in memory of Devendra Singh

Devendra Singh was a clever and charming firecracker. So smart. So gentle. So caring. So persistent. 

In my dissertation acknowledgments, I wrote this about him: 

Dr. Singh has shown me that loving what you do will keep you alive. His wisdom about life, enthusiasm for teaching, and concern for my well-being have bettered my life in countless ways. I have learned from him how to think like a scientist and will forever remember his unmatched ability to captivate a classroom.

I remember the first class I ever TA'd for him. We walked slowly for several blocks in the brutal Texan summer heat. I didn't think he would make it. When we arrived in the classroom, he got up on a table, sat cross-legged-- looking half like a child, half like a yogi, and hacked away until he caught his breath. When it was time for class to begin, he was ON - no signs of distress until the 'high' of teaching escaped, an hour or so after class.  

I've never seen a classroom of college kids listen as intently as they did to Dr. Singh, day after day, no matter what the content. I've also never seen someone command a room so powerfully with such a gentle voice, strong Indian accent, and transparencies dating back to the 60's. 

Dev loved teaching. He also loved when people appreciated his teaching; thus our relationship. He inspired everyone who stepped foot in his classrooms. And this, only one of his many dimensions-- brilliant researcher, devoted and very, very proud father, gourmet chef, and so many other facets that came up over the years. 

Dev was groundbreaking and controversial. He would be disappointed in me to know I memorialized him without mentioning his research on the evolutionarily preferred .67 waist-hip ratio and the adaptive significance of female attractiveness. Students were literally on the edge of their seats when he gave the backstory on this research-- again, using his old transparencies. 

I know he suffered over the past few years, especially this last semester when he was prevented from teaching. I'm so sad he's gone. Missing him so much already. 

May everyone have a fig today to honor the passing of this inspiring man. 

not (just) listening anymore

The Listening space just got exciting. Again.

Or should I say the Social CRM space?

Coming from what used to be called a social media monitoring research firm, I find changes in this space very interesting-- whether they revolve around the quest for the ultimate metric for engagement, the hot new look of a dashboard, or the advancement of semantic technology. Most interesting is when companies join forces, including oldies like BuzzMetrics and NetRatings and Cymfony and TNS and, those hot off the press, Attensity and Biz360 and Scout Labs and Lithium - both of which are being billed as dominant forces in the suddenly expanding Social CRM space. 

Merging open and closed networks is an important move for businesses; so is responding in real-time; so is amassing massive amounts of data. Each of these, a promise of social CRM. 

And with each of these much-anticipated-features of Social CRM comes important watch-outs:  

Merging networks:

One of the most important precursors to merging data sets is data quality. Have you evaluated the breadth (e.g. which networks, blogs, forums, Usenet, tweets, videos, etc.) and depth (e.g. comments, likes, wall posts, etc.) of the data set you're querying? Be wary of the mechanics of your data before you assume they can be married.   

Real time response:

An often overlooked aspect of real-time response is a corresponding workflow to enable a sufficient response. Are there formal processes in place to connect the subject matter experts to the consumers? Before trying to respond too quickly, prioritize the signals you're responding to and make sure there's a process in place to both facilitate response and fix any associated problem.  

Amassing data:
People love to talk about warehouses full of data. With APIs opened up, are you hoarding additional data or making sense of it? Make sure you're not mindlessly adding apples and oranges. Add variables together with cause, and look for patterns beneath the surface. 

I'm really excited about Scout Labs and Lithium joining forces, largely due to their stellar casts of characters. Jenny Zeszut, Margaret Francis, and Jochen Frey at Scout Labs; Joe Cothrel and Michael Wu at Lithium all are enlightened minds I always learn from. Congratulations to all of you!

Your customers are indeed everywhere and you need to be as well. My colleague, Peter Kim is hosting a webinar on this today. Join him as he shares his observations on social media trends and the market factors driving businesses’ need for expanded customer intelligence over the Social Web, Wednesday 5/19 at 3CT/4ET. 

I'm anticipating a lot more creative moves in the listening space in the near future. Just be wary of the basics before you identify your new Social CRM provider.

I'm back!

I'm a little out of practice, having been gone for the past 2 months on maternity leave. I haven't been blogging, and only infrequently tweeting. But that doesn't mean I haven't been thinking about social business. As the folk wisdom goes, sometimes taking a step back gives you a fresh POV.  

