LeveragePoint Applications

Leveraging semantics and Web 3.0

Monitor's LeveragePoint team is investing in semantic technologies. This may seem like an odd direction for a strategic consulting company focused on supporting its clients to grow in the ways that are meaningful to themselves, but there is method in our madness.

The LeveragePoint solutions are designed to deliver business outcomes, they are focused on driving results that will impact the top and bottom lines, market share and presence, and ultimately share value, and they have a track record of delivering this. Our current focus is on strategic marketing, see LeveragePoint for Strategic Marketing, and additional offerings around Strategic Pricing, Innovation and Strategic Analysis are in planning. So why apply semantics to this?

The short answer is that the LeveragePoint solutions are designed to help teams act on complex business problems, and that this requires an approach that supports dynamic change and configuration, clear communication and the connection of many concepts, processes and data sources. A longer answer must begin with a sketch of what semantic technologies are and why the bring significant leverage.

What are Semantic Technologies

Semantics involves the study of meaning. here are a few definitions culled using Google's define: function.

Definitions of semantics on the Web:

"is the study of meaning"

"The use of language in meaningful referents, both in word and sentence structures"

"meaning. If a computer understands the semantics of a document, it understands the meaning, rather than just interpreting a series of characters."

As LeveragePoint is concerned with communicating methods and results between team members and with the users of the results, the ability to clearly define the meaning of different pieces of content, of tasks, of data and how these fit together is at the heart of our solutions.

We do this using the new generation of semantic languages that have been developed for use on the Internet. The World Wide Web Consortium (W3C) takes a leading role in this work and has excellent resources available at its website.

The main Language that we are using at this point is the Resource Description Lanaguage, or RDF, one of the foundations of the W3c's semantic web program. RDF is deceptively simple. At its root is the notion of a triple, a set of three things linked in the form subject-predicate-object. As long as each of these things has a URI, it can become a subject, object, or even predicate in term, making it possible to build webs of connected meanings. Even a triple can become the subject of another triple. It looks something like this.

 

Of course there is a great deal more to RDF than this. The best way to learn about this is to read the W3C's excellent introduction RDF Primer. For applications that require a more precise model, and the automated reasoning and inference this makes possible, the W3C has developed the Web Ontology Language OWL (this is not a mistake, it is a sly reference to a scene in Winnie the Pooh where Owl is spelt 'Wol"). This is a rich area of thought that we will return to many times.

Application at LeveragePoint

At LeveragePoint we use RDF to define all of the different components that go into our solutions. The different business objectives, methods, data, and the content describing them are broken down into the 'smallest coherent unit'. These units and, more importantly, the relationships between them are described in RDF. This does several things for us.

1. It helps us think very clearly about how business outcomes are related to our different types of user and what outputs will support those business outcomes.
2. It makes it possible to have highly configurable solutions, for different industries, in response to different events, even for each user.
3. The RDF models are very useful as filters in search applications.
4. By giving our models explicit representations we are able to evolve and improve them much more effectively.

We also use RDF to organize and describe our internal knowledge base and ongoing learning. And in the future, we expect to add it to the web services we provide, to simplify integration.

Wider Business Potential

Analyst Mills David has described the future potential of these approaches as a Semantic Wave. As semantic technologies are adopted they will change the way in which we organize and share information, and they will help us to uncover and to link areas of knowledge in new ways. This will transform search, making it much more intuitive, but more importantly will help us to think about much larger webs of relationships in a more coherent manner. Issues such as climate change, the impact of demographic change, how innovation is cultivated and transferred, will all become much more tractable to human thought, and more and more people will be able to think together, uncover their differences, and explore resolutions. The first big impact is likely to be in the life sciences, where extensive use is already being made of semantic technologies in projects such as Ontogene. Monitor is one of the first consulting companies to recognize the potential of the semantic web, what some have called 'the mathematics of meaning' and begun to apply it to business and organizational issues in a way that impacts business results.

Learning Plans

LeveragePoint is about enabling effective action, but the people who deliver LeveragePoint have to learn constantly to do this effectively. This means that we need to actively plann and share how we learn, what we are learning, and how we are putting it to work. We will share some of this in the LeveragePoint Applications blog.

At LeveragePoint, a learning plan has a number of pieces: Strengths, Learning Styles, a link to Organizational Objectives, Learning Goals and Learning Themes. The Learning Goals are supported by Mentors, Buddies, Resources and demonstrated by Evidence. All of these are woven together in a dynamic model that supports search and sharing.

