The Softer Side of Marketing Analytics

In their seminal new book, “Competing on Analytics,” authors Tom Davenport and Jeanne Harris devote an entire chapter to the important role that organizational culture plays in transforming a company into one that embraces analytics as a competitive advantage. “When most people visualize business analytics, they think of computers, software, and printouts or screens full of numbers,” they write. “What they should be envisioning, however, are their fellow human beings.”

Davenport strongly reiterated this point in recent presentations at the IRI Summit and the Business Analytics Concours, an executive education program he leads at Babson College. I couldn’t agree more with his view that becoming what he and Harris term an “analytics competitor” is first and foremost a change-management exercise.

After all, deploying analytics requires fundamental changes in how people think and act. This is especially true within the realms of marketing and customer relationship management, where many companies still rely heavily on gut instinct and age-old metrics of “what works,” including conventions such as gross rating points and brand awareness surveys, to guide their marketing decisions.

Of course, few people naturally embrace change. Instead most people follow Newton’s first law of motion, which is to say they tend to remain at rest or in uniform motion unless compelled to change by the action of an external force. So how does a company translate an analytics vision into aligned action? How does it ensure that related initiatives are embraced, not resisted, by the rank and file? The key is to think systemically about multifaceted organizational issues.

The seven steps to organizational Nirvana
Many books posit theories about how organizations change and what obstacles prevent them from changing. One model that has gained widespread acceptance for explaining organizational excellence is the classic “7S model” proposed 25 years ago by consultants at McKinsey & Co.

The model contends that organizational excellence demands superior fit among seven “hard” and “soft” dimensions. The hard dimensions are strategy, systems, and structure. The soft dimensions are staff, style, skills, and shared values. The basic message is that high-performance organizations are distinguished by the amount of attention that they devote to the soft dimensions.

Mohan Sawhney of Northwestern University and I drew inspiration from this model in defining the processes involved in managing organizational change associated with e-business transformation. The model we developed for our book, “The Seven Steps to Nirvana,” would seem to be equally applicable in the context of making analytics work, complementing the excellent guidelines that Davenport and Harris put forth.

The dimensions in our model are logically related processes that flow from the business vision. They define the steps that need to be taken to convert the vision into reality. With the ends and the means serving as anchors, the seven dimensions are catalyzing, diffusing, motivating, skilling, externalizing, and structuring and staffing. Taken together, these dimensions ensure that the organization is aligned with the vision and that every individual becomes an enabler of change.

Catalyzing: lighting the spark
Analytical transformation is not the job of a middle manager. Instead, the context for change and the drive to build an analytical orientation needs to be established by the CEO and the senior management team. Davenport and Harris agree, noting that these individuals must “set the tone for the organization’s analytical culture.”

By now most CEOs and senior executives of large companies have made the appropriate noises about the importance of quantitative analysis and fact-based decision-making. That said, there’s a difference between espoused values and enacted values—what people say as opposed to what they actually do. People have a natural tendency to tune out the empty pronouncements that emanate from the corner office if they see much talk but little action. The CEO’s conviction about the need for analytics has to run deep, and it has to be visceral.

To light the spark, CEOs and senior executives should be encouraged to experience firsthand the power of analytics. To this end, an immersion exercise like the program Davenport is leading or like the workshops that Fair Isaac now offers through our Predictive Analytics Institute can serve as an excellent vehicle for creating a common understanding for what analytics means in the context of a company’s own priorities. An intensive, off-site retreat lasting two or three days, the exercise should generate actionable insights into how analytics capabilities can be deployed to drive improvement in sales, marketing, customer relationship management, and various other aspects of the company’s operations.

Diffusing: communicating the vision
The CEO, the chief marketing officer, the chief information officer, and other senior management can serve as catalysts for initiating change, creating the push from the top. But the challenge remains: How do you get the attention of brand managers and other people who are focused on the lines of business and operating results? Like any “new order of things,” the analytics vision needs to be diffused slowly and systematically throughout the organization.

Beyond defining what the company seeks to achieve with analytics as a key enabler, communication should stress when these changes need to happen. Because change needs to come faster than the time that the organization usually takes to react to new initiatives, the CEO needs to establish a general sense of urgency focused on producing results. In the case of direct-to-consumer marketing and customer-centricity programs, early results might include nonfinancial metrics around improvements in customer segmentation schemes, customer data acquisition and integration, and customer value measurements.

