As a US taxpayer, Information Technology professional, and one who feels that healthcare spending is waaaay too high and increasing too rapidly, I have high hopes for the latest push on healthcare IT.  High hopes, but, frankly, tempered expectations!

Process Literacy and Automation

Marketplace business competition is a wonderful thing.  It forces operational excellence – to beat your competitors, you have to have the highest quality, lowest cost ways of providing your product or service.  This competitive pressure has led companies, industry by industry, to reengineer their business processes.  Manufacturing, discount retail, high technology, financial services – all stepped up to the reengineering challenge over the last 10 to 15 years.  In some cases, it was a strategic preemptive strike designed for a major competitive advantage – think WalMart and its supply chain initiative, or Federal Express and its reinvention of overnight package delivery.  In other cases, it was a response to someone else’s first move – think the US auto industry response to Japan, Inc. in general, and Toyota in particular (In retrospect, too little, too late?)

The point is that throughout industry and commerce, across the globe, competition has forced process discipline.  It was not just that these companies reengineered their major business processes – they also institutionalized “process thinking.”  They manage their work through end-to-end processes (e.g., order-to-cash, procure-to-pay, hire-to-retire, supply chain), and have a culture of continuous process improvement.  They are lean, cost-effective and agile – these were perhaps the most valuable legacies of the reengineering movement.  They busted silos (see my recent post on Bustin’ Silos With The Role Bomb!), established metrics that drive improvement, flattened their organizations, and engaged their entire workforce (and suppliers and customers) in the relentless push for continuous process  improvement.

Many Healthcare Institutions Lack Process Discipline

And there’s the rub!  While industry and commerce have either jumped into process management, or been dragged into it by their competition, most healthcare institutions have not traditionally focused on end-to-end process management.  Within silos, you will often find good processes, and, to be clear, most institutions are staffed by highly trained and dedicated professionals who do an excellent job providing healthcare.  However, they have not had to tackle the kind of cross-functional reengineering that competitive industries have been dealing with for a decade or more, and that are necessary for deploying and gaining benefits from Electronic Health Records.

And yet, with Electronic Health Records and the US government’s $17 billion stimulus package for doctors and hospitals that adopt EHRs, processes will have to be reengineered (and then continuously improved).  And this has to be done against a highly accelerated timeframe.  And that’s what worries me the most.

How Long Does it Take to Master Process Discipline?

From my experience and based on many enterprise system research projects I’ve been part of, most enterprise reengineering efforts take about 3 years of “heavy lifting” and about another 2 years to “settle down” and really start to deliver their benefits.  Many health care institutions are on a much faster fuse than that – I hope they make it!

Is There a Fast Path to Healthcare IT?

In industry, some viable alternatives to wholesale process reengineering and ERP deployments surfaced about half-way through the primary reengineering era (say 1990 to 2005).  These included business process outsourcing.  Companies from American Express to BP outsourced their “back office” processes.  And it was not just back-office processes that were outsourced.  Companies such as Solectron (now part of Flextronics) and Flextronics took over electonic design, manufacturing and logistics services from many household names in electronics, freeing them to focus on sales and marketing.

Perhaps we will see similar moves in the heathcare industry.  In fact, earlier this year I posted on The Wal-Martification of Healthcare IT and one particular initiative targeted at small physician groups.  This may just be the beginning of a major restructuring of the healthcare industry.

While generally a believer in how collaboration can lead to better insights and greater efficiency, I continually see examples of where it is neither effective, nor terribly efficient – and in the worst cases totally counter-productive. I work in a highly collaborative environment and study many others, and my experiences have led me to two areas where problems typically emerge:

1. At an individual level people suffer from cognitive overload. As people get busy and collaborate across a multitude of projects, the brain gets distracted, and the quality of the output suffers. In short, one person can only do so much.
2. At a project level where you run into a situation of ‘too many cooks spoiling the broth.’ In short, only so many people can do one thing.

If you put the two of these together, the worst-case scenario is that in an individual could join a project as the Nth person who ‘spoils the broth,’ while the time they dedicate towards doing so distracts them from their other work – which, continuing the cooking metaphor, leads them to burn the toast as well.

