Beyond Social Media, Creating Social Capital

Rich conversation and insights flowed on Friday morning when the Booth Strategy Discussion group happily pondered four key questions on the topic of Social Media, Not just for Marketing.

This month, David Friedman of Bridgewell Partners offered to facilitate and he began inviting us to consider four key questions:

  1. Do social media supported interaction practices represent a fundamental change in how people work?
  2. What barriers exist to adopting these practices and are the practices optional?
  3. How many, and what kind of resources does converting existing social media activities into successful practices require?
  4. What kind of governance and rules makes social media work and how do you find and manage the advocates?

As usual, the conversation flowed from topic to topic, not chaotically, just indicative of authentic interactive thinking. In hindsight, the face to face conversation and personal value participants derive from ongoing, live exchange of perspectives offers a contrast to the online tools we had met to discuss.  I’ll do my best to share some of the key learning and insights. As usual, I took  time to extend, document sources and supplement my notes, so please do add your thoughts.

People are social animals

Learning is a social endeavor. Knowledge sharing, collaboration and innovation processes succeed when they leverage the subtleties of social interactions. Today’s social media tools facilitate social engagement and may solidify associations that typically erode over time and as geographic distance increases. Today, it is easier than ever to stay actively in touch with associates—neighbors, classmates, friends or colleagues that we no longer see regularly. Their value however comes in creating opportunities that go behind the real world encounter.

Business requires connection and by design, social tools enable people to connect to others for every possible purpose. Want to grow your expertise, make new acquaintances, qualify and connect with experts on specific or general problem or topic areas?  The social tools are a two –way street.  The same behaviors gain new understanding and win support for specific activities and perspectives.

Google changed the way we look for ideas, people, places and things. Twitter  compact messages unleash conversations, debates and ongoing thoughts.  The messages are easy to find and monitor. Content once shared in exclusive forums once closed become public. The virtual location and use of links expands the audience once limited to insiders. Dedicated communities of practice consistently create value for participants, and switching up technology choices amplify the reach of these conversations, e.g. threaded topic discussions used by groups on Linked in.

Closed, restricted conversations however too have their place and have been the domain of  membership restricted list-serves such as those used by MENG—the Marketing Executives Network email list serve, or SERMO (http://www.crunchbase.com/company/sermo) for surgeons.  Some individuals have always been keen to share best practices, or seek out the specialized knowledge of admired colleagues.

Social Capital

Businesses don’t make decisions, people do.  In Bowling Alone, Robert Putnam described the growing isolation that technology promotes. Leveraging  work by Gary Becker and others the book opened new conversations.

Social Capital, embedded in the social realm, is not based on assets or individuals.  Social Capital resides in the fabric of relationships between individuals and in individuals’ connections with their communities (Putnam 1995c)

The emphasis to calculate ROI from Social media misses this point.  No wonder many organizations fail to capture value from socially shared knowledge to improve the way people work? Among the articles we reviewed were some promising signs some companies are making the leap, changing the way they work and incorporating social media practices.

How are some companies succeeding? 

“Organizations operate more like machines, their structure a legacy of the industrial age, taking comfort and finding security in maintaining bureaucratic control.”   In 2006, Chris Anderson published The Long Tail: Why the Future of Business is Selling Less of More.  Transitioning from a command control operating model to deliver unlimited variety to meet specific, personalized needs demands a complete upheaval of management practices, organization charts that operate according to very different rules, beliefs and values.

The industrial age made power free. Many industries gained advantage harnessing that power. Similarly, the present social age, enables communications to spread freely. Success flows to those who manage to find and amplify freely exchanged messages, support their business proposition and gain competitive advantage.

The social paradigm’s counter-intuitive approach contrasts sharply to old push process, where a company worked hard to choose the message and then spent ample budget to promote messages designed to attract the interest of buyers. Today, businesses who listen and move to position themselves within the ongoing conversations that match their product or service set, stand to gain.

Examples of social media transformations of work

Edelman’s business is public relations. They turned their entire recruitment process around by pursuing and inviting those people who demonstrate ability to build an active following.

Intuit’s TurboTax built customer comment threads directly  into their interactive software   allowing people using the platform to learn practices and see examples from other users.

Ernst & Young  created mobile applications on ITunes giving customers insights , tax guides, legal tips etc.   They also created EYE, Ernst and Young Executive, an IPAD based magazine .

