Dennis D. McDonald (ddmcd@outlook.com) is an independent consultant located in Alexandria Virginia. His services and capabilities are described here. Application areas include project, program, and data management; market assessment, digital strategy, and program planning; change and content management; social media; and, technology adoption. Follow him on Google+. He also publishes on CTOvision.com and aNewDomain.

Bringing Knowledge, Relationships, and Experts Together in the Enterprise

By Dennis D. McDonald

Introduction

In the first article in this series I commented on the web based evolution of systems for matching up experts (and their expertise) with users based on relationship management and social software technologies. Since then I've found out more about the "expertise management" aspects of knowledge management. Related terms are "expertise management systems," "expertise location," and "expert locators."

In this article I discuss the implementation of such systems within large organizations. Key points include:

  • Large enterprises operate according to their own rules.
  • All organizations manage knowledge and expertise.
  • Individuals with specialized knowledge - "experts" - play key roles in the production, management, and use of knowledge.
  • Relationship management and social software technologies have great potential for making the most of the role of the expert within the enterprise.

Enterprises operate according to their own rules

Social software and collaborative applications such as blogging, MySpace, wikis, and Flickr have taken off "outside the firewall" through rapid adoption by writers, young users, and others not constrained by enterprise restrictions on communication and collaboration.

Adoption of such technologies within enterprises has been slower. Reasons include:

  • Reliance on technical architectures (e.g., web hosting) viewed by some as inappropriate for managing certain types of corporate information.
  • Resistance by management  to a perceived "loss of control" over both message content and who the sources and targets of enterprise related messages are.
  • Dependence on technical architectures that may be viewed by IT departments as difficult to support or incompatible with current corporate standards.

Viewed by evangelists of "new technology" these points are viewed as examples of old fashioned resistance. Viewed by corporate managers faced with justifying every penny, these points just seem rational.

As with most things, the truth is somewhere in between, especially since we are discussing intangible and difficult to quantify concepts such as "knowledge" and "expertise." Yet it is just this intangible nature of "knowledge" that may make the management of relationship based expertise more acceptable within the organization; more on this below.

All organizations manage knowledge and expertise

The types of knowledge that corporations need to manage, and the organizational constraints that such management needs to take into account, are different from the needs of what used to be called the "general public."

Managed corporate functions such as new product development, marketing, customer service, financial services, and manufacturing all require people with appropriate levels of experience and knowledge to operate.The resources that support these functions are usually managed so they are aligned with the goals these functions support. Appropriate knowledge and expertise are examples of such resources.

Management is concerned with how this alignment is accomplished. Management may involve imposition of constraints related to corporate knowledge that would not be found necessary, acceptable, or relevant in the context of private or public activities outside the organization. Not revealing corporate secrets to competitors is an example of one such corporate constraint.

Individuals with specialized knowledge - "experts" - play key roles in the production, management, and use of knowledge

Within  any organization there are key individuals who are especially knowledgeable about different aspects of the organizations. In fact,  expert knowledge is viewed by professionals such as Luis Suarez as an important topic within the field of Knowledge Management. Sometimes this knowledge is well aligned with the functions being managed or performed; a manager of a manufacturing operation is an expert on manufacturing, a manager of a biological research department is an expert on biological research, and so on. When stated like this, knowledge and expertise are fairly visible and assumed; managers and others responsible for a particular operation or function are assumed to be experts.

As organizations, product lines, and services become larger, more numerous, and more complex, the knowledge required becomes more complex, specialized, and potentially sharable. This is true for the work performed  by "knowledge workers," by skilled technical employees, and by any other individuals who have a variety of skills and experiences that may not be immediately required by their current job but which -- if known to others in the organization -- might provide significant value.

Unfortunately, barriers often exist to the sharing of knowledge and expertise within organizations.

One is the difficulty in knowing about someone' else's skills or experience, especially if that person is somewhere else in the organization either departmentally or geographically. That person may possess a nugget of knowledge or experience you need desperately, but unless you know about it, you're out of luck.

Another difficulty is  that organizations and how they are managed may be structurally resistant to the sharing of knowledge and expertise. The most common example is "siloed" organizations where functions and expertise are duplicated and where both horizontal and vertical information flow may be discouraged. Even within siloes, however, some organizations may discourage communication "down the chain of command." Again, the end result is that potentially valuable knowledge is not shared.

Relationship management and social software technologies have great potential for making the most of the role of the expert within the enterprise

The term "knowledge" can refer both to recorded knowledge and to the knowledge possessed by an individual. For simplicity's sake it's the latter type of knowledge that I am referring to as "expert knowledge."

Managing the location, evolution, and communication of expert knowledge within an organization is a complex process. One approach is simple: when you have a problem or question, you start calling the people in your organization you think might be able to help. Eventually, with enough calls, you may find an answer to your question. But in the process you've made multiple calls, taken a lot of time, and by the time you get an answer to the original question, the requirement may have changed.