The problem is, it’s very difficult to apply a scientific approach to measure exactly how many people per project, and conversely how many projects per person is optimal. The most well-known study around this is Dunbar’s Number, which sets “a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships” at 150. In terms of collaborative overhead, Dunbar speculates that “as much as 42% of the group’s time would have to be devoted to social grooming.” Now that might be acceptable for the hunter-gatherer societies described in Dunbar’s anthropological study, but I would imagine this amount of “grooming” time would be extremely unproductive in an enterprise context.

In his book Collaboration, released this month, Morten Hansen, a professor at the University of California, Berkeley and INSEAD, identifies two costs related to enterprise collaboration. The first is the opportunity cost collaborating (i.e. the opportunities individuals could have been pursuing had they not been collaborating), the second is the cost associated with fostering co-operation. In both cases, as the number of projects or the number of individuals grow, so too does the potential for diminishing returns.

At the project level, I feel as though most people have general understanding that there is a certain point at which there are simply too many stakeholders and collaboration breaks down.

However, at an individual level, I think we are less cognizant of – or less willing to admit – our own limitations. I’ve seen many cases where an enthusiastic and eager collaborator was clearly overburdened and well past the point of optimal effectiveness. Incidentally, my personal hypothesis is that this point of optimal effectiveness is a fairly small number of projects per person. My main “proof” for this is anecdotal, but I notice that the busier one is, the more likely they are to quickly skim a topic and provide feedback in short (sometimes valuable) chip-shots without contributing to a better in-depth understanding of the topic space. Worse, in some instances perceived value comes from dissenting, so instead of constructive feedback, you get wildly varying opinions with no one working towards a coherent solution.

On the subject of cognitive overload, a recent Deloitte report notes, “Even a Sunday newspaper contains more information than the average 17th century citizen encountered in a lifetime. Add to that the stress of decision-making amidst uncertainty, corporate change, and a tidal wave of tasks. Never before in history have workers been asked to absorb and make sense of so many data points.” One more sensational study even suggests that information overload is more damaging to the brain than smoking pot. I think we can certainly make an argument that where collaboration is most likely to break down is at the individual level.

This brings up another point: What about the virtues of solitude? Are we losing our capacity for individual decision-making? Moreover, who’s actually doing the deep thinking needed to solve complex problems? We talk about the multitasking Net Gen brain that is not actually doing multiple things at once, but rather switching more efficiently. Does constant switching allow for deep analytic thought?

So what is the solution? Overall, I’m wondering if there’s a Dunbar Number for the optimal number of simultaneous projects per person (small and large). How is this number affected when you take into account broader ecosystem participation and places where quick feedback from multiple participants is actually desired over in-depth participation?

As a start, I think collaborative technologies can help by streamlining different types of feedback. So, for example, a project can have 1,000 collaborators if they are providing feedback via a prediction market. Conversely, if only three people are collaborating on a document, perhaps a wiki is most effective.

One possible model for managing cognitive overload is letting individuals self govern – i.e. everyone decide where they can add the most value. Of course, this also raises many issues, including: people, especially in high-performance cultures, tend to overextend themselves; people tend to pick project that interest them, but that may not add the most value to the organization; and people tend to be social and so will gravitate towards the same projects, thus contributing to project inefficiency.

In order for this to work, you would have to architect a system that would allow people to allocate their own time in a structured way (similar to the Freiburg budget example). I’m envisioning a system where resources are finite but can dynamically allocated; where employees are guided by decisioning logic that identifies the projects that provide the most value to the organization; and where limits are set that prevent projects from being staffed by too many people and that stop people from taking on too many projects.

An increasing percent of the work done today depends, as Blanche Dubois might have said, on the kindness of strangers. Your success as a leader hinges on your ability to entice people - many of whom you may never even meet - to want to go the extra mile for your business.

Discretionary effort is the life blood of today's economy.

As we move to business models that depend on people working together, on innovation, on individual expertise and craft, on crowds contributing to the whole, we must also move sharply away from our traditional concepts regarding the key responsibilities of senior executives.