Two books, Smart customers, Stupid companies  and Opting In, by IBM Lotus Notes Executive and social business thought leader Ed Brill, admirably illustrate how knowledge IS social, the more interactions the smarter each of us get.

Likewise, peer-to-peer interactions occur within a pertinent context. Customer to customer interactions share very different information than when customers are sharing with company representatives.  The relevance of the exchange to the participants by itself offers  insights around customer perceptions and suggest alternatives to address and resolve their pain points.  This is the very stuff companies once paid researchers to find.  Brill describes the process unleashed by social media as “Thou Shall advocacy,” vs. the traditional company approach of thou shalt not employee governance.

The results?  Resources freed from “finding” should be put to use listening and gravitating to where their customers are actively engaged, communities created to talk about a company rarely happen to be the place the company created for its customers.

Changing the way we work

We all believe that change and changing behavior and processes at work continues to prove hard for several reasons.

Legacy workflows with established internal processes supporting hierarchical, command control organizations clash with the general ease people collaborate and bond outside of work.  Monsanto exemplifies a company who learned quickly how to use social media to build and strengthen what were formerly weak relationships.

Communications become conversations, as illustrated by their 2012 letter to shareholders proclaiming “the ways in which we are all interconnected…” Monsanto continues to evolve their communications beginning  with a move beyond stylistic changes to their communications as  this 2009 St. Louis Biz Journal story illustrates. Communications redesigned their department to listen and engage in honest dialogues with a wider audience of stakeholders. The corporate stakeholders no longer bequeath the controversial issues to the opposition. Instead of releasing official stances,  their communications team speaks directly to specific concerns and in so doing taps expertise inside the organization to share and engage employees as well as externally with consumers.

Value above replacement

At the core, social network mechanics leverage an individual’s ability to influence the behavior of others in their circles or network. The CEO of Klout wants everyone to believe that influence is the currency of the social web. Those companies who understand how to leverage their players may very well gain advantage.

 Ron Burt’s work calculates the “value of social capital, showing how in the business world reputation has come to replace authority and …. from other researchers’ studies, provide robust evidence of the value of brokerage.”  If you consider, as Burt does, that social capital is a metaphor for advantage then it’s not that hard to see how the sports world has put this to work.

Value over Replacement, aka VORP, may have begun with baseball but has since infiltrated the fan base of many other sports.  I even found the concept used to evaluate Rock and Roll band members. The adoption of  this concept by other domains illustrates word of mouth at work, and also the nature of social capital flows.  Studies and metrics rarely explain why some words travel and others remain where they were first spoken.

Is the problem workflow design?  The landscape of successful migration to enterprise2.0 practices remains checkered. In part, connected enterprises and successful adoption and implementation of social media platforms and tools require behavior shifts beyond adoption of new tools.  Successful organizations, who do the heavy lifting and restructure their organization, amplify the effects of influencers who in turn, encourage and promote informal collaboration.

The landscape however is littered with numerous unsuccessful change initiatives because they overlook how to put influencers to work. For example, Knowledge management systems, another extension of VORP, sought to capture the tacit as well as explicit understandings and intelligence of workers about to retire. What made them successful also brought success to the organization and it made sense to create the means to keep that knowledge around as people left.  The capture process however proved challenging and few organizations made conscious use of network analysis. This latter tool infiltrated strategic planning activities, but the record of deployment and use remains spotty.

Kraft’s KM initiative in 2000, shows the consequences of missing the opportunity to leverage individual players skills and influence.  The idea was to capture learnings from Consumer Intelligence and Research and Development. In theory, there would be an expert directory, discussion board and an electronic library.  Tagging information properly makes it possible for others to search and find relevant information.  AT Kraft, suppliers were asked to tag their own research, not good for their business model.  But this also diminished the value of the researchers and librarians whose knowledge and tagging skills were never acknowledged as added value.

In contrast, Stack Overflow, illustrates a very different knowledge sharing resource that isn’t dependendent on tagging.  It’s a give and take resource.  The value available depends on people providing good answers and asking good questions.  Participants with high stack overflow scores are deemed experts.

To Be Continued…More on this topic to follow shortly.

If you care to review the articles that were the basis of this discussion, links follow.  So much more to say and so little time, care to share your reaction?  or contribute some new inspirations?  Please do!

