The Wisdom of Monty Python and the Failure of Learning and Development Teams to Notice

As organizations become large, complex and distributed, the transactional cost embedded in their day-to-day operations, which at one point may have been an acceptable trade-off for getting things done, can suddenly become crippling. Still many organizations turn to up-scaling existing solutions to address growth and continue to re-purpose strategies that are no longer suitable for the size, complexity and breadth of their network.

Organizations, like the people that operate within them, will often continue to do something that has in the past proven to be successful until it becomes blatantly clear that they are now failing. Recognizing failure is difficult because companies that have invested significant effort into their current processes are likely to try to replicate approaches several times over before being open to exploring new ideas. Unfortunately, under today’s rapid change and diminishing competitive barriers, slowness is a problem.

In the Corporate Executive Board Company’s (CEB) publication Preparing Learning and Development for the Future the authors’ sentiment that Learning and Development teams can no longer focus on learning intervention is right, but lacks the commitment to do things differently. Thomas Handcock and Ducan Harris definition of “network learning” emphasizes the importance of creating cross functional teams to facilitate learning. They distinguish “network learning” from “social learning” by suggesting that the former focuses on informal, on-the-job learning and the latter implies structured learning . While I don’t support the distinction, I believe the more relevant and true point is that Learning and Development teams need to better support on-the-job learning. Still, when we consider Handcock and Harris’ suggestions for a future learning function, we can see that the paper remains on familiar ground.

Suggestions that include elevating a corporate learning strategy to the enterprise level, strengthening skills of learning practitioners to assert learning principals with operational leaders, and focusing on helping people better understand how they can learn instead of pushing learning to them, will all certainly resonate with the intended audience. Similarly, methods that emphasize strategies such as coaching will have most readers nodding their heads, professing they’re doing just that. I like the spirit of this paper, but can hold it up as an example of how Learning and Development teams and their organizations have not yet hit the level of exasperation that jars them into considering new possibilities.

Handcock and Harris very effectively set up the context for change, but their proposals don’t address transactional costs, which will have proponents screaming, “It sounds good in theory but it’s not practical”. To effectively coach a large network, for example, organizations distribute the load, making it everyone’s responsibility. Centralizing , on the other hand, often results in rigidity and organizations will ultimately return to decentralized models in pursuit of agility. We’ve seen the story played out time-and-time-again and we go on inheriting more and forever shifting responsibilities.

“One thin mint?”

“I’m stuffed.”

And for those who have seen Monty Python’s Meaning of Life, you’ll recognize the paraphrase. We know the ending of that scene, don’t we. For those that haven’t seen it, watch it.

We can avoid such a dramatic conclusion if we are willing to re-imagine what learning could look like for organizations. Our solutions need to take heed of obvious signs that organizations don’t want to be taught, but want to learn; don’t want to be managed, but want better situational awareness; don’t want more, but want to do more of the right stuff. Yes, Learning and Development professionals have a role to play, but it won’t be the role they play today. They won’t be engineering experiences or managing processes, but rather they will be engineering the network itself so that it can function without them.

What we need is a quest for a “Holy Grail”, to loosely make another Monty Python reference, that guides our direction forward. I suggest we start to think about how we can create autonomous networks that learn on their own. As a member of that network, I should be able to learn what I need, when I need it without a Learning and Development team. Every step we take forward should be in that direction.

Dynamic Leadership - New Leadership Development for Collaborative Organizations

A recent report by the Conference Board of Canada, A Snapshot of Leadership Practices in Canada, confirms that leadership development is among the top priorities of Canadian companies; however, leadership investment wanes during economic downturns. The same report also suggests that the main strategies companies use to develop leaders often focuses on internal leadership programs and 360 degree feedback assessments, which are less effective than stretch assignments, job rotations and real-time coaching. Perhaps, what this suggests is that companies are not as committed to developing leaders as they may profess to be, either deprioritizing investment at times when it is most critical, or investing in leadership development solutions that are easier to manage instead of those that are more effective.

What struck me most, however, as I reviewed the Conference Board of Canada's report was the focus on individual leader development. While the discussion solely remains on how to develop individuals, we are missing the proverbial forest-from-the-trees. In today's global, virtually-connected, hyper-communicative, technology-based environment, our discussion needs to consider not only the individual within the system but the system itself. To put it simply, we need to ask "how can we enable the system to demonstrate market leadership". With this question, we are forced to shift our thinking away from an autocratic, scientific-management, leadership model to one of coordinated decision making across a community.

The fact that companies today have yet to explore shared leadership models and complex adaptive leadership strategies suggests that most organizations are not expanding their leadership perspective to account for new capabilities. We can easily point to financial markets, democratic governments, open-source movement, open-government, predictive markets and crowd-sourcing as inspiration. I am not suggesting we abandon our current leadership development practices in favour for more pioneering approaches, rather I think the time has come for strategic experimentation to ensure that companies exploit collaboration and maximize everyone's leadership contribution.

