You are currently browsing the category archive for the ‘Big Data’ category.
January 5, 2013 in Big Data, Frameworks, Governance, Information Lifecycle Management, Social Media, Technology Tools | Tags: collaboration, Directories, Knowledge, Lists, meritorcracy, Open Source, people database, rating system, Social media, Web search engine | Leave a comment
First published in Internet Media Labs Blog – 27th October 2012
We are amassing data at an unprecedented rate. In the course of a day the internet handles more than 1,000 Petabytes of data (2011 figures) and is projected to double in less than three years. That’s a million terabytes or a billion gigabytes just on the public internet alone. Granted there is a lot of duplication and the amount of image and video content is greatly contributing to the accelerated growth. Furthermore our growing dependency on mobility demands even greater participation and production that further magnifies digital traffic.
That is a lot of data and a very large amount of noise carrying a decreasing ratio of signal. How do we operate in such an environment and meet our objectives for education, career, parenting, healthcare, community participation, consumerism and entertainment? How do we locate and recognize the availability and qualities of resources that will help us live our lives productively and successfully?
A complex question no doubt, but one that highlights the current capabilities and shortcomings of the network today.
The short and most common answer would be search engines. To a degree that is a reasonable response, but given the immensity of available data it is woefully short of satisfying anything but the last two on my list of objectives (consumerism and entertainment).
The issue starts with search engines and the demands of commercialism. Commerce sustains our civilization and provides the impetus for innovation and discovery. But it also dominates the way we create and prepare content, and the way we search for information. We are also largely dependent on a single search engine, which is still evolving though firmly rooted in textual analysis. Yes there are other search options but the majority of us use Google.
Search technology is beginning to branch out as witnessed by Google’s goal of producing a knowledge graph. Currently it has the ability to determine sentiment which is the first step in semantic analysis. Yet there is a long way to go before search can provide an accurate return on how, what and who we are searching for.
Google spends a lot of capital on developing and improving search algorithms, which are obscured to prevent gaming the system. Those algorithms perform a large number of calculations that include the analysis and synthesis of web content, structure and performance.
Providers of content and information are aware that they can improve the ranking of their published material by optimizing their web site through Search Engine Optimization (SEO), Conversion Rate Optimization (CRO) or improving the quality and attractiveness of their content. In addition the search engine vendor(s) provide consulting services to assist content providers in achieving approved “white hat” SEO status as opposed to “black hat” SEO which is risky, unapproved, and has the potential to be banned.
Any search results in an index of entries ranked by how well they have been produced and optimized. The more content humankind produces the more commercial entities will spend in order to ensure high ranking so that we consume their products or services, after all few consumers go beyond the first page of search results. Hence my assertion above that consumerism and entertainment (which for sake of argument includes news and events) are the principal beneficiaries of the current solutions. And that’s great if you are catching up on news, wish to be entertained or shopping either actively or casually. The ranking system will give you the most up to date, the most popular and the most advertised consumables.
However the ranking system doesn’t scale down for the individual, the community or small businesses or enterprises, unless predetermined keywords are used in the content and search. A small voice cannot be heard where shouting is encouraged even demanded. The more we use search engines the louder that shouting becomes. Furthermore the ranking system doesn’t really scale economically for SEO content as globalization will introduce more competition for the coveted top ranked entries, demanding increased effort and optimization.
But this post is not about search engines and optimization of content. It’s about locating resource and identifying quality and relevancy that will help in collaboration; finding people, ideas, material, skills and availability so the other objectives on my list can be fulfilled.
We need something more than simple signposts or lists, valuable as they are. We need a capability that will not only locate a resource, but one that will also provide us with much needed information about the resource, its properties, location, status, history and relationships to other resources. In short we need directories, repositories of resources and their attributes that are easily accessible and extensible.
Directory databases have been around for a long time and are currently in operation in most large enterprises, most commonly behind corporate firewalls. They meet many of the requirements outlined above, although their use has been necessarily constrained to a management and security function. In most implementations they perform that function well. That style of directory is also appropriate beyond the firewall, especially when authentication amongst diverse communities and populations needs to be supported.
