Culture

A thought hit me the other day which I will briefly share with you in this post.  Read through today’s popular management journals and magazines and you’ll find numerous references to culture and its unique ability to influence quality of work and organizational performance.  Take for instance  Clayton Christensen’s brilliant portrayal in the widely popular article “How will you measure your life?“:

 “Culture, in compelling but unspoken ways, dictates the proven, acceptable methods by which members of the group address recurrent problems. And culture defines the priority given to different types of problems.   It can be a powerful management tool.​”

What hasn’t been clear, at least to me, are the characteristics of culture in achieving this influence.

If you agree with Clayton –  that culture is a mechanism by which individuals prioritize and select ways to tackle recurring problems, then consider that this mechanism is inherently instinctive, not unlike the seemingly innate behaviors that characterize an individual’s unique talents.   So while culture and talent are conceptually different (e.g. the former underpinned by values, the latter by genetics), they both appear to promote instinctive and recurrent behaviors.  It is these same behaviors that can have a huge influence (i.e. positive or negative) on quality and performance.[1]

*** Notes ***

[1] In their book, First Break All the Rules, Marcus Buckingham and Curt Coffman suggest that a focus on talent offers the advantages of a strengths-based hiring approach.  One of these advantages is employee engagement, and as Tom Rath, Author of StrengthsFinder 2.0, points out, “People who have the opportunity to focus on their strengths every day are six times as likely to be engaged in their jobs and more than three times as likely to report having and excellent quality life in general”.

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Quality

Some food for thought on product or service quality.  Deming defined it in relation to the value offered to the customer. Drucker had a similar customer-centric view when he said  “Quality is not what the supplier put in, but what the customer gets out and is willing to pay for”.  (Note: Deming did define a manufacturing centric view of quality in his effort divided by cost equation.)

Moving past traditional management science circles, I like Robert Pirsig’s philosophy on quality from his classic book, Zen and the Art of Motorcycle Maintenance.   Here, Pirsig presents quality not as a thing, but “as an event” – representing a path to discovery of the “right facts” between the creator and her creation.   When you apply his definition to knowledge work it begs the question – do we understand how quality is affected by the relationship between a worker and the tools and materials with which she works?  Consider the elevated joy and satisfaction an individual derives from programming in Ruby vs. Visual Basic, for example.  Returning to the definition proposed by both Deming and Drucker, it’s easy to imagine how Pirsig’s interpretation of quality is the event that leads to creation of customer value.

So there you have it, two perspectives on quality, one is customer centric, the other is manufacturing centric, both highly dependent on one another for the reasons Seth Godin presents in his quality of design vs. quality of manufacture post.

Can we therefore agree that in knowledge work, more important than our collective understanding of the characteristics that constitute ‘high-quality’ is the understanding of the subtle factors that allow these characteristics to emerge?

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Agile #scale

A few years ago I would have had difficulty mentioning failure and Agile software development in the same breadth. On the heals of the ever popular manifesto and effective practices such as XP and Scrum, Agile adoption grew, and the more it grew, the more software developers and managers felt empowered to beat the the long and dismal history of software failure.

Photo: Scott Olson/Getty Images

Now there’s increasing evidence to suggest that Agile software development and Agile management practices have finally earned the interest and attention of larger organizations,  the same organizations who usually find comfort hiring from a pool of 400,000 management professionals carrying the widely recognized PMP industry certification.  This certification, (known as the Project Management Professional), is a leading certification for project managers offered by the Project Management Institute (PMI).  The certification’s popularity makes the PMI very influential in establishing culture and practice of management within larger organizations.  The PMI has now turned their attention to Agile.

But in the spirit of Agile’s promotion of continuous feedback and adjustment, I’ve encountered quite a few challenges scaling agile in larger organizations.  Some of these challenges are structural, others cultural, and so it’s time for me to adjust my own tune on the realities that come from adopting Agile in such environments.

