Brett LindenbergKnowledge retention in the workplace means two things: employees keep what they learn in training, and the organization keeps what experienced people know when they leave. For training, the strategies with the best evidence are to make learners recall answers instead of rereading, to space short reviews over weeks, and to give them real tasks that use the new skill soon after the course. For expert knowledge, score each role for how soon its holder may leave and how hard the knowledge is to replace, then capture the high-risk knowledge with interviews, shadowing, and recorded walkthroughs. The demo below is a round of mixed practice, another method with research support: three printer faults look alike, and you pick the right first check for each symptom.
What knowledge retention and transfer mean at work
Teams use the term for two different problems, and each one needs its own plan.
- Learning retention is the share of what people learned in training that they can still recall and use weeks or months later. It is a training design problem.
- Organizational knowledge retention is the work of keeping critical know-how inside the company when an expert retires, changes roles, or quits. It is a knowledge management and succession problem.
Knowledge transfer is the step that connects them. Retention means a person can still recall what they learned. Transfer means they apply it in a new situation on the job, or that one person's knowledge reaches a successor. A training program can score well on retention and still fail at transfer if people never use the skill at work.
For study methods you can use on your own, see our guide on how to retain information better.
Knowledge retention statistics: how fast training fades
Skills fade when people do not use them. In a 2025 meta-analysis in Psychological Bulletin, Christopher Tatel and Phillip Ackerman combined 1,344 effect sizes from 457 reports on procedural skills. Without use, learners lost half of their initial training gains after about 6.5 months on accuracy measures, 13 months on speed measures, and 11 months on mixed measures. The authors list chances to perform the task between training and the test among the possible factors that change how fast skills decay.
Memory for new material fades fastest in the first days. Hermann Ebbinghaus measured this curve in the 1880s as the only subject of the experiment, and a 2015 replication by Jaap Murre and Joeri Dros in PLOS ONE produced a similar curve. Both studies used lists of nonsense syllables learned by one person. Claims such as "employees forget 90% of training within a week" circulate widely, but we could not trace them to a study of workplace training, so leave them out of your business case.
The end-of-course quiz hides the problem. In a 2006 study by Henry Roediger and Jeffrey Karpicke, students who reread a passage did better on a test five minutes later than students who practiced recalling it. On tests two days and one week later, the recall group remembered more. The rereading group also felt more confident. A quiz at the end of a module measures what is fresh, so a high score there does not tell you what people will still know next quarter.
Knowledge retention strategies for training
A 2013 review of ten learning techniques by John Dunlosky and colleagues gave its highest rating to two of them: practice testing and spaced practice. Interleaved practice, elaborative interrogation, and self-explanation received a moderate rating. Rereading and highlighting rated low. The strategies below apply those results to workplace training, plus two factors from research on skill decay and transfer: use on the job and support from the manager.
| Strategy | What you do | Evidence |
|---|---|---|
| Retrieval practice | Ask learners to answer from memory during and after training | High utility (Dunlosky et al., 2013) |
| Spaced review | Return to the material after a gap sized to when people need it | High utility (Dunlosky et al., 2013); Cepeda et al., 2008 |
| Use on the job | Assign real tasks that use the skill soon after training, then keep them coming | Skill decay with nonuse (Tatel and Ackerman, 2025) |
| Mixed practice | Mix related problem types so learners must choose the method | Moderate utility (Dunlosky et al., 2013) |
| Explain why | Ask learners to explain the reason behind a rule or step | Moderate utility (Dunlosky et al., 2013) |
| Manager follow-up | Have the manager plan, check, and coach use of the skill | Supportive work environment relates to transfer (Blume et al., 2010) |
| Job aids and search | Make rare procedures easy to look up at the moment of need | Practical design choice; reduces what people must memorize |
1. Ask for answers from memory
Retrieval practice means the learner produces the answer before seeing it. Put a question right after each key point, and ask for a decision the person makes on the job, such as "Which form do you file first?" Give feedback right after each answer so a wrong answer gets corrected while the context is fresh.
