Modeling Coverage When an Executive Team Spans Time Zones

The coverage question is arithmetic before it is a staffing decision

A global executive team creates a deceptively simple question: how many assistants are needed to cover the working day? The answer is not the number of executives divided by a standard ratio. It depends on the hours that require live coverage, the overlap needed for handoffs, the response time the executive expects, and the difference between being available and being on call. This report builds a transparent model so an agency or client can test assumptions instead of relying on a vendor's rule of thumb.

The model uses clock hours, not headcount folklore. It treats coverage as a window that must be staffed, then subtracts the hours that can be handled asynchronously. The output is a range, not a precise answer. That is appropriate because the inputs are policy choices: whether a request at 9 p.m. local time needs a reply within fifteen minutes or by the next morning. The value of the model is that it makes those choices explicit and shows their cost.

Define the coverage window first

Start by listing the hours in which each executive expects a live response. A CEO may need coverage from 7 a.m. to 7 p.m. local time, while a CFO may need only 9 a.m. to 5 p.m. except during close. Convert every window to a single reference time zone, usually UTC, so the overlaps are visible. Then identify the hours that are genuinely shared across the team and the hours that are unique to one region. The BLS occupational profile notes that most secretaries and administrative assistants work full time, which is a useful reminder that coverage assumptions should not quietly rely on unpaid availability.

Do not assume that a full workday requires full coverage. Much of an executive assistant's work is asynchronous: drafting, scheduling, research, and preparation. The live window is for decisions, urgent changes, and relationship management. Separating live from asynchronous work prevents the team from overstaffing the quiet hours and understaffing the two hours when everything converges.

Calculate overlap with a simple formula

For two regions, the shared coverage window is the later of the two start times to the earlier of the two end times, measured in the same time zone. If New York covers 8 a.m. to 6 p.m. Eastern and London covers 9 a.m. to 6 p.m. Greenwich Mean Time, the overlap is roughly 1 p.m. to 6 p.m. GMT during standard time, or five hours. In summer, the offset changes and the overlap shifts. The formula is simple, but the daylight-saving transition is where many coverage plans break.

Daylight saving, holidays, and the weeks that do not fit

A coverage model built on standard time can fail twice a year when one region changes its clocks before another. The overlap may shrink by an hour for several weeks, which is enough to leave the last hour of the London day uncovered. Build the schedule on local time with an explicit offset table, then verify the transition weeks separately. The same discipline applies to national holidays, which differ by country and sometimes by region within a country.

Holiday coverage deserves its own line in the model. A day when one office is closed is not a day when the executive's work disappears. The other region may need to cover a full day with a smaller team, or the work may need to be deferred with a clear message to the executive. Decide in advance which holidays require live coverage and which can run on an on-call basis. The answer should be written down, not rediscovered each year by the person who happens to be scheduling.

For three or more regions, calculate the overlap pairwise and then look for the window that covers the largest number of executives. A hub-and-spoke model often works better than trying to find one global window that suits everyone. The hub assistant covers the majority region and hands off to a regional assistant for the remaining hours. The handoff time should be chosen for low message volume, not for the convenience of the schedule. A capacity error in the hub can ripple through every region, so the hub needs explicit backup.

Turn coverage hours into staffing hours

Once the live window is defined, calculate the number of assistant hours required per week. Multiply the daily coverage hours by the number of days, then add a factor for handoff, administration, and absence. A common mistake is to divide the weekly coverage hours by forty and call the result the headcount. That calculation ignores breaks, training, supervision, and the fact that one person cannot cover every hour without becoming unavailable for the asynchronous work that makes the support effective.

A worked example makes the gap visible. Suppose a team needs twelve hours of live coverage on five weekdays, or sixty hours per week. Dividing by forty suggests one and a half full-time assistants. But if each assistant is productive on live coverage for six of eight hours, the same sixty hours require ten assistant-days, or two full-time people before absence and training. Add a realistic absence factor and the requirement moves closer to two and a half. The arithmetic changes the answer, and it changes the conversation about cost.

A more honest model separates prime coverage from backup coverage. Prime hours need an assistant who is actively monitoring the queue. Backup hours need someone who can respond within an agreed time if the primary is unavailable. The two have different costs and different scheduling rules. Write both into the service agreement so the client understands what "24/5 coverage" actually means. A promise of coverage that depends on one person's phone is not a coverage model. The calendar conflict rules should also say how urgent requests interrupt a scheduled block.

Cost the handoff, not just the hours

Every handoff has a cost: the time to write the status note, the risk of losing context, and the delay before the next person acts. A team that hands off three times a day may spend more time coordinating than a team that hands off once. Estimate the handoff cost in minutes per transition and multiply by the number of transitions per week. Then ask whether the handoff is necessary or whether an asynchronous note would suffice.

Reduce handoff cost with a standard template: open items, decisions pending, urgent risks, and the next check time. Keep the template short enough that people actually complete it. If a handoff routinely takes thirty minutes, the coverage window is probably too fragmented. Consolidating into fewer, longer shifts often improves both quality and cost, even when the raw hours look less efficient on a spreadsheet.

Test the model against real weeks

A model is only useful if it survives contact with actual work. Pick four representative weeks and log the timestamp of every request that required a live response. Compare the demand curve with the coverage window. Look for clusters outside the window, long gaps between requests, and days when the queue backed up. The pattern will show whether the team is covering the right hours or simply covering the hours that are convenient.

Also test the absence case. If the primary assistant is out for a week, does the model still hold? If not, the backup arrangement is fictional. Add the cost of a realistic backup to the staffing calculation, even if the backup is shared across clients. A coverage plan that works only when everyone is present is not a plan. It is a best-case scenario with a schedule attached.

What the model cannot decide

The model can show the hours and the handoffs, but it cannot decide how much responsiveness an executive is willing to pay for. That is a management choice, and it should be made with the executive, the assistant, and the finance owner in the room. The model also cannot capture the value of continuity, local knowledge, or a relationship that took years to build. Those factors may justify a higher cost than the arithmetic alone suggests.

Use the model as a structured conversation, not as an answer key. State the assumptions, show the range, and identify the two or three inputs that change the result most. Then revisit the model when the team adds a region, changes its service hours, or shifts to a different employment model. Coverage across time zones is a design problem, and a design problem deserves a visible set of assumptions rather than an inherited ratio. If your team is redesigning coverage, start a conversation with us.