WRITING AND DATABASE TECHNOLOGY
NOTE: Article originally written in 1996
Data reports refers only to printed reports that are composed of both tables of numbers, words, or both. Tabular reports are the most common.
Reports consisting of data tables are vital to almost every business function. These reports are used by marketing, budgeting, production, and sales. This means many people may require many different versions of the same report, catered to their own personal needs. These reports can be intended strictly for the specific person reading them, or for a general group of readers.
The value of reports is organized record keeping and problem solving. However, many businesspersons lack the proficiency to generate a form and content that directly address a pressing business problem. According to a survey, managers were spending almost half of their work year looking for such data. Often, current reports would need to be adjusted and mathematically figured so that the new reports actually did provide the correct data. This process can be very frustrating and little attention is given in either business or in technical and professional writing classes to building people’s skills in writing effective data reports.
To develop these reports, writers have to transform raw data (“facts”) into meaningful information for a given context, audience, and organizational purpose, and it must be communicated in an effective way. This transformation is a rhetorical activity. People learn about data reporting, not through specialized courses, but in computer training classes, therefore stressing technological skills over rhetorical. This sends the message that knowing how to operate a technology is commensurate with knowing how to use it to its full advantage to achieve a purposeful exchange of information.
Data reporting demands a dynamic interplay between a writer’s rhetorical and technological skills. As such, it should have a place in technical and professional writing classes. The purpose of this essay is to explore unique skills and knowledge that data-report writers need to learn in order to produce effective data reports. Mirel argues that if data reports are to serve readers’ needs for record keeping and problem solving then writers’ technological skills must serve their rhetorical aims and strategies.
DATA REPORTING AS COMMUNICATION
To analyze the interactive rhetorical and technological competencies involved in data-report writing, Mirel first presents a framework for understanding the communicative dimensions of report writing. Historically, data tables have been associated with scientific rationality. However, this asocial view of tabular data ignores the inescapable rhetorical intentions and practical consequences of retrieving and reporting data. Many researchers argue that facts are not simply transferred from senders to receivers, but rather that it is based on a relationship between readers and writers. This relationship-based view of constructing knowledge casts a new light on the writing of data reports.
Many composition specialists examine computer literacy and electronically produced information through this constructivist lens. However, they omit databases and nonlinear tabular communications from the technologies they examine, such as word processing, desktop publishing, electronic conferencing, and E-mail. Some research in rhetoric, visual design, and human factors, however, does focus on database-related communications. This research reveals that
Key rhetorical strategies inform data searches, retrievals, and reporting;
Rhetorical and technological skills mutually support and shape each other; and
Designs for functionally effective tables must facilitate readers’ strategies for answering business questions.
Key Rhetorical Strategies Inform the Searching for, Retrieval of, and Reporting of Electronic Data
Sullivan (1986) concludes that rhetorical invention is the defining feature of electronic data searches. She finds that searchers must possess the following skills, all of which involve invention processes:
Knowing the meaning of “invisible” data that are stored in the system;
Focusing on what is at issue in a communication situation (stasis); and
Determining the most effective topical orientation of a particular purpose (topoi).
Rhetorical invention also comes into play in reporting data. Research finds that writers do not experiment with enough formats. Therefore, they rarely produce the best format for their exact purposes. As on overview of qualities necessary for effective data reports, Zmud (1978) identifies four characteristics that are implicitly rhetorical, as noted in the parenthesis:
Quality of information (selecting appropriate and relative data);
Accuracy and sufficiency of information (selecting the right scope and detail);
Quality of format (sequencing, ordering, and chunking information effectively); and
Quality of meaning (evoking emphasis, patterns, and relations through logic and layout).
Skills in Rhetoric and Database Technologies Support and Shape Each Other
A number of studies show an inextricable link between rhetorical and technological strategies in data searching and retrieval. Researchers find that unless people know (or invent) (a) the meaning of the data, (b) the significance of data relationships, and (c) the right level of detail for a questions, they will have difficulty understanding the basic program logic of search principles and data structures.
Designs for Functionally Effective Tables Must Facilitate Readers’ Strategies
Developing effective tabular displays of data should lead writers to research on visual rhetoric. A list of such research reports is found on page 384. These researchers emphasize the need to design tables to answer questions that readers will ask. There are three distinct levels of questions and answers: elementary, intermediate, and overall. The goal for designers is to choose a tabular image that answers the majority of questions the information is capable of generating.
Functionality is also important in designing tables. While simplicity works best as an aesthetic preference, it is not always the best strategy for displaying information. Designers should realize that the effectiveness of a table does not depend on how much information it includes, but on how information is layered and ordered to facilitate readers’ interpretations. Developing effective data reports requires writers to be adept at rhetorical strategies for invention, arrangement and delivery, and to understand the logic and capabilities that a program offers for defining, searching for, and retrieving data and for organizing it into printed reports.