In video training, place the question where the concept ends and make it required. Mindstamp questions pause the video and can require an answer before playback continues. With Repeat Until Correct, a learner who misses the question tries again. You can also send a wrong answer back to the explanation with Change Time. The help article on scores and retries explains both settings and how attempts count toward the score.
2. Space reviews by a rule
A single training day with no follow-up leaves the skill to decay on the schedule described above. Short reviews spread over weeks hold up better. In a randomized trial with 537 urology residents published in 2007, B. Price Kerfoot and colleagues sent one group one or two study questions by email each day for 27 weeks in a repeating, spaced pattern. The other group got all 96 questions at once. The spaced group scored higher on online tests given 1 to 14 weeks after the program. Their scores stayed stable across those weeks, while the other group's scores dropped. The gain did not carry over to higher scores on the residents' annual in-service exam, so treat it as evidence for retention of the material taught.
The right gap depends on when people need the skill. A 2008 study by Nicholas Cepeda and colleagues with more than 1,350 participants found that the best gap before a review grew as the final test moved further away.
| When people need the knowledge | Best gap before the review |
|---|---|
| About 1 week after training | 20% to 40% of the delay, or about 1 to 3 days |
| About 1 year after training | 5% to 10% of the delay, or about 18 to 36 days |
For a skill people need for months, a practical schedule is a short recall check the next day, another about a week later, and another about a month after that. Keep each review to a few questions that people answer from memory. For more on breaking a course into short pieces that fit this schedule, see our microlearning strategies.
3. Give people real use of the skill within days
Training teams cannot schedule this step alone, so plan it with managers. Before the course, agree with each manager on two or three real tasks the learner will do with the new skill in the following week. A new support agent who learns a refund policy should process actual refunds with a reviewer that week. A new manager who learns a feedback model should hold a scheduled feedback conversation within days.
Keep the tasks coming after the first week. A skill that people use once a year, such as an annual inventory count or an emergency procedure, needs a refresher or a drill before the next use, because the Tatel and Ackerman results show large losses after months without practice.
4. Mix related problems in practice
When practice covers one problem type at a time, learners know which method to use before they read the problem. Mixed practice removes that cue, so they must recognize the situation first, which is the hard part at work. Robert Bjork called this kind of effort a desirable difficulty: practice feels slower and harder, and people remember more later. The Bjork Learning and Forgetting Lab at UCLA publishes the research behind this idea.
Build a mixed round from cases that look alike but need different responses. The demo at the top of this page does this with three printer faults. In customer service training, alternate a billing complaint, a technical fault, and an upgrade request so the agent has to choose the path each time. Our scenario-based training guide shows how to write these cases.
5. Ask learners to explain why
A rule is easier to remember and to apply in a new case when the learner knows the reason for it. After a rule or a step, ask "Why does this step come before that one?" or "What goes wrong if you skip it?" Let learners answer in their own words with a free-response question, then show the expert explanation.
A teach-back goes one step further. The learner explains the procedure as if to a new colleague. With video response questions, learners record that explanation inside the training video, and a reviewer can watch it later.
6. Make the manager part of the plan
A 2010 meta-analysis of 89 studies by Brian Blume and colleagues found that a supportive work environment was positively related to the transfer of training to the job. The effects of motivation and work environment were stronger for open skills such as leadership than for closed skills such as a software procedure.
Give each manager a one-page brief before the course: what the learner will learn, the real tasks you agreed on, and two questions to ask in their next one-on-one. Our guide to employee engagement best practices covers how manager conversations also affect engagement with training.
7. Make rare procedures easy to look up
For a procedure people perform twice a year, finding it in seconds matters more than memorizing it. Keep a short checklist or reference with each course, and link to it from the place where people do the work.