ARTICLES

1. Keynote: Invest in Scalable Social Business Programs

by Jeremiah Owyang on Apr 05, 2011

http://www.slideshare.net/jeremiah_owyang/keynote-invest-in-scalable-social-business-programs

2. Large Scale Transformation–how social lies at the core of your strategy
by Dion Hinchcliffe

http://www.informationweek.com/thebrainyard/news/strategy/how-smart-businesses-reorganize-for-soci/240006107

3. The Collaborative Organization: How to Make Employee Networks Really Work
MIT Sloan Management Review Magazine: Fall 2010Research Feature

October 01, 2010 Rob Cross, Peter Gray, Shirley Cunningham, Mark Showers and Robert J. Thomashttp://sloanreview.mit.edu/article/the-collaborative-organization-how-to-make-employee-networks-really-work/

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BIG DATA: Big Deal or Just Big Business?

Technology evolves and for those of us who spend their lives adapting and endeavoring to keep up with the advancements it’s hard  not to notice a curious underlying dynamic.   Data and our ability to calculate or manipulate it for greater meaning is a little like resolving the chicken and egg paradox.  More of one begs more of the other, and yet we continue to ask which came first as if that question were important.  For many of us, our interest in  closing the uncertainty gap wishes for more data. We expect it will  help minimize the error or noise because the present picture of relationships remains a little too ambiguous. The constraint in this case is often our own experience and knowledge.

Professionally,  my own work warns against this unconscious bias.  I simply ask people to imagine three dots and ask that they line them up.  I then remind them that all three dots are coincident data points in time, and ask whether this new piece of information has changed their vision of the dots?  I then ask them to place the dots on an axis of time, and tell them that the dots now represent demand, growth or performance like ROI.  Does the way you’ve visualized the dots changed again?  I explain that the context I’ve added snapped into their own experience to create an image that creates a new puzzle as what they see fights with their expectation and they need more data to explain it.

The Economist in revisiting the Growth Matrix in 2009, put it another way. Bruce Henderson, credited with originating this framework reportedly believed  “while most people understand first-order effects, few deal well with second-and third-order effects. Unfortunately, virtually everything interesting in business lies in fourth-order effects and beyond”.

Big Data and the volume variety and velocity of its availability now has several partners,  real time processing power and plummeting data storage costs and lest we forget, simple access and manipulation tools  placing the data in an ever increasing number of users’ hands.  It is the number of people who now want to use the power of analytics that lends Big Data its influence, or at least that’s what several Chicago Booth alums who shared their thoughts last week recognized.

On May 18, 2012 Chicago was busy preparing for the arrival of NATO delegates and support.  The result was many businesses strongly encouraged their employees to work from home, leaving the monthly strategy discussion homeless.  We took advantage of the opportunity to launch our first virtual discussion combining a real-time interaction platform  (Group Systems Thinktank) and conference call (freeconferencecall.com).  Interest in the topic proved overwhelming prompting us to open up a second lunch interaction following  our usual early morning time.  The comments that follow represent a condensed version of the conversation.  Note, links to the discussion prep video and articles we encouraged participants to review in advance can be found at the bottom of this post. Also, a full transcripts are available to those who interested in seeing the automated output from ThinkTank, just drop me a note.

What’s the deal

Its a toss up whether mobility or big data has captured the imagination of business media more. The duel isn’t the point. Other driving forces and a growing need for critical thinking skills that were already in short supply.  Data reduction may be an emerging competency.  As the earlier references to Henderson point out, the questions you are trying to answer don’t get any easier just because you suddenly have access to more data. What to do with this new wealth of rich information are the bigger questions and challenges not merely for business but for consumers as well.

In the process of  generating the following list of examples, the interaction on Thinktank let participants also provide some links, raise new questions and add additional comments.

Twitter ,Telephone call records, Smart Grid, Real time Electricity meter  data , Nike + ,Scanner data,  Comments from Call Centers,  Providers’ case and disease management notes, EMR records, Geospatial (GoogleEarth, Navistar, etc), Mobile and GPS,  Gov’t DBs (big-data in an unstructured/non-uniform sense) , The quantified self, Output or processed Data from SAS, Salesforce.com, other enterprise databases, Loyalty program, Amazon purchase history, Mint.com, Moneyball (Big data in baseball), the new NSA data warehouse in Utah, QR, The internet of things, Data.gov, The London Datastore, created by the Greater London Authority (GLA–Chicago has similar initiative) offers citizens open access , Netflix movie recommendations, SAP’s HANA usage (profiled in the report on their Sapphire Conference )

Twitter for example has evolved in ways that surprised their founders and also launched a number of new businesses with very unusual purposes. As one article pointed out routing the data can be equally important as tallying it, as illustrated by Procter and Gamble’s practice of funneling social media conversation/data to the appropriate person’s screen for monitoring and response.  In other words to be meaningful, sometimes just knowing something happened is enough, it doesn’t necessarily have to be mathematically manipulated to derive value.

