A manager must constantly balance quality and quantity in their team's output, namely how fast can a task be completed versus how well it is performed.
No spoiler alert needed here. It is generally agreed that quality has no upper limit and, therefore, the time allotted for a task is of great importance and its enforcement must be strict. Nevertheless, quality can easily drop below par, especially when faced with a pressing timeline.
But what is "par"? What is the lowest acceptable level of quality? How is it established and maintained within the team? How is it defended and justified outward, towards the rest of the organization, as well as externally?
Quality output can be highly beneficial. For example, individuals may gain the respect of their peers and superiors and secure greater compensation for their efforts, organizations may strengthen their brands and avoid complications with their customers and end users, and so on. Naturally, this comes at a cost; directly, in the form of resources expended to achieve the desired quality level, and indirectly, in the form of losing the potential gains that could have been made in other avenues of activity, using the resources consumed by the efforts directed at achieving the desired quality, which is also known as "opportunity cost", or "alternative cost". In other words, a balance exists between the positive and negative effects of an organization's quality standards on its key performance indicators, such as time to market, brand strength, service costs, sales, reputation, etc.
Because quality must be kept within a narrow range, not too high, to ensure timely delivery, and not too low, to gain the benefits of a job well done, it is the manager's role to balance their team's work processes. The manager must clearly communicate the expected output and timeline for a task. However, the output is often defined in terms of scope ("what"), but not in terms of quality ("how well"). As always, setting expectations in the most detailed and precise manner is a best practice, especially at first. Over-communication is key. During the initial learning curve, the manager may choose to define a strict timeline and examine the quality of the resulting output, or set a strict quality level and examine the time required to achieve it. KPIs should be identified and measured to indicate the quality level.
With time, experience will establish a relationship between output quality and the time it consumes. If this relationship is quantified and documented consistently (KPIs), it becomes a powerful tool in the manager's hands. A performance standard, incorporating both time and quality is established and can be used as a benchmark to assess the work of the individual team members. It can also be used to defend the team's output and justify a demand for additional resources, when applicable.
Although many managers try to do this to some extent, it is extremely rare to find one who meticulously quantifies their team's work and continuously adjusts the performance standard. Nevertheless, the discipline and effort required to do so are surpassed by the aforementioned benefits. Moreover, as the team grows accustomed to be measured not only for time and scope, but also for quality, and assuming KPIs are indeed set up to reflect it correctly, quality performance will increase even further, as each individual adjusts to their environment, gains a better understanding of what is expected of them and strives to be more competitive within the team and the organization.
One recommended KPI reflecting quality performance (not necessarily exclusively) is the number of iterations, i.e. the number of times the output was reviewed by the manager and returned with comments for improvement. It is somewhat subjective and requires consistency and discipline from the manager, but is useful in communicating the expected quality level during the work process. Over time, this KPI should decrease and asymptotically approach some level between zero and one. When the number of iterations for an individual team member is greater than one, that team member might be struggling to keep up or the expectations are not being communicated clearly and/or consistently enough. When the number of iterations for the entire team, on average, is greater than one, it is almost certainly the latter.
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