I've had the opportunity to conduct a lot of research over many years on how and why people collaborate and innovative; through it all, one conclusion stands clear: you can't make anyone do these things. There is no correlation between traditional "push" management approaches - directives, power-based approaches, or even compensation and performance management, and people's willingness to be a little more creative, more enthusiastic or service oriented with customers, to ponder the challenges they face with greater focus and energy, to be more emotionally contagious and proud.

Today, encouraging a greater number of people to go just a little bit further is the essential job of leaders. Long gone is the time when our primary management challenge was to insure that workers performed tasks consistently and reliably, using standardized best practices. Now we need "pull" approaches, geared to encourage individuals to share their ideas more widely and constructively, to push the boundaries of what's possible further - to be more collaborative and innovative.

Statistics tell a striking story. The number of total goods producing jobs - manufacturing, construction, extraction - has declined sharply in the U.S. economy, from 36% of all jobs fifty years ago to 15% today. In the service sector, the most rapid job growth has occurred in those areas demanding high levels of expertise or knowledge. Education and health-related jobs have gone from 5% of the U.S. economy in 1959 to 14% today. Professional and business services, from 7% to 13%.

While any work can benefit from the extra push of discretionary effort, consider the contrasting characteristics that add to the shifting management challenge: most manufacturing jobs need everyone to be in the same place at the same time; in-process activities can be easily inspected by a supervisor. Knowledge-based work can often be done virtually and asynchronously, making it difficult to judge an individual's performance based on observation of the approach. Quality is often assessed only after completion, based on the product produced. While the work is in process, we count on the individual to give it their very best.

Consider your leadership approach against this changing template. Is your style likely to engage the "kindness of strangers?" What would you imagine a leader who was able to entice others to contribute greater levels of discretionary effort would do or be like?

Here are three characteristics that I'd put at the top of my list:

• Interesting and intriguing - able to capture people's imagination and create excitement about the task


• Tolerant of ambiguity - open to considering a wide range of possible ideas and respectful of divergent points of view


• Authentic - offering a consistent "deal" and delivering on commitments reliably

What would you add? What characteristics of a leader have prompted you to go that extra mile?

Citizens of Holyoke, Mass., had reason to celebrate this week as the governor of Massachusetts and other dignitaries--including Cisco CEO John Chambers, EMC CEO Joe Tucci, and the presidents of Boston University, MIT, and the University of Massachusetts--announced plans to build a $100 million data center in their town. It's an ambitious proposal, but is it necessary?

With the singularity ever-present around the next corner (or two) it’s easy to fixate on the futuristic present — and near-future — and forget about how we got to where we are. For most of History, if you wanted to send a message to someone, that message needed a person to deliver it. Later, human couriers were replaced by carrier pigeons (though packet loss was very annoying), then later by pneumatic tubes, telephones, and finally the Internet.

The move from people to pigeons as carriers was important in that all the sudden there was a task performed over a distance that could now be automated. Nowadays, instantly sending a message to someone on the other side of the world is trivial — but that doesn’t mean that modern technology has yet been exhaustively used to solve older problems.

There’s plenty of old technology that still works — works well enough in fact that no one has bothered to replace it with a better, more efficient alternative. Here are a small list of examples:

• The Steam Engine. A.K.A. nuclear power. It’s pretty much the same principle, just instead of burning coal or wood to boil water and use the steam to move turbines, it’s nuclear fission. We’ve supplemented an old technology with new components, but the base principle hasn’t changed in 300 years.
• Physics. More accurately, Newtonian Physics. It’s easy to forget that just as things like steam engines and the internet are tools, so are ideas like laws of Physics. The set of tools for modeling the Physical world that Newton and his contemporaries invented were, and are, extremely useful and accurate. They’re also inaccurate and have been superceded by ones that take into account a larger picture of the universe.
• Government. The oldest governments of today were built for a different world, structured to address different issues, for people with different priorities. The election of representatives worked well for people whose lives were spent largely on farms and in factories, unable to travel the distances required to participate in the democratic process. The stability that has made governments reliable in the long run also makes them resistant to change, after all, you go with what you know. Governments are, to their credit, now adapting to involve citizens in the process of running their country, but it’s necessarily a slow going process as this new technology is tested and accepted.

In the business space, the drive of competition should drive the constant reevaluation of all technological assumptions in favor of more efficient alternatives. But the same might not be true in other areas of society.

