Below are a few pointers via Kevin Gray at Cannon Gray on how to tie knowledge, skills, tools and data together by using core business skills, scientific thinking and a dash of common sense.
In the past 10 years, market research as an industry has faced more sweeping change than at any period in its history. Changes including new threats and opportunities, and a growing obsolescence of past business models.
Digital is shaking up the landscape and it’s still in its infancy. There has been a quantitative analytics explosion that includes time-series analysis, Bayesian statistics, mixture modeling other machine learners, and of course the massive beast known as Big Data.
The growing amount of new data and tech has enabled us to accomplish parts of our jobs in quicker and better ways, but the learning curve requires time and money. The flip side of progress is of course overspecialization, which has emerged as a significant threat. New jargon appears daily and confusion around these new innovations and how they fit into MR is pervasive. As is common with hype train mentality, “new” methods are basically repackaged old ones, leading to communication breakdowns and misunderstandings.
More than ever researcher skill sets need to be both broad and deep. We require a sound knowledge of fundamentals and specialization in other areas. Choosing skills means gambling that you’re not ignoring a future revenue channel. In an attempt to help overwhelmed researchers, Gray has prioritized the knowledge and skills that researchers should be focusing on:
- Core business skills (eg. business acumen, marketing savvy) remain the most fundamental focus and a market research organization weak in these skills will likely fail.
- Scientific thinking means using a logical, science-based form of decision-making. Understanding scientific methods separates successful researchers from the pack.
- Research fundamentals will always remain as a core important proficiency for researchers. A basic understanding of qualitative methods, survey design, and data analysis remain necessities for communicating with researchers and clients.
- Specialist techniques could make a unique difference to why your firm is chosen. (eg. conjoint, structural equation modeling, predictive analytics, mobile ethnography, computer science skills). But not without a total understanding of business and the science and methodologies of research.
- Proprietary techniques can place your organization head and shoulders above the competition, but you’ll quickly crumble without the four core fundamentals ranked as more important by Gray.
The way you choose to use the knowledge and skills above is essential. Gray has offered some practical tips on how to combine knowledge, skills, tools and data with the help of core business skills, scientific thinking and common sense:
- Frame the issue: When designing a research project, think about the key business issues, deliverables and the end users first and work backwards. Time is often wasted correcting mistakes made in early project stages due to undefined end goals.
- Construct a path diagram: Path diagrams help you visualize plausible ways that variables can be interrelated. You can usually get away with basic path diagrams – they’re still helpful even when sketched onto a notepad.
- Exploit the researcher’s toolbox: Consider multichannel. It often requires more than one research method or channel to get the job done. Time and budget need to be considered, of course, but let them dial back a project from its ideal form, so you start out by knowing what methodologies would best serve the project.
- Remember: fascinating results may be wrong. Even apparently clean data can have insight-changing errors. Your data may not represent your target population. If some pattern seems weird or unexpected (even if it would thrill the client!), there could be a problem with the underlying data. Dig deeper.
- Just the facts, ma’am. Clearly identify facts, hypotheses, and speculation. Sexy interpretations based on speculation, confirmation bias or pseudoscience can easily seduce even the most seasoned research vets.
Market research has been resilient to wide-ranging changes over the years, but it still attracts unconventional, forward-looking people with diverse skills and experience. If those people can continue to adapt to the changes (without sacrificing rigor), it will remain strong.
As an industry, we’ll need to be jacks of all trades and masters of some. No single set of skills will suit everyone, nor would that make for a very innovative/adaptable industry.
But above all else, the essence of the scientific method requires critical thinking and common sense, both of which can serve as a bridge among research specialists with dissimilar skill sets. A combination of generalists and specialists will prevent MR from becoming a salespeople with little business savvy or understanding of client needs.