METHODOLOGY
To study the rhetorical and technological skills involved in data reporting, Mirel analyzed readers’ reported responses to the actual data reports that they receive and use at work. From these responses, she inferred some knowledge and skills that writers should have to develop effective reports.
Mirel had 25 respondents – project administrators in a national research laboratory. She gathered information on their responses to a report that they received each month. The report was generated from a mainframe financial system. The respondents used the report for tracking costs, managing accounts, and assessing budget over- and under-runs. Mirel conducted a semi-structured interview with the respondents that usually lasted an hour. She asked the respondents the same four questions; then she analyzed the participants’ combined responses for patterns in their strategies and purposes for analyzing the report, for their satisfactions and dissatisfactions with the report, and for their methods of overcoming problems with it.
Mirel showed that the respondents are uniformly dissatisfied with the report and use the report for the same general purposes.
RESULTS
Each month, respondents use the report to answer four central cost-accounting questions: (1) Are all the changes legitimate? (2) Where do high or unusual charges come from? (3) What are the differences between actual and budgeted costs? and (4) Which accounts are likely to run over budget (and how should resources be allocated to avoid that overrun)? The respondents criticized the reports with the following six reasons:
Information overload: the report has too much data.
Overly narrow content: it does not give a big enough picture of cumulative months.
Random data: it does not group or emphasize data for easy interpretation.
Unprocessed data: it does not calculate key relationships such as variances between actual and budgeted costs.
Unintelligible data: it labels rows or columns with terms that have unclear meanings.
Unpresentable data: it has low legibility and layouts with little difference between figure and ground.
Some respondents rearrange their information in some ways, but six of the respondents rearrange their report either on their own PC or in the interface program. These six are considered writers as well as readers. The other respondents believe they lack the technical knowledge to reorganize their reports.
DISCUSSION
Most respondents felt that they lacked the technical knowledge to adapt the software or applications to their specific needs. They need to know how to translate their rhetorical aims into a technologically produced document.
To develop effective reports, writers must learn the database capabilities that enable them to achieve their rhetorical aims for invention, arrangement, and delivery.
The Aims and Processes of Invention in Data Reporting
The success of data reporting depends on fundamental invention processes, namely writers becoming familiar with a subject, identifying issues and questions that concern readers, understanding the optical orientations that address these concerns, and selecting content accordingly.
The respondents’ unhappiness with the report can be traced to many invention issues. The report does not select and display key data relevant to their needs. Many of the respondents wanted other content as well, such as more verbal description about purchases. The report writers need many technical competencies in database applications, but databases are one of the most complicated technologies for lay users to manipulate for their specific purposes. Writers also need to understand if the connections among data that make sense, practically, for solving a business problem are technically feasible. It is only feasible if the data are set up in a special way to allow writers to retrieve data from different databases.
Once the databases are created, report writers have to know how to frame their searches for information in statements that a program will accept and process. Writing search statements involves abiding by the syntax of a program and, at times, becoming creative with its search logic.
Finally, report writers’ technological strategies include assessing whether the data they retrieve are in fact the right data for their purposes. Database users rarely check the answers yielded by a search “failing to search for other levels of data which could supplement or contradict what they already found.”
The Aims and Processes of Arrangement in Data Reporting
One of the greatest challenges for report writers is to choose an appropriate organizing logic for tables that are multifunctional. They need to know that data reports for marketing purposes may take as many as five drafts of a table before a report convincingly shows a supervisor that it is best to target a very small group of low-volume customers because they generate the highest revenue.
Rhetorical purpose should determine whether the best display is a table or some other graphic form. The preset order of columns results in separating data that these readers want to compare. The row headings also do not accommodate the “cut into the data” that some respondents want to take because of the unique structures of their projects.
The Aims and Process of Delivery in Data Reporting
Delivering information in effective visual designs involves giving readers easy access to the data and data relationships relevant to their concerns. Reports used for reference usually display large amounts of data in a small amount of tabular space. Legibility is paramount.
Reports used for problem solving need designs that draw readers’ attention to key information and that help them to distinguish important types and groupings of information. Table displays should create for readers’ paths through the table so that readers perceive particular groupings of data as individual “locales” that they may access at random and read as self-contained information. Type size, style and variation are vital for emphasizing specific elements and relationships; positioning and locating data support people’s conventional strategies for reading left to right and top to bottom. Use of white space is important in creating tables that maintain readers’ understanding.
IMPLICATIONS FOR TEACHING AND FURTHER RESEARCH
For invention, arrangement, and delivery, writers of data reports must dynamically relate rhetorical and technological strategies to produce accessible and purposeful tables of information. The effectiveness of data reports, as judged by readers in an actual communication context, hinges on writers having chosen and implemented conceptual and visible displays that answer readers’ concerns and questions.
Mirel suggests introducing undergraduate students to a curricula including technical and professional writing. It would be especially beneficial if the writing and computing teachers could provide some collaboration for the students and can include team teaching to show how both areas cross over.