In the three examples above, all three work well in their native context, especially Newtonian Physics. If you’re calculating how long it takes to fly between Toronto and New York, you don’t need to take into account relativity, so there’s an argument that, in that context, the older tool is just fine. This leads us to the question: should we be aggressively looking for ways to apply new technology to everything in our world, constantly re-evaluating old problems with modern eyes and modern problem solving skills? Or were some problems solved wel-enough the first time, and we should focus our attention on other areas?

Similarly, when you look at your day to day life, how many of the tools and technologies that you use everydayseem like little more than sleeker versions of Historic designs — what items are missing from my list?

I still keep in touch with a handful of teachers from high school. One of those teachers, Mike Perosevic, taught me grade 11 economics and always seemed to push the envelope when it came to innovative teaching methods. Integrating SMART boards, classroom wikis and discussion-based lessons, Mike challenged his students (and still does) to take initiative, collaborate with others and develop a real love of learning. I have been a technology lover since my dad brought home our family’s first Apple II computer, but Mr. P played a big role in my appreciation for technology and collaboration.

Don’s post yesterday, “Will universities stay relevant?”, sparked some interesting discussion around the idea that our education system is in crisis. Given Mike’s innovative perspective on teaching, I sent him the article and asked for his feedback. To be clear, Don addressed the university system and Mike’s perspective comes from teaching high school, but I still thought it would be interesting to hear what his experience has been like in the classroom.

With his permission, I’ve posted some of his email response here, which he also published on his blog “Teaching, Technology & More“:

“You must understand that students like yourself are not the norm in terms of being in touch with the digital world and having the passion to use the tools available to them in the pursuit of knowledge.  Most of these students head off to university (and our new inflated grading system is making it easier) with little self-initiative and passion for learning.  I have been using technology in the classroom for 3 years now but I still fall back to the lecture style often because most of my students are not mature enough to embrace student-directed project based learning.

That being said, the first two years of university (as I recall them) are designed to “weed out” those who really do not belong, so to speak.  Although most of my professors in the 80’s and early 90’s used the lecture style, their classrooms became more open to critical thought and discussion after second year.  From what I am told, this is still the case.

Right now, I have reached a point in my classroom where I cannot proceed any further with student-driven methods due to lack of technology and support.  We do not have the bandwidth nor the requisite hardware in place to allow students to develop their critical thinking skills using web based applications.

I sympathize with the universities somewhat.  Many of these professors grew up without technology and are now being pushed to adopt it.  The process will take time and embracing a digital pedagogy does not ensure critical thinking skills will be developed.  The passion for learning must come from the students and that passion is something that transcends generations.

What I mean to say is students, like yourself, who have a passion for learning always embrace the latest technology the world has to offer to enhance their critical thinking skills and understanding of concepts.  The fact that you are using Twitter, etc. to accomplish this is no different than a student in the early 1980’s using one of the first computers to be more productive or a student in the 1950’s using a slide rule to do the same.

We need to work on fueling the passion for learning if we want to produce a generation of critical thinkers.  I try to use technology to inspire students to become passionate about knowledge.  The technology on its own is merely a conduit to critical thinking.  The passion for learning must come from within.”

I’ve been posting on and off about Cloud Computing since I began this blog a couple of years ago.  But, as one who spends most of his time with IT leaders of large global enterprises, sometimes the promise of the Cloud seems more like a mirage!

I’ve Looked At Clouds From Both Sides Now

Back in August 2008, not being able to resist the title to the wonderful Joni Mitchell and her reference to “cloud illusions I recall”, I posted on the denial I was witnessing among my client base.   I likened it to the denial that was common among CIO’s back in the early 1980’s.  To quote from that post:

(CIO’s) were mostly in denial, even as executive offices just down the corridor from the CIO’s office were beginning to become home to a variety of rogue PC’s – machines such as Apple II’s and Radio Shack TRS 80’s.

Fast forward 25 years or so. Now the press is full of predictions and prognostications about Cloud Computing, several key players are investing heavily in this space (pun intended) but many CIO’s and CTO’s either just don’t believe it, see it as warmed over service bureau computing from the 60’s and 70’s, or believe it’s the greatest threat to enterprise computing sanity since computer viruses first appeared.