Yet we can do so much more with directories, especially if we liberate their extensibility and open them up to collaborative contributions and housekeeping. Today we keep our own lists and collaborate on those in communities of interest. There are several listing applications on Social Media such as list.ly, Twitchimp or the late lamented Formulists. These are great applications and no social media maven can exist without one. But they are only lists and they only carry a small number of entries and attributes.
Open collaborative directories will be able to scale to support large numbers of entries and attributes, including attributes that are determined by the participants and their communities. In other words directories will carry the hard facts about a resource as well as attributes that are determined by those who use and collaborate with those resources.
This is very similar to Facebook’s like, (and imaginary don’t like), but applied to the performance or quality of resource as experienced in collaboration. Such peer review and measurement lies at the heart of Open Source development, a meritocracy where your contributions are evaluated by peers to determine your value and position within the group. Such information will prove invaluable to those seeking knowledge and the resources to get things done.
And why stop at people? Open Collaborative Directories can support any resource be it curated knowledge bases, dictionaries, almanacs and compendiums.
As long as they are open and accessible they will serve and be served by the communities that need them. Because directory searches have little need for ranking they will be the first port of call for those who want more than the latest news or consumable.
Data image via Tom Woodward in Flickr Creative Commons
January 2, 2013 in Big Data, Information Lifecycle Management, Social Media | Tags: Business, collaboration, Information Integrity, Internet Marketing, Online Communities, Social Contribution, Social equity, Social marketing, Social media, Trustworthiness | 1 comment
Changing social platforms is like moving to live in a new country.
How do I know? Because I have done the latter three times and met the same hurdles to a settled existence as I now detect in moving to a new platform on social media.
The largest of those hurdles is collateral. When I came to live in the US, for example, I had no credit rating, because there was no record stateside of my economic conduct. I had no guarantors other than my employer because friends and family lived in Europe. Slowly I established myself, connecting with the economy and communities until my rating facilitated the more desirable loan rates.
The second of the major hurdles is equity or net worth. Equity comprises assets, liquid and fixed. Liquidity or cash is necessary for every day living, the small transactions that allow us to commute, feed ourselves and be entertained. Fixed assets are a little more problematic, because they are usually hard to convert to liquid status. Furthermore they tend to be anchored in the environment from which you have departed, and have little value in the new environment. Owning a house in Europe has no weight when trying to buy a house in the US, and vice versa.
The same holds true when one considers investing effort in an additional or alternate social platform. While you may have a generic social score aggregated across active platforms, your credit rating on a new, or seldom used platform is non-existent. Collateral in this case is not about your financial credit rating, it is your trustworthiness as a social participant. Just as in immigration that rating has to be built gradually and cannot be transferred from the old to the new.
The analogy is consistent for equity as well. Equity in social terms is the value of contributions. These most commonly are the status updates, messages, tweets, replies, mentions that make up the social media conversations of each second, hour and day of our lives. It is also the knowledge base and territorial familiarity of that platform, knowing who does or knows what, where expertise lies, or when particular events occur, or what time is best to capture the attention of your networking collaborators.
All this is platform equity. Not surprisingly very little, if any, of that equity is transferable. Those contacts, the followers and those followed, like the friends and relations in the old world, belong and remain on that platform. Those contributions and the manner in which you supplied them is also tied to the platform. Unlike property or disposable assets these cannot be liquidated into cash.
The new platform requires new equity and collateral, it cannot easily be bought, at least not without compromising trustworthiness. The only alternative is to invest a similar amount of time and effort in building equity on the new platform, thus forcing a decision on whether to build and then maintain multiple platform equity and collateral. That factorial investment might be too high a price to pay, especially for those individuals whose roles do not include 100% social engagement.