The following are four challenges confronting Agile practitioners in larger organizations:

  1. System of reporting” differs from the “System of production” – The corporate hierarchy (i.e. “system of reporting”) renders difficult the self-organization and a cross-functional focus required for successful Agile teams.
  2. Financial cycles differ from management cycles which differ from project cyclesExcellent article by Jim Highsmith on the temporal challenges an iterative approach brings when the organization thinks and acts on a quarterly and yearly basis.
  3. Definition of done –  Procurement, budgeting and yearly reviews all necessitate a formal understanding of when the project will finish. You may even reach consensus on a scope and date to appease management but your first release plan that extends past the terms of this definition may present problems.
  4. Rewarding individuals over teams – Yearly corporate performance review programs focus on the individual yet Agile makes no provisions for this kind of evaluation, in fact it can be detrimental (pdf) to the team’s trust and self-organization.

What challenges have you encountered scaling Agile in larger organizations? How are you overcoming them?

 

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“Slip the Jab”

Fan’s of Sylvester Stallone’s Rocky series may recognize the expression “Slip the Jab”.  During the fifth sequel, Stallone’s character, Rocky Balboa, returns to his Philadelphia origins, and location of the gym willed to his son by his late trainer Mickey Goldmill.  After entering the abandoned, dusty gym, Rocky is overcome with emotions as he flashes back to his gym training days with Mickey insisting “Slip the jab, Rock, slip the jab!”.

Rockey and Mickey in Rocky V

During this flashback, Mickey offers Rocky remarkably wise lessons on life.  These lessons carry with them a curious applicability to knowledge work,  which is the subject of this post.

1. “Slip the jab”

Mickey’s insistance that Rocky “slip the jab” refers to a common practice in boxing whereby a boxer learns avoid incoming punches, while also quickly regrouping in order to seize the vulnerability resulting from the missed punch.

A knowledge worker requires similar preemptive and reflexive abilities in order to look ahead, avoid oncoming industry, organizational, or career perils, while simultaneously positioning herself for success once the peril subsides.

“Slipping the jab” for a knowledge worker allows her to operate as the CEO of her professional life.  To do so effectively, she should borrow from leadership models such as Peter Drucker’s Effective Executive, or career management techniques such as Charles Handy’s Sigmoid Curve.

2. “Mesmerize”

“Mesmerize!  See that bum in front of you, see yourself do right and you do right”.  What a wise set of words from Mickey as he instructs Rocky to the benefits of looking ahead and envisioning the result during his shadow boxing session.

Effectiveness is wisdom, and wisdom requires prediction.  What better way for a knowledge worker to boost his effectiveness than to envision the scenarios that may unfold in his project, while also imagining the best possible ways he can respond.

An example of this predictive component can be found  in some software development practices.  Consider test-driven development, whereby a programmer “envisions” his future implementation by first establishing the boundaries for success.

3. “Motavisation”

“The fact that you’re here and doing as well as your doing gives me the, what do they call it  – motavisation – to continue on.” Here Mickey opens up with Rocky, revealing just how important his relationship with the promising young fighter truly is (while succumbing in his struggles to correctly pronounce the word).

Motivation has become a key lever in management’s quest to build  high-performance knowledge worker teams.   Daniel Pink’s Drive offers a simplistic but helpful understanding to the components of this Motivation, as does Fredrick Herzberg’s Two Factor Theory.

But the real essence of a knowledge worker’s Motivation is implied in Mickey’s words.  Think about it – Rocky’s career is doing well, Mickey is his trainer, and so he has every reason to believe he is being effective as a trainer.  Effectiveness brings motivation as is the case with Mickey.  A highly-motivated Mickey will only increase Rocky’s chance to be a successful boxer.

The same applies to knowledge work.  Staying motivated requires an individual increase the chances her efforts will lead to the desired effect.  Aligning work with strengths offers one such way for an individual, as does a strengths-based hiring approach for organizations.

4. “Nature’s smarter than people think”

“People die when they don’t want to live anymore, and nature is smarter than people think”.

Not only is nature smarter than people think, as Mickey suggests, but there’s a growing pervasiveness to incorporate the principles of Evolutionary theory and Complexity Science into management and engineering disciplines to prove it.  Just look at the recent successes of adaptive approaches to management and software development, for example.

5. “Outside the ring”

Later in Rocky’s flashback, Mickey is heard saying “When I leave you, you’ll not only know how to fight but you’ll know how to take care of yourself outside the ring”.

