Read the scenario, examine the four habits, then complete the reflection activities before revealing the suggested responses.
Aisha is a service manager in a community health centre. She is reviewing the monthly performance report and notices that the average waiting time for follow-up appointments has increased significantly over the past two months.
The scheduling team, led by Marcus, has been under pressure because of staff shortages, increased demand, and several changes to appointment procedures. Aisha is concerned because longer waiting times may affect patient experience and could create additional pressure on clinical teams.
She writes the following message to Marcus:
From Aisha's perspective, the message is clear. She wants to show that the issue is serious and needs prompt attention. However, Marcus may receive the message differently. He may feel that his team is being blamed for a problem caused by several factors, or that Aisha does not recognise the pressures the team is already managing.
This demonstrates a common challenge in written communication. The sender understands their own intention, but the receiver only sees the words in the message. A message intended to create urgency can therefore be interpreted as criticism, blame, or lack of appreciation.
Before sending the message, Aisha considers the possible communication risks.
The issue is sensitive because it relates to team performance, patient access, workload, and management responsibility. The message also refers to a previous discussion and suggests that the team has failed to improve.
Aisha recognises that if Marcus feels blamed or judged, he may become defensive. This could make it more difficult to have an open discussion about the real causes of the waiting-time problem.
Being risk-aware does not mean avoiding a difficult performance issue. It means recognising that the way the issue is communicated can influence how effectively people respond to it.
Aisha uses the Coconsider prompt with a Gen AI tool as an interpretation mirror.
She asks the AI to consider how Marcus might interpret her message and to identify wording that could sound blaming, dismissive, or overly critical.
The AI highlights phrases such as “the scheduling team has not improved the situation” and “this level of performance is not acceptable.” These statements may make Marcus feel that responsibility has already been assigned before the causes of the problem have been fully discussed.
The AI also notes that the message does not acknowledge possible contributing factors such as staffing levels, demand, appointment processes, or capacity constraints.
This helps Aisha see that her original message communicates urgency, but may not encourage the open discussion needed to understand and solve the problem.
Aisha does not assume that the AI's interpretation is completely correct.
The AI does not know all the operational details, the seriousness of the waiting-time trend, previous discussions with Marcus, or the service standards that the health centre is expected to meet.
It may also suggest language that is too cautious and fails to communicate the importance of the issue.
Aisha therefore reviews the AI's feedback carefully. She decides that the final message still needs to make clear that the waiting-time trend requires action. At the same time, she wants the message to encourage Marcus to explain the causes and help develop a practical response.
She uses the AI's perspective as one source of input rather than allowing it to make the management decision for her.
Aisha clarifies the purpose of her communication before revising the message.
Her goal is to understand what is driving the increase in waiting times, agree appropriate actions, and improve patient access. Her goal is not simply to express dissatisfaction.
She therefore revises the message:
The revised message still identifies the performance concern clearly. However, it focuses on the problem rather than immediately placing blame on the team.
It also recognises the wider context and invites Marcus to contribute information that may be important for deciding what should happen next.
Aisha remains responsible for judging whether the message is appropriate and whether further management action is required.
The four habits support each other.
Being risk-aware helps Aisha recognise that a message about performance can easily affect trust and working relationships. Using Gen AI gives her an additional perspective on how her wording may be interpreted. Using the AI with care reminds her that its interpretation may be incomplete or unsuitable. Staying human-led ensures that the final communication remains focused on the real management objective.
The purpose is not to make every message softer or more positive. In health management, some messages need to communicate serious concerns, standards, risks, or accountability.
The value of the Coconsider approach is that it helps the sender communicate these issues more deliberately, with greater awareness of how the message may be received.
In this situation, the approach helps Aisha separate the performance issue from personal blame.
This may make it easier for Marcus to share useful information about staffing, demand, systems, or other contributing factors. A more open discussion can support better problem-solving and reduce the risk that people focus mainly on defending themselves.
The approach can also support stronger working relationships. Health services often depend on collaboration between managers, clinical teams, administrative staff, and support functions. Communication that is clear but considerate can help people address difficult issues while maintaining trust.
It may also improve the quality of management decisions because people are more likely to raise concerns, explain constraints, and share relevant information when they feel able to contribute openly.
The approach cannot guarantee that a message will be interpreted positively or that agreement will be reached.
Gen AI may not understand the full organisational context, the history between colleagues, local policies, service pressures, or the seriousness of a performance issue.
It may also suggest wording that reduces necessary clarity or accountability. For example, if a serious patient safety or regulatory issue exists, the communication may need to be more direct than the AI recommends.
The Coconsider approach should therefore support, rather than replace, professional judgement, management responsibility, organisational procedures, and appropriate escalation.
Some issues may also be too complex or sensitive for written communication alone. In these situations, a direct conversation may be more appropriate, with written follow-up where necessary.
Type your own response. When you are ready, compare it with the suggested answer.
The message appears to place responsibility directly on the scheduling team and uses language such as “has not improved the situation” and “not acceptable.” Marcus may therefore feel blamed before he has had an opportunity to explain the causes of the problem.
The Gen AI helped her see how the message could be interpreted from Marcus's perspective. In particular, it highlighted wording that could sound blaming and showed that the message did not recognise other possible factors contributing to the waiting-time problem.
Aisha defined the purpose of the communication, reviewed the AI's suggestions critically, considered the operational context, and decided what message would best support the required management action. The AI provided another perspective, but Aisha remained responsible for the final judgement and communication.