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Friday, August 11, 2017

How the demographics of the organisation affect Knowledge Management

The demographics of your organisation determine the distribution of knowledge, and therefore the Knowledge Management Framework

Here's another factor that can affect the way you address KM in an organisation; the demographics of the workforce. Because the demographics are is linked to the distribution of knowledge across the staff, it determines how many sources of knowledge you have, and how many net users, for example:

  • A company with very many junior staff and few experienced staff will have few knowledge suppliers and many knowledge users; while
  • A company with very many experienced staff will have many knowledge suppliers, each of whom is also a knowledge user.

Please note that I am not talking here about whether older people behave differently to younger people - there are many assertions made about these differences in behaviour, few of which seem to stand up to scrutiny.

Take a Western engineering organisation. 

Here the economy is static, and the population growth is stable. Engineering is not a "sexy topic". The workforce is largely made up of baby boomers. A large proportion of the workforce is over 40, with many staff approaching retirement - the blue line in the graph above.

Experience is widespread in the organisation - this is an experienced company, and knowledge is dispersed. Communities of Practice are important, where people can ask each other for advice, and that advice is spread round the organisation. Experienced staff collaborate to create new knowledge out of their shared expertise. Knowledge can easily be kept largely tacit. The engineers know the basics, and a short call to their colleagues fills in any gaps. The biggest risk is knowledge loss, as so many of the workforce will retire soon, and a Knowledge Retention strategy would be a good investment.

Take an Asian engineering organisation. 

China or in India the economy is growing, the population is growing, there is a hunger for prosperity, and engineering is also a growth area. The workforce is predominantly very young - many of them fewer than 2 years in post. There are only a handful of real experts, and a host of inexperienced staff - the red line in the chart above.

Experience is a rare commodity, and is centralised within the company, retained within the Centres of Excellence, and the small Expert groups. Here the issue is not Collaboration, but rapid onboarding and upskilling. The risk is not so much Retention of knowledge, it is deployment of knowledge, although the reliance on a few experts means that they must be given a Knowledge Ownersgip role, rather than using them on projects.  Rather than keeping knowledge tacit, it makes sense to at least document the basics in explicit form (the experts will be too busy to answer so many basic questions), keeping this documentation updated as the organisation learns.

These two demographic profiles would lead you to take two different approaches to KM. The Western company would introduce communities of practice, and use the dispersed knowledge to collaborate on building continuously improving practices, processes and products. Wikis could be used to harness the dispersed expertise. There would be huge potential for innovation, as people re-use and build on ideas from each other. Crowd sourcing, and "asking the audience" are excellent strategies for finding knowledge.

The Eastern company would focus on the development and deployment of standard practices and procedures, and on developing and deploying capability among the young workforce. The experts would build top-class training and educational material, and the focus would be on Communities of Learning rather than Communities of Practice. Innovation would be discouraged, until the staff had built enough experience to know which rules can be bent, and which must be adhered to. Crowdsourcing is not a good strategy, and the "wisdom of the experts" trumps the "wisdom of the crowd".

This is one of the factors that KM must address, namely the amount of expertise in the company, and how widely it is dispersed.

from Knoco stories

Leaving lessons in a lessons database doesn't work - an example from NASA.

NASA found out the hard way that just collecting lessons into a database is not enough.

Image from wikimdia commons
5 years ago, NASA conducted an audit of lesson-learning. At the time, NASA spent 750,000 annually on their lessons learning approach, centred around a tool called LLIS (The Lessons Learned Information System).  NASA was at the time (and still is) one of the worlds leaders in Knowledge Management, and they wanted to know if this money was well spent, and if not, what could be done (note of course that lesson learning is only a part of NASA's KM approach, and thanks to Barbara Fillip for bringing me up to speed).