The idea of improving not just one aspect of an individual’s life, but larger aspects is not unlike principles we see in software development and/or manufacturing.  Consider, for example, the “See the whole” principle which is a cornerstone of Lean software development and Continuous improvement.   In order for Rocky to remain a champion fighter for a long time, Mickey realizes he’ll need to ensure Rocky’s success outside the ring as well.

This fits the continuous improvement mantra.  Sustaining and leveraging the improvements in knowledge worker processes requires improving their dependent aspects as well.

6. “Angel on your shoulders”

Finally, towards the end of Rocky’s flashback, Mickey is seen removing his most favorite possession, a cufflink given to him by Rocky Marciano.  He offers this as a gift to Rocky suggesting it will serve as “an angel on your shoulders”, while also suggesting when Rocky feels himself going down “the little angel will scream at you saying: get up you son of a bitch cause Mickey loves you”.

Whether we’re talking about mentors, coaches, retrospectives or daily stand up meetings, to name a few, the key point is to establish necessary feedback channels in order to help individuals and teams adjust early and often.

***

I hope you enjoyed this post.  For any questions or comments please email techdoer@gmail.com.

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How vs. Why

Here is an interesting parallel between the Data, Information, Knowledge, Wisdom pyramid and the knowledge worker roles and responsibilities defined by Peter Drucker.  Depending on what you read, there exists a tendency to refer to Knowledge as “doing things right”, which happens to fit Drucker’s classic definition of “efficiency”.  On the same token, there’s also a tendency to see Wisdom as “doing the right things”, which also neatly fits Drucker’s definition of “effectiveness”.


Data/Information/Knowledge/Wisdom
Figure 1: DIKW Pyramid

So from Drucker we know that management represents efficiency, leadership represents effectiveness, executives need to be leaders, and all knowledge workers need to think and act like executives.

This leaves us with a curious relationship between [Knowledge, Management, Efficiency]  vs. [Wisdom, Leadership, Effectiveness]. Description is at the heart of the former, which defined work in the 20th century.  Prediction, on the other hand, is at the heart of the latter, and it will define work in this 21st century.

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Best (mal)Practices?

What if I tried to sell you on the notion of “best practices” as just a bunch of superfluous hogwash?  You know, the kind of waste another best practice – Lean’s “Eliminate Waste” principle, attempts to eradicate.  I’d try hard to convince you of the uselessness of pair-programming, ineffectiveness of test-driven development, or the wastefulness of the more appropriately named Sick Sigma. “You’re just wasting time and money”, I would plead.

You might try to convince me otherwise by showing how it’s clearly possible for a best practice, like SWOT, in helping a naturally deliberate person find his new career path (read part 1 and part 2 first), or how there’s not a lack for imagination in applying Theory of Constraints to electronic trading.  Heck, you could even remind me of my own past success with Charles Handy’s Sigmoid Curve, or the undeniable boost in software quality brought by test-driven development.

Backpedaling, I would formulate my own rebuttal, including convincing and equally dizzying material from David Snowden on best practices in complex adaptive systems.  “Those examples worked because the system was ordered!”, I’d bark.

I had the pleasure of listening to David Snowden speak on the issue of effectiveness in Complex Adaptive Systems.   He suggests to lay off best practices, particularly in knowledge management when applied to complex domains.  To understand why, simply imagine what comes of trying ‘to fit the square peg to a round hole’.   A best practice represents a codification of knowledge, and “knowledge cannot be entirely codified”.  He instead advocates using approaches which promote the discovery of shared context:

“…shared context is vital to knowledge exchange, and such context always involves some human trusted validation.  This is not to say that codification of material in advance of need is not advantageous, but the effective reference is nearly always human.” – David Snowden

Returning to our discussion, the lightbulb finally goes off for the both of us.  “To boost effectiveness in complex domains, practices need to be adaptive and promote continuous feedback, the software industry must have known this all along when they moved away from predictive practices towards adaptive ones like Agile”, I conclude.  To which you respond,  “yes, but even David Snowden suggests there’s still plenty of value to glean from a best practice.”

