May 26, 2011 Leave a comment

OrchestratorMail is an innovative application that brings efficiency to email communication. By fitting into your existing email platform, OrchestratorMail provides a simple, yet elegant structure to simplify the back and forth of email communications. OrchestratorMail effectively decreases email overload, minimizes misinterpretation and organizes email into an easily viewable system.

In a diverse, global workplace where immediacy of response and clarity of communications is critical, OrchestratorMail facilitates clear communications. It applies deadlines to communications making it more explicit and easy to track.

OrchestratorMail is a hosted application, independent of any email platform or client and uses email as a communication medium. OrchestratorMail fits right into your work style which means you do not have to change the way you work.

OrchestratorMail, works as its built on the fundamentals of language. The use of language varies by the culture, the geography and inter-personal relationships for the most part, even if it is all in English. OrchestratorMail distills the language to its unit elements to create an overlaying structure, reducing misunderstandings and bringing people on the same page. OrchestratorMail’s approach ties into world of language philosophy that has been around for hundreds of years.


Categories: General Tags: , ,

Speech Acts

March 19, 2011 Leave a comment

Speech act is a technical term in linguistics and the philosophy of language. The contemporary use of the term goes back to John L. Austin’s doctrine of locutionary, illocutionary and perlocutionary acts. Many scholars[who?] identify ‘speech acts’ with illocutionary acts, rather than locutionary or perlocutionary acts. As with the notion of illocutionary acts, there are different opinions on the nature of speech acts. The extension of speech acts is commonly taken to include such acts as promising, ordering, greeting, warning, inviting someone and congratulating.

* 1 Locutionary, illocutionary and perlocutionary acts
* 2 Illocutionary acts
* 2.1 Examples
* 2.2 Classifying illocutionary speech acts
* 3 Indirect speech acts
* 3.1 John Searle’s theory of “indirect speech acts”
* 3.2 Analysis using Searle’s theory
* 4 History
* 4.1 Historical critics
* 5 In language development
* 6 In computer science
* 6.1 Uses in technology
* 6.2 In multiagent universes
* 6.3 Other uses in technology
* 7 In management
* 8 Notes
* 9 See also
* 10 Bibliography
* 11 External links
Locutionary, illocutionary and perlocutionary actsSpeech acts can be analysed on three levels: A locutionary act, the performance of an utterance: the actual utterance and its ostensible meaning, comprising phonetic, phatic and rhetic acts corresponding to the verbal, syntactic and semantic aspects of any meaningful utterance; an illocutionary act: the semantic ‘illocutionary force’ of the utterance, thus its real, intended meaning (see below); and in certain cases a further perlocutionary act: its actual effect, such as persuading, convincing, scaring, enlightening, inspiring, or otherwise getting someone to do or realize something, whether intended or not (Austin 1962).
Illocutionary actsThe concept of an illocutionary act is central to the concept of a speech act. Although there are numerous opinions as to what ‘illocutionary acts’ actually are, there are some kinds of acts which are widely accepted as illocutionary, as for example promising, ordering someone, and bequeathing.
Following the usage of, for example, John R. Searle, “speech act” is often meant to refer just to the same thing as the term illocutionary act, which John L. Austin had originally introduced in How to Do Things with Words (published posthumously in 1962).
According to Austin’s preliminary informal description, the idea of an “illocutionary act” can be captured by emphasising that “by saying something, we do something”, as when someone orders someone else to go by saying “Go!”, or when a minister joins two people in marriage saying, “I now pronounce you husband and wife.” (Austin would eventually define the “illocutionary act” in a more exact manner.)
An interesting type of illocutionary speech act is that performed in the utterance of what Austin calls performatives, typical instances of which are “I nominate John to be President”, “I sentence you to ten years’ imprisonment”, or “I promise to pay you back.” In these typical, rather explicit cases of performative sentences, the action that the sentence describes (nominating, sentencing, promising) is performed by the utterance of the sentence itself.