Creative Thinkers Undervalued by Executives

In the Preliminary Survey Report: The Skill Needs of Major Canadian Employers issued by the Canadian Council of Chief Executives, Canadian employers rank creative thinking amongst least important skills for entry level employees. At a time of exponential change and when barriers to global competition across established industries and product offering are diminishing, an organization's capability to innovate is critical. John Hagel's blog "The Big Shift in Business Strategy"  calls for businesses to strategically position themselves as central nodes within industry networks to intercept multiple information points. Companies privy to a broader breadth of information points early in their gestation are uniquely positioned to identify trends and possibilities before their competitors and influence downstream recipients to shape outcomes to their benefit. Who better to draw connections between disparate points of information than creative thinkers. Perhaps then Canadian executives should rethink creative thinking. If they don't, they risk building stagnant organizations that operate well, but which risk being left behind as new innovations transform their industry.

Many, I suspect will argue that creativity can be developed later; it's more important entrants come equipped to work effectively with people, follow process and be able to apply analytical reason to immediate problems. The unromantic in me interprets that as people who can smile and put things in boxes. What Canadian companies need is individuals who can expand those boxes, maybe transform them into something else.

To illustrate the point, consider a recent conversation I had with a fellow management consultant. I presented my views of the future of learning. "Technology", I told him, "will monitor every digital transaction you make, interpret its meaning and identify your level of competency by cross comparing it with every other related digital artifact". I continued, "...the system will know you better than anyone else by tracking you over time and when you step beyond your capabilities it will support you like a personal assistant until you develop the required proficiency."

"I'm not sure I like the idea of being so accurately assessed," he responded. "...and if cognitive tools can be used to overcome knowledge gaps, then what will my value proposition be?"

My colleague's concern is grounded in today's knowledge market in which we sell information and experience. We are valued for what we know and not for our future knowledge potential . A new reality, however, is on the precipitous of unfolding. In the not so distant future cognitive tools will enable everyone to know. People will no longer be valued for what they know, but rather they will be valued for what they can learn and learning will be defined as knowing something before everyone else. Once it is learned it quickly becomes collective knowledge and you must quickly learn something new to remain relevant. Creative thinkers will likely generate new knowledge faster than everyone else because they will connect what for many seem to be irrelevant points of data.

Tin Can: Potential to Transform Learning Services and Programs

On April 27, Tin Can API 1.0 (the Experience API), was released and learning product vendors are quickly adopting the standard which will certainly succeed SCORM. So what is Tin Can and why does its quite emergence signal the beginning of a transformational change for learning services and programs?

Unlike SCORM, Tin Can is able to record user transactions in content outside of courses and extends reporting variables beyond the limited set of SCORM variables. For the first time, instructional designers can track learner actions across vast information landscapes that will inform design. Organizations will now be able to peek over the shoulder of their members as they roam distributed knowledge environments that include web pages, apps, online videos and so on.
 
“More data, so what,” you may ask. By the rumblings of learning professionals who attended the ASTD International Conference last year, I’d say that you’re not alone. So let me connect a few points and I hope that you’ll agree that “Wow” is more in order. First, however, let me share some basics about Tin Can that will help set the stage.
 

What is Tin Can?

Tin Can is a protocol that captures someone’s identity, the action that they’ve performed and the object on which the action occurred. A statement such as “John Smith opened Article X is a simple example. I could have just as easily decided to capture how long John spent on a page or whether John added a comment and if so what comment did he make.

The Tin Can statement is generated by the application in which the transaction occurs and is passed to a learning records store (LRS) which resides independently on some server. Here, once again, Tin Can differentiates itself from SCORM, by allowing statements to be generated and stored on devices that do not have an active browser session and then submits such statements to an LRS when an Internet connection is reestablished.

Having applications generate statements instead of courses is a significant advancement, however, it still presents a serious constraint. This approach limits the applications from which statements can be collected. At present, learning organizations will likely be confined to collecting information from their internal knowledge platforms and tools that are both Tin Can compliant and accessible to them so that they can tailor statement generation as required. This constraint left me wondering what we could do if instead we had a way of deploying a persistent Tin Can statement engine that was attached to a user instead of an application.


