New venture strategy and profitability: A venture capitalist's assessment

This study uses theoretically justified criteria from the industrial organization (IO) strategy literature and applies it to a new domain, namely, venture capitalists' decision making. Specifically, the study investigates the types of information venture capitalists utilize when evaluating new ventures and how venture capitalists use this information to assess likely new venture profitability. In the interest of advancing our understanding of the decision making policies of venture capitalists, this study addresses many of the limitations of previous research. A review of IO research suggests important relationships between a number of strategy variables and new venture profitability. Some of the relationships proposed by IO strategy research are contingent in nature. The strategy variables and their relationships with profitability are investigated in the domain of venture capitalists' decision making. Individual and aggregate decision making analyses identified those strategy variables (criteria) venture capitalists utilize in assessing likely new venture profitability, namely, timing, key success factor stability, lead time, competitive rivalry, educational capability, industry-related competence, timing × key success factor stability interaction, timing × lead time interaction, and timing × educational capability interaction. On average, the most important criterion for venture capitalists in their assessment of profitability is industry-related competence. The second tier of importance is competitive rivalry, timing, and educational capability. The third tier of importance is lead time, key success factor stability, and timing × lead time interaction. Other interactions are less important. Therefore, while venture capitalists use contingent decision policies, main effects dominate. If venture capitalists use a reported 8 to 12 minutes on average to evaluate a business plan (Sandberg 1986), then this study's findings may help the inexperienced venture capitalist allocate time towards assessing those attributes of primary importance. Although more complex relationships exist between the attributes, the inexperienced venture capitalist can take comfort from this study's findings that main effects dominant amongst senior venture capitalists. Senior venture capitalists may take less comfort from their importance placed on main effects in light of research from IO, which suggests the importance of contingent relationships. The results may also have practical application towards training. How should venture capital firms train their new employees? Should venture capital firms rely solely on experienced venture capitalists lecturing the inexperienced on the criteria they use in assessing a new venture proposal? Like most decision makers, venture capitalists have limited insight into their assessments and venture capital firms need to be aware of the gap between "espoused" policies and policies "in use." The information being taught needs to be supplemented with venture capitalists' decision-making research that investigates decision policies "in use", such as this study. Venture capitalist training could also involve experiential learning, in conjunction with cognitive feedback about the decision policies used, to accelerate the learning process. Experiential learning using cognitive feedback maximizes industry related learning while minimizing the cost of inexperienced decisions. For the entrepreneur seeking capital, this increased understanding of venture capitalists' decision making may help them better target their business plans and presentations at those criteria venture capitalists' find most critical to the profitability of a new venture.