Originally Published in Forbes
Written by Mark Smith
In the early days of marketing technology, the bleeding edge of innovation came in the move from analog to digital. With the introduction of personal computing, marketing teams began to collect customer information in new digital depositories, ushering in the era of database marketing. The web, the growing ubiquity of email and the emergence of CRM systems opened new doors to data analysis and persona-based targeting.
Since then, the rise of social media, the widespread adoption of mobile devices and the proliferation of marketing technology (martech) solutions have increased the complexity of marketing as a discipline. What’s more, these changes have transformed sporadic interactions between brands and customers into symbiotic relationships. These ongoing interactions shape a customer’s perception of a brand, and there’s always the potential for the relationship to sour instantly — which means the stakes are high.
Marketers experience this state of affairs as a steady barrage of business decisions concerning everything from digital strategy and technology in an omnichannel world to specific methods for optimizing buyer journeys. To adequately prioritize and make these decisions in an efficient manner, marketers need a framework.
The framework I believe to be best suited for navigating the rapidly evolving chaos of contemporary marketing is one with the unusual name of Cynefin.
The Cynefin Framework
The Cynefin (kuh-NEV-in) framework was introduced in 1999 by Dave Snowden. The framework establishes five decision-making contexts:
Obvious: Options are clear, and there’s a plain cause-and-effect relationship. There are often processes already in place to address the issues fitting in this domain, and best practices are established. The proper approach is to “sense, categorize, respond.” That is, assess the situation; categorize it, and base responses on best practices.
Complicated: There may be multiple right answers for any given situation here, and although there is a clear relationship between cause and effect, it’s not always apparent. The approach here is to “sense, analyze, respond.” This domain relies on good practice, not best practice, since there might be several good options, and decisions often involve input from experts.
Complex: This is where we see a majority of modern business decisions. As opposed to the complicated domain, where there’s at least one right answer, complex situations often don’t have easily identifiable solutions. Snowden makes the comparison between a Ferrari (complicated) and the Brazilian rainforest (complex). A Ferrari is a complicated machine, but an expert can break it down and put it back together. A rainforest, on the other hand, is constantly changing due to weather, environmental factors, human intervention and so on. The approach in this domain is “probe, sense, respond.” You need to set the stage, look for patterns and make educated guesses about responses most likely to succeed.
Chaos: Here, the relationship between cause and effect is constantly shifting, and there are no patterns to be found. The immediate response is to act. Stop the bleeding so you can see where any stability might be present, and then shift the situation to complexity — to “act, sense, respond.” Organizations often end up in chaos via the obvious domain. When complacency takes root, best practice shifts to past practice, and leaders react too late to new information.
Disorder: The fifth domain is disorder, when it’s unclear which domain a situation fits into.
What does it mean for marketing?
When we look at the historical arc of digital marketing, we can fairly neatly fit various marketing techniques into the Cynefin framework. Mass marketing, batch emails and persona building are all tasks that fall into the obvious domain and can be safely addressed through best practice.
In the complicated domain, we see database marketing, campaign management, analytics and segmentation — challenges that have more than one right solution, where experts might need to be brought in.
The complex domain is where marketing leaders find themselves today, best illustrated by the belief that the customer experience (CX) is the new competitive battleground. When product, for example, was the competitive battleground, the situation was complicated: You either made your product cheaper than your competitors, or you made it better. Customer experience is a different beast.
The factors that impact CX are numerous, and many are beyond your control. For example, expectations for a “good” experience are often set by brands outside of your space (e.g., Uber or Apple). CX can be influenced by many different parts of your organization as well as partners associated with your brand. Even here, centralized control can be a challenge, and actively tracking customer interactions can be extremely difficult.
Almost 50% of consumers say that brands fail to meet CX expectations, and two-thirds couldn’t recall a time when brands exceeded expectations. Looking through the Cynefin lens, we can see that many brands fall short because they treat CX as a complicated, not complex, challenge.
The complexity of CX calls for complex solutions, capable of adapting to the changing dynamics of customer interactions. To do that, the solution has to operate in real time, have access to data to understand context and be flexible enough to learn and respond appropriately.
Real-time decision making allows brands to do the right thing for every customer, every time. But this requires core machine learning and predictive modeling capabilities that can obey complex rules for arbitration and prioritization, as well as instant access to all relevant data, the fuel for real-time decision making.
With all this in place, and guided by optimal journey logic, real-time decision making can guide customers to the next best interaction so seamlessly the customer won’t even notice. And that kind of seamless convenience is the most basic form of the “good” experience customers are looking for.
Marketing can be complicated, and the demands of CX can be complex, but marketers must meet complexity with complexity. By harnessing the powerful machine learning and predictive analytics capabilities available today and using cutting-edge data management and journey orchestration tools, marketers can create a decision engine tailor-made for the CX battleground.