It was in the middle of winter in 1930, the heart of the Great Depression, when Howard Tuthill walked through the cavernous factory thinking about what to do with his family’s business. It was eerily quiet as dim sunlight streamed through the narrow rooftop windows onto the grease-laden cast-iron machine tools. Only a couple of people were working at a wooden bench on a small order for cutting-blade parts for one of the local furniture companies. The once bustling factory that manufactured woodworking equipment-saws, sanders, planers, and lathes-no longer had a steady stream of orders coming from the area’s premier furniture makers. Everything had slowed to a crawl.
Predicting winners is the result of the application of multiple approaches. An objective and holistic analysis of all of them together increases the likelihood of finding the Holy Grail – a commercially successful product that reaps rich rewards.
Some of the approaches to finding winners include:
a) Franklin (2003) argues that the type of idea matters. Ideas that result from random event (but with the creator having previous existing knowledge) and solution spotting have the highest success rates and lowest failure rates.
Beyond generating ideas, companies that successfully produce a steady stream of innovative products and services have a disciplined process for capturing, prioritizing, developing, and commercializing these ideas. Howard’s bread-slicing idea did not follow a disciplined process, but subsequent company developments did. The adjustable-width slicer that could cut thick Texas toast or thin deli slices followed a new product development process that clearly identified the unmet needs of customers and guided the path to market introduction.
c) Focusing on losers as opposed to winners. There are many, many more failures than there are successes, consequently, focused processes that weed out losers can save much time and investment.
d) Many product failures result from a lack of focus. With no clearly defined solution in mind, the chances of failure increase drastically. Ultimately success is measured by user take-up, which can easily be measured using models such as the user utility layer and the buyer experience cycle
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