There is one positive to this situation and it is somewhat paradoxical in the fact that the fixed social equity is more versatile than the liquid. I refer to blogs. The platform that best supports communicating complexity, rationale and clarification. Blog posts like this one allow ideas and insights to be expanded, formatted and packaged for distribution through any social media platform. However they do only offer the foundational piece; the interactions, connections and short communications still have to be performed.
There are several implications of the above, especially as we consider scale:
Consistency: Equity and collateral are both affected by inconsistency. And we all know that consistency is more than desirable in social media, it is almost obligatory. However context can vary and what might be considered consistent in one platform could be seen as inconsistent even contradictory in another. Furthermore maintaining dialogues and connections across multiple platforms can easily foster miscommunications, especially if the connections themselves participate on multiple platforms. Since we cannot easily store our contributions, we cannot easily reference our interlocutors’ or our own previous conversations. The more platforms we engage with the higher the likelihood of miscommunication and inconsistency.
Social Marketing Investment: It would be fair to assume that few social-media active consumers will engage heavily on a large number of platforms and will more likely inhabit and contribute on a manageable handful (2-4). It is also unlikely that consumers of specific brands will inhabit the same platforms. This is not dissimilar to the position industry faced with the proliferation of television channels in the latter part of last century. The answer then as now is to promote on the most popular channels or platforms. Unlike television however marketing organizations would be cautioned against abandoning platforms that drop in popularity, since their collateral and equity will remain, albeit diminished over time. The danger is of course that the least attended platform then becomes the greatest liability. Such platforms are more prone to negative activity that could fester unaddressed.
Social Collaboration: Perhaps the biggest challenge for industry will be in the requirements for and selection of collaborative services, especially if the components and resources have preferred social platforms of participation that are different. Ideally a common platform solves this problem, one where context integrity is assured. Multiple platforms dilute that integrity unless all contributors and contributions are consistent across all platforms, though such purity would inevitably be strained by diversity of geography and culture. This suggests that established collaborative groups and activities will be more conservative and less exploratory of new platforms. It also suggests that new collaborative groups and activities can explore new platforms, especially those that offer better functionality or efficiencies. But these organizations also warrant caution in deciding for a new platform, for it may well exclude them from collaborating with resources and communities on the older platforms.
I am sure there are many other points to consider, but one thing is certain: adding or moving to a new social platform is a non-trivial event, and one that demands a lot of adjustment and effort. This post is my attempt to bridge the increasing number of platforms to which I contribute as I will distribute it on all. Hopefully it will spark further discussions on the challenges as well as progress on removing the walled garden barriers to the preferred open environment.
December 1, 2012 in Big Data, Book Review, Frameworks, Governance | Tags: Asset Management, Book review, Business Challenges, Business Development, collaboration, Distributed Resources, Enterprise Architecture, Evan-Greenwood, John Boyd, New Instability, New Work Culture, Strategic Planning | 1 comment
One of the things I like about the social media is electronic serendipity, especially when it comes to finding new books and articles to read.
Before the rise of Twitter, Google+ and Facebook I was a frequent visitor to bookstores where I could browse the titles, pick them up and read a few paragraphs or pages according to the patience or generosity of the shop staff.
I would also take recommendations from book reviews and frequently from colleagues and friends. Finding a hidden treasure was both rare and pleasurable. Which is why I have to thank the social network for introducing me to The New Instability by Peter Evans-Greenwood.
One day I just happened to catch a conversation on Twitter between two enterprise architecture mavens, one I knew and admired and the other a complete unknown who had recently published his first book. The discussion was about whether enterprise architecture would be needed in the evolving world of virtual services, globalization and crowd sourcing. I was unable refrain from entering the conversation. One week later Amazon delivered Peter’s book.
“The New Instability” is an important contribution to our embryonic understanding of the challenges to industry and the changes necessary to compete in the new world of ubiquitous connectivity, virtual services and social activity.
It is unlike books like Nicholas Carr ‘s “The Shallows” and Thomas Friedman & Michael Mandelbaum‘s “That Used to Be Us” which have gently and persuasively indicated the path on which we are traveling, where we have come from, our current position, the perils that surround us, and our likely destination. Such tomes have identified the challenges and behaviors that this new world order evokes.
