Building a Loop around a Requirement
In this text, I take a requirement, explain why it exists, identify variables that matter, hypothesize their relationships, and explain how to use this information when designing a solution to the requirement, and the mechanism for evaluating how well the solution satisfies the requirement. In other words, I take a requirement and build a Requirements Loop around it.
1 The Requirement
Start from the requirement. Let’s phrase it as follows: It is necessary to address student complaints that they receive irrelevant mass emails from the university.
2 How have observed events in an environment have led, or are leading to the creation and persistence of those requirements?
To explain what causes the requirement, we need to describe a process whose outcome is the requirement. The process, as well as it causing the presence of the requirement, is a hypothesis, until we have evidence that this is so.
The process that leads to the requirement is as follows.
- University staff prepare and send mass emails to students.
- A student receives a mass email message from the university.
- The student decides if the email message is relevant or not.
- If the student decides that the email message is irrelevant, then, at least after receiving some such messages, the student complains verbally or in writing to other students and/or some university staff.
- At least some university staff voice the need to address these complaints, that is, to work towards reducing their frequency.
3 Are the events leading to the requirement observable?
In the step above, I did not indicate which events are observable. While it is probably possible to observe university staff sending emails to students, it is unnecessary. Evidence that may be enough to accept that that event is occurring, is to count the number of emails sent to students. In other words, we can identify variables whose values correlate to the occurrence of the events of interest.
| Event | Variable | Observable |
| University staff prepare and send mass emails to students. | Number of emails sent from University staff to students | Yes |
| A student receives a mass email message from the university. | Average number of emails a student receives from University staff | Yes, can be derived from the variable above |
| The student decides if the email message is relevant or not. | A student’s perception of relevance of an email from University staff (or average of those over received emails in a given period of time) | No, the value of the variable depends on mental states / attitudes, that are not observable; a proxy variable would be needed |
| If the student decides that the email message is irrelevant, then, at least after receiving some such messages, the student complains verbally or in writing to other students and/or some university staff. | Number of verbal or written complaints | No, even if there may be records of written complaints, this is partial at best (since there are also verbal complaints); the absence of a formal process to submit and track a complaint means that the variable is not observable |
| At least some university staff voice the need to address these complaints, that is, to work towards reducing their frequency. | Number of requests from University staff to address student complaints | No, for the same reasons as above – the absence of a formal process to submit and track a complaint means that the variable is not observable |
4 How should the environment be changed in order to satisfy the requirement in the future?
We should identify variables that correlate with the decision to complain. We can hypothesize that one such variable is the judgment that the student makes, that a mass email message is irrelevant to them. We then need to understand what influences that decision. Through a workshop with 10 randomly selected students, an email message was defined as irrelevant when it does not concern the faculty where the student is enrolled and her current year of study. The same 10 students all said that they do not want to receive irrelevant email messages.
It follows that there is a correlation between the match of faculty and year of study that the message is about and the student’s faculty and year of study, and the relevance of the message for the student.
How do we change the environment so that it leads to different events, which now reduce the frequency at which students will evaluate email messages to be irrelevant? Changes are
I’ll use a conservative and simple approach to solving this requirement, although others may be more interesting. We’ll ask University staff to create distribution lists specific to the year of study and study program of the student, and send emails only to matching students. This change is described in the table below.
| Event | Changed Event |
| University staff prepare and send mass emails to students. | University staff define distribution groups, so that students in a given program and year only receive email messages directed at that program and year. |
| A student receives a mass email message from the university. | No changes. |
| The student decides if the email message is relevant or not. | No changes. |
| If the student decides that the email message is irrelevant, then, at least after receiving some such messages, the student complains verbally or in writing to other students and/or some university staff. | No changes. |
| At least some university staff voice the need to address these complaints, that is, to work towards reducing their frequency. | No changes. |
With this solution, I am assuming that the targeting by study program and year correlates negatively with the unobservable variable, namely the student’s perception of irrelevance of an email from University staff. Targeting, as described above, is hypothesized to reduce the irrelevance of the emails that the student receives from University staff.
5 How should the change in the environment be measured, in order to evaluate the extent to which requirements are satisfied?
In Step 4 above, I described the change to make. However, we are still stuck with the same observable and unobservable variables as before, and consequently, there is no way to evaluate the impact of the change on the complaints, and thereby, on the satisfaction of the requirement.
We probably cannot fully eliminate verbal or random written complaints, but we can introduce another way for students to provide complaints, and assume that the number of those correlates negatively with the satisfaction of the requirement. Again, to keep things simple, the change will be that every email sent to students includes a link for the student to mark that email as irrelevant – doing so would be counted as a complaint; each click a student makes, to indicate that the email is irrelevant, is called an Irrelevance signal.
A final change is to report the level to which the requirement is satisfied. This will be done by regularly reporting the number and trend of Irrelevance signals to University staff who prepare and send emails to students.
The initial process, its changes, variables, and their observability, is summarized in the table below.
| Event | Changed Event | Variable | Observable |
| University staff prepare and send mass emails to students. | University staff define distribution groups, so that students in a given program and year only receive email messages directed at that program and year. | Number of emails sent from University staff to students | Yes |
| A student receives a mass email message from the university. | No changes. | Average number of emails a student receives from University staff | Yes, can be derived from the variable above |
| The student decides if the email message is relevant or not. | New change: Every email includes a link, that the student can click to indicate that that email message is irrelevant. We’ll call one such click an “Irrelevance signal”. | A student’s perception of relevance of an email from University staff (or average of those over received emails in a given period of time) Observable proxy variable for the above: Number of Irrelevance signals | No, perception of relevance depends on mental states / attitudes, that are not observable; a proxy variable would be needed Yes, the proxy variable is observable. |
| If the student decides that the email message is irrelevant, then, at least after receiving some such messages, the student complains verbally or in writing to other students and/or some university staff. | No changes. | Number of verbal or written complaints | No, even if there may be records of written complaints, this is partial at best (since there are also verbal complaints); the absence of a formal process to submit and track a complaint means that the variable is not observable |
| At least some university staff voice the need to address these complaints, that is, to work towards reducing their frequency. | Regularly report the number and trend of Irrelevance signals to University staff who prepare and send email messages to students. | Number of requests from University staff to address student complaints | No, for the same reasons as above – the absence of a formal process to submit and track a complaint means that the variable is not observable |