***

Visit the newest version of Boost Practices – the strengths based knowledge worker practice tool: http://boostpractices.freebaseapps.com.

 

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Social Skills

LinkedIn recently introduced a “whole new way to understand the landscape of skills & expertise, who has them, and how it’s changing over time.”   So essentially they have created a social network around knowledge worker skills.  Although the site confuses skill with technology (e.g. Wii, Blackberry and iPod as skills?), it nonetheless represents an innovative step towards better understanding skills and their relationship to the larger topic of competence (i.e. talent, skill, knowledge).

With LinkedIn Skills, I can now see the who, what, where and when of a particular skill, which is inline with the people-oriented features we’ve come to expect from other social media technologies such as Twitter, Facebook and Foursquare.  With Skills, I can track the growth of a particular skill, determine which skills are on the up and up, and which should be dropped in favor of greener pastures.   As the idea matures, I’m sure we’ll see commercial opportunities such as: Click to …”Verify, Improve, or  Share” your skill, but the precedent has been set.  Skills are now first class citizens in the world of social media technologies.

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Manager != Leader

All too often we see knowledge workers, media and other professionals confusing the role of a leader with that of a manager. Peter Drucker spelled it out clearly for us – leadership is about ‘doing the right things’, in other words about being effective. Management on the other hand is about ‘doing things right’ – it’s about being efficient, the first looks outward, the latter looks inward. What’s the big deal in confusing the two you ask?  There are two general problems:

  1. A manager who strives for the glory of leadership, without understanding the essence of his role as a manger, will increase the risk of demotivating the team he manages, while also increasing the probability that goals and objectives go unmet.
  2. A leader who strives for the operational control of a manager, without turning his focus and vision outward,  will cement the ineffectiveness of his decisions.

This begs the question, can an individual be both a great leader and manager?

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Technology of Doing

Over the course of the past twenty years or so, the software development community has created or sought axioms, metaphors, techniques, approaches, analogies, processes and other practices (sometimes borrowing them from automobile manufacturing) that render software development work more productive and the worker more effective.  These practices continue to influence work across organizations, teams, and individuals and their recent rise to prominence in other knowledge worker disciplines supports the notion that software developers are in fact “pioneers in knowledge work”, as was suggested by Watts Humphrey.

Many of these practices resulted from the need to improve the effectiveness of software development efforts after the general ineffectiveness experienced with projects that followed the traditional management and engineering mindset.  As other forms of work continue to evolve to depend more and more on the effective application of specialized knowledge,  we may find that what has proven effective for the software development community (e.g. Agile) may be equally so when applied to other work disciplines.

Background

About ten years ago I started implementing my vision for a repository of knowledge worker tools and practices that could help promote this cross-pollination of practices.  At the time I referred to it by the name “Metaframeworks” and the idea was to organize, document and digitally capture these popular practices so they could be effectively studied, referenced, mixed and matched across disciplines.  An example of the practices I set out to capture were all those defined under the compound software development practices such as Scrum and Extreme Programming. With Metaframeworks however, I wanted to capture the practices emerging from many knowledge worker disciplines, not just software development.

So as the ‘need-to-know’ culture of Web 1.0 began a transition towards a ‘need-to-share’ culture in Web 2.0, I also started looking for ways to add more structure to this repository as well as introducing new ways to share the knowledge and information it captured.  At this point the project was renamed ‘CGuide’, and supported a new hierarchical classification of practices, with the classification scheme borrowed directly from Google Directory.  The repository had also moved from my local hard drive to Amazon’s online Simple Storage Service (S3) and while CGuide’s predictable structure and online accessibility made it easier to find and navigate towards a relevant practice, there was something missing.  Needed was a common metamodel and associated metadata to capture key characteristics of these practices.  This metadata would be critical in promoting the development of semantic tools capable of searching through the directory of practices, for example.

Which brings me to the third generation of this repository.  This new phase operates in a web increasingly dominated by social media technologies such as Twitter and Facebook but also increasingly limited by traditional keyword based search tools of Web 1.0 and 2.0.   As our collective maturity in using the Internet increases, along with the tsunami of data it generates, users are demanding more relevant search results to their increasingly sophisticated queries.  Back in 1999 the founder of the World-Wide Web, Tim Berners-Lee, was quoted as follows:

I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize.