Classifying illocutionary speech actsSearle (1975)[1] has set up the following classification of illocutionary speech acts:

* representative = speech acts that commit a speaker to the truth of the expressed proposition, e.g. reciting a creed
* directives = speech acts that are to cause the hearer to take a particular action, e.g. requests, commands and advice
* commissives = speech acts that commit a speaker to some future action, e.g. promises and oaths
* expressives = speech acts that express the speaker’s attitudes and emotions towards the proposition, e.g. congratulations, excuses and thanks
* declarations = speech acts that change the reality in accord with the proposition of the declaration, e.g. baptisms, pronouncing someone guilty or pronouncing someone husband and wife
[edit] Indirect speech actsIn the course of performing speech acts we ordinarily communicate with each other. The content of communication may be identical, or almost identical, with the content intended to be communicated, as when a stranger asks, “What is your name?”
However, the meaning of the linguistic means used (if ever there are linguistic means, for at least some so-called “speech acts” can be performed non-verbally) may also be different from the content intended to be communicated. One may, in appropriate circumstances, request Peter to do the dishes by just saying, “Peter …!”, or one can promise to do the dishes by saying, “Me!” One common way of performing speech acts is to use an expression which indicates one speech act, and indeed performs this act, but also performs a further speech act, which is indirect. One may, for instance, say, “Peter, can you open the window?”, thereby asking Peter whether he will be able to open the window, but also requesting that he do so. Since the request is performed indirectly, by means of (directly) performing a question, it counts as an indirect speech act.
Indirect speech acts are commonly used to reject proposals and to make requests. For example, a speaker asks, “Would you like to meet me for coffee?” and another replies, “I have class.” The second speaker used an indirect speech act to reject the proposal. This is indirect because the literal meaning of “I have class” does not entail any sort of rejection.
This poses a problem for linguists because it is confusing (on a rather simple approach) to see how the person who made the proposal can understand that his proposal was rejected. Following substantially an account of H. P. Grice, Searle suggests that we are able to derive meaning out of indirect speech acts by means of a cooperative process out of which we are able to derive multiple illocutions; however, the process he proposes does not seem to accurately solve the problem. Sociolinguistics has studied the social dimensions of conversations. This discipline considers the various contexts in which speech acts occur.
John Searle’s theory of “indirect speech acts”Searle has introduced the notion of an ‘indirect speech act’, which in his account is meant to be, more particularly, an indirect ‘illocutionary’ act. Applying a conception of such illocutionary acts according to which they are (roughly) acts of saying something with the intention of communicating with an audience, he describes indirect speech acts as follows: “In indirect speech acts the speaker communicates to the hearer more than he actually says by way of relying on their mutually shared background information, both linguistic and nonlinguistic, together with the general powers of rationality and inference on the part of the hearer.” An account of such act, it follows, will require such things as an analysis of mutually shared background information about the conversation, as well as of rationality and linguistic conventions.
In connection with indirect speech acts, Searle introduces the notions of ‘primary’ and ‘secondary’ illocutionary acts. The primary illocutionary act is the indirect one, which is not literally performed. The secondary illocutionary act is the direct one, performed in the literal utterance of the sentence (Searle 178). In the example:
(1) Speaker X: “We should leave for the show or else we’ll be late.”(2) Speaker Y: “I am not ready yet.”Here the primary illocutionary act is Y’s rejection of X’s suggestion, and the secondary illocutionary act is Y’s statement that she is not ready to leave. By dividing the illocutionary act into two subparts, Searle is able to explain that we can understand two meanings from the same utterance all the while knowing which is the correct meaning to respond to.
With his doctrine of indirect speech acts Searle attempts to explain how it is possible that a speaker can say something and mean it, but additionally mean something else. This would be impossible, or at least it would be an improbable case, if in such a case the hearer had no chance of figuring out what the speaker means (over and above what she says and means). Searle’s solution is that the hearer can figure out what the indirect speech act is meant to be, and he gives several hints as to how this might happen. For the previous example a condensed process might look like this:
Step 1: A proposal is made by X, and Y responded by means of an illocutionary act (2).Step 2: X assumes that Y is cooperating in the conversation, being sincere, and that she has made a statement that is relevant.Step 3: The literal meaning of (2) is not relevant to the conversation.Step 4: Since X assumes that Y is cooperating; there must be another meaning to (2).Step 5: Based on mutually shared background information, X knows that they cannot leave until Y is ready. Therefore, Y has rejected X’s proposition.Step 6: X knows that Y has said something in something other than the literal meaning, and the primary illocutionary act must have been the rejection of X’s proposal.Searle argues that a similar process can be applied to any indirect speech act as a model to find the primary illocutionary act (178). His proof for this argument is made by means of a series of supposed “observations” (ibid., 180-182).
Analysis using Searle’s theory

