"An expert is a man who has stopped thinking -- he knows!" - Frank Lloyd Wright
As we progress in our careers and our lives, it's only natural for our professional perspectives to change. There's a reason that you won't find too many 40-somethings working at startups.
Call it the human condition: We get old. What was once exciting and adventurous now seems unnecessarily risky. We start to crave rules and certainty. Behavioral economists like Dan Ariely have written about how, as we mature, we start to emphasize the costs of failure more than the benefits of success.
Perhaps nowhere is this mind-set more prevalent than in the need for many professionals, groups, departments, and companies to only act when they believe that they'll meet or exceed return on investment (ROI) thresholds. In this post, I'll argue that this is precisely the wrong way to look at things.
There's been no shortage of books written by experts on data-driven marketing and social media ROI. On one hand, putting numbers around investment is totally understandable. Who can argue with the need to quantify the expected return of a marketing campaign, radio ad, or content marketing program? Doesn't the rise of big data mean that we can be more certain of where we're spending our money?
Seems logical, right? Except that accurately measuring ROI has never been easy. These days it's downright dizzying -- and not for lack of trying. MarketShare director Daniel Kehrer echoes this sentiment on Forbes:
Is "return on investment" an accurate way to measure marketing effectiveness? Sadly -- and perhaps even shockingly to some -- the answer is no.
It's not that the notion of ROI is evil or anything. After all, linking marketing to financial performance is absolutely critical. It's just that most people who use ROI in a marketing context probably aren't applying it correctly, or really mean something else, says Dominique Hanssens, professor of marketing at UCLA Anderson School of Management. ROI's roots are in evaluating one-time capital projects. "But is marketing a one-time capital project?" asks Hanssens. Clearly not.
Kehrer and Hanssens are spot-on here.
Based on the impossibility of determining anything resembling a precise ROI, some marketing muckety-mucks are suggesting alternative effectiveness measures. Consider the advice of Susan Gunelius, president and CEO of KeySplash Creative. Gunelius advocates abandoning ROI. In its stead, why not evaluate fuzzier things like return on impression, return on opportunity, return on engagement, and return on objectives? If this sounds like more art than science, you're absolutely right.
Let me give you a personal example of the folly of trying to predict ROI. Before my fifth book, "Too Big to Ignore: The Business Case for Big Data," was published in 2013, I dutifully hired a PR firm at a cost of $2,500 per month for three months.
Some of my friends asked, "Why?" Sure, I wrote for Inc., The Huffington Post, and other high-profile media outlets, but I wanted to make a really big splash with this one. I wanted to continue the momentum that my previous book had generated. When my firm landed me on CNBC to talk about big data, I was extremely happy. It was an A-list placement, the kind that I imagined when I wrote that check. But would that appearance by itself justify the expense? I had no idea. I can't say that I sold thousands of books that day on Amazon or that my speaker bureau was deluged with calls.
Did I waste my money on the PR firm? Maybe, maybe not. I just don't look at it that way. I realize that spending the money on a PR firm increases my chances of going where I want to go. No reputable PR firm can promise me anything, and I eliminate those that feed illusions of grandeur. The CNBC gig ultimately landed me a speaking gig that nearly covered the cost of the PR firm, but that didn't happen until a few months later.
I spoke at the Netflix headquarters in Los Gatos, California, as part of my book tour for "The Visual Organization." It was obvious to me from the minute I set foot in the place that the company believes in the power of data. (Data visualizations adorn the walls, and Tech Emmys line the lobby.)
At Netflix, ROI calculations don't rule the day. In fact, the company's decisions are based on both data and belief. Case in point: dropping $100 million on season one of "House of Cards." In this vein, Netflix is like many progressive companies. (Amazon, Apple, Facebook, and Google are certainly in that cohort.) For its part, Netflix knows that (accurately) predicting ROI is impossible. In fact, we can only partially understand ROI in hindsight. What's more, it's important to embrace probabilistic thinking. That is, to paraphrase Nate Silver, we should trust the process, not the outcome.
Do the right things, and good things are more likely to happen. Just don't make the mistake of believing in guarantees. Even in a world of big data, there's tremendous uncertainty and risk.
What say you?
Phil Simon is a frequent keynote speaker, recognized technology expert, and award-winning author of six management books.
On Twitter? Follow Simon at @philsimon. Follow iMedia Connection at @iMediaTweet.
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Phil, Just want to point out that I never recommended abandoning ROI in my article for Forbes. Instead, I recommend expanding your analysis of ROI to include additional components.
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