The field of Human Performance Technology (HPT) is systemic and systematic, but not very human. For that we also need to support informal andt social learning. However, HPT, especially performance analysis can be a useful tool, if used selectively and appropriately.
HPT does not work well for tasks that require high degrees of tacit knowledge and cooperation to address complex problems. But I find it useful for confirming that training is the optimal solution, as it is often the most expensive option, so it’s best to be sure. Some barriers to performance that are often overlooked when prescribing training include:
- Unclear expectations (such as policies & guidelines);
- Inadequate resources;
- Unclear performance measures;
- Rewards and consequences not directly linked to the desired performance.
In some cases, these barriers could be addressed and there would be no further requirement for training. Where there is a genuine lack of skills and knowledge, training may be required, but it should only be in cases where the other barriers to performance have been addressed. A trained worker, without the right resources and with unclear expectations, will still not perform up to the desired standard.
The performance analysis process shown below is based on Mager & Pipe’s book, Analyzing Performance Problems. According to this chart, training is only warranted when there is a clear lack of skills & new knowledge and the person has not done anything like this before. If there is any doubt, one should confirm that there are no obstacles to performance; there are adequate resources; NOT performing is not being rewarded; performance is not being punished; and performance does matter. My experience is that individual performance issues are often the result of inadequate resources or conflicting messages from management.
Here is my updated graphic, as the previous one, made several years ago, was a bit hard to read.
Having enough tools, and knowing which ones to choose, is important for any discipline. In organizational performance, it is critical because we are always dealing with complex adaptive systems. We should consider that all models are flawed, but some may be useful. But we shouldn’t get too attached to our models.
In many cases, when training is prescribed for a work performance issue, it is a case of assuming it is a “training problem” without any further analysis. I can think of two examples in my own business experience.
In one case, e-learning was prescribed to address the performance needs of nurses changing to a new nursing care methodology. In that instance, I was able to convince the client that a quick performance analysis could be used to confirm the assumption that e-learning was the solution. As a result of the analysis, we changed the intervention to the development of an online diagramming tool, because we determined that nursing staff already had 80% of the necessary skills and knowledge, but they didn’t know how to use the new diagramming and reporting procedures. The initial e-learning program was greatly reduced and job aids were created.
In another case, training was prescribed in order to get staff up to date with a new organization-wide policy. Each person received an average of 17 days classroom training. As an observer for part of the training, I would estimate that all of the classroom training could have been done in less than a week, had the new procedures and some job aids been first developed. The total cost of training approached millions of dollars, plus the cost of missed work. The change in performance appeared to be minimal, but the training provider generated significant revenue.
The right tool, for the right job, in the hands of an experienced practitioner, can often ensure that the right problem is addressed.
70%: Experience