Michael Hannan: Startups Need to “Think Employees” from the Get-Go

How companies manage their employees turns out to be critical to their long-term success.

January 01, 2007

| by Marguerite Rigoglioso

Start-up firms should pay as much attention to creating a pattern for managing their employees as they do to developing the vision for their product. A decade-long study of Silicon Valley (California) technology startups finds that companies were three times more likely to fail if at some point they altered the founder’s blueprint for employee relations than if they maintained their original employee model.

After tracking the success of more than 150 start-up firms founded since 1994, Stanford Graduate School of Business Professor Michael Hannan and collaborators found that not only did altering the system for managing employees hamper success, but also such firms had long-term stock valuations that were nearly six times lower.

During the firm’s first decade, changing blueprints for employment relations proved even more disruptive to a company’s success and growth in market capitalization than replacing a founding CEO with an outsider. The advent of a new leader by itself did not significantly increase a firm’s failure rate even if it did temporarily depress the rate of growth of stock prices. What counted was whether or not the original blueprint for the employment model was preserved in the transition.

Research coauthored by Hannan builds on previous work identifying which of several major employee relations models seem to work best for a high-tech start-up company at various stages. According to Hannan:

Bureaucratic and autocratic models, in which employees are managed by formal controls and procedures or close oversight, lead to the greatest failure rates and lowest growth rates in market capitalizations. The “star” model, which recruits, rewards, and supports employees on the basis of their talent; and the “commitment” model, in which employees work essentially as a close knit family, support start-up success.

“The tension comes in,” says Hannan, “when the company gets larger. As you’re trying to scale up, bureaucratic and autocratic models work better. But making the transition to that from a star or commitment blueprint proves to be dangerous.”

Anecdotal evidence from interviews with Silicon Valley founders and CEOs revealed that sometimes entrepreneurial ventures switched from a looser employee framework to one involving greater controls under pressure from investors, particularly during a financial crunch period. “Changes in how employees are managed are frequently made as a cost-cutting measure,” Hannan said.

His study, coauthored with former GSB professor James Baron and Greta Hsu and Özgecan Koçak, both graduates of the school’s doctoral program, is the culminating piece of research to spring from the Stanford Project on Emerging Companies (SPEC). Founded by Barron and Hannan in 1994, SPEC represents a unique effort to understand the issues involved in managing emerging companies, particularly in their early years. This latest study, which appeared in the October 2006 issue of Industrial and Corporate Change, is the last of about 10 papers published by Hannan and his colleagues in major journals to draw on SPEC-related interviews, surveys, and archival research into Silicon Valley startups.


“While most research has looked at entrepreneurship from the financial angle, through our SPEC-related work we’ve shown that organizational theory is also highly relevant to this field,” says Hannan, the Business School’s StrataCom Professor of Management. Additionally, SPEC provided the School with the impetus to take advantage of research opportunities in one of the most vital entrepreneurial belts in the country.

Echoing the advice he’s been offering since he first began publishing his SPEC findings in 1994, Hannan notes that company founders should think much more carefully about their employee blueprints from the start. “Business plans usually have 20 pages on the product, and a paragraph about employee relations, and that needs to shift,” he says. “You don’t want to find you’ve backed your way into something without realizing it. Once systems get coded, they’re hard and risky to change.”

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