Evans-Greenwood goes much further. His book challenges the scalability and structure of the current industrial model, based as it is on an imbalanced focus on asset ownership and process improvement through extreme measurement (the current though Victorian approach to manufacturing efficiency devised by Frederick W. Taylor). In order to survive and grow these concepts have to be more than just revised, they have to be rejected. Businesses will have to be deconstructed with many of the functions distributed and externally resourced. “The New Instability” provides grist for the mill, it forces the reader to think as the author confronts established wisdom and illustrates its redundancy.
But the author is more than just a detractor of modern practices, he also suggests the nature of successful navigation in the developing new business environment. This is not a silver bullet, they simply don’t exist, or even a recipe that can be easily followed. It is a paradigm that is evocative and immediately understandable, based on the experiences and keen insight of an American pilot by the name of John Boyd.
Boyd offered a bet that he could beat any other pilot in a dogfight in less than 40 seconds, even with the other pilot sitting close on his tail. He never lost that bet. According to Boyd “…success in a rapidly changing environment depends on your ability to orient yourself and decide on and execute a course of action, faster than the environment (or your competition) is changing.”
“The New Instability” explains what this means and what it infers for both individuals and organizations. Evans-Greenwood devotes a chapter to the topic of Labor, starting with how technology has enable workers to address and execute greater complexity. His model is equally applicable to knowledge and knowledge working, since the ability to manage information complexity may well provide the greatest competitive advantage. Equally importantly he understands the nature of the new work environment with its close similarities to Massive Player Online Role-Playing Games (MPORG) such as the World of Warcraft.
“The New Instability” is a challenging book, not in the sense that it is hard to read or comprehend, but challenging to one’s preconceptions and understanding of structure and stability.
It is a book that should be read slowly, because its value lies beyond the page within the mind and cogitations of the reader. There are many points that cry out for discussion and progression and some that prompt resistance, all commendable especially if they compel others to online debate. It is a brave book and one that deserves an appreciative and responsive audience. May serendipity lead you there too.
June 12, 2012 in Big Data | Tags: Analysis, BigData, collaboration, Curation, Data Definition, Data model, ILM, Knowledge, Knowledge Management, Lifecycle Management, Meaning, Networking, Open Source, Peter Drucker, Semantics, Social media, Social Media Value, Social Network, Tony Walker, Unstructured data | Leave a comment
The more we know the less we understand. Nowhere is this more true than on the Social Network, where volume, velocity, volatility and variability are increasing on a daily basis. Those 4 V’s are part of a definition of big data, which includes both structured and unstructured data. We may have a reasonable chance of obtaining valuable information from the structured data population. That depends, of course, on the extremity of any single one or combination of the 4 Vs, yet author, time stamp, location or any other tag that accompanies a communication is easily identifiable. Howerver unstructured data poses a challenge several orders of magnitude greater. Structured data benefits from data models, data definitions and rules that enable us to extract reports and analyses even to the point of discovering new relationships and information from the regimented data. To do so, we need to nurture and maintain these structures, to prevent a degradation of data quality and avoid conflicts and loss, a goal that often eludes the best efforts even in mature IT shops. However this is not the case for unstructured data.
In general there are no data models, no data definitions, no rules and no discipline of housekeeping for unstructured data in Social Media. At least nothing that is commonly held. Individually, of course, we have an idea of what we are communicating, and we probably use both our own data definitions as well as those we assume are being used by others in any conversation; but these are amorphous concepts and certainly nothing that can be referenced by others or by cyber analysis. The same is true to a lesser degree in IT organizations and the worlds behind the firewalls. At least in those environments best practices such as change management and planned organization of unstructured data (viz Sharepoint) should ensure some semblance of control and order if not insights into hidden information.
