1. The software is intuitive. Our users are smart and can figure it out themselves.
The software is just one part of the training equation. Yes, data warehouse users have to know how the software works, but they also need to know what the data means, what the metrics actually measure, how to construct queries to answer business questions specific to their needs, and how to interpret the results. These latter issues lie at the heart of user performance, not software skills. Formulating queries draws on a lot of prerequisite knowledge about business processes and data as well as new information about how data warehousing works - not to mention understanding the new terms and measures used in the warehouse. The actual mechanics of the tool end up not being so important.
2. We don't have to teach business processes. Our people know that. Just focus the training on using the data warehouse.
This is one of the most common pitfalls affecting data warehouse use and one of the easiest ones to fall into. Everyone says they know the business process-after all, who is going to admit that they don't? But gaps in business process knowledge can adversely affect user performance. Users can only construct a meaningful query and get a correct response if they understand the business process behind the terms, criteria, and measures used in the query. What does this measure mean and where in the business process is it taken from? What criteria do I have to select for or deselect for to give me the answer I want? You may find that there is not the political will to develop training on business processes; however, you may find informal methods of sharing business process knowledge - brown bag lunches for example.
3. Our key people can develop and teach the training. They're smart; it's part of their job.
Key people or subject matter experts (SMEs) are smart - in fact, they're too smart to do the job. As knowledgeable and qualified as SMEs are, they may not have the skills to teach a new user. Experts' knowledge does not necessarily break down into the small chunks of information a novice needs, thus their explanations are often over the head or contain too many details for the new user who is struggling to grasp the basics. The expert's knowledge is still needed, but they should not play the major role in designing the training. The best approach is to pair experts with persons skilled in instructional design. This pairing will result in sound training that takes into account what learners know, what they need to know, what instructional strategies are appropriate to bridge the gap, and what and where the practices should be. If your instruction is well-planned and organized the first time, people are going to walk away with confidence and a desire to use the data warehouse. If it's not - they will walk away thinking the tool doesn't work. That is a costly mistake to get over.
4. New employees can use the data warehouse as well as experienced ones. The ROI is the same.
Many managers send new employees to company training classes-data warehousing being one of them-- with the noble intent of orienting the new employee and making them productive faster. However, training new employees to construct ad hoc data warehouse queries is often for naught. New employees don't have the prerequisite knowledge of business processes. They are often frustrated trying to get a grasp of the data, the measures, the software tool, as well as understand the business process behind it all. Perhaps more importantly, new employees have trouble interpreting the results. They don't have a sense of what is within normal parameters and what is not, and may make important business decisions on incorrect data. Although it may be easy to fill those empty training slots with newer employees, the return on investment is not there, and may actually skew your data on user performance later on as they stop using the system.
5. We've done enough communication with managers in the company. They know what it's for and will support the users.
The environment the trainee goes back into has more influence on performance than the training itself. Is there time to use the data warehouse? Are other duties getting in the way? Is there any incentive for using it? Does anyone care? Management, not training, controls these issues of user performance. Managers must support trainees' use of the system to make it work. Despite the nods of agreement you received when you explained the concept of data warehousing to managers in your early rounds of communication, when it comes right down to it, managers want to know what's in it for them before they give their whole-hearted support. Data warehousing is supposed to solve business problems. Find those problems and show how the data warehouse answers will make the managers' life easier, better, more effective, more empowered, etc. This is an on-going effort. You may have to schedule another round of communication, target departments one by one, or tailor training to each department. But the bottom line is, managers need to support trainees back on the job or usage will drop, and the best way to remind them of the value is to show what's in it for them - again and again.
6. All the training should be on the web.
As satisfying as this caveat is - after all, a high tech solution deserves high tech training--you may find that such a strategy may not prove to be as effective or as efficient as first expected. All individualized instruction, whether print, CD-ROM, or on the web, needs to be robust enough to stand alone-that is, with no instructor support. This strategy works well when teaching the software, or the data, or even what data warehousing is because the pitfalls that a trainee can fall into can be easily anticipated and accommodated. However, this methodology may not work as well with subject matter that is more complex, where learners need to perform high level skills such as create, generate, synthesize-in other words, create a query, generate an answer, and interpret the results. Pitfalls are many and cannot be so easily identified and accounted for. A methodology that provides more guidance and coaching is called for, often best provided in the form of an instructor. This is not to say that learning cannot be distributed with an instructor in a central location and learners in various locations hooked up via NetMeeting or other telecommunications program. Technology can be a part of the solution. Consultation with an experienced instructional designer can help you choose the methodology and organization best suited to your situation.
7. Once users are trained, nothing should impede their use of the data warehouse.
Having the skills and knowledge-in other words, training-to use the data warehouse is just one aspect of user performance. Other technological and organizational factors impact both user performance and user satisfaction.
In regards to the technology, is the data warehouse available when users need it? Is the system responsive? Is the data accurate? Is it complete? Is it even there? How complex is the data model? Does its complexity impact the users ability to form queries? All these factors affect users satisfaction and use of the data warehouse.
In regards to the organization, are people and resources available to help when needed? Do supervisors and managers support its use? Do they ask for the data? Are there resources or documentation available to support its use (e.g. a data dictionary)? Are there resources for continued education? The structure and culture of the organization also impact the use of the data warehouse.
It is helpful to know the organization's driving and restraining forces before launching a large technological initiative such as a data warehouse. An organization survey focusing on the key factors for success is recommended as one of the early steps. Such a survey will identify the organization's strengths to be leveraged as well as limitations that need to be changed or worked around. strategies for launching-and maintaining-the technological initiative can be tailored according. Such an organizational survey provides the context for the technological, political, and organizational work ahead.