May 19, 2017
With so many paths to success, the research field of entrepreneurship began to emerge and studying the various interdisciplinary fields that integrate into the overall success became an important tool to understanding the why. Prior to Techstars, I worked in research at the Kauffman Foundation. We marveled at the newness of the general academic study of entrepreneurship.
The Beginning of Entrepreneurship Research
There are many theories to the different epochs that developed research in entrepreneurship, but no doubt that it in the past couple decades the the study of entrepreneurship has become a rapidly evolving and critical field of study from top universities.
When studying entrepreneurship, we need to consider other disciplines, psychology, sociology, anthropology, management, finance, economics, and on and on, to get a full understanding as to the individual, team, company, and market factors that affect whether the endeavor will be successful. Each of those disciplines take on a different type of data point and methodology for study, together giving a more complete picture of entrepreneurship.
And we took this enigmatic topic, and put infrastructure around it.
Building Infrastructure Around Entrepreneurship
To understand how the discipline evolved, you have to look at the history. From 100 formal entrepreneurship programs in 1975, to 500 in 2006, to many schools requiring education in entrepreneurship in 2013. From 250 entrepreneurship courses in 1985 to more than 5,000 in 2008, a strong focus on entrepreneurship is practically an expectation at universities today.
And then, accelerators came on scene. The first accelerator, Y Combinator, was started in 2005 and a year later, Techstars was founded. And now, somewhere between 300 and 2,000 accelerators exist around the world, according to researchers Susan Cohen and Yael Hochberg. And, we’re getting better at identifying what it takes to qualify as an accelerator.
As the researchers explain, programs such as Techstars fall into the category of seed accelerators, or “a fixed-term, cohort-based program, including mentorship and educational components, that culminates in a public pitch event or demo day.”
In terms of research, accelerators are only 12 years old and data is still in its early stages. CrunchBase, AngelList, and the accelerators themselves are commonly used as data sources for researchers in this area. However, new methodologies are being developed using techniques like randomized controlled trials to measure certain interventions in entrepreneur’s success.
Understanding Our Unknown Unknowns
So, why does the study of entrepreneurship help startups? Simply put, research improves conditions. In starting up an accelerator program, I’m learning quickly that unknown unknowns naturally arise. Questions like: how can accelerators best serve a diverse pool of founders? When is the right time for a company to join an accelerator?
Research seeks to better understand the unknowns and accelerators seek to better improve outcomes for their entrepreneurs. The two go hand in hand.
The more unknowns we face, the harder it is to run a successful program. And, when companies join us, we’re putting emphasis on our beliefs and methodologies (say, the particulars of building a pricing structure) that we as an accelerator hold as truth for long term success in a company, and we ought to know with certainty and evidence that those things really do matter for founders.
Transparency With Data
Researchers and accelerators need to get better at collecting data on entrepreneurial outcomes to conduct studies on the work that we do. One of the great things about Techstars is that it was started by engineers who love data, and love making that data public. Transparency and honest data is critical to improving the conditions on something that we are all on the very cutting edge of developing (accelerators).
With every passing year, we know more about entrepreneurs and how to make companies more successful who enter our accelerator programs. It is an exciting time to be a part of this experiment — creating infrastructure on the phenomenon of entrepreneurship.
Read more tips to improving your startup business practices at Tech.Co
Photo: Flickr / Stanford / HarshLight
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