Join Jeff Toister for an in-depth discussion in this video Introduction to data collection, part of Instructional Design: Needs Analysis.
Once project goals are established, the next step in a needs analysis is gathering data. Later on, we'll need this data so we can analyze the training needs and ultimately learn how to make the training program succeed. Without good data, your analysis may lead you to the wrong conclusions. For example, let's say you wanted to train customer service reps on how to work with angry customers. You might assume they need techniques for diffusing customers who are already angry. But what if you had data that told you that the customer service reps often triggered the customer's anger? Armed with that data, you might focus the training on preventing angry customers.
There're a lot of applications for good data. It can help you learn what specific skills need to be trained. The best way to deliver the training and what resources are available. Of course there are some challenges. The sheer volume of available data can sometimes be overwhelming. The specific data you want may not be readily available and data can lead you to the wrong conclusion if you don't use it carefully. When gathering data for your needs analysis, a good way to start is creating a list of questions you'd like to research. Let's go back to the interviewing skills project as an example.
The project overview sheet we created after meeting with Stacey Jones, Regional Vice President, can help us make our list. Now we'll start with objectives. The business goal was to reduce new hire turnover from 30% to 15% within twelve months. So we're going to want to know, what are the causes of turnover for employees within their first 90 days. What is the turnover rate for each supervisor in the Midwest region? Is the turnover rate higher among less experienced supervisors? Our project goal is for supervisor to be proficient with the new interview process.
Of course that means we need to know what is the new process? Now for our audience, that consists of 50 supervisors at 14 locations in the Midwest Region. We're going to want to find out what's causing supervisors to feel pressured to make quick hiring decisions. How can we insure supervisors buy into the new procedure? How can this training make supervisors' jobs easier? What interviewing experience do new supervisors typically have when they come to the job. How do supervisors conduct interviews now? What are supervisors in other regions doing? What's the best way to train everyone given there are 14 locations? And what's worked or perhaps not worked with similar training programs in the past? Now let's look at our constraints as well.
We're given two hours for this training, but is that enough time? Are there opportunities for supervisors to do some pre-work before the training? And with the one month development time, what subject matter experts, or SME's, are available to help us out? We also know there's no extra budget so what resources do we already have that could be leveraged? Now we want to be careful not to assume we know the answers to any of these questions. That's where good data comes in, for example we might assume the new supervisors don't make good hiring decisions as well as the experienced supervisors.
But is that really true? We won't know for sure until we get some data to back it up.
- Setting project objectives
- Identifying the target audience for training
- Selecting data sources
- Facilitating focus groups and interviews
- Designing effective surveys
- Identifying participant needs
- Defining learning outcomes
- Presenting results to project sponsors