Larger organizations put processes and systems in place to help shortcut the problem of finding out whom to call. Specialized phone directories, searchable resume banks, skill indexes, personal home pages and blogs, information analysis centers, newsletters, and document repositories are examples.

One of the problems that exists with all such systems that incorporate recorded or databased information is that they are difficult or expensive to keep up to date. An alternate approach is to focus not so much on recording and indexing details of the  type of knowledge or experience possessed by the expert, but rather, use elements of social networking technology to facilitate the creation and navigation of relationships within the organization.

How would this work in practice?  Here's one possible example:

  1. Start with a one page visual map of the functions or operations touched on by the organization. I suggest "one page" since I have a preference for hierarchical structures and a belief that focusing on "one page" has a way of sharpening one's thinking. Perhaps we can display the high level map visually (e.g., like the way Kartoo displays search query findings) or via clusters (e.g., see how Clusty displays search results). Whichever approach is selected, the map needs to be updateable either manually or via automated processes.
  2. When I move my mouse pointer over a cluster, a sub-list of topics appears, along with the number of registered "experts" - people who are listed as being able to answer questions related to the topic. (Please hold your questions about "how do you make sure the volunteers really know what they are talking about?" I'll get to that below.)
  3. By selecting a sub-topic, I'm presented with a list of names, faces, and recently asked questions for each listed expert, including the name of the person who nominated the expert if the expert was not self nominated. I'm also shown data on the overall scoring of questions answered by the expert (based on scoring provided by the questioners) as well as status information about the expert (online, in office, out of office, email accessibility, etc.). If someone isn't available I can scroll on to the next related person or the system can suggest a replacement.
  4. When I select a person to contact I click the phone or email button. It's then up to me to communicate the question and rate the quality of the result. The system handles follow up, e.g., re-calling busy signals, call/question transfer, suggesting replacement experts in case no response is received to an email, pestering me to evaluate the quality of the expert's response, etc.)

I'm sure if you have followed online mapping, mashups, picture sharing, tagging, rating of articles, tag clouds, and other examples of current web technology, you'll recognize most of the bits and pieces of the above system, which is intended to function within the enterprise.

Back to the question of "who's an expert?"  I don't know for sure how to handle this question (maybe Luis can suggest an answer?); here are some suggestions:

  • "Experts" need to know this is a serious venture and that they will be evaluated according to their availability and their performance as measured by feedback they receive.
  • System feedback will provide data on areas that may be collapsed or deemphasized; usage data may also provide feedback on areas that need to be expanded due to sudden spikes in demand.
  • The system may incorporate limits on the availability of key individuals (e.g., to enable them to do other things they are responsible for doing).
  • Experts will nominate other experts, and this "network of recommendations" will be available for examination during the search for an expert to call.
  • Automatic data mining techniques that track certain types of online transactions could also support identification of experts.

Another key element is the level of detail that must be represented for the areas of functionality and expertise.  Thought must be given to whether a single drilldown map is sufficient or whether multiple maps will be required at the top level. Since great minds may differ in terms of how best to represent the intersection between a map of expert knowledge and a map of the types of questions that experts might be asked within an organization, the system needs to be able to incorporate as much flexibility as possible.

(Personally, I'm impressed with how slickly the Apple iPod user interface operates, even for individuals with thousands of songs classified into a relatively small number of categories, only in this system, clicking on the "play" button connects the user with the expert.)

Now, there are all kinds of reasons why a system like this would be resisted within some organizations, assuming that the technical design issues and the maintenance and support costs could be justified. (I'm assuming a major reason to locate an expert is to reduce the amount of time it takes to get the answer to an important question and, as we all know, "time is money.")

One reason for resistance is simple: there will be costs associated with development and maintenance. No matter how much automation is incorporated, the system will have to be managed, and that will include constant human interface over the operation and the quality of the output.

Another reason for resistance has to do with organizational  politics and hierarchies.  In some organizations expertise does not necessarily align with organizational structure. What happens if people in one department regularly seek out an expert from another department even though they have a self-identified expert in their own? Won't the "flattening" of the organization such a results-oriented expertise management network might generate be thought of by some as threatening the status quo?

No doubt that will be true in some cases. But this is similar to the situation where a staff member moves from one department to another yet that staff member's former colleagues still call him or her even though a replacement has been put in place. People in the organization learn to adjust.

Summary and Conclusions

In this  brief article I've provided some idea of how currently available concepts and technology related to social networking might be applied in a relatively straightforward way to help organizations do a better job of providing access to the expertise that already exists in their organizations. While the "devil is always in the details" of systems such as this, I am assuming that I am not the first person to have thought about such applications and that products are already under development or are being marketed that perform some or all of the functions described above.

In any event, I'd be very interested in hearing from you concerning your reactions to the above, either positive or negative. Please use the comment form below or send an email to Dennis McDonald at ddmcd@yahoo.com.

 

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Bringing Knowledge, Relationships, and Experts Together