What happens after the SWOT analysis?
The first step is to match the company's strengths with its opportunities to enhance its level of competitiveness. Then you consider the vulnerabilities that need to be improved. Finally, you assess the risks identified in the analysis and take preemptive measures before growth is affected.
The process of the SWOT analysis enhances management’s awareness of trends in technology, changes in competitors and industry-wide shifts. It also provides them with a good idea of where they can tap into new opportunities. Its most important asset is that it forces management to look to the future and to be proactive.
Roger Martin's critique
Martin asserts that SWOT analyses are a relic of a bygone era of management and that they are completely ineffective in the modern business world. Creating the SWOT analysis entails many hours of work and significant expense, with the end results usually a binder’s worth of findings with vast amounts of data.
Because SWOT analyses are overly complex with pages of unwieldy charts and graphs, they often go on the shelf until the next go-around. By nature, the analyses are impossible to complete within a reasonable amount of time, according to Martin.
Further, Martin argues, you cannot be specific about strengths or weaknesses without understanding a particular context. A SWOT analysis’ identification of strengths/weaknesses is useless until you have first figured out the Where-to-Play/How-to-Win (WTP/HTW) choice first, he adds. But when you are starting the process to plan strategy, you don’t know which WTP/HTW choice you will need to make, so the SWOT doesn’t provide valuable insights.
For example, if your business’ HTW requires you to have the most reliable delivery, then consistent delivery will appear as a strength in your SWOT analysis. But if having a wide range of products is the HTW, then reliable delivery is no longer a strength.
By accidental design, SWOT analyses are “a mile wide and an inch deep,” he writes, generating lots of work and lots of pages but producing little insight.
Science versus data mining
SWOT gathers vast amounts of data but with no stated hypothesis, so it is puzzling to see such an analysis applied without explanation, says Martin. The people performing the SWOT usually do have hypotheses that are kept secret, and they tend to impose their theories on the data collection and analysis itself. Martin dismisses SWOT as a tool used by those who aren’t thinking strategically.
Using a hypothesis-driven approach
No analysis is scientific unless it has a hypothesis, writes Martin. The hypothesis is what drives an analysis with scientific accuracy and determines what data should be crunched and how, and with which standard of proof.
But SWOT only compiles data into four ambiguous categories while the creators hope for something illuminating to emerge, says Martin. Having no hypothesis when developing and testing ideas prevents you from thinking rigorously.
“[N]ever do an analysis without first generating an hypothesis,” Martin writes. “Otherwise, you will engage in aimless data mining.”
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