According to the levels of use and application found by the auditors 5 years ago, there was plenty of room for improvement in lesson-learning. Specifically -
"We found that NASA program and project managers rarely consult or contribute to LLIS even though they are directed to by NASA requirements and guidance. 
In fact, input to LLIS by most Centers has been minimal for several years. Specifically, other than the Jet Propulsion Laboratory (JPL), no NASA Center consistently contributed information to LLIS for the 6-year period from 2005 through 2010. 
For example, the Glenn Research Center and the Johnson Space Center contributed an average of one lesson per year compared to the nearly 12 per year contributed by JPL .....  
Taken together, the lack of consistent input and usage has led to the marginalization of LLIS as a useful tool for project managers" 
With minimal contributions (other than at JPL), and with rare consulation, then this system was just not working.

Why did it not work?

The project managers that were surveyed offered a variety of reasons for not using or contributing to LLIS, including:
  • A belief that LLIS is outdated, and is not user friendly
  • A belief that LLIS does not contain information relevant to their project
  • Competing demands on their time in managing their respective projects.  
  • Policy Requirements have been weakened over time. 
  • Inconsistent Policy direction and implementation. 
  • Lack of Monitoring. 
Interesting that three out of these six reasons are directly related to governance. One wonders that, even if a spanking new LLIS were introduced, whether (without better governance) anyone would bother to use it. 

The auditors suggested a number of improvements, including improvements to process, policy and resources, but one of the main issues with a lessons database is that it is a clumsy solution. Lessons should not be stored in an ever-accumulating database - lessons need to be embedded into design, into principles and into process.

Levels of lesson learning

I described, earlier this year, 3 levels of lesson learning, and the approach reviewed by the auditors is Level 1 - reactive capture of lessons in the hope that others will review them and learn from them.

Ideally any organisation should aim for level 2 - where lessons lead to changes in designs, practices or procedures. A lesson is therefore an increment of knowledge, and those little increments are used to build an ever-improving body of knowledge. Once the lesson has been embedded as a practice change, or a design-principle change, or a change in a checklist,  then it can be removed from the database.

Ideally the NASA database would be empty - all lessons would be incorporated in some body of knowledge somewhere. The only lesson in the system would be those pending incorporation.

If this system works well and quickly, then there should be no need for anyone to consult a lessons database - instead they should go to the designs, the checklists, and the design principles.

By relying on a Level 1 lesson learning system, NASA were already making things difficult for themselves. 

from Knoco stories

Thursday, August 10, 2017

Free and cheap technology is killing organizational effectiveness

Technologies supporting knowledge work are deceptive, especially for knowledge work shared among groups and teams. The ease of getting started obscures the challenge of learning to be effective. We focus on the details of particular features and functions at the expense of ignoring the cognitive challenges of deep thought and collaborative work.

I’ve been participating in a Slack team with a loose group of colleagues scattered across two continents. I was off the grid for about two weeks and found myself lost when I returned to the conversation that had continued in my absence. My first hypothesis was that Slack was the culprit and that some magically better UX would eliminate the problem. Slack, of itself, isn’t the problem but it is emblematic of the deeper issue that should be tackled.

In trades and crafts, the most experienced and effective practitioners would never invest in cheap tools or materials. Learning to use those tools and materials effectively is the work of years of deliberate practice. The strategy shouldn’t be any different if you are manipulating ideas than if you were manipulating clay. But the marketing and deployment of software rejects these hard won lessons. Software fame and fortune is built on promises of simplicity and ease of use, where ease of use has been interpreted as ease of getting started and minimally productive. We’ve all become facile with learning the first 5% of new tools and services. We’ve been led to believe or we pretend that this is enough. Few among us are prepared to invest in pushing further. Fewer still belong to organizations willing to support this investment.

The payoff from even this 5% has long been sufficient in terms of personal and organizational impact. We’re reaching the limits of the return from this minimalist strategy–it’s even more acute when we shift focus from individual knowledge workers to teams and groups.