We do however have some rudimentary tools at our disposal, but like early man our technical bows and arrows are a poor match against the stampeding herd of beasts that is the social network stream. So like our ancient ancestors we have to develop strategies and skills that help us survive and thrive in this world of pervasive communications. Tony Wagner, author of “The Global Achievement Gap” identified three such skills that he believes are fundamental for us to foster and teach. He calls them the “three C’s – critical thinking, effective oral and written communication, and collaboration.” He also believes that this should be the prime focus of our educators, and that we should establish “a new National Education Academy, modeled after our military academies, to raise the status of the profession and to support the R and D that is essential for reinventing teaching, learning and assessment.”
Knowing how to perform the three C’s is therefor one of the keys to success. Being able to put this knowledge into practice, and bring organization and governance to bear on the resources and data requires additional skills if enterprises plan to approach and consume the labor and thoughts of distributed social resources.
Taking these observations a little further I believe the following 5 components are necessary in order to navigate, participate and collaborate in world of social information.
1. Understanding – we need a better understanding of what we are dealing with in the social media so that we can properly distinguish and farm target crops whether they are preferences, demographics, opinions, gossip, information, knowledge, wisdom. or something altogether different. However to improve that comprehension we need to be more aware of the dynamics of how we think, analyze, and communicate effectively. What, for example, is a thought, and what are the attributes of thought that make it consumable? We have a notion of answers to those questions but they are personal and subjective. Yet we cannot rely solely on subjective interpretation, so we need a shared and objective framework or model of knowledge. Knowledge is the loadstone of the social community, and the more we understand it, its nature, behaviors and properties the more we can improve the discovery, sharing and use of valued information in the social stream.
Peter Drucker(1909-2005), one of the most respected commentators on management theory and practice, believed that “knowledge worker productivity” would be the next frontier of management. Drucker was also famous for his quote “If you can’t measure it, you can’t manage it”, to which I would add the following prefix, “f you cant understand it, you can’t measure it.” Building a common understanding and framework(s) for knowledge management is essential in determining meaning, relevancy, relationship or other characteristics of information within contextual and cultural settings. We need to be able to detect when ambiguities and obfuscations are intended and make a documented judgement on meaning when they are not.
2. Networking – it might be stating the obvious to point out that people, individually and collectively, lie at the heart of the global social community. And it stands to reason that knowing who is who, and what they know is another fundamental layer needed for success. The size and complexity of big social data demands a superior set of skills that can identify, analyze, classify and then connect individuals to each other and their knowledge sets. I described this in my previous post Network Weavers which attempted to define the needed attributes (acquisition: filtration/review: association: curation: construction). As the dimensions of the network, the participants and their contributions grow so will the level of skills, and proficient network weavers will become more of a premium resource than they are today. It is likely that networkers will depend on directories, personal or even corporate at first, but increasingly the directories will become more public and entries will contain more social information such as skills, contributions, preferences and factors that others will be able to use to determine relevancy and fit for purpose.
3. Analytics -With improved understanding of knowledge and how we use and abuse it, we can approach analysis with a higher level of confidence in the accuracy of our observations. There are techniques and technologies that attempt to extract meaning from unstructured data but they still fall short of the human computer that is the brain when it comes to analyzing written and visual communications. As with humans machine semantics are bounded by self imposed rules and definitions, and like humans, communication is improved if there is an agreed set between participating bodies. If those rules and definitions remain hidden and obscured then the output can only be regarded as personal opinion. Rating the relevancy or social worthiness of an individual or entity against undisclosed rules and definitions has as much value as the street corner tipster who whispers a sure fire winner for any given horse race. Consequently social media demands semantic definitions that are shared amongst correspondents and a semantic analysis engine with the flexibility to parametrize selected characteristics so that relevancy can be tuned to group or community objectives.
