Should retailers trust their gut or their data?
Through a special arrangement, presented here for discussion is a summary of a current article from MarketingCharts, a Watershed Publishing publication providing up-to-to-minute data and research to marketers.
Recent studies indicate U.S. marketers often rely on their gut for marketing budget decisions. But this may not be a universal view: a new survey sponsored by Applied Predictive Technologies (APT) and conducted by the Economist Intelligence Unit finds that global business leaders are much more likely to describe their approach to making significant management decisions as being "data-driven" (42 percent) than "intuitive" (10 percent). Even so, the study results also suggest a low amount of confidence in data analysis when it comes into conflict with intuition.
Asked what they would do if the available data contradicted their gut feeling when making a decision, a majority 57 percent of respondents said they would re-analyze the data, while another 30 percent would collect more data. Only 10 percent would take the course of action suggested by the data.
That suggests that business leaders continue to rely on intuition, if only in a supporting role. In fact, roughly three in four respondents said they trust their own intuition when it comes to decision-making and two-thirds "would be trusted to make a decision that was not supported by data."
Data-driven decision-making can also fall victim to internal politics, per the study. Indeed, 53 percent of respondents from companies with more than $5 billion in revenues agreed with the statement: "Company politics trump evidence in decision-making." Overall, a plurality of 43 percent of respondents agreed with the statement.
Few respondents to the survey believe that more data would help their organization improve decision-making. Rather, a slight majority feel that a better ability to analyze data would serve their decision-making efforts, with many also pointing to more accountability for decision-making.
The EIU conducted a survey of 174 business executives from a range of industries in February 2014. Of these, 35 percent are from Europe, 27 percent from North America and 26 percent from Asia- Pacific.
Discussion Questions
What role, if any, should intuition play in organizations that self-identify as data-driven? Why do you think some companies are particularly reticent when it comes to making decisions based on data and data alone?
The answer may be neither. When in doubt, leaders should neither trust their intuition nor their organization’s data. It is the consumers who vote everyday with their wallets and plastic.
The problem with “gut instinct” is that that many of the old “instincts” are being totally disrupted by the omnichannel behavior of consumers. The problem with organizational data is that most of it is internal-facing. It is data collected from the minority of the consumers who shopped there. What about the majority who are non-customers?
The third leg of the stool in making decisions today, particularly forecast decisions, is the voice of the consumer. When in doubt, leaders need a pulse on what consumers think and do. A good example is Nordstrom using Pinterest to get a pulse on what consumers want to see in upcoming fashion.
In retail, which we all knows is very different from many of the “range of industries” that this study fed off of, the data element is important, but may not be the final deciding factor. Why? In retail we have trends that move so fast that sometimes the data points are not solid enough yet for decision making. Thus, the gut has to step in and drive the decision. This is especially true as retailers reshape their operations to meet the demands of the Millenial shopper.
Another area is the social impact. Numbers could show on a Monday that a retailer should go a certain direction with assortments, promo or price for a select category or SKU. By Friday some social flood of emotions relating to this is category or SKU may cause the retailer to abort plans that might have been based on recent product performance data.
The other issue is that data-driven decisions in retail must be based on real-time activities. Week old information derived from collected data sets is not as valid today as it was in the old, glory days of retail and data warehousing. Real-time is data blended with that true artistic merchant gut feel.
Well, my gut tells me that the data cited in this piece is accurate and in line with reality, and I think the rationales cited about data/gut driving decisions are totally reasonable. Over the years, gut instinct has made me re-analyze data or collect more data, and saved me from some bad decisions. I don’t think that’s a rare experience, either. Some companies won’t make decisions based solely on data because they’re smart. Everything should come into play.
This piece almost begs us to get weird and ‘other-worldly’—and I love it.
Since the beginning of time we’ve known there are two levels on which to experience everything. Immanuel Kant: phenomenon and noumenon. Larry Dosey: local and non-local. William Tiller: d-space and r-space. Ben Zanger: the world of measurement and the world of possibilities. Ian Percy: mechanistic and energetic.
In each case the second option is where you find intuition. We access intuition through the subconscious. Indeed it is the subconscious that makes 95 percent of all your decisions, about marketing or whatever. There is a world beyond the dimensional that we cannot see and we cannot ignore. Oh, we try, but we can’t.
(Note: the subconscious isn’t infallible either, and it can really mess you up. But that’s a discussion for another time.)