– Tim Berners-Lee, 1999

His ambitious vision is turning out to be the seed for the Web’s next generation.  In the spirit of evolving this repository with the times of the Internet, I am moving it to Metaweb’s excellent structured data platform known as Freebase, with the vision of turning it into the world’s largest open linked data repository of knowledge worker practices.

The Project

Technology of Doing includes a comprehensive dataset of knowledge worker practices.  You can start using this dataset by visiting http://technologyofdoing.freebase.com.   Practices are none other than methods, concepts or phenomena that feed from a large body of true sciences and/or experiences and provide an effective way to achieve a set of objectives.  For example, ‘Pair-programming‘ is a type of knowledge worker practice prevalent in software development , ‘DIKW‘ is a type of practice found in knowledge management, and ‘Strengths-based Selection‘ is practice adopted by business management specialists. Each of these practices can be associated to one or more objectives (e.g. improve productivity) as well as a one or more practitioner strengths (e.g. empathy).

Semantic Possibilities

With the structure and metadata in place, the development of semantic tools capable of offering a strengths-based practice selection to individuals, teams and organizations alike is now possible.  An example of this is the Boost Practices application, where individuals can use it to better align their work practices with their natural talents.

Check back throughout 2011 as I cover more of the Technology of Doing.

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Boosting Effectiveness

Remember the “Computers are Everywhere” slogan from this vintage 80’s cartoon commercial?  It appeared on broadcast television during Saturday mornings as a way to educate young audiences to the newfound efficiencies computers were bringing to all aspects of society, including air traffic control, fire response, and space travel.  The commercial delivered an important message to kids, probably the same ones who a few decades later, would be at the center of the tidal wave of innovation and speculation that came to be known as the dotcom era.  Notwithstanding the commercial’s positive message and influence, it neglected to mention the importance of doing things faster, cheaper, and better, presumed the right things were being done to start with.  Which is to say, it didn’t pay to be quicker at doing the wrong things.

This is the basis for effectiveness, which has become the mark of quality for 21st century knowledge work.  But what exactly is effectiveness and what renders a person, process, or technology more effective?   In this series, Boosting Effectiveness, I will present the essential characteristics for effectiveness in knowledge work, and discuss how you can improve effectiveness in your own day-to-day knowledge work.

Purpose and Objectives

Legendary management scientist, Peter Drucker, differentiates the logic of work from the logic of working.  Work, he says, represents the tactical actions defined by an organization to fulfill a set of objectives.  These objectives in turn, represent the direction and “action commitments” of the organization towards a common purpose while also setting the standard for measuring performance.  You may hear terms like ‘mission’, ‘vision’, ‘strategy’ or ‘tactics’, but the general concept is the same – purpose, objectives and the tactical actions derived from them form a framework meant to inspire and concentrate an organization’s thoughts and efforts towards a common point.

Countries are founded on this type of framework.  The United States of America defines its purpose in the Preamble to the U.S. Constitution.  This constitution in turn defines a set of objectives, that include the Bill of Rights.

Business organizations also hold their thoughts and actions accountable to this framework. Consider a a high-tech company with the mission of “organizing the world’s information and make it universally accessible and useful“.

The logic of working follows a similar principle.  Drucker reminds us that  “making the worker achieving implies consideration of the human being as an organism having peculiar physiological and psychological properties, abilities, and limitations, and a distinct mode of action”.   Consider, for example, an individual who decides to live a life that remains true to her core values and principles.

Therefore, boosting effectiveness in knowledge work first requires we maintain an intimate understanding of the context for what is ‘right’.  The key is to understand that there are two contexts for effectiveness in knowledge work.  The first embodies the purpose and objectives of the organization through the definition and creation of work, and the second embodies the purpose and objectives of the worker through their ‘distinct mode of action’, which includes their talents, skills and knowledge.

This brings me to the first principal for boosting effectiveness in knowledge work:

Boosting effectiveness in knowledge work requires an intimate awareness and understanding of the purpose and objectives of the work (logic of work), along with the purpose and objectives of the knowledge worker (logic of worker).