Now, nearly 1 year later, I’m still seeing the same denial – Cloud Computing, for the most part, is on the back burner – a technology to watch!  Clearly, there are significant risks with the untried, standards are still evolving, and there’s something intimidating about such a simple concept being able to replace so much enterprise technology and expertise – the “heart and soul” of the typical IT organization.  In fact, for many IT shops, this “heart and soul” is where they’ve invested many of their improvement efforts over the last few years, implementing ITIL and process improvement approaches.  That’s been a hard-won fight, and CIO’s are loathe to admit that there might now be an easier and better way!

In another post earlier this year on The Dangers of Cloudy Thinking, I wrote:

I’m fascinated and bemused by this Cloud Computing phenomenon. Never before have I had such a strong feeling that something really, really important is happening – a fundamental discontinuity, if you will, in the way we leverage IT – and yet most of my clients and those I am interacting with in a couple of multi-company research projects are essentially standing on the sidelines.

Hincliffe’s “8 Ways That Cloud Computing Will Change Business”

Dion hits the nail on the head once more with his excellent June 5 post in which He says:

(Cloud computing offers) benefits that can potentially change the game for many firms that are willing to be very proactive in managing potential downside. These include access to completely different levels of scale and economics… Easier change management of infrastructure including maintenance and upgrades (cloud vendors extensively virtualize and commoditize the underlying components to make them non-disruptive to replace and improve) … Cloud computing also offers an onramp to new computing advances such as non-relational databases, new languages, and frameworks that are designed to encourage scalability and take advantage of new innovations such as modern Web identity, open supply chains, and other advances.

He goes on to show the major pros and cons, and then to cite 8 compelling ways that cloud computing can change business.

Cloud Computing – Ideal for the “Edgy” Opportunities?

Dion refers to the use of cloud computing beyond “edge†computing (which he describes as minor applications and non-critical business systems).  This is the only place where I take issue – I think “edge” computing is where the exciting action is, where the high value and innovative opportunities lie.

Back in July 2008, I posted on “Edginess and Innovation.”  In that post, I differentiated between “core” and “edge”:

Many IT leaders when talking about the “core†are referring to the “legacy†systems…  built over the years and have to maintain.  But in reality, the core goes much deeper than the systems and technologies. Business processes – especially when you include the unautomated practices and workflows that interact with the automated ones, are hard to change. The mindsets that dominate “core†thinking and “edge†thinking are radically different. I’ve noted before that quality guru Joseph Juran distinguished between “preventing bad change†(keeping processes under statistical control†and “creating good change†(innovating processes and products, or creating “breakthrough†performance as Juran put it) and the different management approaches and structures each requires. Most IT leaders have focused for years on management approaches more consistent with preventing bad change than creating good change. This has created a mindset that abhors risk taking.

I believe most of the “core” opportunities have been addressed in the typical global enterprise.  Sure, there’s always more to do (and the trap of saying “yes” to all the business requests to continually tweak and bolt onto core systems) but I believe you can move the business value needle significantly to the right by tackling more of the “edge” opportunities, and that is where, to Dion’s point, the Cloud (and its related technologies) offers real promise – now!

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After I wrote about SAP’s new SaaS strategy Wednesday, several SAP competitors sent emails slamming the strategy. Not an unusual response from competitors, right? But I did accept the offer to talk to Lars Dalgaard, CEO of SuccessFactors, which just landed a massive deal for 420,000 seats of its talent-management SaaS with longtime SAP partner Siemens AG. This conversation, I thought, might be interesting.

Last week I wrote a substantial essay for the Edge arguing that the universities are entering a period of crisis.

I argued that is a widening gap between the model of learning offered by many big universities and the natural way that young people who have grown up digital best learn. The reaction on Twitter, mainly from students has been enormously positive. So far two academics have written critiques of my views at the Edge.

However because the Edge does not enable readers to comment, I’d like to know what you think. Please read a summary below and then check out the Edge article and let the world know what you think here on Wikinomics.com.