To go beyond the 5% we need to modify our expectations and approaches about how we blend powerful tools with powerful practices. We need to adopt the attitudes of those who think in terms of craft and expert practice. Organizationally, we need to provide the time, space, and support to design and invent this new craft.

My hypothesis is that there are models to look to and borrow from. In particular, I believe that the world of software development has the longest and richest experience of dealing with the individual and group production of the thought products of the knowledge economy. Further, there are individual expert knowledge work craftspeople in various other fields; their tools and practices are also worth understanding and reverse engineering.

I don’t have this all figured out yet. Nonetheless, I ‘d like to get a new conversation going about how to improve on this train of thought. Where are good places to look?

The post Free and cheap technology is killing organizational effectiveness appeared first on McGee's Musings.

from McGee's Musings

Wednesday, August 09, 2017

The Role of Storytelling in a Team of Teams

Team of teams and storytelling

Four-star general Stanley McChrystal became the commander of US forces in Afghanistan in the mid-2000s. When he arrived in the country, he found the American military operating much as it always had, through command-and-control organisational structures. It didn’t take him long to figure out that wasn’t working against an enemy organised in flat networks that could adapt and reconfigure at a moment’s notice. So McChrystal restructured his forces into what he called a Team of Teams, which is the title of his 2015 book on the subject.

The principles of a Team of Teams are grounded in an understanding of complex versus complicated environments. A complex environment is where there are so many interconnected parts with non-linear relationships that it is impossible to predict with any certainty what might happen next. Cause and effect are intertwined and only make sense in hindsight. Complicated environments, on the other hand, can be pulled apart and analysed.

Human systems tend to be complex, whereas mechanical systems, such as the workings of the giant Airbus A380, are complicated. The Cynefin framework makes this distinction nicely. I have a minor YouTube hit with a simple explanation of the Cynefin framework which you might like to take a look at.

Companies have been quick to implement the ideas behind a Team of Teams, although to be frank it’s not easy. It requires culture change, even in modest-sized companies. But if you want to give it a try, here are some of the things to consider when implementing this approach.

Key elements of a Team of Teams

The first step involves structure. You have to move from a fixed hierarchy to a set of teams that interact in the same way people do inside a high-functioning team. This means, at a minimum,

  • having a clear and common purpose across all teams
  • being able to speak your mind with other teams1
  • having the freedom and trust to make decisions and get on with the job
  • having a shared consciousness around values and what ‘good’ looks like
  • trusting the capabilities, track records and intentions of others
  • leading like a gardener, focusing on creating an environment in which good work can happen rather than task-managing.

How stories can help

You need to carry out three jobs to embed the Team of Teams approach:

  1. craft and tell the change story of why a shift to a Team of Teams is necessary
  2. enhance everyone’s story skills, particularly those of your leaders and sellers, to enable people to find and share stories that illustrate the new way of working, foster rapport, and allow influence without hierarchy
  3. develop a systematic and purposeful process of embedding stories across teams that illustrate values and what ‘good’ looks like, and grow a shared consciousness.


Story trainagle

Change story

Leadership expert Simon Sinek has shown the importance of starting the change process with the question ‘Why?’ If you answer this question using a story, people quickly get the cause-and-effect and, more importantly, take away the intended meaning. In the first paragraph of this post, for example, I told a short story about why Stanley McChrystal moved to the Team of Teams approach.

Each organisation needs to create its own version of this story. It’s best done by involving as many individuals in your company as possible, so that the maximum number of people understand and own the change story.

Story skills

A few weeks back I worked with a group of executives at a large UK supermarket retailer at their learning academy just outside London. I was reminded of just how much retailers are numbers people who, at the same time, are in positions where they must influence thousands of employees. Everyone was a storyteller, but I needed to help them become systematic and purposeful in sharing their own experiences and those of their colleagues. Within a couple of days, their story switches were on and they were all actively looking for stories to tell.