In order to generalize this sketch of an indirect request, Searle proposes a program for the analysis of indirect speech act performances, whatever they are. He makes the following suggestion:
Step 1: Understand the facts of the conversation.Step 2: Assume cooperation and relevance on behalf of the participants.Step 3: Establish factual background information pertinent to the conversation.Step 4: Make assumptions about the conversation based on steps 1–3.Step 5: If steps 1–4 do not yield a consequential meaning, then infer that there are two illocutionary forces at work.Step 6: Assume the hearer has the ability to perform the act the speaker suggests. The act that the speaker is asking be performed must be something that would make sense for one to ask. For example, the hearer might have the ability to pass the salt when asked to do so by a speaker who is at the same table, but not have the ability to pass the salt to a speaker who is asking the hearer to pass the salt during a telephone conversation.Step 7: Make inferences from steps 1–6 regarding possible primary illocutions.Step 8: Use background information to establish the primary illocution (Searle 184).With this process, Searle concludes that he has found a method that will satisfactorily reconstruct what happens when an indirect speech act is performed.

For much of the history of linguistics and the philosophy of language, language was viewed primarily as a way of making factual assertions, and the other uses of language tended to be ignored.[citation needed] The work of J. L. Austin, particularly his How to Do Things with Words, led philosophers to pay more attention to the non-declarative uses of language. The terminology he introduced, especially the notions “locutionary act”, “illocutionary act”, and “perlocutionary act”, occupied an important role in what was then to become the “study of speech acts”. All of these three acts, but especially the “illocutionary act”, are nowadays commonly classified as “speech acts”.
Austin was by no means the first one to deal with what one could call “speech acts” in a wider sense. Earlier treatments may be found in the works of some church fathers,[2] and scholastic philosophers,[3] in the context of sacramental theology,[4] as well as Thomas Reid,[5] and Charles Sanders Peirce.[6]
Adolf Reinach (1883–1917) has been credited with a fairly comprehensive account of social acts as performative utterances dating to 1913, long before Austin and Searle. His work had little influence, however, perhaps due to his death at 33 in the German Army at the onset of war in 1914.
The term “Speech Act” had also been already used by Karl Bühler in his “Die Axiomatik der Sprachwissenschaften”, Kant-Studien 38 (1933), 43, where he discusses a Theorie der Sprechhandlungen and in his book Sprachtheorie (Jena: Fischer, 1934) where he uses “Sprechhandlung” and “Theorie der Sprechakte”.
[edit] Historical criticsCritical theorists in other areas of critical theory use speech act theory as a way of approaching aspects of their own discourse. It is used mainly in the fields of linguistics and philosophy, meaning that, in speaking, a person is doing so through a particular set of pre-set conventions. The basics of the theory centre on the idea that words, when placed together, do not always have a fixed meaning. Austin’s work has had many critics; Gorman (1999, p. 109) explains that many people have used his work without fully understanding its criticisms, and Austin’s main arguments have had only one notable follow up work, that by Searle in 1969. Speech-act theory is a continuing discourse, still written about and criticised in hundreds of articles and books. MacKinnon (1973, p. 235) states that ‘the various conceptual systems we have indicated are only intelligible as extensions of an ordinary language framework’, meaning that, as its basis, the theory must first have an already working or ‘ordinary’ set of rules that are indisputable and reliable.
In language developmentDore (1975) proposed that children’s utterances were realizations of one of nine primitive speech acts:

1. labelling
2. repeating
3. answering
4. requesting (action)
5. requesting (answer)
6. calling
7. greeting
8. protesting
9. practicing