One of the best perspectives I got came from the worst part of my maternity leave: a 3 day stint at the Children's Hospital, where they had the most impressive analytic dashboards. 

In the pediatric ICU there are monitors everywhere, with all the right real-time analytics. At first, I was in awe of the gold 'standardness' of it all -  they know exactly what to look at to monitor the health of their patients. One dip or rise and the alarms sound. If only we knew the equivalent of heart rate, blood pressure, and body temperature in social business... 

But what I learned is, even when you've got the right metrics, it's still complicated. So as you continue to chase the holy grail of business metrics, here are some things to think about.

• Don't set thresholds too aggressively. The monitor in our room buzzed all the time. Initially, I panicked each time. Inevitably, a nurse would come in and turn it off. No exam necessary. No big deal. They had set the thresholds for various measures as early warning signals- the beeping wasn't really cause for concern. Eventually I learned to ignore it. When your metrics aren't calibrated to levels that require action, it leads to non-response.
  

• Connect your sensors to the right surface (think: people, department, products).  My son's blood pressure gauge was on his ankle. With any kicking, the monitor was overcome with noise. He kicked all the time. Again, I endured the meaningless beeping and worse, an eye-opening flatline would appear on the monitor. The signal was great when it worked, but it was hard to read patterns over time with so much missing data. If you want your signal to come in loud and clear, be sure you're accessing a reliable location.
  

• Single measures mean little in isolation. Each of the measures monitored was a very strong indicator, but never did movement in one call for action. Action was the result of a configuration of activity across measures, over time, and as a result of consensus across nurses and doctors. Here was the biggest lesson: 'metrics that matter' actually means more than identifying the right metrics, the holy grail-- it's about finding the ones that act in concert to yield something meaningful, having the right people monitoring them, and instituting the right processes for crisis response.
  

Now, this is NOT a critique of the medical practice. This particular hospital had it down- they knew exactly how to 'listen' to their dashboards. Having internalized tactics like the above, they knew exactly when to intervene. 

This is, instead, a lesson about valuing what it is that you're currently measuring. The right metrics will come; for now, make sure you're making the most of your current dashboards.

More to come! 

Awaiting Igon Valuation

In Steven Pinker’s eloquent review of Gladwell’s new collection of essays, he coins a new calamity - “the Igon Value Problem,” mocking Gladwell for his misunderstanding/ misspelling of the term “eigenvalue” as igon value. The Problem, as defined by Pinker is,

when a writer’s education on a topic consists in interviewing an expert, he is apt to offer generalizations that are banal, obtuse or flat wrong.

Now, I’m laughing all the way home, believe me, but I’m concerned that our industry is one that is fueled by Igon Valuation. Is it not true that there’s a deep hunger for sweeping generalizations in lay speak? A thirst for buzzy buzz words to capture compelling psychological constructs? Isn’t that essentially what industry analysts are lionized for?

My concern is that this Problem is keeping answers at bay. There are solutions available to some of today’s more complex business problems, but they’re waiting to be "Igon-valued" before catching on. Take the measurement of social technology usage, for example.

Meanwhile, academics are often brought on to firms with fear-- left in the back room, lest they promise to dumb down everything they’re thinking of uttering client-side.

I too have criticized Gladwell for his banal generalizations, for his cursory foray into psychology and statistics, for somehow stealing the credit for entire literatures-- but I'm constantly reminded that Gladwell is hailed as a business guru! His books are on the business best seller lists for months, years. 

I’ve come to the conclusion that business wants things Igon Valued. In a recent embarrassment at Web 2.0. Expo NYC, danah boyd was publicly humiliated for speaking too densely, quickly, and smartly... I used to think it was compelling stories about data that were lacking, but I’ve now decided banal generalizations are more effective. Please tell me I’m wrong.

I think the essence of business problems are waiting to be solved by a combination of social network analysis (SNA), text analysis, and some good, old-fashioned, proper attention to human beings-- not all things that have been here all along, but things that are readily accessible now.

By measuring connections through SNA, we can identify things like:

• who’s connected to whom in an organization, however informal those connections are. 
  
• the roles people play in communication and collaboration - whether they’re information brokers, originators, or hoarders (alas, a potential opportunity to make blatant generalizations!)
  