Embedding stories

If you want to change a workplace culture, you need to change the stories within the workplace. Now you could just leave that to chance and see what stories emerge. Or you could develop a process where, across all the teams and on a regular basis, stories are shared and discussed that illustrate what ‘good’ looks like. The great thing about stories is that they are not directives or checklists. Instead, they illustrate a pattern of behaviour which people can choose to copy and modify for their own purposes.

Of course, this approach is relevant to any change you are introducing. The more stories you get into the system, the more concrete and real the change will feel for all involved. You will quickly move away from corporate doublespeak to people authentically talking to each other and sharing real-life examples.

1. If you want a simple tool to assess how well connected your teams are then I recommend you check out

To change a culture you need to change the stories told. Learn how Anecdote can help you do this

The post The Role of Storytelling in a Team of Teams appeared first on Anecdote.

from Anecdote

Monday, August 07, 2017

The Hidden Knowledge Problem in Organizations

Having had the opportunity to observe many conversations in organizations, I have come to understand that the greatest knowledge deficit in organizations is not the lack of sharing nor is it poorly designed repositories. Rather it is the inability to hold authentic conversations. What I have too often observed is teams and units where members do not offer their best thinking out of fear; fear of not being viewed as a team player, fear of being seen as incompetent, fear of embarrassing themselves or someone else, fear of acknowledging that they do not understand something. I find team members unwilling to say they disagree with the boss or saying they agree when they do not.  

When I say fear, I don’t mean shake in your boots fear or fear of being immediately fired. I mean the everyday reluctance of individuals to say what they know or believe, because of the threat of embarrassment or a negative response from others.  I see it both at the highest organizational levels and with front line employees. When fear exists, critical knowledge is lost and serious problems remain hidden. The time waste is both enormous and expensive. Rather than speaking honestly to one another, people invent costly workarounds, delay, procrastinate, or make agreements they don’t intend to keep. This problem is so long standing in organizations that people have become resigned to it as, “just the way things are.” We hear that resignation in the familiar phrases people use to explain not speaking out, “You have to choose your battles,” “You just don’t tell the boss that he’s wrong,” or, “Saying that would be career limiting.”  

But at a time when “critical shifts have taken place in the wider culture away from hierarchy towards networks, from top-down to widespread engagement with greater emphasis on innovation and creativity” (Gilmore) the need for making use of the knowledge of all employees has become a major imperative.

Fortunately, along with the knowledge demands made by these critical shifts, has come a richer understanding of how to access this hidden knowledge (Edmondson, Kegan, Turco).  These new perspectives demonstrate that it is possible for authentic conversations to be the norm in organizations or even within a team that is embedded in a larger organization. But they also illustrate that such a deeply embedded deficit does not succumb to quick fixes such as a simple workshop or admonitions for authenticity from the C suite.  Rather to address the problem requires a sustained focus on three elements 1) developing a culture of psychological safety, 2) members’ gaining awareness of their own blind spots, and 3) building learning routines in everyday work.   

It is possible to find case studies of organizations that have accomplished this. They include some that I have written about and some that others have detailed, Kessels & Smit, Bridgewater, Next Jump, Decurion, TechCo (pseudonym in The Conversational organization),  Lake Nona Project, The Defense Intelligence Agency.

from conversation matters

The CKO of Microsoft Services Has a Surprising Perspective on Knowledge Management

I recently had the opportunity to interview Jean-Claude Monney, for a project I was working on for USAID.  He is the CKO of Microsoft Services, the largest Division of Microsoft with over 22,000 people. One of the questions I asked him was, Do you know of research completed or any underway that demonstrates the value or effectiveness of KM to the larger entity – the society, the organization or the project?” 

Screen Shot 2017-07-18 at 2.20.19 PM

His surprising answer was, “Everyone talks about effectiveness as if it’s thae holy grail.  It’s the wrong question! KM is key to providing insights, for example, on how to improve sales and marketing, but KM is not the one to define benefit. You can’t measure the ROI of knowledge.  Like his unique position on effectiveness, Jean-Claude has atypical views on the familiar KM maxim of People, Process and Technology.