Persistent challenges remain in dealing with the enormous variety of formats in which data are presented — some  sources are difficult to analyze — their pages long data dictionaries  often include details about its collection.Add to that the realization that Data is not just numbers anymore. The automatic semantic annotation required to make sense of this has also entered a new era.

Facebook, LinkedIn, Google+, Pinterest and similar social media sites would fit in here, as well.  All offer a richness of information, much of it real-time, that can be monitored, mined and used to drive decisions and actions. The customer center conversations , or customer audio recordings , transcribed to text, and then subjected to text analytics is helping improve performance management practice, allows for campaign conversion performance tracking etc

The impact or convergence of the evolving technologies with all of this new data, is as overwhelming as the scanner data that was available and stored historically but few had resource capability or interest in mining it. That era has passed and with it, new questions and promises arise.https://i1.wp.com/www.connectedaction.net/wp-content/uploads/2012/04/20120421-NodeXL-Twitter-Global-Warming-Labeled-Groups-Network.png

Can we better understand and use consumers sentiment as in  do retail customers use more electricity/phone service/etc in a method that correlates to changes in the economy? weather? Or SAPs HANA data, now makes cancer DNA genome type analysis possible in minutes.

FB and Twitter,  may be drawing more attention, but those who  bring together the different streams  and mining more deeply old sources such as scanner data  are also causing quite a stir. Target found out that teenage girl was pregnant before her dad did using methods such as these.

Add the RFID  and imagine the benefit to stores knowing the quantity of each SKU that they currently have?  Can they coordinate sharing of product between their brick-and-mortar stores?

Perhaps the focus on twitter, etc., rather than scanner data comes from hoping that trending sentiment will precede and can be used to predict purchase, rather than log it as with scanner data. At cars.com, a participant shared  that vehicle search data on our website is predictive of sales.

It looks like QR codes might achieve the same benefits of RFID as smart phones are becoming ubiquitous.

The Geo-spatial data, according to McKinsey’s recent report on Big Data as the next big innovation, quantified billions in time savings from just helping consumers avert traffic.

Several other behavioral nudging based on real time feedback is now possible. Nike is exploring and furthering this automatic feedback. Check this article for more brands using the quantified self, and more information

TOOLS

SAP’s HANA, Google’s BigQuery , Splunk, Hadoop and NoSQL databases , Tableau, Tibco Spotfire, Omniture ,Pentaho (open source BI), Amazon’s Web Service suite (more of a platform), Cloud computing platforms, Data visualization, most business users, make the data preparation easier and allows them to focus more on analysis and develop insights in combination with Machine learning tools (neural networks, support vector machines, natural language processing, etc.)

Decision making , can and does BIG data make more accuracy possible?

It offers higher granularity — like Target’s ability to create coupon books customized to individual households, Or integrate GPS level stuff — e.g. texting coupons to customers right while they’re standing next to a certain store.  Or 2nd/3rd order analysis – correlating Target’s sales with weather data; creating ‘real-time’ personalized coupons; identifying ‘trend-setters’ among the customer base to influence ‘trend-followers’ coupons

The downside? Detecting or separating out spammers from these data sets or paid to  express a certain sentiment. Totally! Like those girls paid to say great things about clothes on Facebook — not maybe necessarily analyzing big data, but using the platform.

Greater real-time evidence  can reduce risk and  insure assumptions in product/service development and marketing are on or off target.

Hard to appreciate the analytic without the qualitative context or understanding;  but maybe some strange new ideas can come out of the data, like the “diapers next to beer” epiphany. Data needs some drivers to make it meaningful, as in cause and effect. In part because qualitative data is harder to analyze.

Is quant vs. qual or the social science methods to data collection really that different from the scientific data analysis approach?  Both approaches seek to explain cause and effect, or the relationship between a stimulus to produce a predicted response. The problem is  too many people will extend a model beyond it’s capacity. Claiming “the data said so”  lets people off the hook and avoids responsibility for  decision-making.

Suggested tips include  avoid extending a model beyond its capacity, or  understand and differentiate descriptive and predictive Stats. Likewise, be wary of  finding trends that don’t exist (e.g. “data mining” or “straws that look like needles”) and confusing correlation with causality.