For video, long recordings are hard to search. Add chapters so a learner can jump to a step by name, and use search so they can find the moment where a term is spoken.
How to measure knowledge retention after training
Measure retention with a delayed check, because only a delay shows what fades. A common way to express the result is a knowledge retention rate:
Knowledge retention rate = delayed test score ÷ immediate test score × 100
For example, if a group averages 85% on the quiz at the end of a course and 68% on a parallel quiz 30 days later, the retention rate is 68 ÷ 85 × 100 = 80%. There is no standard benchmark for this rate, because it depends on the test, the delay, and the skill. Use your first measurement as a baseline and compare the next course against it.
- Write the questions from the job tasks, so each one tests a decision people make at work.
- Give a short check at the end of training and record each person's score.
- Send a parallel check, with the same skills and different wording, 30 days later. Add a 90-day check for skills that matter for the year.
- Find the questions most people miss on the delayed check. Re-teach those points to the whole group.
- For skills, add an observation. A reviewer watches the task on the job and records whether the person did it correctly.
In Mindstamp, identify each learner with an email address or a custom ID such as an employee number, and use the same identity on the course video and on the follow-up video. The completion report has one row per learner with a score for each video you select, so the end-of-course score and the 30-day score sit side by side. The help article on exporting training records lists the fields. If your LMS assigns the courses, a SCORM package sends completion and score to a compatible LMS on supported plans. For the wider question of whether training changed results, see how to measure training effectiveness.
How to retain employee knowledge when people leave
The second kind of knowledge retention starts with a list of who knows what. In January 2026, the median U.S. wage and salary worker had been with their current employer for 4.1 years, according to the Bureau of Labor Statistics employee tenure release of September 24, 2026. Workers aged 55 to 64 had a median tenure of 9.6 years, more than three times the 3.0 years of workers aged 25 to 34. Long experience in an organization is concentrated among the people closest to retirement age.
Score knowledge loss risk for each role
The International Atomic Energy Agency publishes a simple scoring method in Knowledge Loss Risk Management in Nuclear Organizations (IAEA Nuclear Energy Series No. NG-T-6.11, 2017). The IAEA reports that many nuclear power plants have adopted it, and nothing in the scoring is specific to nuclear work. A manager rates each employee on two factors from 1 to 5 and multiplies them.
| Score | Expected departure |
|---|---|
| 5 | This calendar year or next fiscal year |
| 4 | In the third calendar year from now |
| 3 | In the fourth calendar year from now |
| 2 | In the fifth calendar year from now |
| 1 | In the sixth calendar year or later |
| Score | Knowledge held by the person |
|---|---|
| 5 | Critical and unique, mostly undocumented; a replacement needs 3 to 5 years of training and experience; no ready replacement |
| 4 | Critical, with some documentation or someone elsewhere who knows it; 2 to 4 years to train a replacement |
| 3 | Important and documented, or others on site know it; 1 to 2 years to train a replacement |
| 2 | Procedural, with current procedures and training that takes less than 1 year |
| 1 | Common; new hires with the skills are easy to find |
The total risk factor is the attrition score times the position score, from 1 to 25. The IAEA guidance treats 20 to 25 as high priority with immediate action, 16 to 19 as a priority for staffing plans, 10 to 15 as roles to plan for ahead of time, and 1 to 9 as roles where you note the replacement need. It also recommends a retention plan for anyone with a position score of 5, whatever their departure date, because people also leave through promotion and transfer. The same guidance warns that managers tend to rate their high performers as holders of unique knowledge. Base the position score on the knowledge itself.
Build a knowledge retention plan for each high-risk role
The IAEA guidance gives each high-priority person a written plan. Adapted for any workplace, a knowledge retention plan lists:
- The critical knowledge or skill, described as tasks and decisions ("approves supplier exceptions", "diagnoses line 3 jams").
- The person who holds it, the successor who will learn it, and the manager who owns the plan.
