Description of the Extant Data Technique
Extant data analysis …..
· Unearths the results of employee behavior
e.g., sales figures, accident reports, enrollments
· Makes it possible to determine the relationship between employee effort and organizational goals
e.g., matching sales with expectations
· Assures that internal. Regular, corporate data is part of the front end inquiry
e.g., accident reports or exit interviews as part of the study
· Involves cajoling and negotiating for information
· Is gathered and examined by human resources professionals but not originally generated by them
When do you use this technique?
Ealy and repetedly when confronted with performance problems in ongoing situation – usually not new systems, product or technology.
Under ideal circumstances, a supervisor or manager has used extant data to determine the details of the problem be for you are assigned to it. He or she then provides you with and initial description of the situation based on review of the records. That doesn’t always happen.
What most often happenes is that one slippers of extant data ( like an accident or a letter the CEO) gets to the momentum going. “ Put together a course on this thing so we don’t have anymore accidents!” or “ do something on communication for our flight attendants.” It’s obvious they don’t know how to keep our passengers happy.” Before doing anything, make certain that you hve first taken a close and careful look at all natural, related records and information.
Once you hve examined records and are now involved in all the stages of TNA, you will want to keep referring back to natural records. Extant data is a reality touchstone; it doesn’t lie, especially if it is based on results of employee performance gathered over time. For example, you may be told by employees that they know all about the ‘Salt of the earth’ account. Go back to the extant data to check the records and see if there are any customer complaints about inaccurate information. Are the cards filled out correctly? Have customers been properly qualified? Match what you hear from sources during needs assessment with extant data. Pursue discrepancies.
How Is Extant Data Analysis Done?
Extant data analysis is a sleuthing technique which gets developers and trainers to outcomes of performance. Extant data analysis is unlike other front end technique because it involves use of INFERENCE, OBSERVATION and PERSUASION only. Trainers willnot intervies or survey, instead they will pour over and paw through records and files. The keys to the technique are figuring out what kind of information you need, determining where it is, gaining access to it and incorporating what you find.
Here is a series of steps which will enable training professionals to carry out this technique :
Step 1 : Examine the job and Its Outcomes. Examine the job, focusing attention on the duties or tasks which have been identified as problematic. Think about what employees do, might do, and the opportunities or challenges with which they are confronted. For example, look carefully at the tellers’ opportunities to sell ‘Salt’ accounts. Examine the materials that they have been given to give ti customers who inquire about “Salt of the earth” accounts. Look at recent directivies related to customer wait time. Has there been any recent corporate pressure to diminish the moments that customers stand on line? What else is going on in te branches now? Has there been a major ad campaign that might increase traffic for purposes other than ‘Salt?’ Are there any other new , competing products? When tellers were informed about ‘Salt,’ what else did they learn or get?
Step 2 : Identify Quantitative Results of the Job. List the tangible and possible quantitative outcomes of that portion of the jb. There are enroute outcomes and there are terminal outcomes. For example, an enroute outcomes is the forms that the teller must fill out to initate an account. The terminal outcome is the nuber of accounts sold and the size of the accounts. Word processing provides another example. Enroute quantitative outcomes would be the telephone and electronic mail questions logged regarding the system and its uses. A terminal outcome is the number and kind of documents generated per employee. Establishing quantitative outcomes is based on corporate or agency goals. It is enroute outcomes. What the company is seeking to achieve is job stability and statisfaction. If that is the case, then a more appropriage terminal outcome would be the number of request for transfer and information collected during interviews. Note that this step focuses on the kind of results which can be counted and measured objectively. When you begin to seek subjective information. For example, the kinds of aggregate feelings which might appear on exit interviews, then you are talking about the qualitative eefects of employee performance. That moves us to Step 3.
Step 3 : Identify Qualitative Results of the Job. List any likely reports of qualitative impact of performance om people. What are others, like customers or users, saying? Are there letters or telephonic comments that have been collected? What about performance appraisals or exit interviews? Most companies or agencies gather information about others’ responses to t hem. What are they? Where are they? The classic example of this kind of subjective and important data is letters of complaint and appreciation. For whom? What are they saying? Remember that you are seeking the records and natural collection of opinions and responses. When thinking about qualitative outcomes, it is important to do more that count comments. You will be pressed to do a content analysis, a serious examination of the recurring and often subjectively derived themes within the extant data.
While both steps 2 and 3 involve systematic creation of lists, don’t forget the richness of what Joe Arwady calls “ eureka finds.” There are piles of interesting indicators hidden within companies and agencies : old newsletters, esit interviews, requests for transfer, union mailings, etc.
Step 4 : Determine How to Get Extant Data and Eradicate Obstacels. Now that you have a list, you need to do something with it. Where is the information? Who has it? Who else has it? Will there be resistance to your efforts to dig into files and peruse computer print-outs? Have there been any reports produced for other purposes which might relate to the problem or situation?
Not all extant data is equally accessible. Usually, you can gain acces to enroute outcomes more readily than the extant data which is very close to the bottom line. The company might, for example, give you copies of the account slips and cards that have been filled out by tellers. Where they will balk is at the computers print-out which present sales per teller. Per supervisor andper branch.
It is not unusual for managers throughout the company to want to know “why somebody from training wants to look at accident. Breakage or cold call reports?1?” you might have to construct elaborate justifications to gain acces to extant data. I remember a performance appraisal project like that. Upper level management was dissatisfied with the quality of performance appraisals filed by middle managers. They turned it over to training and to an external consultant. They wanted a course to fix the problem. Before progress could be made, a verifiable picture of actual, current middle manager performance on these appraisals was necessary. It made sense to examine randomly selected performance appraisals that had been submitted over the past 18 months. Sounds reasonable? Sure. Still, the group had ti justify, implore, reason and nearly beg to get their hands on this extant data. Finally, with names appropriately masked, the training group was allowed to serutinize those appraisals and use them to infer actual middle manager skills and knowledge. If you are clear about what the extant data does for you, how it contributes to your TNA puposes, you will be more likely to be able to make a clear and compelling case to examine that data.
Step 5 : Examine the data. What are you going to do with it once you have it? Look back at the list of possible uses for extant data included at the beginning ot his chapter. Which are appropriate in your situation?
In the performance appraisal example, hand in hand with a subject matter expert from the Personnel group, you would examine these randomly selected appraisals for frequently recurring problems. Where are they? On which lines? What exactly are they? Is it a lack of specificity? Failure to use behavioral statement? Failure to substantiate? The exact nature of the erros which appear on the forms must be analyzed and then summarized.
Let’s turn to the ‘Salt’ example. It is possible that extant data analysis will prove that tellers are filling the usual number of cards and that they are filling them out people who are qualified by income and circumstance to purchase the ‘Salt’ account. If that is the case, you need to ask questions about why they don’t qualify purchasers. In that example, extant data directed the instructional designer to seek very specific information on cause.
