Have you ever been in a presentation, where the speaker was obviously an expert but they just couldn't convey their ideas to the audience leaving them confused and uninspired?

It's been quite some time since my last post and for those of you that have been asking, I thought I'd write an update on what I am up to these days.

In Mid-January I took on an exciting opportunity as Technical Director - e-Collaboration and Content Management at Research in Motion (RIM). It's simply such a great opportunity to continue my journey into the collaboration space and further extend my work in social computing, along with aspects of content management.

I can't go into any details of the specifics but I am extremely excited to get this opportunity. Perhaps in another post, I'll talk a little about how structured and unstructured content can intersect and diverge.

Leaving Bell was difficult but I know the collaboration areas are in the hands of some very capable people, and will undoubtedly continue to thrive.

Wrapping up my time with Bell, and starting my new role has kept me extremely busy not to mention all the fun winter activites with the family which seem to consume any time I have outside work (my excuse for not keeping up with my blogging).

That's it for now. If there are topics you think I should write about please feel free to drop me a line.

With the economy on everyone’s minds these days, it’s not surprising to see articles looking at the impact the economy has on usage of collaborative technologies (eg. enterprise 2.0).

I’ve found several articles interesting but not quite resonating with me. For example a recent Wikinomics article by Naumi Haque suggests that there are 2 emerging schools of thought on the subject: A) the need for productivity means greater investment in enterprise 2.0 or B) the need to focus on core takes priority over anything else. I actually don’t think it’s one or the other but both. If you could prove productivity/collaborative gains this actually enables greater focus on your core. But since it’s hard to prove, the concept of Risk/Reward needs to be considered.

In my opinion, there are 3 main variables that predict adoption of these tools: Corporate Risk Tolerance, Corporate Performance, and Perceived Risk/Benefit of collaborative technology. These variables are depicted in the visual model above.

The relationship between corporate performance (which is impacted by the economy) and risk tolerance is illustrated by the “U” curve. Basically, a corporation that is doing very poorly tends to take bigger risks as it becomes “desperate” or believes it has “nothing to lose”. Consider the example of Goldcorp that on the brink of bankruptcy decided to share it’s “top secret” data to the world in an attempt to crowdsource a solution to their pressing challenge of finding and extracting gold from it’s property. Would Goldcorp have been so eager to do this if it was doing well?

At the opposite end of the performance spectrum, those companies that are doing well can “afford” to experiment with new approaches and new opportunities while resting assured that the remainder of the business will still thrive and be able fund these initiatives. IBM’s investment in social computing and it’s World Jam for example are things IBM has been able to explore and develop while still maintaining sufficient resources in it’s other core business.

According to this model, companies that are doing “OK”, are least likely to accept corporate risk. “Why change if it ain’t broke”, and “we just simply can’t spend resources on things that aren’t proven to provide us a return”. These companies tend to be risk averse to supporting technologies which aren't core.

The curve is only part of the picture. The other variable is the concept of perceived risk. Risk in this model is loosely defined as the likelihood of an expected benefit versus the expected cost. Costs include implementation but also opportunity cost, and negative side-effects. For those corporations that view social computing investments as low risk/high reward the decision to implement social media in any economic climate is “obvious”. As perceived risk increases however, it would require the company performance to either increase substantially or decrease substantially relative to the perceived risk they place on collaborative technology.

So what does this mean when times are tough? Well, based on this model, I would speculate that corporate performance on average will decline creating a stronger likelihood for adoption of social computing initiatives even at higher perceived risk. Companies that in the past wouldn’t have tried to leverage social computing may actually be willing to “give it a try”. The success/failures of those initiatives will eventually have an impact on perceived risk as stories mount that either prove/disprove the real costs & benefits.

It’s a fairly basic exploratory model and I’d be interested to hear your thoughts. Is your organization about to implement enterprise 2.0 applications? Would they fit this model?

Be cautious in rating employee E2.0 contribution.

Andrew McAfee recently questioned the need and value for rating employees and their usage of E2.0 applications. The chart on the left is his example of some of the things he would consider.

Although these metrics may be of interest to those managing or designing various E2.0 programs, these statistics can be quite misleading. Specifically, I caution those that want to use these indicators as 1) the sole measure in determining the success of their E2.0 programs and 2) the sole means of ranking the value of a contributor.


Success of your E2.0 program can not be based only on adoption/usage percentages. The value of E2.0 includes just giving people an opportunity, enabling self-organization of the most relevant participants, identifying valuable conceptual outliers, reinforcing culture, accessibility for future benefit. These don't show up in adoption rates. I discuss these in greater detail in an earlier post, "5 benefits of social computing that adoption rates don't show". Success isn't a simple metric but requires various perspectives well beyond just adoption rates.


Without any ratings, how would you know whether to trust the content? Rating a contributor based on activity levels is intended to provide participants with a gauge to the "quality" or "accuracy" of the content. This is a dangerous and false assumption. Just because someone may post a lot, or interact a lot, doesn't mean that their content is necessarily of high quality. As an analogy, I spend a long time doing house repairs, not because I am good at but for the exact opposite reason!


A heavy focus on individual ratings will also diminish the real value of tapping into the long-tail. Clay Shirky gives a good example on how one can completely miss the point. He points to comments made by Steve Ballmer dismissing the open source concept of Linux as not really being true/valuable since the majority of work is really done by a small group of participants. Steve's flaw is that he's associating "value" with "quantity". The question isn't about how much input you provide. Even if you provide only one single piece of contribution, what if that contribution turns out to be a major breakthrough? Or in the software example Clay suggests, what if that one patch provided a fix for a major security hole in the software? What's that worth?


My suggestion for those looking at designing E2.0 programs is that ratings are valuable, but they should be at the content level. Individual ratings could be derived (aggregates or averages) from the various ratings of the individual contributions. There is sometimes a desire to use ratings as a means to motivate employees to contribute. If you focus on "quantity" you are incenting the wrong behaviour, focus instead on "value".


One final point. SIMPLICITY. Just because we can measure something, doesn't mean we should. From my perspective, having 6 metrics can be confusing and intimidating to participants. I prefer to get it down to a single metric which has intrinsic value. For example, in a recent application we've designed, we allow (and encourage) participant rating on the content by asking, "Did this content help you?". This means the rating is the total number of people helped by the content. It provides meaning to both readers and authors. Do we track other metrics that we don't display? Absolutely. Is this method perfect? No, but it is simple and in my opinion worth the trade-off.