In computer science

Computational speech act models of human-computer conversation have been developed[7].
Speech act theory has been used to model conversations for automated classification and retrieval[8].
Another highly-influential view of Speech Acts has been in the ‘Conversation for Action’ developed by Terry Winograd and Fernando Flores in their 1987 text “Understanding Computers and Cognition: A New Foundation for Design”. Arguably the most important part of their analysis lies in a state-transition diagram (in Chapter 5) that Winograd and Flores claim underlies the significant illocutionary (speech act) claims of two parties attempting to coordinate action with one another (no matter whether the agents involved might be human-human, human-computer, or computer-computer).
A key part of this analysis is the contention that one dimension of the social domain- tracking the illocutionary status of the transaction (whether individual participants claim that their interests have been met, or not) is very readily conferred to a computer process- independent of whether the computer has the means to adequately represent the real world issues underlying that claim. Thus a computer instantiating the ‘conversation for action’ has the useful ability to model the status of the current social reality independent of any external reality on which social claims may be based.
This transactional view of speech acts has significant applications in many areas in which (human) individuals have had different roles- for instance- a patient and a physician might meet in an encounter in which the patient makes a request for treatment, the physician responds with a counter-offer involving a treatment she feels is appropriate, and the patient might respond, etc. Such a “Conversation for Action” can describe a situation in which an external observer (such as a computer or health information system) may be able to track the ILLOCUTIONARY (or Speech Act) STATUS of negotiations between the patient and physician participants even in the absence of any adequate model of the illness or proposed treatments. The key insight provided by Winograd and Flores is that the state-transition diagram representing the SOCIAL (Illocutionary) negotiation of the two parties involved is generally much, much simpler than any model representing the world in which those parties are making claims- in short- the system tracking the status of the ‘conversation for action’ need not be concerned with modeling all of the realities of the external world- a conversation for action is critically dependent upon certain stereotypical CLAIMS about the status of the world made by the two parties. Thus a “Conversation for Action” can be readily tracked and facilitated by a device with little or no ability to model circumstances in the real world other than the ability to register claims by specific agents about a domain.
Uses in technology

In making useful applications of technology to domains such as healthcare, it is helpful to discriminate between problems which are very, very hard (such as deep understanding of pathophysiology as it relates to genetic and various environmental influences) and problem which are relatively easier, such as following the status of negotiations between a patient and a health care provider. Speech Act (Illocutionary) Analysis allows for a useful understanding of the status of a negotiation between (for instance) a health care provider and a patient INDEPENDENT of any well-accepted credible and comprehensive understanding of a disease process as it might apply to that patient. For this reason, systems which track the status of PROMISES and REJECTED-PROPOSALS and ACCEPTED-PROMISES can help us to understand the situations in which (human or computer) AGENTS find themselves as they attempt to fulfill ROLES involving other agents, and such systems can facilitate both human and human-computer systems in achieving role-associated goals.
In multiagent universes

Multi-agent systems sometimes use speech act labels to express the intent of an agent when it sends a message to another agent. For example the intent “inform” in the message “inform(content)” may be interpreted as a request that the receiving agent adds the item “content” to its knowledge-base; this is in contrast to the message “query(content)” which may be interpreted (depending on the semantics employed) as a request to see if the item content is currently in the receiving agents knowledge base. There are at least two standardisations of speech act labelled messaging KQML and FIPA.

Thomas Reid – Social and Solitary Acts

March 19, 2011 Leave a comment

Reid’s technical term for such uses of language as promisings,warnings, forgivings, and so on, is ‘social operations’. Sometimes he also calls them ‘social acts’, opposing them to ‘solitary acts’ such as judgings, intendings, deliberatings and desirings. The latter are characterized by the fact that their performance does not presuppose any ‘intelligent being in the universe’ in addition to the person who performs them. A social act, in contrast, must be directed to some other person, and for this reason it constitutes a miniature ‘civil society’, a special kind of structured whole, embracing both the one who initiates it and the one to whom it is directed.

Will That Be Coordination, Cooperation, or Collaboration?

November 11, 2009 Leave a comment

The Idea: Three Words: Coordination, Cooperation, and Collaboration, are often used interchangeably. They shouldn’t be.