We are afraid, as a society, of recognizing an unlimited resource beyond our senses. Yet you know your best insights have come to you in the night, in the shower, on a walk or while washing the car. In short, once you stop trying to have insights and let some other ‘mind’ take over.
We somehow think that ‘data’ is divinely inspired and immune to badness, but it’s not. How data is generated is suspect. How it is analyzed is even more suspect. It’s analyzed by software that, according to guru Capers Jones, has 750 faults for every 100,000 lines of code; 250 of those are capable of erroneous output or of shutting the whole system down. Other experts think it’s 3 times that number. The annual cost of faulty software that gives us this precious ‘data’ is more than the entire cost of the recent financial meltdown, only it keeps happening year after year growing at 15 percent annually—and THAT is what you want to rely on?
Why are companies reticent to rely on data to make decisions? Because their higher self tells them to be, and we’re wiser than we think.
The only thing I would trust is the activity on the sales floor. This is why having cameras pointing at the sales floor and doing computer vision (CV) analytics such as traffic flow, object movement and sales associate movement (they can be tagged in CV with a green square) is important. This is the data I would look at before transactional data to make decisions.
Professional sports team look at film footage and do detailed analysis and so do Las Vegas casinos to understand foot traffic. It’s time for retailers to focus on CV to get the right data instead of trusting their gut or looking at after-the-fact transactional data.
Raw data is the solution of an equation or the affirmation or denial to a simple proposition. The ability to add connotative and/or denotative input into a solution is limited by the scope and content of the inquiry.
This is a large portion of the error that can be contained in raw data especially when the intangible aspects are placed in high relevance in the need for measuring for a solution and/or answer to a problem or event. The addition of abstract applicable data must be prearranged and tested for validity and consistency of response from the test subjects.
With all of the variables in play, no matter the human sample size, the margin for error increases quickly for many unpredictable reasons to make subjective decision making wrong most of the time. The building blocks of any company must be capable of supporting the purpose and goals that are necessary to secure and grow the company.
“I/we thought it was the right decision because X” is the predominant disclosure for failure in business and should be avoided at all costs. What people say, think or hear is of no value to a business decision. The bottom line and all of the supporting data is a result of what they do, did and should/could have done. What is needed in terms adding of subjective reasoning is to objectively measure the practicality if a decision or rule. This will keep the mittens and snow shoes off of the shelves during the summer months.
Past performance is no guarantee of future results. Intuition and experience provide context. All of the rich data available to anyone today can often be used to support any number of different outcomes. Without context, data-driven decision making sometimes completely misses the point.
Data is only as good as how you go about getting it, from whom you get it and how you manipulate it. Don’t get me wrong. Having data is good, even key, to decision making but—and that’s a big but!—it must be interpreted with wisdom.
Note that I did not say “intuition”. There is a big difference between gut intuition and knowledge- and years-based intuition, aka wisdom.
In the ever changing world we live in, with data abundant and easy to capture, organizations absolutely should be gathering as much data as possible that is pertinent and relevant to their brands and their brand’s target audience. Then it takes the right level of wisdom to distill that data down to drive decision making.
To put it another way; I share my opinions frequently, whether you want them or not. When asked how I know certain things, my answer is often, “I just do”. This, my friends, is not just intuition. It’s 40-plus years in the trenches, creating my own mental store of data matched against whatever argument is posed.
So, yes, if the data comes back contradicting my position, I would have to go back to the data as questionable. But my mental stores have seen and done so much over the years, they know how to recognize new truths, too. THAT is my two cents!
A great number of retailers arose from the college of corn and canned peas, the display cases of polyester goods, and sharpening their intuitive skills by watching customers’ maneuvers every day. They trusted their intuitions to build businesses to beat their competitors. That was fun. Data isn’t so much.
Such folks still trust their self-identified intuitive powers in today’s data driven world. Meanwhile, their replacements were trained to get financial acumen and are data driven. They are less secure acting without scads of data, research and “outside” input because the stakes are so high.
In retailing’s more recent evolution, yesterday’s intuitive merchant entrepreneurs and dreamers have been displaced by financially-driven experts, which has opened up the “dreamworks” to people such geniuses such as Bill Gates, Howard Schultz, Steve Jobs and the founders of Google, Amazon, Apple, eBay, etc.
There is definitely room for both data and intuition in the equation. On one hand, data is important as it can provide quantifiable information. But it does matter how the data is collected, from whom, and at what frequency, as well as how it is interpreted. On the other hand, intuition is valuable given years of wisdom and experience. Here, the downfall can be lack of relevant experience, a rapidly changing retail environment, or an unwillingness to be objective, or to even consider data or other opinions. In the end, it is really important to find the right blend of data and intuition to make the best decisions.