- Whether the knowledge is documented (explicit) or held in the person's head (tacit).
- The capture method for each item, with an owner and a due date.
- How you will check that the successor can do the task without help.
Match the capture method to the type of knowledge:
- Structured interviews draw out tacit knowledge: the exceptions, warning signs, and contacts the expert relies on. The IAEA publication includes interview guidelines and sample questions in Annex II.
- Shadowing and paired work let the successor do the task while the expert watches, which no document can replace.
- Recorded walkthroughs keep the expert's reasoning. Ask the expert to narrate why they do each step while they do it.
- Decision logs record why the team chose a supplier, a setting, or a workaround, so the reason survives the person.
A recorded walkthrough becomes training when you add structure to it. In Mindstamp, add chapters for each step, add questions at the points where newcomers usually go wrong, and use search so a successor can find the moment the expert explains a term. Genie AI, on supported plans, lets viewers ask questions in their own words and answers from the video and the material you train it on.
Tools that support knowledge retention
The two kinds of knowledge retention need different tools. To track learning retention, you need a tool that records a score for each person on a delayed check. To keep expert knowledge, you need a place where the captured knowledge stays current and easy to find.
| Tool type | What it does for retention | Examples |
|---|---|---|
| Learning management system (LMS) | Assigns courses and refreshers, records completion and scores per person | See our comparison of LMS platforms for small businesses |
| Spaced reinforcement app | Sends short question sets to learners over weeks and tracks answers | Qstream describes spaced learning for long-term retention; Axonify describes microlearning for frontline workers |
| Knowledge base | Stores documented answers with owners and review cycles | Guru describes routing content to experts for review and verification |
| Interactive video | Adds questions, feedback, and branching to training and expert recordings; reports each learner's answers and score | Mindstamp (see interactive video for training) |
A knowledge base tracks content, so it cannot tell you what people remember. If your question is which solutions track knowledge retention, look for tools that record each person's score on a check given weeks after training.
Common questions about knowledge retention
To promote retention of skills, which action is most effective?
Regular use of the skill with feedback, spread over time. A single long refresher session does less than short practice sessions spaced over weeks, and skills that people never use decay the fastest. In the 2025 Tatel and Ackerman meta-analysis, learners lost half of their initial gains on accuracy after about 6.5 months without use. Schedule real tasks or drills before that point.
What are the strategies for knowledge retention?
For training: retrieval practice, spaced review, use on the job within days, mixed practice, explaining why, and manager follow-up. For organizational knowledge: score roles for knowledge loss risk, write a retention plan for high-risk roles, and capture tacit knowledge through interviews, shadowing, and recorded walkthroughs.
What is a good knowledge retention rate?
There is no published benchmark that applies across courses. The rate depends on the difficulty of the test, the delay, and how often people used the skill in between. Measure your own baseline with the same delay each time, and aim to raise it from one course run to the next.
Does bite-sized training improve knowledge retention?
Short lessons help when they make spacing and recall easier: a five-minute module with three recall questions, sent again a week later, puts two of the strongest methods into practice. A short lesson that people watch once and never revisit has the same problem as a long one.
How should a beginner approach structured CRM training to ensure long-term skill retention?
Train by workflow, one at a time: log a call, move a deal to the next stage, create a follow-up task. For each workflow, show it once, then have the learner do it in a sandbox with realistic records. Add a recall check the next day and the next week, keep a one-page reference next to the CRM, and after 30 days review real CRM records for the same tasks, such as deals with missing next steps. The records show whether the skill held.
Where to start
Pick one course where forgetting costs you money, such as a safety procedure, a product launch, or a new system. Add recall questions with feedback inside the course, agree on real tasks with each learner's manager, and schedule a parallel check for 30 days later. Compare the 30-day scores with the end-of-course scores, then re-teach the points most people missed. In the same month, score the people in your most critical team for knowledge loss risk and start a plan for anyone at 20 or above.
