Optimizing Knowledge Networks

Executive Summary

Knowledge transfer problems pervade every organization. supply chain practices have already helped us develop sophisticated and efficient processes for the management of tangible products. so why not use them to help achieve visibility and manage the intangible and sometimes elusive concept of organizational knowledge?

Knowledge is dynamic, mobile, and time sensitive. Unfortunately, in most organizations, knowledge  holds many of the opposite characteristics  static,  immobile, and dated. The critical reason for this is  the lack of adequate knowledge transfer protocols.  Knowledge created in one part of the organization or  residing in the mind of an employee has a difficult  time moving to other parts of the organization. In  many cases, there are large delays even if knowledge transfer is possible. 

Moreover, when knowledge is transferred, it may get damaged or destroyed during the transfer process, resulting in a depreciated value. Many companies complain of cumbersome knowledge flows  between individuals, departments, and divisions, highlighting the fact that knowledge is trapped and powerless to deliver value. Organizations frequently feel the disappointment of knowing that an answer is within reach but not delivered in the time frame or format needed.

Remedying knowledge transfer problems is a significant concern for organizations. Today, there is a multitude of work underway that focuses on eradicating pitfalls of knowledge transfer. Studies include the dynamics of knowledge transfer from a psychological perspective that is, understanding the motivations of the producers and consumers of knowledge. Other studies are looking at tools such as social network analysis to identify and understand the informal networks in the organization, and even others have examined human resource interventions such as cross-functional teams and job rotations as a means to move knowledge from one part of the organization to another.

In this article, we will analyze lessons from supply chain management for their application in knowledge transfer. We believe that examining best practices in the supply chain realm can point us to innovative solutions. After all, in the final analysis, supply chains are concerned with transferring products to the consumer using the most optimal paths. Knowledge transfer is the act of moving knowledge created in one sector of the organization to another sector in an optimal and reliable manner.

Looking at knowledge transfer through a supply chain lens allows us to see knowledge as a product. And it lets us use processes to mobilize and optimize knowledge’s value in the organization.

Knowledge as a Product

Knowledge is often treated in a common manner or typecast into a single role. It is not uncommon to find knowledge management systems that contain a hodgepodge of various kinds of knowledge, including everything from how to fix a printer to sales presentations for client engagements. The problem with this approach is severe: The organization has a difficult time discerning what represents knowledge, and the organization cannot focus its management efforts on knowledge objects based on their characteristics and value. 

Let’s examine how products are managed in a supply chain system. Products are classified, segmented, catalogued, and attended to according to their characteristics. Many companies have an inventory class system or a prioritization approach that distinguishes parts based on price, likely number of customers, historical demand, or supplier lead-time. For example, an expensive part with a long lead-time might be an AA part number; a low-cost commodity part might be designated CC. The inventory policies and the procurement strategies for each category are designed to leverage value and manage associated liabilities and risks. That AA part number with high usage and value might be managed daily by material management, in contrast to a CC part that gets a quarterly review. 

Information systems are used to monitor the transformation of products as they move through the supply chain. The systems provide information of varying levels of details, at varying intervals, and to various stakeholders depending on the nature of the product being examined. For instance, if a product is of high value (perhaps it’s the most expensive part of a given product), an organization can use RFID tags to track its movement. Information systems can also provide information on how much of a given product was used, how much was defective, and who produced defective parts. Today, systems and well-designed workflows automate the information flow, offsetting what would be a prohibitive individual analysis on a daily basis. Using this information intelligently allows us to optimize resources as well as inventory. 

Consider the act of classifying knowledge. Hewlett-Packard’s classification scheme for knowledge provides an excellent example. At the lowest level, they classify personal knowledge that represents knowledge stored in the minds of subject matter experts and their personal artifacts. At the next level, there is community knowledge, which is know-how captured and housed in distribution lists and discussion forums. Next, they classify knowledge representing proven practices, such as presentation templates and knowledge briefs. Finally, HP has institutional knowledge representing  the knowledge embedded in the organization that governs behavior, such as standardized sales and delivery models, and process documentation. 

It is important for organizations to take a proactive and concerted effort to segment knowledge. Segmentation can be done on several dimensions. We suggest that the organization consider the concept of resource usefulness when segmenting knowledge assets. They must adopt a resource-based view, asking if the knowledge object is rare, non-substitutable, non-imitable, and valuable. 

Most knowledge objects will meet the conditions of valuable, but only a select group of an organization’s knowledge resources will meet the requirement of rarity. While almost all knowledge can be argued to provide value, it does so in an operational sense — aiding in getting routine tasks
complete. In contrast, knowledge objects that meet the condition of uniqueness can contribute to strategic goals. The conditions of non-imitation and non-substitutability are critical. Knowledge that cannot be imitated easily by members of the organization or by other organizations is truly valuable because it is not easily subject to acts of substitution. It is this kind of knowledge that forms the basis for competitive advantage. 

