Researchers vs Consultants
Typically, consultants and in-house analytics teams use existing methods to interpret and leverage data while academic researchers develop entirely new approaches to important analytic problems. This is why WCAI encourages its corporate partners to reach for their most fundamental and critical business issues so researchers can develop new ways to solve them. Due to the “new frontier” nature of the Research Opportunity process, it’s important to note they generally take longer than commercial analyses and the outcome is less predictable. But once interested, researchers are committed to finding insightful solutions to your complex data-driven problems.
What Drives Academic Research?
The peer-review process encourages researchers to invent new approaches, rigorously test them on data, and then demonstrate that their approach performs better. This type of high-risk, high-reward innovation can be too costly and time-consuming for companies to undertake alone. By tapping into the academic research community, tackling new problems can be cost-effective since researchers possess the rigor, creative freedom, and incentives (i.e., academic publications) to develop novel approaches to complex data challenges.
WCAI Bridge Building
While some companies recognize the unique value academics can bring to analytic methods (and their competitive advantage), it often proves too difficult for companies to identify best-fit academics. A research center with thought leadership at The Wharton School, WCAI seeks to bridge the traditional divide between business and academia, most notably through its Research Opportunity, a carefully structured program that helps business leaders connect with researchers already working on similar problems.
WCAI has partnered with over 20 companies, and in each case, academic researchers paired creative solutions with rigorous methodology, offering truly novel approaches to previously unsolved challenges, including:
- Breakthrough mechanics
- Extending findings to new industry and context (industry agnostic)
- Implementing vs. developing (R&D) models