Tag Archives: algorithms

Management by Algorithm

In a recent post by Brian Solis “Influencing the Influencer” I was struck by the image showing a definition of leadership. Solis goes on to suggest how important people are in the marketing mix. Rightly so, he sets the context as the ‘attention economy’ as many who participate in social networks have an insatiable appetite for attention, notably those who see themselves as “authorities and tastemakers” or at that exalted level of self-actualisation, brands. Apparently, these are the folks that brands must recruit across the social media galaxy in order to truly lead, then connect with the broader audience – the ‘everyman’, in a most sincere and meaningful way.

So, like the days of television rabbit ears, brands need a shill: “A person who publicizes or praises something or someone for reasons of self-interest, personal profit, or friendship or loyalty.” (via Dictionary.com)

This is the oldest game in the advertising playbook.  The difference is of course, that the brand is supposed to recruit people who come from a superior gene pool, that of the online reviewer or opinion leader. It’s real time, it’s from the heart and… it’s transparent. To reinforce this approach, a number of SaaS applications are mentioned such as Klout and PeerIndex that use ‘human’ algorithms to calculate one’s social currency (capital?). It’s so valuable, anyone can calculate their influence scores for free.

Has it occured to those who advocate this kind of approach to identifying influencers that some consumers have no interest is what others think? Rather, consumers prefer to try things themselves. In otherwords, they prefer to take the lead, thank you very much.

For marketing managers, understanding customer preferences and value drivers, is really the first place to start. Management by algorithms alone is a very dangerous thing to do as it places limits on the ability to learn, develop insight and understand consumer behaviour in context.

As in using spell check, your facility with language doesn’t improve over time.

– Ted Morris, 4ScreensMedia

Data: The New Capital of the Digital Age

Data: The New Green

The Economist recently ran a special report on managing information that prompted some thinking. First, some big numbers from the report: Wal-Mart handles over 1 million sales transactions per hour. Facebook houses some 40 billion photos (after only 4 years of operation). Cisco estimates that Internet traffic will reach 667 exabytes by 2013.

 With some 60 million people on Twitter, according to comScore data (November 2009), there are roughly 10 million tweets a day. This doesn’t account for the content – characters, photos, articles and video content. I also found that YouTube has generated more video content than all of the television networks combined have ever generated. The current upload rate is equivalent to about 100,000 Hollywood movies being made on a monthly basis. Finally, almost 100 trillion e-mails were sent in 2009.  

Bringing this a bit closer to home, consider the number of daily transactions that take place for banking, air travel, credit card processing, phone calls and e-commerce. You end up with some very large numbers indeed. This data also says a lot about how we behave. Most intriguing perhaps is what it can tell us, through the use of complex algorithms, how we might behave at some future point in time – and where new business opportunity may dwell.  

This growth in the information industry is not reflective of recessionary times. It points to a shift in investment, new business models, the laying of new infrastructure (servers, storage, cloud computing, software) and global workforce expansion in business information. It’s also transformational as the CIO’s role is increasingly one of contributing directly to business growth in contrast to the dogmatic notion of keeping the lights on in the boiler rooms of Enterprise Resource Planning and Supply Chain Management.  

It’s the effect of the peta, exa and yottabyte world that is most intriguing. Conventional ways to sense and understand consumer behaviour  will be challenged by the new wave of business analytics. Marketing research is but one example. If predictive analytics can do a better job of identifying which category of SKU’s is trending upward or which meal combo is gaining favour, what will marketing research be used for? Data analytics can also be used to generate new ideas for services, products and as importantly, help companies shed under-performing assets and balance inventories. By implication, there is a clear line of sight to the financial payback as firms like Amazon and Marriott have learned.  

This point from the Economist is worth noting:  

“…all these data are turning the social sciences upside down, he [Sinan Aral, NYU] explains. Researchers are now able to understand human behaviour at the population level rather than the individual level.”  

It’s no wonder Big Tech (IBM, Microsoft, Oracle, SAP etc.) is loading up on search, storage and processing capability. In exchange they will reap new profits from the digital age, largely unnoticed from behind the curtain of social networks and online store fronts.   

– Ted Morris, 4ScreensCRM