In my presentation, From Training, to Performance, to Social, I describe how Human Performance Technology (HPT) is systemic and systematic, but not very human.

However, HPT, especially performance analysis can be a useful tool, if used selectively and appropriately. It 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.

In his book Drive, Dan Pink looked at rewards, consequences and motivation at work and showed that much of what we have taken for granted is just not supported by the research. Extrinsic rewards only work for simple physical tasks and increased monetary rewards can actually be detrimental to performance, especially with knowledge work. The keys to motivation at work are for each person to have a sense of Autonomy, Mastery and Purpose, as shown in this video. With this in mind, there are times when rewards and consequences are not linked to a desired performance, and this can lead to confusion or even worse. Rewards are still an important aspect to consider in workplace performance. Consider the case of medical researchers sharing their professional knowledge and findings amongst peers.

In a research-oriented work environment, it makes sense to share one’s knowledge so the whole team can be more productive. Insights from one person can save another a lot of wasted time. But what happens when this sharing is not recorded, or people are not given credit for their input? Compound this with a system that only rewards final discoveries, so that researchers have their bonus and career directly tied to their published work. Would you help out a colleague knowing that he alone would get credit for the final discovery? Would you be willing to share if the two of you were in competition for a promotion? Would you share if the company was letting go of staff based on merit, as measured in the annual performance reviews?

Klaus Wittkuhn wrote about human performance system imbalances several years ago in the Performance Improvement Journal.

It is not an intelligent strategy to train people to overcome system deficiencies. Instead, we should design the system properly to make sure that the performers can leverage all their capabilities.

Even if we trained researchers how to share their knowledge using social media tools combined with good network weaving behaviours, we likely would not get the knowledge-sharing behaviours the enterprise leadership say they want. This of course puts the knowledge management and learning support staff in a very difficult position. They know that the leadership says that collaboration is critical, but they see that the internal system has long-established barriers to real knowledge-sharing.

While a performance analysis can be helpful in determining the barriers to performance, sometimes these are controlled at such a high level that they are beyond the scope of those implementing new systems and initiatives. Perhaps the only thing that can be done is to highlight the issue by making it as clear as possible that all the technology and skills will not overcome systemic barriers. In the case of the researchers described above, not performing is rewarded.

Looking at Dan Pink’s three motivational factors, one can also say that even with a good degree of autonomy, mastery of a complex field of research, and a sense of purpose to create products for the benefit of society; there are still obstacles in creating an effective collaborative workplace. This is why anyone responsible for a collaboration project, such as promoting communities of practice, needs to look at all the factors influencing behaviour at work. There are no easy answers when it comes to changing behaviours in large organizations.

Performance Analysis process based on Mager & Pipe’s book
Analyzing Performance Problems