To better understand the rhetorical and technological competencies involved in data reporting, researchers need to investigate the ways in which various features and functions of database applications enhance or constrain rhetorical choices. More studies should focus on report writers and actual readers in natural work settings, closely assessing the qualities that characterize effectiveness for different types of data reports and the processes involved in producing them. These studies need to extend long enough for researchers to iteratively test writers’ choices and revisions against readers’ actual uses of a document.
10 comments:
I do not have a strong first-hand knowledge of data reports. Yet, I have read research papers or other documents that have an overabundance of numbers with not much explanation-authors hoping that the numbers speak for themselves. So, I definitely agree with what Mirel was discussing-writers of these reports need to acknowledge the importance of audience analysis when putting the report together. Writers need to anticipate and answer readers’ questions before they even have them. I also thought her comment on the need for undergraduate courses in this type of writing is an important part of absolving the problem of ineffective data reports.
Some excellent suggestions in this article. I have a confession to make: I have never made myself a template for data reporting, yet I think it is the most beneficial thing in that kind of work. Perhaps it is because I am still a student, but I can see how templates for work would make every part of the process (from reporting data to retrieving it) much easier for writers and audiences.
As for online databases, I have little experience. What software do companies typically use for data reporting/archiving?
I think collaboration would be extremely helpful in producing data reports. This article discusses how the writer must take into consideration the design of the report to best communicate the data to the readers. It sounds essential to then pull together the writer with a designer who specializes in the layout of the reports. The audience's understanding is the most important part of data reports, and it seems collaboration could be the best way to achieve this.
Unfortunately, many data reports are internal documents, and the company probably won't want to spend bucks getting multiple specialists involved in their production. Often, it will be up to one or two people to understand the database structure, query the database, produce a report, and edit for formatting and content. That's a tall order for most people because, as mentioned in the article, not very many people have dual expertise in working with databases and writing excellent reports. The suggestion that there should be more training in technical communication programs on database interaction is a great one.
I agree with David's assessment that most companies are not going to spend the kind of money that is really needed to produce good data reports. Additionally, I think that most managers think that data reporting has a limited audience and not that important, at least in the corporate world. The thought must be that it isn't difficult to produce the occasional bar graph or pie chart for an annual report or quarterly sales presentations. But that's not really the type of data reporting that Mirel is addressing in this article. I think the key to good data reporting lies in the ability of the writer to fully comprehend the material to be presented and to have excellent knowledge of the end user's needs. I'd really enjoy seeing great data reporting that's easy to comprehend and use. Too often, data doesn't get presented in the most understandable manner. Perhaps if there were some studies about the damage that bad data reporting does, then companies might be willing to spend some additional money on better writing and designing of data reports.
I appreciated this article's focus on the needs of the reader. It seems like a lot of the literature seems to focus more on the technical communicators, which, while essential, is only a part of the equation. Without readers, who would we communicate to, and without communicators, what would there be to read? I found Zmud's list of rhetorical qualities necessary for effective data reports to be particularly useful.
Just like Jennifer I do not have much experience with writing data reports. But I have come across reports that include too much data and not enough data or ambiguous explanation of the data.
Rhetorical context is a key in data reporting and as author states herself “…more important than the format of a table-is for writers to select and present only the information integral to their communication context”(p. 384).
But this also leads to dangers of overly narrow content thus not explaining data within their appropriate contexts. I have an example- There is a data report I will need to comply and present to my bosses related to computer literacy levels of speech communication students. If I only present data and make no explanation or make the explanations too narrow, the data will have no significance to anyone but me. In this case, data can be misinterpreted thus ushering ethical implications.
I love data and statistics! Over the years, however, I have learned to be cautious about embracing data and reports that form a conclusion based on dala collection. The reader needs to consider the source of the data, confirm its validity and also analyze the intent of the data usage. It is easy to use statistical data in different contexts and shift the message the data portrays. The reader needs to remember that data is a support tool: it supports the writer's message.
We have a few experts in my company who are great at pulling useful information out of a gigantic database of information and presenting it in a way that is helpful and understandable. It is definitely a talent (skill) that not everyone possesses. Those who do are in great demand and are absolutely amazing at listening to what kinds of information you are seeking and then working their magic. Voila--there it is. Like many computer skills, expertise doesn't just happen. For the limited experience that I have with databases, I find that the programs are not as intuitive as Word or Excel are. A person can usually muddle through in Word and get the computer to do what you want it to do. However, databases take some basic understanding to even create simple reports. So training is helpful. But the interesting thing that this article points out is that the training usually doesn't address the rhetorical needs of the users. That kind of expertise probably only comes after lots of practice.
Like the poem, a good report can be "very very good" and a bad report can be "horrid". It's extremely frustrating when you can't make sense of data -- even more so if you're not familiar with the information to begin with. As always: consider the audience!
I have never written these types of reports, but I have a better appreciation of the nuances after reading this article.
Post a Comment