Harmony

Any bicycle mechanic will tell you the importance of regularly maintaining a wheel’s ‘trueness’.  This process involves the careful adjustment of tension, provided by the wheel’s spokes, to achieve a perfectly straight wheel.

Boosting effectiveness follows a similar logic.  Both require finding a harmonic balance between potentially opposing elements. When truing a wheel, a single turn of the spoke can impact any of the four variables controlling its shape and performance.  In knowledge work, any decision or action that doesn’t fully harmonize logic of work with the logic of the worker can have a detrimental impact on one, the other, or both.   Consider the following examples that benefit both the work and the worker:

This brings me to the second principal for boosting effectiveness in knowledge work:

Boosting effectiveness in knowledge work requires that decisions concerning people, process or technology harmonize the logic of work with the logic of the worker.

Responsible Commitments

In his book ‘Reflections on Management‘, Watts Humphrey talks about the importance of creating and communicating ‘responsible commitments’.  These commitments are key to a team’s performance, and according to Humphrey ‘the only way for the team to operate’.   Thus far, the principles for boosting knowledge worker effectiveness have focused on the logic of work and the logic of the worker.  Responsible commitments, although rooted in a work plan, are also designed to elicit and nurture a shared vision and commitment from all team members.  This is key in an era of knowledge work where the body of knowledge required for effective decision making rests with the knowledge workers themselves.  Humphrey points out four necessary characteristics of these commitments:

  1. They should be based on a work plan
  2. They should be freely assumed and publicly accessible
  3. They should follow a phase of diligent preparation
  4. They should precede the performance required to fulfill them

Responsible commitments thus ensure that the vision and commitment towards fulfilling an objective starts with the specialists, while also providing a motivational boost for two reasons.  First, the individual and/or team will feel more confident in achieving commitments they help define.  Second, with their name associated to the commitments, credibility is also on the line.

Therefore, the third principle for boosting effectiveness in knowledge work:

Boosting effectiveness in knowledge requires  a culture of creating and communicating ‘responsible commitments’ of work, by engaging and eliciting the thoughts and opinions of all members whose responsibility it is to fulfill them.

Quality Feedback

In February 2001, 17 software developers met to discuss lightweight software development methods. Heavyweight predictive software development approaches, such as the Waterfall method, were perceived ineffective, complicated and slow to respond to changing requirements.  The software development community was heavily criticized through widely quoted statistics showing the failure rate of software development efforts.  The air was right for a change and this now infamous meeting resulted in what has become the Agile software development movement.

The software development practices born out of this movement share a common characteristic.   They are all designed around the early and continuous discovery and adaption to change.    Test driven development, for example, which forces a programmer to confront the question “Why am I doing that?” more times than not, has been proven more effective at improving the quality of software being produced.  Or take Agile’s promotion of daily meetings, which inspire all team members to open up and think through their work day, anticipating changes while also better understanding their previous issues through shared feedback.   There is also Scrum’s burndown chart, which helps team members visualize their daily progress, or Agile Retrospectives, which give all members a chance to reinforce what they liked, learned, lacked and longed for from the previous software release.  These practices are all designed to generate quality feedback so teams can make the necessary adjustments.

This brings me to the fourth principal for boosting effectiveness in knowledge work:

Boosting effectiveness in knowledge work requires practices designed to generate timely, accurate, precise, and complete feedback regarding the work’s output or the worker’s performance.

Trust

Arguably the most fundamental and overarching element when talking about boosting knowledge worker’s effectiveness is trust. By trust, I’m referring to professional trust and its components.  In order to establish the foundation for boosting a worker’s effectiveness, there needs to be a strong and growing foundation of trust between a worker and his team, his employer as well as the technologies and processes underlying her work.   Knowledge management researcher, David Snowden, confirms the importance of trust (pdf) for the effective exchange of knowledge by suggesting “shared context is vital to knowledge exchange, and such context always involves some human trusted validation.”

This brings me to the fifth and final principal for boosting effectiveness in knowledge work:

Boosting effectiveness in knowledge work requires the growing presence of professional trust between the worker and his colleagues, employer, tools, processes and customer.

This concludes the series on Boosting Effectiveness.

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