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Rice Business study finds that a daily routine can foster creativity in the workplace

Having a routine can help foster creativity, a Rice University study found. Getty Images

Think of a routine: your morning workout, walking the dog, making your bed. It's hard to imagine these as creative pursuits. After all, Leonardo da Vinci may have made his bed every morning, but it's probably not what inspired him to paint the Mona Lisa.

So it's no surprise that workplace analysts have long considered routines to be the antithesis of creativity. But it turns out that the relationship between the two is more complementary than previously believed. Scott Sonenshein, a management professor at Rice Business, studied just how this relationship works. What Sonenshein wanted to know was, how can an organization achieve creative outcomes through routine?

For the answer, think of da Vinci again. Certain repetitive aspects of style make his work recognizably his. It's how we can instantly see that The Last Supper, St. John the Baptist and the Mona Lisa are all the work of his hand. In that sense, they are both repeated patterns and feats of genius.

For Sonenshein, some retailers are, in a sense, the da Vincis of suburban America. Sonenshein examined data from a fast-growing retailer that operates a chain of roughly 400 clothing, jewelry, accessory and gift stores across the U.S., and was fascinated to see how it could surprise its customers each season while maintaining a brand image that makes the retailer easily identifiable. Sonenshein realized that the retailer was effectively routinizing creativity.

When he interviewed corporate managers and store employees at the retailer he calls "BoutiqueCo," a pattern emerged. Sonenshein discovered something he calls "familiar novelty" in the way the retailer designs its stores. While most stores use a rigid floor plan for the display of merchandise, BoutiqueCo instead adopts a set of flexible guidelines.

These rules of the road are explicit enough to ensure that each store is readily identifiable as a BoutiqueCo outlet. But because the display rules afford a great deal of flexibility, they allow space for creative employees to come up with their own ideas. If merchandising were a musical score, Sonenshein observed a dynamic that is less like marching band music and more like jazz. Employees are encouraged to riff off of the main themes of the chain to regularly create something unexpected.

Of course, creating novel effects doesn't come naturally to everyone. It takes a certain kind of individual to achieve it, especially in the highly visual area of merchandising. Store managers told Sonenshein that they actively look for employees who are willing to take visual risks and engage creatively while still keeping to the rules of the company road.

Finally, creativity is routinized in the stores' feedback systems. This takes place both among employees, who frequently discuss and even debate their work with each other, and in the more formal setting of managerial feedback. Managers actively encourage creativity, urging employees to put their personalities into the work of the store, to the point where brand identity and individual identity intermingle.

So what does the experience of one outlet tell us about the relationship between creativity and routines? Sonenshein suggests that there is a strong role for personalization of routine tasks in the creative workplace. When employees bring their own preferences to routine performances, it can elevate them from mundane to novel.

Of course, it's unlikely that a window dresser will create the next Mona Lisa while promoting the spring line. Genius like da Vinci's may only come along once in a millennium. But if we put a little soul into our work under the guidance of managers who allow us to riff off of the corporate sheet music, remarkable things become possible.

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This article originally appeared on Rice Business Wisdom.

Scott Sonenshein is the Henry Gardiner Symonds Professor of Management at Jones Graduate School of Business at Rice University.

Keeping on track with trends is crucial to growing and developing a relationship with your customers, these Rice University researchers found. Getty Images

Every business wants to read consumers' minds: what they love, what they hate. Even more, businesses crave to know about mass trends before they're visible to the naked eye.

In the past, analysts searching for trends needed to pore over a vast range of sources for marketplace indicators. The internet and social media have changed that: marketers now have access to an avalanche of real-time indicators, laden with details about the wishes hidden within customers' hearts and minds. With services such as Trendistic (which tracks individual Twitter terms), Google Insights for Search and BlogPulse, modern marketers are even privy to the real-time conversations surrounding consumers' desires.

Now, imagine being able to analyze all this data across large panels of time – then distilling it so well that you could identify marketing trends quickly, accurately and quantitatively.

Rice Business professor Wagner A. Kamakura and Rex Y. Du of the University of Houston set out to create a model that makes this possible. Because both quantitative and qualitative trendspotting are exploratory endeavors, Kamakura notes, both types of research can yield results that are broad but also inaccurate. To remedy this, Kamakura and Du devised a new model for quickly and accurately refining market data into trend patterns.

Kamakura and Du's model entails taking five simple steps to analyze gathered data using a quantitative method. By following this process of refining the data tens or hundreds of times, then isolating the information into specific seasonal and non-seasonal trends or dynamic trends, researchers can generate steady trend patterns across time panels.

Here's the process:

  • First, gather individual indicators by assembling data from different sources, with the understanding that the information is interconnected. It's crucial to select the data methodically, rather than making random choices, in order to avoid subjectively preselecting irrelevant indicators and blocking out relevant ones. Done sloppily, this first step can generate misleading information.
  • Distill the data into a few common factors. The raw data might include inaccuracies, which must be filtered out to lower the risk of overreacting or noting erroneous indicators.
  • Interpret and identify common trends by understanding the causes of spikes or dips in consumer behavior. It's key to separate non-cyclical and cyclical changes, because exterior events such as holidays or weather can alter behavior.
  • Compare your analysis with previously identified trends and other variables to establish their validity and generate insights. Looking at past performance through the filter of new insights can offer managers important guidance.
  • Project the trend lines you've identified using historical tracking data and their modeling framework. These trend lines can then be extrapolated into near-future projections, allowing managers to better position themselves and be proactive trying to reverse unfavorable trends and leverage positive ones.

It's important to bear in mind that the indicators used for quantitative trendspotting are prone to random and systematic errors, Kamakura writes. The model he devised, however, can filter these errors because it keeps them from appearing across different series of time panels. The result: better ability to identify genuine movements and general trends, free from the influence of seasonal events and from random error.

It goes without saying that the information and persuasiveness offered by the internet are inevitably attended by noise. For marketers, this means that without filtering, some trends show spikes for temporary items – mere viral jolts that can skew market research.

Kamakura and Du's model helps sidestep this problem by blending available historical data analysis, large time panels and movements while avoiding errors common to more traditional methods. For managers longing to glimpse the next big thing, this analytical model can reveal emerging consumer movements with clarity – just as they're becoming the future.

(For the mathematically inclined, and those comfortable with Excel macros and Add-Ins, who want to try trendspotting on their own tracking data, Kamakura's Analytical Tools for Excel (KATE) can be downloaded for free at http://wak2.web.rice.edu/bio/Kamakura_Analytic_Tools.html.)

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This article originally appeared on Rice Business Wisdom.

Wagner A. Kamakura is Jesse H. Jones Professor of Marketing at Jones Graduate School of Business at Rice University.