The old-style lecture, with the professor standing at the podium in front of a large group of students, is still common. It’s part of a model that is teacher-focused, one-way, one-size-fits-all and the student is isolated in the learning process. Yet the students, who have grown up in an interactive digital world, learn differently. Schooled on Google and Wikipedia, they want to inquire, not rely on the professor for a detailed roadmap. They want an animated conversation, not a lecture. They want an interactive education.

Students are making new demands of universities, and if the universities are to remain relevant, they will have to change.

Professors will have to abandon the traditional lecture, and start listening and conversing with the students — shifting from a broadcast style and adopting an interactive one. They should be encouraging students to discover for themselves, and learn a process of discovery and critical thinking instead of just memorizing the professor’s store of information. They need to encourage students to collaborate among themselves and with others outside the university. Finally, they need to tailor the style of education to their students’ individual learning styles.

Some leading educators are calling for this kind of massive change; one of these is Richard Sweeney, university librarian at the New Jersey Institute of Technology. He says students are smart but impatient. They like to collaborate and they reject one-way lectures. While some educators view this as pandering to a generation, Sweeney is firm: “They want to learn, but they want to learn only from what they have to learn, and they want to learn it in a style that is best for them.”

This is not fundamentally about technology per se. Rather it represents a change in the relationship between students and teachers in the learning process.

In the old model, teachers taught and students were expected to absorb vast quantities of content. Education was about absorbing content and being able to recall it on exams. You graduated and you were set for life - just “keeping” up in your chosen field. Today when you graduate you’re set for say, 15 minutes. If you took a technical course half of what you learned in the first year may be obsolete by the 4th year. What counts is your capacity to learn lifelong, to think, research, find information, analyze, synthesize, contextualize, critically evaluate it; to apply research to solving problems; to collaborate and communicate.
This challenge to the existing order raises a deeper issue — the purpose of the university

“The time has come for some far reaching changes to the university, our model of pedagogy, how we operate, and our relationship to the rest of the world,” says Luis M. Proenza, president of the University of Akron.

He asks a provocative question: Why should a university student be restricted to learning from the professors at the university he or she is attending? True, students can obviously learn from intellectuals around the world through books, or via the Internet. Yet in a digital world, why shouldn’t a student be able to take a course from a professor at another university?

Proenza thinks universities should use the Internet to create a global centre of excellence. In other words, choose the best courses you have and link them with the best at a handful of universities around the world to create an unquestionably best-in-class program for students. Students would get to learn from the world’s greatest minds in their area of interest - either in the physical classroom, or online. This global academy would be also be open to anyone online. This is a beautiful example of the collaboration I described in the book I co-authored, Wikinomics.

The digital world, which has trained young minds to inquire and collaborate, is challenging not only the lecture-driven teaching traditions of the university, but also the very notion of a walled-in institution that excludes large numbers of people. Why not allow a brilliant grade 9 student to take first-year math, without abandoning the social life of his high school? Why not deploy the interactive power of the internet to transform the university into a place of life-long learning?

Share your thoughts here.

SaaS startup Paglo has added monitoring for Amazon's cloud to its IT search and management service.

Although there are many opinions on the role of government in society most would agree that governments can play a leading role in tackling the environmental crisis. Governments in essence provide the rules and incentives that govern many aspects of how our society operates. They also have the power to tax and spend public funds to further policy goals such as the lowering of carbon emissions. Combined with emerging communications technologies, such as Web 2.0, governments now have the tools to meet policy goals by building platforms for innovation and collaboration. These tools can be used to improve policy, drive consensus and unleash creativity in the private and civic sectors. The five specific areas of opportunity include:

• Collaboration with citizens to change behavior or inform policy through an efficient flow of information. This can range from information on municipal recycling programs to citizen reporting of industrial pollution.

• Building platforms to integrate not for profit organizations with government provided services and initiatives. For example a government grant to clean up a ravine could galvanize local conservation organizations to help.

• Building of markets or platforms to spur innovation or adoption of greener alternatives in the private sector. This can be done through tax breaks such as ones encouraging home retrofitting or through spending on programs such as feed in tariffs.

• Collaboration with government employees to green the public sector by harnessing their knowledge and sharing best practices. For instance a waste reduction innovation in one department should be instantly applied across the entire government and beyond.

• Collaboration with other governments around policy. This includes sharing knowledge and experience on the effectiveness of various programs.