.
Story points power planning poker, allowing rapid estimation debates within the team. Relative units permit quick reassessment as understanding improves without recounting hours. Grouping by story points also helps identify delivery risk and batch priorities for iteration planning.
Comparing effort between stories
Story points enable comparing efforts between stories, establishing a velocity baseline for the team. By tracking actuals against story point estimates over iterations, patterns emerge from which to derive future capability. The emphasis rests on overall throughput rather than precision for each item.
Within a team’s velocity range, higher story point estimates imply greater complexity or unknowns compared to smaller ones. The art lies in consistent relative allocation even with imperfect information. Through use, the team aligns on standards for assigning story points to tasks of varying scope.
When detail is still emerging
Especially early in analysis, user needs may lack clear specification, making hour estimates difficult. Story points allow placeholder sizing for roadmap planning until the product owner refines the stories. consequently, teams avoid wasting energy prematurely detailing requirements likely to change.
Even during iteration planning, new complexities often surface requiring reassessment. Teams can rapidly recast estimates in story points as discoveries emerge. Hour-based estimates would require repetitive recounting as details shift.
When to Use Hours
Hour-based estimation provides detailed bottom-up quantification of the work required to deliver a story. When teams have high confidence in specifications and priorities, estimating in hours allows accurate capacity planning, tasking, and scheduling.
For bottom-up estimation
With clear requirements and visibility into the work structure, estimating hours makes sense to quantify lower-level tasks fully. Hours correlate better to actual delivery timelines, permitting precise iteration planning when teams can accurately scope stories.
By breaking down stories into granular components, teams derive data points to refine estimation skills. Comparing actuals against estimates provides calibration and insights to improve future precision. When uncertainty decreases, hour-based estimating boosts predictability.
When there is clear specification
Well-defined requirements with stable priorities enable precise scoping and hour-based estimation. Given thorough upfront analysis and low ambiguity in the stories, teams achieve higher accuracy predicting delivery timelines.
In later iterations after much discovery work, the backlog consists mostly of clear enhancements for which size in hours gets readily estimated. Even complex domains become reasonably quantifiable after factoring in earlier learnings.
Capacity planning and resourcing
To match workload to capacity, development teams estimate hours at the iteration level based on velocity ranges. Given stable teams and a consistent workflow, hour forecasts help quantify resource needs. By sizing at the milestone level, management secures budgets and staffing.
Hour estimates also allow targeted allocationEfficiency improves when assigning the right people and skills to fine-grained tasks. Granular scoping surfaces specialized work that benefits from expert pairing early in requirements.
Getting the Best of Both
Leveraging both story points and hours at different phases helps balance agility and precision. Story points offer flexibility for planning and prioritizing squishy stories. Estimating hours delivers detail when increased confidence in the work allows specificity.
Leveraging each method’s strengths
By matching the approach to the context, teams maximize strengths while mitigating weaknesses at each point. Early on, fast story point estimation facilitates prioritized backlog sequencing. Later once stabilized, detailed scoped hours improve the accuracy of release planning.
Even as projects progress, a mix helps account for new objective discoveries and scope changes. As certainty increases, teams gradually shift from points to hours while retaining some agility buffer through keeping a few story points in play.
Establishing when to transition approaches
The product owner plays an instrumental role in determining when to guide teams to pivot techniques. As understanding builds through iterations, the backlog mix changes with decreasing uncertainty around well-analyzed stories.
Hour estimation signals the requirements and acceptance criteria are clear to the team. The product owner likewise feels confidence in priorities and user value. By assessing risk factors, they jointly determine the appropriate split between agile story points and detailed hours.
Techniques for bridging story points and hours
To relate story points and hours, teams retroactively derive conversion rates from actual delivery effort. By comparing estimates against actuals, they produce data to cross-walk between units. Rounding hour totals to fall within ranges for each story point band aids the translation.
Some teams associate target hour ranges based on story point scores, for example: 1 = 5 hours, 3 = 10 to 15 hours. Such guidelines help teams frame hour estimates as details emerge from discussions. This simplifies transitioning partly defined stories into hours.
Key Takeaways
Together story point and hour estimating enable both responsiveness to change and delivery precision over the iterative project lifecycle. Clarity on when each approach applies ensures appropriate agility or exactness.
Precision and agility as complementary goals
Estimation presents an optimization challenge to maximize precision for planning while retaining flexibility to incorporate learnings. By outlining techniques suited to ambiguity or specificity, teams tactically apply both story points and hours.
Rather than compromising between accuracy and agility, leveraging each method at the right stages provides strengths with fewer downsides. Thanks to hybrid approaches, teams improve both prediction reliability and adaptability over time.
Picking the right technique for the situation
Teams deliver optimal results when matching approach to context – story points for discovery, hours for execution. In practice, project realities involve plenty of fluidity, making blended practices necessary in parallel.
The product owner holds responsibility for directing techniques by backlog priority with teams estimating jointly. As new objectives or technical challenges arise, flipping work packages between methods helps balance planning needs.
Using multiple techniques through the project
Software initiatives progress through phases of exploration, elaboration, construction, and maintenance – each with distinct needs. As specifics emerge from vague ideas, the project transitions from variable to fixed scope.
Accordingly, agile teams shift estimating modes, starting broad then tracking increasingly granular. However, shocks still arise so retaining contingency through flexible story points buffers risk. By adapting precision/agility ratios across the timeline, accuracy and possibilities co-exist.
