Linear and parallel thinking

Over the last 20 years the divergence of two different modus operandi of getting work done has increased: the paradigm of linear versus parallel thinking and concept development. One could track the birth of parallel thinking to the emergence of the 64 bit processor at the end of the 80ies, co-developed between the company “Thinking Machines” and the MIT. This innovation enabled synergies and processes that the human brain has difficulty to replicate. The first super computers utilizing the power of parallel processing were early indicators of a new wave of information analysis that challenged the traditional human paradigm of linearity.

And this has significant implication for any marketer. Most marketers are still heavily entrenched into pure linear thinking and concepts, most have never intellectually digested the rise of the parallel thinking modus. This is well reflected in the dominant marketing phenomena of the sales funnel, a purely linear pseudo real representation of how consumers approach shopping decisions. Or in the concept of brand building that always needs to start with creating a huge amount of awareness and recall amongst target consumers. Both concepts are plain wrong or too simplistic in the postmodern universe of parallel value creation and behavior.

I am arguing for introducing the concept of parallel thinking into our marketing design and strategy universe. What could this mean for our marketing practice?

• Replace the concept of linear marketing creation with an approach that is simultaneous and parallel value creation by all participating marketing functions. It’s not about improving the communication between different functional marketing silos but about destroying any functional boundaries for any key moment within the marketing value creation process
• Hire people who are not used to linear thinking processes anymore. These are individuals who have grown up with the similarity of most of their activities, from computer games to simultaneous multi-media consumption and communication pattern
• Don’t force a marketing team into a step driven process. Give the team a desired outcome and let the team create any process that they like. The only process relevant guidance is a clear description of the desired outcome. The team can create its own individual path.
• Teach the benefits and limitations of linear and parallel thinking and value creation. It’s not about deciding between any of these paradigms; it’s about the smart usage of the right approach for a particular situation.

The traditional separation between linear and parallel thinking and approaches will be soon dissolved. It’s not that the parallel paradigm will make the linear one obsolete but digital innovations will require a productive coexistence of both. It should make of interesting times. But first we marketers need to integrate the paradigm of parallel thinking and creation into our daily practice.

Automation of Targeting

Is the end of the marketing analyst near? This question seems almost insane, since the job market for quantitative driven marketers is as good as rarely before. But the last years have seen a significant shift from manual data analysis and derived marketing programs to a software based automation of targeting. There were quite a few near failures like Epiphany at the beginning of the 21st century but the landscape has changed. Google has created its complete business model based on algorithm driven relevant messages and the marriage of consumer intent with most relevant offer without involving any marketing analyst.

The Googlization of most media channels is nothing else as the expansion of the “Search” marketing pattern (algorithm driven real time match between intent and message/offer) to any kind of media. And still, there are two very different business models between Google type firms and most Marketing Service providers: One is based on automated software solutions that incorporate smart upfront thinking of analysts (all translated into code), the other is based on smart individuals who use software solutions to derive the right marketing program with significant lag time. It seems pretty apparent, who will win in the long run.

Most marketing services’ traditional strength on designing targeted programs in the last mile of interaction between brand and consumer (nowadays the last mile is real time and takes not even a second) is not just threatened but could vanish sooner than most of us envision. The trend of Targeting Automation will decrease the dependence on smart people (for which clients have to pay for) and will move budgets to algorithm infused soft- and hardware solutions and services (=AdSense).

Therefore I believe that the future of marketing analysts is not in the last mile of optimizing the 10% of the last mile of brand/consumer interaction but in strategically changing the full 100% marketing investments against any relevant marketing dimension (e.g. Geography, Segment, and Product). The end for marketing analysts is not near at all but the need for changing our work focus is critical in providing value.

Bloomberg's information machine

In this month’s Fortune magazine Caroly Loomis writes an outstanding article about the company “Bloomberg” http://money.cnn.com/magazines/fortune/). Bloomberg has grown over the last 25 years into one of the most successful and profitable information providers in any category. They are less a financial firm, than they are a very smart information provider with high loyalty amongst its user base. Bloomberg has perfected the game of mashing up publicly available information, proprietary content, and derived key metrics focused on improving professional investment decisions.

The success of Bloomberg can be explained by several core principles that haven’t changed much since its inception in 1982:

• Synthesize key financial data and metrics for investors and traders onto 2 screens
• Create proprietary and relevant content for an information obsessed investment community
• Make the usage of Bloomberg information a critical part of the daily routine of customers
• Constantly innovate with new functionalities
• Provide high touch services to customers to ensure ease-of-use and stickiness

These five principles could be the foundation of any marketing information or insight division, either within a marketing services firm or a big brand company: Synthesize, create, integrate, innovate, serve! No more, no less. Why don’t we see more information teams following these principles? It’s mainly due to a…

• Lack of Visionary Power. Most analysts are comfortably happy with their marginalized positions within an organization
• Lack of Ambition: Most analysts don’t want to change the world or become famous. Only the drive to make things happen is creating a space that allows for innovation
• Lack of Relevance: Most analysts still try to optimize a direct marketing campaign by 1% instead of figuring out how a brand should spend the overall marketing budget most efficiently

Bloomberg’s success story should inspire us to push our information and insight teams to an even higher ground. We are not about just providing information and insights, we are about changing marketing.

Data Transparency

This month’s Wired edition (http://www.wired.com/wired/) writes extensively about the need of organizations and companies to be more transparent than ever. One of the key drivers is the fact that no one can hide anything anymore due to the constant publication of any kind of information on the Web, accelerated through all Search Engine’s ability to connect anyone with almost any kind of information. Wired’s Clive Thomson correctly summarizes is with “Google is not a Search Engine. It’s a reputation management system”.

How can we marketing analysts be in the avant-garde position of this more and more dominating pattern? I am making a couple of suggestions:

• Make all marketing data accessible to anyone within your organization. What Google has done for all publicly available information, we need to do for any kind of marketing information within our firms. The Marketing Insights or Analytical division has to become the “Internal Google” (I call this the Internal Transparence layer)
• Broaden the available data points and insights for partners of your organization or firm, all with the intent to be more transparent allowing partners to act smarter. What major retailer have done on the supply chain by sharing information with their supplying partners, we have to do with all the marketing partners in our particular marketing eco system. (I call this the Partner Transparence layer).
• Engage the Consumer in a dialog of transparency. While protecting the privacy of our consumers, we have to be more aggressive in sharing aggregated marketing data with our consumers. Why wouldn’t we share how our brand is perceived, how our marketing programs are performing, how we are utilizing marketing dollars to improve the brand-consumer interaction? It’s not about communicating confidential information but allowing consumers to be better informed about marketing of a particular brand (I call this the Consumer Transparence layer).

If we would believe Thomson’s longer term prediction, then the differences between these three layers will dissolve completely over time. Everyone will have sufficient access to any kind of marketing data while protecting privacy concerns. I don’ think this will happen any time soon but at least in the short and medium term, we should focus on improving our transparency in all three described layers.