Decades ago, Business Intelligence began as Decision Support Systems. The former may have been a better moniker. Decisions are best made with human experience and intuition, informed by high quality data-driven insights. Quality is a function of accuracy, breadth and detail, not simply size. Big Data brings breadth and detail, but can also be “dirty,” inaccurate, improperly summarized and erroneously or misleadingly presented.
Decision makers should ask “What does the data say? How do I know I can trust it? What is the data missing? What do I expect the outcome to be? How can I measure it?” Then act.
Great article.
As a former retail executive, it was a natural process to use what I knew or thought I knew as well as my gut to make decisions. Now as a service provider to customer brands for the last 20 years, I still see that as the norm in many of my clients.
With the advent of real-time customer surveys, financial reporting and dashboard technologies, there is really no reason to use your “gut” as a basis of decision making.
Today more than ever before, understanding your customers wants, needs and expectations matters more to your brand than any other strategic imperative your organization may have.
Customers are the lifeblood of any business. In fact, you have no business if you have no customers. I’d go as far as saying they’re probably the only voices that are worth listening to.
Let’s hope more of us move from listening to our “gut” and begin listening to our customers.
The best leaders will use data to help make their decisions, but rely on other factors such as input from the front line, other leaders, maybe some of their intuition, but most important—their customers.
Remember that there was a lot of data that the New Coke would work. Bad decision. Many factors need to be considered to make good decisions.
The survey indicates most people will take the common sense route: if there’s a conflict, investigate further (and yes, if the survey’s data hadn’t been what I expected, I would have had to decide whether/not to accept it). What’s unclear is what people will do—or even what they’re “supposed to do”—if that further study doesn’t resolve the conflict…perhaps if they’re still unwilling to act on the data, they should stop identifying as “data driven.”
Few sectors in the B2C economy have better potential to make data-driven decisions than brick-and-mortar retailers—yet few sectors are worse at doing so.
I don’t want to deny that there are all kinds of challenges to becoming genuinely data-driven, and even when you reach that stage, there is still no substitute for sound decision-making processes that leverage institutional knowledge. But retailers should aspire to move in that direction and fight the temptation to go with gut instinct as often as they currently do.
And while I’m on a snarky rant, I’ll boldly say that “listening to the customer” is frequently a cover story to fall back into gut-oriented decision-making….
I believe that primary decision processes should rely upon data analyses. There should, however, continue to be human interaction to confirm decisions made by technology, not undermine and rewrite those decisions. The key is to ensure that the data is actually trustworthy. That’s where I have seen retailers and CPGers tell me that they simply don’t trust the data. That’s a whole other issue, though.
If a retailer doesn’t have faith in the integrity of their data then they need to identify the systems and processes required to correct that situation. There is nothing more destructive to the process of data-driven marketing than a lack of faith in the data. It’s hard, costly and essential to success going forward in retail.
Yes, partial, incongruent, and non-aligned data (and data sources) presents a formidable barrier to a retailer going down a data-driven path. But with the introduction of mobile and social retailer have the ability to understand their individual shoppers better than ever before. Besides, rules of thumb and gut feelings have been shown to be terribly inaccurate in complex decision making.
Most good business decisions rely on a combination of art and science. As analytics and computational power have become more widely accessible, the overall process of allocation of marketing budgets has become more analytically driven, which in my experience has usually resulted in far better results. But intuition is usually the result of years of relevant experience and should be used to assess the outputs from the analytical part of the process to reality check the recommendations. If the analytical recommendations make sense from an intuition perspective then that is usually a good sign. If they don’t make sense then it usually indicates a need to dig deeper into the analytics to understand the drivers of the recommendations. More often than not this results in the marketer gaining a more complete understanding for marketing performance and helps the intuitive perspective to further evolve.
I am a strong proponent of being data-driven, but the key is converting the data into profitable insights. It is inevitable that retailers will all be relying on data going forward, though it may make sense to retain some level of manual control during the transition to getting there. The progression to data and algorithm-driven models as the basis for decision-making strikes me as similar to what we experienced with the transition from pilots to autopilots, human traders to trading algorithms. In both of these cases, there was some resistance to the innovation but the improved results ultimately won out. In retail, similarly, there will be some resistance and even some justifiable use of human intervention as these solutions and systems are improved, but there will be a tipping point when it no longer makes sense to override the data-driven algorithmic decisions.