Recently I specified the requirements for collaboration:

Collaboration entails finding the right group of people (skills, personalities, knowledge, work-styles, and chemistry), ensuring they share commitment to the collaboration task at hand, and providing them with an environment, tools, knowledge, training, process and facilitation to ensure they work together effectively

but I didn’t define the term. The term is being cheapened (“collaboration tools”, “collaborative environments”) to the point where in many people’s minds it’s indistinguishable from cooperation and coordination, which are less elaborate and less ambitious collective undertakings. How can we differentiate between these terms in a meaningful way? Here are a few ways that I think they differ:

Coordination Cooperation Collaboration
Preconditions for Success (“Must-Haves”) Shared objectives; Need for more than one person to be involved; Understanding of who needs to do what by when Shared objectives; Need for more than one person to be involved; Mutual trust and respect; Acknowledgment of mutual benefit of working together Shared objectives; Sense of urgency and commitment; Dynamic process; Sense of belonging; Open communication; Mutual trust and respect; Complementary, diverse skills and knowledge; Intellectual agility
Enablers (Additional “Nice to Haves”) Appropriate tools (see below); Problem resolution mechanism Frequent consultation and knowledge-sharing between participants; Clear role definitions; Appropriate tools (see below) Right mix of people; Collaboration skills and practice collaborating; Good facilitator(s); Collaborative ‘Four Practices’ mindset and other appropriate tools (see below)
Purpose of Using This Approach Avoid gaps & overlap in individuals’ assigned work Obtain mutual benefit by sharing or partitioning work Achieve collective results that the participants would be incapable of accomplishing working alone
Desired Outcome Efficiently-achieved results meeting objectives Same as for Coordination, plus savings in time and cost Same as for Cooperation, plus innovative, extraordinary, breakthrough results, and collective ‘we did that!‘ accomplishment
Optimal Application Harmonizing tasks, roles and schedules in simple environments and systems Solving problems in complicated environments and systems Enabling the emergence of understanding and realization of shared visions in complex environments and systems
Examples Project to implement off-the-shelf IT application; Traffic flow regulation Marriage; Operating a local community-owned utility or grain elevator; Coping with an epidemic or catastrophe Brainstorming to discover a dramatically better way to do something; Jazz or theatrical improvisation; Co-creation
Appropriate Tools Project management tools with schedules, roles, critical path (CPM), PERT and GANTT  charts; “who will do what by when” action lists Systems thinking; Analytical tools (root cause analysis etc.) Appreciative inquiry; Open Space meeting protocols; Four Practices; Conversations; Stories
Degree of interdependence in designing the effort’s work-products (and need for physical co-location of participants) Minimal Considerable Substantial
Degree of individual latitude in carrying out the agreed-upon design Minimal Considerable Substantial

Where do teams, partnerships, think-tanks, open-source and joint ventures fit in this schema? The general definition of a team is an interdependent group, which suggests that collaborative groups are teams, coordinated groups are not, and cooperative groups may or may not be. Partnerships and joint ventures are both, I would argue, primarily cooperative undertakings, whose objectives evolve over time. Open-source developments can run the gamut among all three types of undertaking. So theoretically can think-tanks, though in reality most think-tank work is solitary and not really collaborative. Even the work of scientists on major international projects is, I am told, substantially individual, with a lot more coordination and cooperation than true collaboration.

The last two rows of the above chart may seem somewhat paradoxical. It is relatively easy to coordinate the activities of a ‘virtual’ group that must work remotely and asynchronously, and much harder (but not impossible) to achieve virtual collaboration, especially if the collaborators already know each other. But once the ‘design’ of the collective work-product is done, the implementation work of a coordinated group is usually very explicit, while the implementation work of collaborators is necessarily more improvisational.

So what? Well, in many cases, collective work may be dysfunctional because it is organized as one of these types of undertaking when what is needed is another type. Or, based on a misunderstanding of the nature of the collective effort, the wrong resources and tools are provided, or the preconditions for success are not met. And collaboration is not always a better approach than coordination or cooperation. In situations where the Wisdom of Crowds is valuable (prediction, optimization and coordination problems), independence of ‘crowd’ members is essential, and cooperative or collaborative processes can lead to ‘groupthink’ and actually detract from the crowd’s ‘wisdom’. There is nothing more frustrating than being invited into a supposedly empowered, collaborative team and then being charged with a task that needs nothing more than a good project coordinator.

It all comes down to what you are trying to accomplish. The ‘Purpose of Using This Approach” row of this chart is therefore perhaps the most important. A hammer, a wrench and a screwdriver are not interchangeable tools, and none is best for all situations.