Segmenting knowledge objects in the organization leads to a better-focused management agenda. The knowledge objects that do not meet any of the conditions should not be the focus of management efforts. Those that meet the basic condition of being valuable should be managed in a limited fashion since the return on those assets is minimal. Critical organizational resources are those that cannot be imitated or substituted with ease. These must be the focus of knowledge management efforts since they have the potential to truly deliver corporate value. Segmenting knowledge helps address the cost-benefit issue because it enables resources to be focused on the most critical knowledge assets. 

Organizations may want to dedicate a group (or individual) as knowledge gatekeepers the equivalent of supply chain inventory managers. These gatekeepers will evaluate knowledge contributions and decide which characteristics of a resource they meet. Based on this evaluation,
knowledge contributors can be given the appropriate management attention. Moreover, they can also be housed on different knowledge management systems depending on their significance to operational and strategic goals of the organization. In addition, segmenting knowledge objects will ensure that the highly sensitive and most valuable products are given the right protective measures (such as being housed on a different system or having password controls). The most valuableknowledge assets should not be capable of walking out the door or be bantered around without authorization, both of which could lead to a depreciation of value. 
 

 Place knowledge in context

Once we have categorized knowledge in terms of classes of products, the next item is to map the processes that require knowledge. Put another way, we need to understand the work practices that generate, consume, distribute, store, and even protect knowledge. Does knowledge ever move as anticipated from A to B to C? We might imagine that knowledge follows a linear pattern, but that is seldom the case. The flow is as dynamic as the knowledge itself.

Supply chain is becoming an outdated descriptive. Our supply chains have evolved into supply networks. As the name implies, supply chains are a series of inter-connected linear links that bridge each entity with the next. This represents the traditional customer/supplier relationships often found in the same geography. Today, rather than links via chains, we have links via networks.

Networks are more complex than chains and are made up of multiple entities interconnected in non-linear and linear fashion. The recent knowledge transfer renovation in response to organizational transformation provides a similar scenario for analysis and a case for mapping knowledge processes. In the past, when organizations were hierarchical and command-and-control structures were typical, it was not uncommon for knowledge to move in linear paths. In best-case scenarios, knowledge moved from the upper hierarchical echelons down to the people in the front lines. Today, organizations are flatter, and horizontal integration is salient.

Moreover, rather than organizations being deterministic and planned, they are emergent and flexible. Knowledge movements are hence not easy to govern, as they are subject to high volatility and dynamism.

Some of the more dynamic supply chains have pushed this technique further, relying on software and computer programs that allow an organization to update the documented processes online and continuously model changing variables. The combination of mapped process and automation support powerful simulation exercises. This advanced approach considers associated costs and elapsed time by process step and can extend to freight options in order to recommend direct routes or most efficient process flows.

First, let us consider a system for explicit knowledge the intranet portal. Today, these are passive and simply display knowledge. It is like going into a factory and seeing a pile of raw materials in room one, tools in room two, and a manual on how to use them in room three. An employee must put forth a lot of effort to consume such knowledge. Intranets can be redesigned using the principles of workflow and layout design to enable employees to consume the knowledge in raw form and build a finished product from it. The advancements in the fields of virtual reality-based engineering can also be imported to help manage and consume explicit knowledge.

Second, consider tacit knowledge, which is transferred primarily through people. How cumbersome is it for you to contact domain experts in your organization? Do you even know who the experts are on various issues? Do you know how to contact them? These are difficult issues faced by many organizations. Couple these questions with some of the dynamics in the workplace, and we have a major problem on our hands. Re-engineering of organizations is pervasive. People come and go from organizations and so does expertise. With the advent of distributed and virtual work, there is no telling when a person will be at the office, available by phone, or even be online to access e-mail. Hence, tacit knowledge is in a constant state of flux in organizations.

Similarly, efforts must be undertaken to map tacit knowledge. This will prevent an organization from losing knowledge through ad-hoc downsizing efforts. Moreover, it will enable the organization to plan for redundancy and failures. We must depict how fragile an organization is to the loss of knowledge possessed by a person. This will help ensure appropriate backups are in place and tacit insights are captured. Many organizations realize the knowledge drain only after the downsizing effort and eventually hire back old employees at twice or three times their original salaries.

Mobilizing knowledge

We are now ready to use the mapping details to start mobilizing knowledge via the network. While understanding that inputs and process steps are important, knowledge transfer culminates in delivery. The objective in mobilizing is the output or final step in a transfer process. It is critical to explore the actual movement of knowledge because in effectively mobilizing this asset, we release trapped knowledge and return its power to deliver value.

Similar to a supply chain, the right knowledge is expected to be available to authorized consumers when needed and in an appropriate format. Extensive processes to capture knowledge and repositories to retain the lessons from across the organization can provide a return on investment only if they are delivered to the consumer on time and in a usable format. This becomes significantly more complex when the sender and the receiver reside in different departments, divisions, or countries. An emphasis on the tactical steps to ensure the transfer is executed effectively is necessary at this stage.

