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From left: Ravi Agarwal, Joy Pahl and Wolfgang Grassl


In a world where business theory and real-world strategic management often meet at dimly lit intersections, subjectivity and objectivity struggle for dominance much like the halting dance of a four-way stop.

St. Norbert College faculty members Wolfgang Grassl (Business Administration), Joy Pahl (Business Administration and International Business) and Ravi Agarwal (Computer Science) have created a software tool that more closely integrates two schools of strategic planning. Called Meta-SWOT, the tool enhances the capabilities of a traditional SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis and is available to the world as a digital download.

“SWOT is something that pretty much everybody is familiar with, but there are so many problems with it,” Pahl says. “There’s alot of subjectivity and no prioritization system, and the theoretical underpinnings are a little loose.”

The rest of the world apparently agrees with that assessment. A paper the trio published in the Journal of Business Strategy has attracted thousands of downloads and been cited in scores of academic papers around the world. (The article has since been selected for inclusion in "Crafting and Executing Strategy: Concepts and Readings," to be published by McGraw-Hill Education in January 2015.) In addition, hundreds have downloaded the Meta-SWOT tool referenced in the article by contacting Agarwal.

“This team is so different, yet so similar,” Agarwal says. “I loved working with these guys. Wolfgang has his strengths, Joy has her strengths and I have mine. We each can contribute something the other two cannot.”

Building a better mousetrap
Grassl became frustrated with the limitations of SWOT while serving on the college’s strategic planning committee several years ago, so he set out to create a simple tool that would provide more structure for the group’s discussions. His first step involved developing an Excel spreadsheet that would quantify SWOT analysis, to an extent.

He recruited Pahl for her theoretical expertise, and the two soon concluded the traditional SWOT model was too limiting in its rigid definitions of external factors as opportunities or threats, and internal factors as strengths or weaknesses. Instead, they moved toward an approach that favors comparative evaluation of external factors in relation to the user’s own organization.

“This idea of fitting an organization’s strengths and weaknesses to opportunities they recognize in the environment is fundamental to strategic management,” Pahl says. “But there’sa whole other stream of theory that’s come in the last few years called the resource-based model.”

The team developed a resource-based model that looks at strategic planning from an inside-out perspective as opposed to a traditional outside-in method, which looks at external factors and attempts to fit them into an organization’s internal workings. Too often, the outside-in method results in trying to fit a square peg into a round hole.“

In the majority of cases, it’s illusionary to believe that a company can change itself to always fit changes in the external environment,” Grassl says. “In most cases, it’s the opposite. The question should be, ‘Given our core competencies, which markets can we go after?’ A good strategy depends on there being a strategic fit between what’s going on out there and what we can bring to the table. We take the outside as a given and try to adapt our strategy to that.”

Equal weighting of variables is another frustrating shortcoming of traditional SWOT analysis that the team sought to improve upon. The Meta-SWOT model allows for differentiation between factors according to their importance. The tool still relies on subjective judgment, and to some extent this will remain indispensable in strategic planning.

Meta-SWOT asks users to look beyond the success factors of their own organization and determine what their competitors excel at as well, especially in relation to each other. Factors receive labels such as “much superior,” “superior,” “about equal,” “inferior” and “much inferior,” rather than a simple yes or no.

As the team continued to add more bells and whistles to the tool, it became apparent that an Excel spreadsheet wasn’t going to be up to the task.

“The more we talked about it, the more elaborate this model became,” Pahl recalls. “We wanted people to be able to describe their resources and determine if the resources and capabilities were really key strengths of their organization – something they could build on and help drive their strategic decisions.”

Moving beyond Excel
After the team first presented its paper on Meta-SWOT at a Chicago management conference in 2011, Agarwal went to work enhancing the tool using C# programming language. The Windows forms application enables users to answer questions and navigate through the program using “Next” and “Back” buttons, with dropdown options and blank boxes for additional input.

“You can do the initial assessment of the inside-out by answering questions on some static forms,”Agarwal explains. “The tool creates what looks like a three-dimensional image with bubble charts that show you where you stand versus the competition. There’s also a form that summarizes the analysis in a textual context.”

Unlike many traditional models, Meta-SWOT allows for numerical data integration when available. “The tool is not fully quantitative in that it relies on judgment,” Grassl says. “It tries to structure judgment into soft qualification. You have to judge your organization with respect to your competition.”

The team has presented Meta-SWOT at several conferences, including the 2012 Sport & Society in America conference at St. Norbert. Using a local youth baseball program as an example, the team described how organizations at any level can use Meta-SWOT to develop better strategies, including their financial and marketing components.

Agarwal considers Meta-SWOT to be in the beta stage and will continue to benefit from updates fueled by feedback from users all over the world. Technological advances such as advanced database integration and artificial intelligence are on the docket for future versions.

“The plan is, as you keep using the system, it’s going to keep learning about your strategies, your competition, things that work for you, and it can actually start proposing better strategies for you,” Agarwal says. “The prioritization that is there can help us make the tool smarter. That’s the next step in the evolutionary process.”

July 9, 2014