Categories: Uncategorized

Cooperation vs. Collaboration vs. Coordination

November 11, 2009 Leave a comment

Cooperation (from Latin co- + operari to work) and collaboration (from Latin com- + laborare to labor) are synonyms, with cooperation being the more common term. Both refer to working together to achieve a goal. Collaboration is used more to describe intellectual, inter-organizational joint work, (and also working with an occupying enemy force). Coordination (from Latin co- + … ordinare to arrange) refers to harmonious movement of different parts or groups; the organization of different parts to work together.
Merriam-Webster, Encarta, Cybernetics Dictionary
A concise and clear general definition is from (Malone and Crowston, 1991): “Coordination is the act of managing interdependencies between activities.” Coordination or Co-Ordination is “the ability to reduce all-together, in oder to generate an only one all.” (Alessio Bissoli, 2006) Coordination, co-ordination is the regulation of diverse elements into an integrated and harmonious operation. Coordination means integrating or linking together different parts of an organization to accomplish a collective set of tasks.

*coordination* is required for all collective activities (bringing the parts together in a way that yields synergy)
* cooperation* employs linear procedures to leverage collective potential (if each participant does exactly ‘x’, then a predictable ‘y’ is the result)
*collaboration* is different in that through nonlinear creative processes (no one knows exactly what they have to do until they do it, and even then the outcome is unknown) a shared understanding is created amongst the participants – one unique to those participants and that collaboration.

By way of example;
coordination = a web search: bringing together parts of the web in a way that creates meaning, i.e. synergy.
cooperation = social bookmarking: if many people tag their webpages using a particular platform, and a particular procedure, a resource much larger than any individual could develop may be generated
collaboration = Wikipedia editing: read an entry, contribute in any number of modes (form, content, discussion, etc) and from an infinite number of perspectives (the multiplicity of opinion and creative volition) one becomes part of a highly complex negotiation of a shared understanding (no one owns or comprehends the whole but contributes a part of it).

Categories: Uncategorized

Great article from McKinsey on Collaboration

November 11, 2009 Leave a comment

Using technology to improve workforce collaboration

27 October 2009

Knowledge workers fuel innovation and growth, yet the nature of knowledge work remains poorly understood—as do the ways to improve its effectiveness. The heart of what knowledge workers do on the job is collaborate, which in the broadest terms means they interact to solve problems, serve customers, engage with partners, and nurture new ideas. Technology and workflow processes support knowledge worker success and are increasingly sources of comparative differentiation. Those able to use new technologies to reshape how they work are finding significant productivity gains. This article shares our research on how technology can improve the quality and output of knowledge workers.

Knowledge workers are growing in numbers. In some sectors of the economy, such as healthcare providers and education , they account for 75 percent of the workforce; in the United States, their wages total 18 percent of GDP. The nature of collaborative work ranges from high levels of abstract thinking on the part of scientists to building and maintaining professional contacts and information networks to more ground-level problem solving. Think of a buyer for a retail chain whose distributed web of contacts span fashion designers in Tokyo to experts on manufacturing in Brazil.

For companies, knowledge workers are expensive assets—earning a wage premium that ranges from 55 percent to 75 percent over the pay of workers who perform more basic production and transaction tasks. Yet there are wide variations in the performance of knowledge workers, as well as in their access to technologies that could improve it. Our research shows that the performance gap between top and bottom companies in collaboration-intense sectors is nine times that of production- or transaction-intense sectors.1 And that underscores what remains a significant challenge for corporations and national economics alike: how to improve the productivity of this prized and growing corps of workers (Exhibit 1).

Exhibit 1: The increasing importance of collaboration

Unfortunately, the productivity measures for collaboration workers are fuzzy at best. For production workers, productivity is readily measured in terms of units of output; for transaction workers, in operations per hour. But for knowledge workers, what might be thought of as collaboration productivity depends on the quality and quantity of interactions occurring. And it’s from these less-than-perfectly-understood interactions that companies and national economies derive important benefits. Consider the collaborative creative work needed to win an advertising campaign or the high levels of service needed to satisfy public citizens. Or, in a similar vein, the interplay between a company and its customers or partners that results in an innovative product.