We begin by introspecting on our strengths, and our learning styles. We then think about how these work together. We use the Gallup StrengthsFinder tool to discover our strengths, though no doubt other approaches couled be used.

For example, my strengths (Steven Forth) are Strategic, Achievement, Ideation, Input and Learning. My learning style is Abstract, Historical, Written, Modeling and Social. These two sets alone tell you quite a bit about me, and help my colleagues work with me. Putting them together, though, adds a layer of insight.

Mapping Strengths to Learning Style

Strategic thinking requires high-level models and an understanding of how and why things are as they are. This is necessary to effect change. My abstract, historical, modeling learning style both underlies and supports my strength in strategic thinking.

Achievement – the drive to excel. I spend a lot of time thinking and learning and working to apply what I am learning to test it and see if it will drive success.

Ideation – abstract thought and modeling drive new ideas, as does the urge to go back to the source and explore other paths and potentials. Generating and sharing ideas through conversations are key to both learning and my achievement.

Input – you only have to look at one of my tag clouds to know that I search out information and apply it to ideas and models.

Learning – well that is a bit recursive, and recursive structures are something that fascinates me. Google’s application of recursive structures to its technical architecture is something to learn from, and one can think of Chris Argyris’s double loop learning as a form of recursive structure.

Organizational Goals

Like most organizations, Monitor's LeveragePoint team has goals and these goals are an important input into our learning plans. Organizational goals are built on the SMART model (goals that are Specific, Measurable, Achievable, Relevant and Timely) and each business funciton has its own cascading goals. Standard stuff. Asking each person to explicitly link Learning Goals to Organizational Goals helps all of us understand the Organizational Goals and what it will take to achive them. We have also found that it helps to build commitment.

Learning Goals

Once we have shared something on how we learn, each person develops a set of three-to-seven Learning Goals. These are also meant to be SMART goals. A good Learning Goal has several parts.

• The learning loal and sub-goals.
• Its link to the organizational goals.
• A mentor.
• Learning buddies (optional).
• Resources (these can be people, communities of practice, books, conferences, conversations, web resources, processes, etc.).
• Evidence (internal and external).

Learning Themes

One interesting thing we have discovered in managing our own learning plans is the emergence of common learning themes. Themes are inferred from individual (or team) learning goals, and have common buddy groups, resoruces or evidence. The emergence of a learning theme is sometimes a leading indicator of new business opportunities.

What does this look like?

There are a number of pieces in these learning plans and a sketch may help show how they fit together.

Click to Enlarge

This is no more than a sketch, and the model evovles with use as new concepts and relationships are uncovered. But it is a starting point.

Implementation

At Monitor's LeveragePoint group we manage our learning themes using a Semantic MediaWiki. MediaWiki is an open source softeware package that was originally developed to run Wikipedia. The Semantic MediaWiki adds in a semantic layer that supports RDF and allows users to jointly create a much more robust knowledge model. As we use semantic technologies extensively in our sollutions, this gives everyone on the team to get their hands dirty, so to speak, and learn by doing. Most people update this wiki several times a week, as new resources are used and as evidence accumulates. In fact, this wiki is slowly becoming our knowledge management system!

Presentation at SemTech 2007

As you can imagine, several of us share 'semantics" as a learning theme. This is a deep area with a lot happening and much to learn. One piece of evidence that we are progressing towards this goal is to make presentations at conferences on our work, and the first such presentation will be at SemTech 2007 in San Jose later this May.

Wikipedia

If you are interested in learning a bit more about learning plans, there is a useful article on Wikipedia.

Enabling Action

Monitor’s LeveragePoint solutions are built around enabling effective action. What does this mean?

Enabling – we assume that the individual and team are central. Our solutions help people to work more effectively, make better choices and then to scale the implementation of the choices. They do not pretend to replace people or the need for hard thought and real choices (a ‘real choice’ is a choice that prevents you from making some other choice, or as Pankaj Ghemawat says, strategy means commitment).

Effective – the choices and actions that follow from them have an impact on the organization. The impact is determined by measuring the outcomes of the choices and the outputs of the action (a double loop). Hypotheses are stated clearly and then tested. Effective action is action that changes in response to the outcomes and the environment. It is not static.