 

Motivating: getting people to play
“Call it what you will,” declared Soviet premier Nikita Khrushchev, “incentives are what get people to work harder.” Khrushchev’s basic point was right on the money: Incentives shape behavioral outcomes.

 

Managing incentives means stepping into other people’s shoes and addressing the issue of “what’s in it for me?” In many cases, the risks are clear while the rewards are ambiguous. Why should people want to participate? What makes it worthwhile from their perspective? Aside from Ph.D. statisticians and behavior scientists who may enjoy thinking about experimental designs and decision models, few people are interested in analytics for the sake of analytics.

 

The key is to sell employees on the fact that analytics tools can provide a way to accelerate their own progress and personal success. They need to be shown that analytics implementation can become one of the most salient levers and promising paths to achieving their goals regarding incremental sales lift, customer acquisition, customer loyalty, increased cross-selling and upselling, and so on. Forget about selling them on analytics; instead sell them on the outcome. In this way, analytics becomes a means to an end, not a goal unto itself.

 

Training: bringing people up to speed

Even if a company can overcome the inherent resistance to change when introducing new analytics capabilities, it may still fail to get adoption if users are not adequately trained to use it effectively. To think that people learn if left to their own devices or forced to attend instructor-led “telling” sessions is wishful thinking.

 

Consider even the most basic types of software, such as the word processor. Chances are you stumbled your way through the learning process, making mistakes and creating workaround solutions for problems, because you never knew how to effectively use the hundreds of imbedded features or which ones even existed.

 

Corporate intranets, knowledge management applications, and business intelligence tools, in particular, are often used well below their potential because insufficient thought was given to the process of bringing people up to speed. Next-generation data visualization tools designed to analyze campaign results and other performance metrics to make smarter marketing decisions can pose a particular challenge, since the software is still highly experimental.

 

Training can be especially difficult to carry out when the users are senior managers. Having always acted as teachers and mentors, senior managers are often unwilling to acknowledge that they might have something to learn from their juniors. When it comes to becoming well versed in the language of analytics and gaining a sufficient command of the enabling technologies, however, reverse mentoring is exactly what senior managers need to do.

Externalizing: bringing partners along
When it comes to implementation, a company can deliver superior work but still fail to get analytics-based initiatives that depend on external data sourcing off the ground without the participation of its partners. Therefore, just as incentives need to be properly aligned internally with employees, they must also be aligned externally with partners.

This was a major topic of discussion at last month’s IRI Summit, which devoted an entire track to retailer-manufacturer collaboration. The sessions discussed how companies are working together to share product, customer, and transaction data to ensure appropriate stocking levels, to improve support for promotional activities, to produce shopper-appropriate store plans, to improve the efficiency of store operations, and ultimately, to provide a better customer shopping experience. 

Staffing: hiring the analytics team

The analytics team typically starts out as a temporary SWAT team. Over time, this SWAT team may evolve into a full-fledged analytics department. Or, in many cases, the analytics function may be largely outsourced to an external vendor that has the capabilities, technology, and industry expertise already in place.

 

In any case, the analytics function requires an internal leader. Paradoxically, selection criteria for this leader should not weigh heavily in favor of the candidate’s expertise with advanced analytics. In this context, personalities count for more than functional backgrounds. Personalities that can rally people around the cause should be the number-one consideration. Find people who are well liked, well respected, and highly credible. Find people who can act in a way that is visionary and inspirational and who understand the barriers, inertia, fears, and political issues that would impede adoption of analytics-related initiatives.

With the implementation of these seven steps for organizational change, companies should be well on their way to bringing the vision to fruition and becoming a true analytics competitor.

Jeff Zabin is coauthor of "Precision Marketing" (Wiley, 2004) and a director in the Precision Marketing Group at Fair Isaac. He blogs at www.paretorules.com and can be reached at jeffzabin@fairisaac.com.

Previous articles by Jeff Zabin:

Channel Integration: Multiple Languages, Seamless Integration

Precision Marketing Is a Green Initiative

A Nation of 300 Million Records

Cracking the Code on Next-Generation Code Promotions

Marketing Dashboards: The Visual Display of Marketing Data

Placing Sure Bets on Customer Knowledge

Visa: Life Takes Rebranding

Jim Brickman Plays the Music of Precision Marketing

The Netflix Paradox: Are Loyal Customers Sinking Your Stock?

Making Sense of Super Bowl Spots in the Age of Precision Marketing

When It Comes to Contextual Marketing, Think Like Chip Davis