Raising the quality of these interactions is largely uncharted territory. Taking a systematic view, however, helps bring some of the key issues into focus. Our research suggests that improvements depend upon getting a better fix on who actually is doing the collaborating within companies, as well as understanding the details of how that interactive work is done. Just as important is deciding how to support interactions with technology—in particular, Web 2.0 tools such as social networks, wikis, and video. There is potential for sizeable gains from even modest improvements. Our survey research shows that at least 20 percent and as much as 50 percent of collaborative activity results in wasted effort. And the sources of this waste—including poorly planned meetings, unproductive travel time, and the rising tide of redundant e-mail communications, just to name a few—are many and growing in knowledge-intense industries.

There are some companies that already are tackling aspects of this collaboration–technology nexus. Cisco Systems, for example, set out to improve interactions between its technology specialist sales teams and enterprise customers. Frequent travel and stepped-up job requirements had resulted in overstretched teams whose effectiveness had become diminished. Cisco tackled the problem by mandating the use of its own video technologies, as well as other collaboration tools. The plan was straightforward: reach more customers and business partners by shifting a large portion of in-person meetings to virtual interactions. Policy and governance changes ensured that technology use became part of daily workflows and not an added task. Over an 18-month period, the initiative saved Cisco more than $100 million in travel and business expenses and reduced the company’s carbon emissions by 24 million metric tons. Internal surveys showed that 78 percent of the targeted employees reported increased productivity and improved lifestyles without diminishing customer or partner satisfaction.

Similarly, P&G has also adopted Web-based technologies to forge better links with partners and customers and to improve the flow of ideas across corporate and regional boundaries. It also set up ideas markets to gather and filter offerings from across the company and signed on with crowd-sourcing network InnoCentive to tap external experts to solve specific problems. In addition, the company used a collaboration strategy to broaden its product offerings and get more of them to market at a faster pace. It set a target of raising the proportion of new products sourced from outside its walls to 50 percent, from 35 percent. Besides the savings P&G realized from nearly a thousand fewer business trips each month, the company met its goals of shorter product cycle times and greater product innovation from external sources.2

But most companies are only beginning to take these paths. That’s because, in many respects, raising the collaboration game differs from traditional ways of boosting productivity. In production and transaction work, technology use is often part of a broader campaign to reduce head counts and costs—steps that are familiar to most managers. In the collaboration setting, technology is used differently. It multiplies interactions and extends the reach of knowledge workers. That allows for the speedier product development found at P&G and improved partner and customer intimacy at Cisco. In general, this is new terrain for most managers.


The interactive graphic that accompanies this article provides a synthesis of our view on how organizations can improve collaboration. It draws upon our work with companies, non-profit organizations as well as our own research and that of outside sources. The graphic’s multilevel approach to improving collaboration is based on the following steps:
1) classify workers by their workflow profile – the daily activities they do to perform their job
2) match new technologies to the workflows to extend collaboration efforts, improve effectiveness, and reduce inefficiencies

click to launch interactive feature

Click the image above to launch the interactive in a new window.

The discussion that follows is both a guide to the interactive and an elaboration on the thinking behind it.

Defining knowledge workers and how they work

As a first step, companies should take a fresh look at their workers, classifying them by how they collaborate. We have identified 12 types of collaboration work (see the interactive exhibit, “Collaboration types and tools”). Each of these is broken down into the day-to-day interactive activities (or workflows) that comprise these work classes. Today most organizations segment their employees by their positions within the corporate hierarchy. They are identified by job titles that, in many cases, obscure the kind of work they actually do. Take the title of manager. Seen through a collaboration lens, this title is often applied to several different collaboration types: in some, a manager builds teams, develops team members’ expertise, sets objectives, and encourages results; in others, a manager is more of an administrator who repeatedly executes processes (such as monitoring the work of others) to a certain standard. Many companies also award the title of manager to the consultant collaboration type – individual contributors who convene or take part in virtual teams to solve problems. Thus, improving collaboration should start with understanding employee workflows to get a more refined view how their work gets done.

At the same time, functional groups—such as sales and marketing, finance, and strategy—within organizations often divide into an array of job classifications that multiply over time. Yet these classifications don’t reflect the interactive aspects of the work. In our experience, jobs within many functional organizations can be grouped into a small number of collaboration types that reflect such interactions. This simplifies the task of improving collaboration. Take the case of one sales organization, where work was splintered into 50 distinct roles. Using interaction requirements as our guide, we found these roles reflected three basic collaboration types: sales people, managers, and administrators. In most sales organizations, each type of sales job is distinct and siloed: employees doing telesales and enterprise sales are given distinct corporate job codes and internal classifications, because they may have somewhat different skill sets. But the process workflows of these jobs are essentially the same—employees receive sales plans or quotas from management, build account plans, and generate and act upon sales leads, etcetera.