Action – as choices are made they have to be acted on. Even the situation where the ‘choice is not to act’ is a kind of action, based on hypotheses, and the outcome needs to be measured and the choice reflected on. In the CAM action is divided into tasks and their outputs which are explicitly linked to outcomes. The outcomes are linked back to the choices.

Our approach to enabling effective action has been captured in what we call our CAM, a formal model of Choice-Action-Measurement. The CAM is being developed together with our clients and users and is grounded in Jonathon Levy’s vision of real-time change management and user-centric learning. Its role in the LeveragePoint solutions is to provide an overall framework to support rapid configuration and evolution of action-focused solutions.

I will write more about the LeveragePoint CAM in future posts, but here I want to look back at some of the work that it is grounded in.

Action Science and Chris Argyris

One of the pleasures of working at Monitor’s Cambridge office is to occasionally meet Chris Argyris in the hall and to have the chance to engage with him, and at times to have one’s motives, assumptions and behaviors questioned at profound and uncomfortable levels. The man is rigorously honest. When we began to look for the foundations of a model of effective action the first place we looked was to the work of Chris Argyris. His notions of ‘Double Loop Learning’, ‘Ladder of Inference,’ ‘Theory Espoused vs. Theory in Use’ are all coded into our work. But more important than any specific tool is his overall approach to learning, to how people work (and fail to work together), and to listening to what is actually said.

Observe Orient Decide Act (OODA Loops) and Col. John Boyd

Another important part of the Monitor family is Chris Myer from Monitor Networks. We went to Chris early on in thinking about our CAM model and he suggested we look at the work of Col. John Boyd of the United States Air Force. Col. Boyd is one of the first thinkers on strategy to realize that in a networked world strategy has to be implemented real time. Being a fighter pilot no doubt drove this. He came up with a model of Observe-Orient-Decide-Act that inspired our own work.

Cognitive Task Analysis (CTA) and Gary Klein

About seven years ago business consultant and Japan expert Carl Kay introduced me to Gary Klein’s book Sources of Power. In this book Klein investigates how people and teams make decisions in high stakes situations – fire fighters, pilots, doctors in intensive care units. This work has informed a growing practice of cognitive task analysis (CTA) that researches how people act effectively to get things done.

Embodied Cognition and Ed Hutchins

One of my passions is sailing. "There is nothing- absolutely nothing-half so much worth doing as simply messing about in boats." -Ratty said to Mole in Kenneth Grahame's beloved 1908 classic, The Wind in the Willows. So I was delighted when cognition researcher Brian Fisher introduced me to Ed Hutchins classic work Cognition in the Wild. Hutchins work is focused on understanding how teams carry out complex tasks in the real world. The ‘real world’ in Hutchins book is that of coastal navigation by the US Navy and open ocean navigation by the Micronesians. In both cultures cognitive tasks are shared between people, complex methods are reduced to practice, and lives are at stake. There is now a compelling body of work on embodied cognition, and related areas such as the role of metaphor and blends in understanding the world, but it is to Ed Hutchins that I turn when I need to go deeper.

All of these are deep themes and there is much more to explore. I hope to return to each of these ‘points of origin’ over time.

Links

Commitment by Pankaj Ghemawa
When I was deciding whether or not to move from Vancouver and join Monitor, our Chief Content Officer Alan Kantrow gave me a copy of this book. Reading it helped me to think deeper about my own decision to move to Cambridge and what I was committing to at Monitor. Knowing what you are committing to includes thought about what you will not be able to do going forward. 

Action Science by Chris Argyris, Robert Putnam and  Diana McLain Smith
This is one of many excellent books by Chris Argyris that set out his thoughts on how people and organizations learn.

Blur by Stanley M. Davis and Christopher Myer
Many of our world systems are at inflection points, which is why real-time change management has become such a compelling value proposition. This book captures the drivers of this change better than most. “The Speed of Change in the Connected Economy.”

Observe Orient Decide Act or OODA Loops
Col. John Boyd published only two papers on OODA loops, but they are compelling. The Wikipedia article is an excellent introduction.

Sources of Power by Gary Klein
The best introduction to cognitive task analysis because it shows what motivated the work and describes real people in real situations.

Carl Kay’s blog is here.

Cognition in the Wild by Ed Hutchins
Read this book.

Brian Fisher is one of the most innovative thinkers on the psychology of human computer interaction. Learn more here.

And of course The Wind in the Willows.