4. Curation – In an earlier post, Curation – In Need of a Cure I raised the need for knowledge workers to approach the care and maintenance of Social Media information in the same way that enterprises manage their data through Information Lifecycle Management. It is not enough just to store knowledge as we do currently with Pinterest, Tumblr, scoop.it and others: beyond catching the item in our personal butterfly net, our efforts resemble little more than childhood scrapbooks of things that caught our interest and appetites. Curation is an excellent term for the housekeeping that needs to be performed on the captured knowledge data. In museums and art galleries curation is a highly sophisticated skill set that seeks to first isolate the item of knowledge, then to expand it with information about its provenance (where it came from) and pedigree (eg what school of thought), augment it with related content (supporting and detracting) and finally exhibit it to educate and edify an interested audience. Curation is an essential component in building a rich and relevant knowledge base, and can and often does lead to new insights and innovations.
5. Collaboration – Unlike “Field of Dreams” you can’t just build a field and expect the games to begin. All the understanding, networking, analyzing and curating will bring but small value if you keep it all to yourself. The key to success lies in participation. The more you contribute, the greater value you generate both for yourself and for your correspondents. The root of the word collaboration is “labor” , meaning work or effort, and the prefix “Co” means sharing. The more you share and contribute the more you will be rewarded by your involvement with the social network. You will be further rewarded as others do the same, whether its contributing common rules and definitions, understanding of knowledge and thought, the names and skills of great social network participants, or exemplary curation of well defined and related content. It is the act of collaboration that provides the secret sauce of success and bridges the resources and knowledge in the social stream. This is not theory: this is proven without any shadow of doubt by the open source community. If you get the opportunity, interact with an open source contributor, and ask them for guidance; they have been doing it effectively, efficiently and profitably for more than a decade.
WARNING: Please don’t attempt any of the steps above without clear and careful planning
- Search is Not Enough: Using Solr for Analytics (architects.dzone.com)
- Examples to help clarify what’s unstructured data and what’s structured? (parasdoshi.com)
- Tackling that unstructured data mess, practically (infocus.emc.com)
- Visualising The Future – New Techniques will revolutionise understanding and interpretation of ‘big data’ (blog.bt.com)
May 1, 2012 in Big Data, Information Lifecycle Management | Tags: Analytics, Application programming interface, Architecture, Big Data, collaboration, Data Administration, Data Mining, Definition, Global, Information, Networks, Open, Signal, Social media, Standards, Streams, Walled Garden | 3 comments
How does one define Big Data and is “big” the best adjective to describe it? There are many voices trying to come up with answers to this topical question. Gartner and Forrester both agree that a better word would be “extreme”. Between the two major consulting firms they have determined four characteristics that extreme can qualify: they are agreed on three: volume, velocity and variety. On the fourth they diverge, Forrester postulates variability while Gartner prefers the word complexity. These are reasonable contributions and may form the foundation for the definition of big data that the Open Methodology Group is seeking to create within their open architecture Mike 2.0.
However the definition still falls short of the mark, as any combination of these characteristics can be found in many of today’s large data warehouses and parallel databases operating in outsourced or in-house data centers. No matter how extreme the data eventually Moore’s Law* and technology will asymptotically accommodate and govern the data. I could suggest that the missing attribute is volatility or the rate of change, but that too can be applied to current serviced capabilities. Another important attribute that is all too often missed by analysts is that Big Data is world data, it is data in many formats and many languages contributed by almost every nationality and culture and the noise generated by the systems and devices they employ.
Yet the characteristic that seems to address this definition shortfall best is openness, where openness means accessible (addressable or through API), shareable and unrestricted. This may be controversial as it raises some key issues around privacy, property and rights, but these problems for big data still need to be resolved independent of any definition. Why openness? Here are six observations:
- Any data that is not open, ie that is private, covert or obscured is by default protected and confined to the private architecture and data model(s) of that closed system. While sharing many of the attributes of “big data” and possibly the same data sources at best this can only represent a subset of big data as a whole.
- Big data does not and cannot have a single owner, supplier or agent (heed well ye walled gardens), and is the sum of many parts including amongst others social media streams, communication channels and complex signal networks
- There will never be a single Big Data Analytic Application/Engine , but there will be a multitude of them , each working on different or slightly different subsets of the whole.
- Big Data analysis will demand multi-pass processing including some form of abstract notation, private systems will develop their own notation but public notation standards will evolve, and open notation standards will improve the speed and consistency of analysis.
