What’s behind a missed target? A gap analysis in practice

A support team aims to answer 90% of eligible emails by 5 p.m., yet only 60% get a reply in time. A gap analysis shows how many more replies the team needs and what to check before it changes the afternoon shift. In Xmind, the team can put each suspected cause beside the inbox records that could confirm or challenge it.

The figures in this example are illustrative. To follow along, start a gap analysis in Xmind with one outcome your team already tracks.

What is a gap analysis?

A gap analysis compares a current state with a desired state on the same measure. A gap statement records the baseline, the target, and the difference between them. You can then investigate why the difference exists and decide what to change. The Help Me Grow Kansas gap analysis worksheet uses this sequence to connect observations about current practice with a desired outcome and the steps needed to reach it.

A gap can be measurable in time, cost, or percentage points. It can also describe a missing capability. If a procedure requires a named backup for every support queue, a queue with no backup has a gap you can verify directly. The words “we need better coverage” give you much less to check.

How to do a gap analysis

1. Agree on what counts

Start with a question precise enough that two people could review the same records and reach the same number. For this team, the question is simple. What share of new weekday emails received before noon get a first human reply by 5 p.m. local time?

That wording settles several easy-to-miss decisions. An automated acknowledgment does not count. An email received at 4:55 p.m. falls outside the sample. The unit is one new customer request, so a long email thread still counts once. The team agrees on these rules before opening the inbox report.

2. Measure the baseline and the target in the same units

Over the previous two full workweeks, 40 new requests met those rules. A person replied to 24 by the cutoff. That gives the team a baseline of 60%. Its agreed target is 90%.

The gap is 30 percentage points. On the same 40 requests, the team would have needed 36 on-time replies, or 12 more than it delivered. That leaves room for four late replies at the target. The team can now ask whether the change it has in mind could bring 12 more replies in on time.

3. Look for the point where work stalls

Open the records behind the average. For each of the 16 late requests, the team checks who owned it at 3 p.m., two hours before the deadline. Ten still had no owner. Six already had one.

The ten unassigned requests make routing worth investigating. The other six raise a different question: what was happening after someone took ownership? Check the assignment time, shift coverage, and handoff notes for those cases. Even if an earlier assignment had brought all ten unassigned requests in on time, the total would have reached only 34 of 40 (85%). To hit 90% in this sample, at least two of the six requests that already had owners would also have needed earlier replies.

4. Choose a small test and decide how to judge it

The support lead can test an earlier handoff without changing the whole schedule. For two full workweeks, they will check the queue at 1 p.m. and assign every eligible request that still has no owner. At the end of the trial, the team will calculate the same-day reply rate using the original cutoff and eligibility rules.

For both periods, count all eligible requests still waiting for an owner at 3 p.m. The original count of ten covered late requests only. Use the full eligible inbox as the denominator when comparing the two periods, especially if email volume changes. Note any staffing changes alongside the results.

A gap analysis example you can use as a template

Download the worksheet, unzip it, and open the .xmind file. Replace the support team’s numbers with your baseline and target, then add one observation from your own records.

For a meeting, keep the table to one outcome. If the team also wants to improve the quality of the replies, give that outcome a separate row set or map. A fast but incomplete answer can meet the timing target and still leave a customer needing help.

Use Xmind Agent to examine a possible cause

A table makes the arithmetic easy to scan. A map earns its place when there are several explanations to investigate. Give each explanation a branch and put the relevant observations underneath it. As the team learns more, it can revise one branch and keep the original measure in view. This is one way of using AI with visual tools to work through a decision.

Open a blank map and give Xmind Agent this brief:

Map a gap in same-day support replies. We count new weekday emails received before noon that get a first human reply by 5 p.m. local time. In two full workweeks, 24 of 40 were on time. Our target is 90%. Of the 16 late requests, 10 were still unassigned at 3 p.m. and 6 had an owner. Show the baseline, target, and gap. Put ticket observations and possible causes on separate branches. For each possible cause, add one question we could check in the inbox records.

Now suppose the support lead discovers that seven of the ten unassigned requests were in the general routing queue at 3 p.m. Select the branch about late assignment and give Agent the new finding:

Add this observation to the late-assignment branch: seven of the ten unassigned late requests were in the general routing queue at 3 p.m. We have only checked late requests. Add a question about how often on-time requests passed through that queue. Keep the other explanation open.

The updated branch asks how often on-time emails also passed through the general queue. Check that first. If both groups commonly used the queue, compare how long each waited for an owner. Similar waits would give the team a reason to look at what happened after assignment.

To let Agent edit the selected branch, turn off Discussion Mode if it’s on. The Xmind Agent guide shows how to work with a selected topic.

Turn the gap into a decision

After two weeks, compare the pilot’s on-time reply rate with the 60% baseline. If the reply rate rises and the share of emails still unassigned at 3 p.m. falls, keep the 1 p.m. check and monitor the next two weeks. If ownership improves but replies are still late, review what happened between assignment and the first human reply.

For your own gap analysis, choose a discrepancy your team can verify this week. Map the gap in Xmind, put the strongest observation beside the explanation it might support, and name the person who can check it.