The beginning of the end of formal accreditation

Okay here’s where the fun begins. First, let’s imagine that we create a Tin Can app. Users can download the app from a service provider such as Google Play, which in turn ensures that all of their registered devices also have the app. This app runs in the background capturing all digital transactions such as websites visited, email exchanges, blog posts, even phone calls. Upon upload to the LRS, an ID validation service such as VeriSign or Microsoft confirms that it’s their transactions and then updates their experience profiles. As such, we’ve now moved Tin Can statement generation to an individual and as Orwellian as this may first appear, I believe that we will take steps in this direction as surely as people are willing to capture their relationships on public platforms, such as Facebook or LinkedIn

 At this point we can do a few interesting things, such as automate transaction-centred award systems to provide behavioral credentials. The emergence of this capability can already be seen in enterprise knowledge portals and applications like Kobo that award users with merit badges for posting content or reading. The difference with our scenario is that it spans information sources and aggregates transactions across a population so that comparisons can be made. We will have a quantitative way to compare members of a community to determine what types of behaviors produce specific outcomes. Yes, interesting, but not yet transformational.

Real transformation starts when we start applying semantic technology to qualify the value of the transactions being captured. Semantic technology allows technology to understand the meaning of digital content. It will allow a system to scrub your posts, emails, calls and even evaluate the knowledge capital of your social networks to not only count the number of times you do something, but to understand whether what you did demonstrated a novice level of understanding or whether you are demonstrating pioneering thinking. A natural language processing and learning machine, IBM’s Watson, has already demonstrated that it is possible for technology to read through and understand volumes of free text. Watson, who displaced Jeopardy! Champion Ken Jennings, in 2011, is now being deployed for business application, including assessing health insurance claims. Such technology platforms will increasingly be able to posture a question, examine arguments and counter arguments, and position an answer. Asking a computer to assess whether or not someone is a smart as Albert Einstein now seems plausible. If a computer can do that, then a computer can just as easily rank expertise and assign the appropriate credentials. At last, informal learning can be formally recognized.

So the question, I’m left with and the one that I will leave you with is this: How will this affect academic and professional institutes as well as corporate training departments? Could it be that in their current form they will become obsolete?

Massive Open Online Courses: Emerging Business Opportunities

With today's student debt exceeding US$ 1 trillion in the US alone, only 10%-20% of graduates in developing countries considered employable by international standards and increasing pressures for older workers to remain employable longer, the World Economic Forum (WEF) calls for an educational reform. In its report, Education and Skills 2.0: New Targets and Innovative Approaches, the WEF points out that Massive Open Online Courses (MOOCs), which hold promise of increasing access to education, has as of yet failed to provide a comparable alternative to pay-for-credit education. MOOC courses tend to focus on lecture and material reference and lack the type of interactivity and assessment offered by traditional education. The same report, however, identifies the opportunities that is presented by MOOCs to academic institutions that seek new revenue sources. For example, online learning programs which can be moderately priced and offered to significantly larger prospective client-base, as well as credit transfer processing fees to allow students who take online courses from MOOC offerings and who wish to apply the course to an accredited program. Still, however, significant obstacles stand before MOOCs; namely costly investments required to provide rich learning experiences and the reluctance to recognize online learning within the educational industry.

With the advancement of natural language process technologies, machine learning and analytics it is possible to overcome such barriers to redefine educational models and open up new business opportunities within and outside of traditional learning institutions. In fact, businesses will likely be the champion of new approaches given the increased global competition for talent, their capacity to inject investment into MOOCs and the potential return that MOOCs present. Through Co-ops, joint training programs and research partnerships, businesses have demonstrated a willingness to partner with academia. However, MOOCs are not partnerships but distinct businesses that in addition to securing talent can help organizations claim training investments against capital assets, elevate revenue and improve cash flow. At the same time, new revenue sources will arise for academic institutes that position themselves as governing bodies in a new educational network to provide program accreditation, administration and record keeping, course development and facilitation services. Further, learning will become increasing accessible through virtual learning solutions and learners will be presented with new options to finance their learning (e.g., professional membership fees).

The natural evolution of today's educational system under current economic pressures and advancements in technology will result in businesses offering accredited programs. Companies will make the investment to build MOOCs on advanced network technologies to reduce transactional cost and scale quality education to the masses. These programs will be just what business ordered and will remain connected to existing eductational standards by placing educational institutes at the governance helm. Students, whether in developed or developing countries, whether entering the workforce, in the workforce or transitioning from one workforce to another, will no longer have to pay tuition up-front, but instead companies can offer a pay-it-upon industry entry or secure ongoing membership dues to retain degrees. The logistics of administering such a payment plan may have been unthinkable prior to advanced networks, but today it's completely possible.

Perhaps the biggest obstacle is breaking free from conventional thinking and beginning serious discussion regarding what educational reform looks like. Companies that can invest in infrastructure to help MOOCs realize their potential are perhaps the best positioned to take the lead in an industry that is larger than all other information industries combined, $7 trillion in the US alone.

For more information on the state of global education please see http://www.weforum.org/reports/education-and-skills-20-new-targets-and-innovative-approaches