A great many market researchers are “numbers people”. This shouldn’t be a surprise, when we consider how central statistics, sampling, projection, and prediction are to our business. But the all-too-common gulf between market researchers and our data scientist colleagues is a surprise. This disconnect between market research and data science inhibits capabilities in the short term and hurts long-term competitiveness. Which is silly, because this disconnect is completely unnecessary.
Whether we’re selling or buying insights, the systematic evaluation of their relative merits is a vital career skill. On the one hand, it allows us to defensibly establish which solutions will provide the most value for our money. And on the other hand, it provides us the means to best articulate the value of those solutions to our internal and external clients.
The insight industry is simultaneously one of the most competitive and most collaborative fields out there. One second we’ll be competing tooth-and-nail over a new account or project, and the next we’ll be working hand-in-hand to develop or market new products together. These longstanding partnerships are driven by a solid strategic and economic rationale.
At the most basic level, we enter into partnerships – often with ostensible competitors – because working together will either improve performance (raise quality, boost sales, strengthen profitability, accelerate delivery, etc.), decrease risk (remove a potential competitor, decrease needed investment, lock in supply, etc.), or almost always: do both.
I believe partnerships create these benefits by delivering value to your back-office (helping your profitability, accelerating time-to-market, raising the quality of your products, etc.) and your front-office (which ultimately improves sales). Taken together, these benefits deliver strategic value in the form of reducing risk factors, boosting profitability, and strengthening competitive position.
Advising clients in the research, analytics, and technology industries on their strategies and products is difficult to generalize, because every client is unique, with their own history, assets, resources, capabilities, and market philosophy.