In terms of People he says KM should be focused on the changing context of work. Where we used to talk about blue collar and white collar, we now need to add “no collar.”  “These no collars are those contributing knowledge on platforms like Stack Overflow, they are software programmers that work freelance and get engaged as contractors. There is a movement happening between full employment and contractors. Contractors/freelancers want quality of life, they want to go on vacation when they want and to do the kind of work they like. The social context is changing. We need more research to understand the social context of the worker, for example, what are the legal aspects of who owns the knowledge? “Taking a job for 30 years is gone – it is the past”. He notes that most customers that Microsoft works with, have a 2020 project to think about how the Digital Workplace will be changing the way they work.

A second People issue that concerns Jean-Claude is that KM should focus on how individuals can rapidly grow knowledge and skills to move into a new task. He notes that the world is embarking on an effort to drive in apprenticeship, so people can be employable in two years.  He sees on-going learning as the new normal and uses himself as an example. He explains that although he just hit retirement age, he can talk machine learning with any 30-year-old engineer because he is continually learning. People should not be so busy at their jobs that they do not make time to continue learning by reading, talking to colleagues, and reflecting on actions their team has taken. He is grateful that Microsoft has embraced a growth mindset culture that leads to a desire to learn and see failures as essential to mastery, find lessons and inspiration in the success of others and embrace challenges with agility.

In terms of Process Jean-Claude thinks that most of the current KM processes are shallow. He explains that at Microsoft they have engineered the three processes of 1) creating knowledge, 2) reusing knowledge (embedding it in daily work processes), and 3) harvesting, curating and growing knowledge. But under those three are 18 sub-processes, each of which is measurable. He says process must get to that level of detail to be effective. The KM principle he supports, is not only about sharing, it is also about the programmatic application of shared knowledge where the processes define the trust level of that knowledge. 

In terms of Technology, Jean-Claude says we need new research on how AI based technology mixed with cognitive science and neuro science, are impacting knowledge work. He points to law firms that are increasingly replacing paralegals with AI, what he calls “knowledge augmentation.” For example, AI is a better way to update expertise finder systems, because the rate of technology change is so fast that individuals won’t go back and update their profile with “I learned this yesterday.”  He explains that new expertise finders will capture the employees' digital footprints, for example, if an employee has written a white paper or acquired certain expertise during a project, the employee’s profile will be dynamically updated.

Another example of the use of AI, coupled with the knowledge of cognitive science and neuro science, is in healthcare. He explains AI-based cognitive services can detect emotions in the faces of people to learn about how they are feeling. There are translation services and speech recognition that could be used if the patient and healthcare worker do not speak the same language. Today, the free Skype translator version offers simultaneous voice translation in 8 languages, and the text translator is available in more than 50 languages for instant messaging, you can experience it in this video. And he notes that audio, text and video could be used to mine a knowledge base of healthcare conversations between doctor and patient using the new Video Indexer Cognitive Service from Microsoft.  As an aside, Jean-Claude said he was horrified at with how the Ebola crisis was managed – another place where AI and KM could have been helpful.  “Given that humans are the most important part of KM, we need to translate the academic principles of cognitive science and neuro science into real life knowledge management.” 

He believes we need more education on KM at all levels and has joined the Columbia University faculty where he will be teaching Digital Transformation, the Digital Workplace and KM at the Information and Knowledge Strategy (IKNS) Masters in Science Program.

Finally, on an encouraging note he explains that he has been invited to share Microsoft Services' KM initiative at industry events like a Keynote at the World Bank's bi-annual Knowledge Sharing Conference and with more than 100 companies in the last 2 years.  He believes that the interest in KM is springing up in all industries. And with the accelerating advances in AI and Cognitive systems, KM will become an expected managerial capability, like finance, operations or HR.

from conversation matters