- Big Data volumes are not just expanding, they are accelerating especially as visual/graphic data communications becomes established (currently trending). Cloning and copying of Big Data will expand global storage requirements exponentially. Enterprises will recognize the impractical economy of this model and support industry standards that provide a robust and accessible information environment.
- As enterprises cross into crowd-sourcing and collaboration in the public domains it will be increasingly difficult and expensive to maintain private information and integrate or cross reference with public Big Data. The need to go open to survive will be accompanied by the recognition that contributing private data and potentially intellectual property is more economic and supportive of rapid open innovation.
The conclusion remains that one of the intrinsic attributes of Big Data is that it is and must be maintained as “open”.
February 17, 2012 in Big Data, Curation, Frameworks, Information Lifecycle Management, Social Media, Technology Tools | Tags: Architecture, collaboration, Marketing, Open, Social media, Social Network | Leave a comment
It takes about 6 months of immersion and splashing about in the waters of Social Media to feel comfortable and confident enough to not just tread water but make strokes that might lead to reaching one of the other sides. That is of course if any of the other sides are visible, as the social network is far larger than any public amenity previously encountered by a an order of magnitude. For those about to jump in for the first time – do not be afraid – the temperature is fine and its predominantly shallow water. You wont get into difficulties and the worst thing that can happen is a little bit of personal embarrassment, but then nobody is really watching that closely.
During those months of familiarization, learning how to engage with Facebook, posting to your wall, writing up your “resume on steroids” aka Linkedin, pinning your curated content on Pinterest or taking the bolder step of blogging or tweeting you may have wondered a little bit about this medium, the proximity of millions of people all swimming about much the same as you. What is it? Rushing through the list of possible descriptors it’s a club, a hangout, its a place to share your thoughts and life with friends , it’s a knowledge pool, it’s the maker and breaker of news. it’s the university of life, the crucible of change even revolution, it’s a marketing paradise. Finally a reliable source on how commercial brands can track the public success of and reaction to their products and identity. And that is how it is viewed today. At a recent Social Media Week event in New York the main topic of conversation was how to use the social network for competitive advantage, with the focus almost exclusively on the marketing advantage. One of the biggest discussions of the week was who owned Social Media – marketing or PR, and ancillary to that was the often expressed sentiment that CMOs owned Social Media and the strategy around it. Furthermore that ownership and the technical budget that accompanies it indicates that the CIO should now report to the CMO.
But before anyone stakes a claim on Social Media, shouldn’t we first understand more about Social Media, what it is, how it is structured (or non-structured) and what are the economics of the model(s), who are the principle players, what are the constituent parts, and what are the appropriate standards and rights that should attend the use and access to this massive data universe. And the questions do not end here. Most importantly what is the value of the Social Network to the individual, the private citizen, the corporate or public sector employee, the community, the enterprise, the nation, mankind? Without doubt it is worth far more than the sum of its parts, but the largest opportunity of all lies in collaboration. Being able to reach out and share is the fundamental behavior of the social network, and millions upon millions of people do so every day. They participate, contribute and collaborate freely and willingly, and it is manna from heaven for the marketing profession, who understandably have sharpened their knives to capture the likes and dislikes of the masses. But if that energy and effort is properly channeled, if tasks can be performed by social network teams, if thoughts and ideas can be evolved and extended to stimulate innovation then marketing will be just the tip of the value iceberg.
In the end no-one can or should own the social network, money will be made from it, reputations will be won or lost, but ultimately the social network benefits and belongs to all of us, to Everyman. We are all contributors, we are all curators, we are all custodians, and our first task as stewards is to define and describe the infant that is our charge, so that we may nurture and care for its health and growth. This blog will attempt to start that process, and with a lot of help from others (both a plea and an invitation) hope to bring some focus and understanding to the ever expanding pool of knowledge and resource that is the social network.
- Extreme Social: Social Media and The Power of Social Networks (michellegilstrap.wordpress.com)