Two roads diverged in a wood, and I—
I took the one less traveled by,
And that has made all the difference. – Robert Frost
These are arguably the great poet Robert Frost’s most famous lines. Why? Because taking a risk is the cornerstone of progress, innovation and growth. It resonates for people because being confronted with choice is inevitable, and sometimes making the right one is difficult. To reduce this iconic piece of literary genius to a metaphor for what is happening in the market research industry may seem like a stretch, but it is true all the same. We are at a crossroads and the choices we make from here on out will determine our progress.
So what are the roads we have to choose from anyway? On the well-trodden path, we have the market research industry’s historically slow adoption of new methods and technologies. The movement from paper and phone to online surveys was agonizingly slow. We talked about mobile (and, unfortunately, are still talking about it) for years before mobile-first strategy became, somewhat, the norm. On the road less traveled, we have the very few innovators who enthusiastically embrace change and are ready to shake up the status quo.
It’s fairly obvious what the next big thing is for our space. Automation, machine learning, AI and now blockchain are the concepts that plaster conference programs and inundate our inboxes. We’re all talking about these innovations for a reason: they stand poised to change the face of our industry. When we look back at things like the shift to mobile, we almost can’t believe it took so long to implement. Why were we so resistant to something that has literally transformed the manner in which we collect data? Why did we need to talk it to death before it became industry standard?
Let’s not make the same mistake in the late 2010s. Here’s why we should be adopting new technologies now:
- Speed & Cost: Faster, cheaper, better is the name of the business game in this fast paced marketplace. In market research, processes that used to take days can now take hours with the proper implementation of things like automation and machine learning for data processing. Other than actually saving time spent doing specific tasks, technology can help reduce errors (see below) and allows researchers to focus their more expensive hours on high-priority tasks to find the stories behind the insights.
- Quality: Placing something like quality next to going faster seems like an oxymoron. After all, how can you do something properly – and do it well – when you are rushing? Early implementations of things like automation have sometimes been poorly done, or abandoned after execution, so that quality suffers. In reality, automation provides a platform that can actually improve quality, reduce errors and go far beyond simple cost and time savings. Proactive, monitored implementations are key to improving outcomes.
- Reliability: Did you know that there is a field of study called “human reliability”? It is a form of risk assessment based on the human’s likelihood to make a mistake. Machines can offer failure prevention by using data-driven truths rather than what can sometimes equal human guesswork. Yet, while they can help to reduce margins of error, implementations across multiple industries have shown that they function best when coupled with the human’s judgment, logic and opinions. Together, reliability can increase.
All poetry aside, it’s time for us to start realizing the full potential that technology can offer us as an industry. When we look back on this era with all the hindsight and knowledge that comes “ages and ages hence” I think we can be certain that we won’t regret taking the road to progress.
About the author: With more than 20 years of experience in software development and data design, Janine is passionate about applying innovative problem solving techniques and designing sustainable solutions that make the complex seem simple and bring data to life. Currently, she works as a data advisor at market research technology company, Infotools. www.infotools.com