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Mak­ing busi­ness pro­cesses easier to un­der­stand

Large en­ter­prises, com­plex struc­tures, and a mul­ti­tude of dif­fer­ent work­flows: Busi­ness pro­cesses are usu­ally made up of many small steps that are im­ple­men­ted in a defined sequence to achieve spe­cific busi­ness goals. Espe­cially in cases where new em­ploy­ees or dif­fer­ent groups of people are work­ing on these pro­cesses, forms of visual rep­res­ent­a­tion, for in­stance pro­cess mod­els, are needed to make these pro­cesses as com­pre­hens­ible as possible for all people in­volved. Kath­rin Figl from WU’s In­sti­tute for In­form­a­tion Sys­tems and New Me­dia has in­vestig­ated the po­ten­tial of visual rep­res­ent­a­tions of busi­ness pro­cesses and looked at how pro­cess mod­els need to be designed to be eas­ily un­der­stood.

According to a study by WU researcher Kathrin Figl, 80% of employees prefer visual representations of business processes over verbal descriptions. When it comes to improving processes, the preference is even stronger, with 90% finding visual process models more useful than verbal descriptions. But even though companies are spending large amounts of money on business process modeling, syntax errors can be found in up to 80% of all models, which is not only indicative of problems in the modeling process but also of comprehensibility issues. Compared to computers, humans only have a very limited working memory and can easily be pushed to the limits of their cognitive processing capacity by complex process models. In her studies, Kathrin Figl from the Institute for Information Systems and New Media investigates the potential of process models as cognitive tools and how process models need to be designed to be understood quickly and correctly.

Finding the right recipe

To find out what process models should look like to be easy to read and understand, Kathrin Figl has carried out experiments with more than 700 participants over the past few years. Comprehensibility issues could be observed especially with regard to complex process structures that include loops and deeply nested control-flow blocks. The choice of modeling language is a particularly important factor for comprehensibility, because the language chosen defines the repertoire of symbols that can be used and the rules for combining these symbols in the modeling process. “One example of a popular visual notation for process modeling is the Business Process Model and Notation system, BPMN for short. BPMN is an industry standard developed by the Object Management Group, and its basic symbol repertoire has been found to be easy to understand for our test subjects,” explains Kathrin Figl. “The modeling language should avoid different symbols representing the same meaning, and it should not use any symbols that have more than one meaning, because this can lead to misunderstandings in the process of reading a model.”

Colors, shapes, and layout

Symbols with similar shapes and colors can also confuse readers. Symbols tend to be easy to understand and to learn if readers can intuitively associate them with their respective meanings. Once business process models reach a certain size, it can be useful to decompose them into various sub-models. Even though it is generally advantageous to avoid communicating irrelevant information to readers, it can be useful to provide them with overview models to give them better orientation and help them find their way around large model hierarchies. Kathrin Figl recently published a literature review which shows that aside from the factors mentioned so far, model layout may also be a “secret recipe” for understandable process models. The first results of an eye-tracking experiment carried out in cooperation with the Technical University of Denmark suggest that certain layout choices (e.g. high visibility of control-flow blocks, avoiding unnecessary changes of model flow direction) can make business process models much easier to read.

Coming up with better ideas

In a joint project with Australia’s Queensland University of Technology, Kathrin Figl also investigated the effects of visual process models on employees’ power of imagination and the quality of their ideas, as compared to the effects of textual process descriptions. This research focused particularly on ideas for improving existing processes. Previously, no research had been done that provided an unequivocal answer to the question of whether visual process models help analysts to come up with innovative solutions or, on the contrary, if visual models restrict their mental perspective. An experiment showed that this latter concern is unwarranted: Visual models worked a little better than textual descriptions in stimulating the creative quality of suggestions for improvements. They do not increase the overall number of ideas for improvements, but they enhance their usefulness and appropriateness for enterprises. “Our test subjects, for instance, came up with more ideas on how to use new technologies in the process. This means that visual process models do not lead to more ideas overall, but they help us to generate ideas of higher quality that are more useful,” Kathrin Figl explains. “Digitalization is bringing changes to enterprises worldwide and across many industries. To remain competitive, it is essential for companies to employ tools that stimulate creative ideas. For this reason, visual business process models are an important tool for optimizing processes and tapping the full potential of digital technologies.”

The studies

The studies Figl, Kathrin (2017): Comprehension of Procedural Visual Business Process Models – A Literature Review. Business & Information Systems Engineering (BISE) (59) 1.

Figl, Kathrin, Recker, J. (2016): Process innovation as creative problem solving: An experimental study of textual descriptions and diagrams. Information & Management (53) 6, pp.767-786.

Figl, Kathrin, Recker, J. (2016): Exploring Cognitive Style and Task-specific Preferences for Process Representations. Requirements Engineering 21 (1), pp.63-85.

Pressekontakt:
Mag. Anna Maria Schwendinger
PR-Referentin
Tel: + 43-1-31336-5478
E-Mail: anna.schwendinger@wu.ac.at



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