Perhaps cross-validation from trained analysts can help avoid  these . Danger of expecting tools to automatically extract value from large datasets.  Need to ensure good analysis, disciplined hypothesis generation, etc.

The data, even when analyzed, does not represent the decision.  This is true with small and big data.

FINAL TAKEAWAYS

 

  • Big data is here to stay – need to figure out how to use it effectively.
  • I liked the point that lots of data is around and that people just don’t know what to do with it.  The best BIG DATA process or engine in the world still won’t create the insights that are needed.
  • Corporate culture is a huge factor–the problem is not availability of data, but commitment and focus of corporate leaders to shape a culture that moves the organization in that direction.
  • Big data is here. It’s a tool and like any other, it’s the latest and greatest on the block, with a bit too much hype. But it has a definite value in providing and stronger qualitative base to identifying trends and activities.
  • My realization  is that, once again, the technology is interesting, but it is the corporate culture and will that will matter. The culture and vision lead; the strategy and models follow.
  • sharing the questions with a wider audience confirms concerns and clearly lots of assumptions that need to be played out. There is a large dark side that we still don’t understand; but the positives and opportunities for real time decision.
  • Big Data! The piles get higher and  higher and wider and wider…to what purpose? That implies the need to “mine” the data, reduce it and subject it to analysis before it can be made useful.
  • Big data will revolutionize business but it is not strategy, potential for a lot of false positives .
  • The wise use of big data offers a huge opportunity for developing differentiating strategies and for finding new product/service needs.
  • “Big data” is the current term for things that have existed for a long time.  All types and sizes of organizations can benefit from big data if they recognize the importance of the human component (not just the data and software) and have specific objectives in mind before starting.
  • Much of the expertise about analytics developed over many decades still applies, and there are new dimensions to integrate and understand because of the availability of the technologies and data.
  • Everyone on the line has experience with Big data, so I don’t think it’s so scary.  Most people have business perspectives, wanting to teach the Analysts that their conclusions need to be driven by business needs.   My comment is that as leaders, and those trained with some behavioral awareness through business school, it is _OUR_ responsibility to try and massage the analysts towards an enthusiasm for our world view…;-)
  • The human side of utilizing the technology and expertise is just as challenging as ever. (Cognitive biases, communication skills, influencing skills) Garbage in – garbage out is a big risk without proper attention and skill in applying the technology and in communicating.  The data, even when analyzed, does not represent the decision.  This is true with small and big data.

In closing, let me return to my observations about the limitations of developing strategy rooted in an expectations of the experience curve relationship.  The frame with which you approach the problem often has far more bearing than the data, your analysis or the tools.  Or at least, in June we  plan to look at some of the assumptions around growth as the ultimate strategy.

Please throw your responses, or continue to post links for others as Big Data continues to be quite newsworthy as its impact and influence continues to unfold.

Articles and links:

We suggest an  Optional  short 5 min. video tutorial , EMC produced to understand what Big Data IS?    http://youtu.be/eEpxN0htRK
The following are required advance reading.

1. IBM’s Institute for Business Value, in collaboration with MIT Sloan Management Review  2010 research findings
Analytics: The new path to value: How the smartest organizations are embedding analytics to transform insights into action

  http://public.dhe.ibm.com/common/ssi/ecm/en/gbe03371usen/GBE03371USEN.PDF

2. Strata keynote  short 7 min. video by Google’s Digital Marketing Evangelist Avinash Kaushik- a bit irreverent and a little over the top – a bit irreverent, bordering on over the top – but not boring  effort to help us understand the problems and the approach undertaken by Google.

Big Data Imperative 
March 2012
http://www.youtube.com/watch?v=CrSX97elHDA

3. Tom Davenport’s Culture of Analytics

April 5, 2011
http://smartdatacollective.com/clifffigallo/34719/tom-davenport-s-culture-analytics 

4. Inside P&G’s digital revolution
McKinsey Quarterly November 2011
http://www.mckinseyquarterly.com/Retail_Consumer_Goods/Strategy_Analysis/Inside_PGs_digital_revolution_2893
overseeing the large-scale application of digital technology and advanced analytics across every aspect of P&G’s operations and activities—from the way the consumer goods giant creates molecules in its R&D labs to how it maintains relationships with retailers, manufactures products, builds brands, and interacts with customers. The prize: better innovation, higher productivity, lower costs, and the promise of faster growth…

One more optional overview

The age of big data
NYTimes, Feb 2, 2012
http://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html