Through text analysis, we can determine things like:

• the nature of signals exchanged-- when work is really getting done as opposed to socialization!
  
• how honest or emotional colleagues are with one another
  

Through asking the right questions on surveys, we can:

• explore perceptions of trust, motivation, awareness, competition 
  
• help validate the root cause of any given problem
  

Compare today's business intelligence to what Dr. Dena Rifkin wrote recently of how our medical interventions -- our attention to “benchmarks and checkboxes” are failing the patients:

As a profession, we are paying attention to the details of medical errors — to ambiguous chart abbreviations, to vaccination practices and hand-washing and many other important, or at least quantifiable, matters.

This too is true in business-- we’re paying attention to quantifiable units because they’re there, buzzy concepts because we want to keep up with the Jones’.  

Be wary of buzz words. Certainly there are outliers, flukes, and things you can accomplish without methodical, long-winded statistical pattern analysis or reasoning, but for the most part, some depth is necessary. Furthermore, means to the depth already exists -- we’re not waiting for it to be figured out, just waiting for it to be popularized.

Also posted on Dachis Group Collaboratory which you can subscribe to here

Three masquerades of metrics

Below is an excerpt of a post I wrote for our Collaboratory today. Curious to hear readers' thoughts on measurement flaws and opportunities in the social space. Please find the full post here. 

[There are three major opportunities that could help unlock the value of conversations and other social interactions. But first, we have to overcome some very basic human tendencies:

• the ease of counts 
• the shine of the surface 
• the convenience of snapshots. 

We need to abandon some traditional standards and stop forcing social data into shapes and sizes that work for other media measurement. Tomorrow is about patterns, depth, and dynamic metrics.]

Reflections on Reflections on Working in Public

When we launched our Collaboratory, I mentioned that it's part web presence, part social business experiment. For now, the most experimental part is the window on our work-- a live stream of communication acts our team engages in, offering up varying degrees of information from having shared an unnamed file on a particular platform to emailing someone at a certain domain to tweeting specific, visible content. 

There are massive individual differences in comfort with transparency. As my team has spent the past few weeks sussing out the comfort zone with the public now privy to the stream, we've reflected on, discussed, and critiqued our perceptions. We're very curious what it's like on the other side of the window... What do you think about our transparency? Too much? Not really that much? Want more? 

Transparency can have a profound effect on behavior. Perhaps not a universal effect. Ironically, the psych study that comes to mind is an old great of Ken Gergen's: Deviance in the Dark (Gergen, Gergen, & Barton, 1973). Gergen was exploring the effect of darkness on behavior. He had students enter a dark room one-by-one, to get to know each other. He provided very few instructions. They chatted, talked more heatedly, and then... eventually the study was called off because it led to some scandalous and unexpectedly affectionate behaviors! Not aggressive ones, as might have been expected. 

I bring this up because of what we know from this and several other studies on deindividuation, or not being able to see or pay attention to individuals as individuals (the opposite of transparency). Deindividuation doesn't necessarily make you aggressive or affectionate, it's a powerful force in making people conform to a perceived norm. This has really interesting implications for transparency in the workplace, especially for leaders and norm-setters. Transparency may not have a single effect - be it competition or collaboration; authenticity or artifice. Read how it's affected my colleagues over the past few weeks and let us know what you think.

 

Dachis Group Social Business Technology Alliances

Another week, another announcement: today, about our Social Business Technology Alliance program. 

With such a wide spectrum of social business needs, it's important to have the flexibility to solve the problem at hand and not shoe-horn an organization into an uncomfortable platform. It should be clear by now that at Dachis Group, we believe technology is part of the overall solution; I typically write about the necessary culture and process-related changes we believe in and practice. Today, we're excited to welcome our technology partners to our ecosystem to help deliver comprehensive solutions.

Our technology and integrator partners include:

• Atlassian Confluence - Wiki-based collaboration
  
• CoTweet - Twitter for business
• IBM Lotus Connections - Enterprise social networking tools
  
• Telligent - Customer and enterprise facing communities
• ThoughtFarmer - Social intranet software
• SocialWare - Social Media risk management
  
• Socialcast - Enterprise microblogging and social networking platform
• Photon Infotech - Open Source Development
  
• Bamboo Networks - Custom application development and rehabilitation
  
• Starpoint Solutions - Application implementation and integration
  

Read the official release on our Collaboratory.