Applying technologies

Improving employee collaboration also depends on selecting the technologies that support their interactions. Companies can best do this by 1) understanding the specific requirements of interactive tasks; 2) identifying which tasks create disproportionate value for the organization; and 3) determining the types of inefficiencies and wasted efforts that bog down many interactions.

Requirements. Even within a given group of collaboration workers, the required interactions and technology solutions may vary substantially. For example, collaboration between two individuals working together on an account plan is very different from that of several dozen individuals meeting to coalesce around a sales strategy. Collaboration work, we have found, varies over a dozen such dimensions—including the scope of the collaboration (number of parties involved), which way information is flowing among the participants, whether participants exchange information equally, and whether the interactions stretch across functional or corporate borders. We examine these dimensions when assigning technologies to collaboration workflows.

Value. Not all interactions are created equal. Some organizations will prioritize focus on collaboration types and even specific activities based on their relative contribution to the organization’s objectives. For Cisco, this means a strong focus on partner and customer intimacy. For P&G, it is about increasing access to new ideas and speed to market. Other common objectives for collaboration initiatives include better talent management, business agility, and a reduced carbon footprint. Imagine the economic benefits for organizations able to double the number of inspired employees or triple the volume of new product releases.

Waste. We have documented 10 types of collaboration waste (Exhibit 2). In the case of managers, for example, effective collaboration demands that the manager not only agrees on specific objectives but also that he /she can communicate how to achieve them. Those efforts can be undermined by divergence (for example, sending teams in different, conflicting directions), misunderstanding (for instance, gaps between the message communicated and the resulting execution), and under- or overcommunicating, as well as other types of flawed interactions.

Exhibit 2: Waste in collaboration

Web technologies can diminish the wasted efforts. Take the case of “searching”: inefficiencies arise when a staffer is unclear about which colleague within the organization may be tapped for specific knowledge to solve a problem. One remedy is network mapping, a technology that plots work relationships among individuals, reducing search time by providing insights into the pools of knowledge within the company,

Meanwhile, as more of knowledge workers’ output involves digital content, other forms of waste multiply. Fact checking, annotations, and edits lead to handoffs and serial revisions that we term “interpretation” waste. Similarly, as this digital information often must serve audiences across distribution channels—printed documents, PowerPoint slides, and videos, for example—inefficiencies arise from “translation.” At times content is needlessly reworked or even distorted as it crosses channel boundaries. Collaboration technologies such as Google Docs, Adobe’s Acrobat.com, or Microsoft’s OfficeLive allow for coauthoring and co-editing content documents. Since parties are frequently tackling the same project at the same time, translation and interpretation waste is reduced.

From our research on workflows across a variety of companies we are able to arrive at benchmarks for the most effective way of performing a task. With that knowledge we can identify inefficient practices and select technologies with which to improve them.


Furthering collaboration excellence demands mind-sets and capabilities that are unfamiliar and sometimes even counterintuitive to many business managers. It requires trusting your collaboration workers to arrive at creative solutions rather than enforcing top-down policies. Business managers should allow time and provide forums for collaboration workers to brainstorm solutions to productivity problems. Corporate technology providers will need to provide tools that are flexible enough to enable experimentation, so that usage and adoption are widespread.3

While the broad gains from better workforce collaboration have been apparent for some time, the management approach and tools needed to capture the benefits at the company level have been missing. By using the methodology outlined here, companies can improve productivity among the growing ranks of their knowledge workers.

1 This was measured as the average earnings before income, taxes, depreciation and amortization per employee.

2 Larry Huston and Nabil Sakkab, “Connect and develop: Inside Proctor & Gamble’s new model for innovation,” Harvard Business Review, March 2006, Volume 84, Number 3, pp. 58–66.

3 Michael Chui, Andy Miller, and Roger P. Roberts, Six ways to make Web 2.0 work, September 2009.
Jacques Bughin, Michael Chui, and Andy Miller, How companies are benefiting from Web 2.0, September 2009.

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