Knowledge management practitioners need more tactical tools and guidelines for better mobilization. Until a comprehensive model is available, the supply chain provides a baseline to draw from to drive tactical improvement for knowledge transfer. Supply chain guidance includes fundamental tactics: Put mapped processes to work, anticipate the unexpected, and provide an operational plan. Understand knowledge demand characteristics and develop knowledge sources. Work collaboratively by setting expectations that will satisfy knowledge demand. Deliver knowledge by making the communication channels clearly visible and accessible.

Track the performance of channels and improve them in a routine manner. Fuel the knowledge asset by using and reusing knowledge, adding experience and value to the organization. Knowledge management practitioners can also ook to supply chains for insight on protocols and mediums to enable mobilization.

In contrast, effective supply chains typically have clear escalation paths or protocols to support day-to-day as well as critical issues.

A sub-question related to the medium is that of timing. Should knowledge be pushed to individuals or should they pull it from central sources? Disagreements or lack of clear protocols will result in either famine or overwhelming abundance, both of which are not optimal. In every organization, knowledge gets ignored because there is no agreement on the path, medium, and timing of transfer.

Optimizing the network

A fundamental challenge in knowledge transfer is determined by the knowledge asset itself and its perceived value to knowledge users. This is as simple as having the right knowledge in the appropriate format available at any given time. The wrong knowledge assets can slow down a system consuming transfer resources. Too often, knowledge created in an organization by employees cannot be used by other employees. A lack of awareness,
compatibility, and integration of the existing knowledge decreases the likelihood of reuse or knowledge turns.

For example, consider a company’s engineering/sourcing procedures. In many cases, the integration between the engineering team (designing in new components), the procurement team (sourcing those components from suppliers), and the commercial bid team (preparing quotes for new products or customers) makes little use of each other’s knowledge. The reasons are not surprising lack of consistent documentation, little trust between departments, or no cross-functional awareness and the result is failed product development. Reuse or knowledge turns are critical to avoid recreating an existing asset and to extend value by building from a knowledge base for incremental organizational knowledge. What discipline is in place to assess and optimize knowledge turns?

Supply chains are most often described by their inventory turns. This metric is an indicator to executives, customers, and investors, each for their own purposes. Internally, executives can rely on inventory turns displayed on a management dashboard to provide a quick measure of asset utilization. Customers might look to turns as an indication of the product freshness, while investors translate turns into a measure of the company’s overall performance as a sales and material management ratio. Successful companies have adopted the discipline to capture inventory turns and drive improvements to optimize assets. Supply chains compete on this metric among others so best-in-class turns by industry are recognized and used as a comparative
measure.

Inventory levels within supply chains are calculated in part by customer demand. A comprehensive understanding of the product lines and SKUs the market requires is a critical variable. Supply chains are also subject to demand variability and uncertainty. While even the best supply chains cannot eliminate variability, they can mitigate risk by calculating optimal levels of inventory at various stages (finished goods, work in process, raw inventory). This approach balances the need to increase inventory turns while preserving service levels.

Knowledge assets require the same discipline that inventory has received. In raising awareness of knowledge objects’ increasing value as they are used more frequently across the organization, similar results in the form of knowledge turns can be expected. Capturing the knowledge demand patterns and using that to project future requirements makes good use of history and arms an organization to plan for more of the unexpected. An organization may consider experimenting with the concept of knowledge markets here.

Consider a traditional bazaar: Goods that are in high demand are found in most stores because there is little risk that they won’t be sold. Goods that are new or expensive are shelved in boutique stores or are put at the front of traditional stores on a trial basis to see how they are received. The driver behind what is stocked and sold is customer demand. The market adjusts its behavior to match customer demands. Similarly, we can devise knowledge markets in organizations.

In most organizations, knowledge is not priced. Most knowledge exchanges can be seen as an implicit barter. Employees exchange their insights with peers in the hopes that their peers will return the favor when needed. No explicit price is set for the knowledge or know-how exchanged.

This behavior contributes to several problems. First, producers of knowledge do not get the recognition they deserve. In most organizations, we see the prevalence of the 80/20 rule: 80 percent of the knowledge needed to run the organization is provided by 20 percent of the employees. Yet they are seldom rewarded. Second, the lack of incentives leads to a system of disincentives. Individuals who share their knowledge do so under the assumption that the rest of the organization will follow suit. However, due to lack of overall participation in  knowledge management, the original producers do not get the return on their investment of time and energy  spent codifying their insights. After all, they spend effort codifying knowledge for its consumption by peers, not by themselves. Third, the lack of a pricing scheme makes the valuation of knowledge difficult and cumbersome.

This makes managing and quantifying organizational knowledge a daunting challenge. Devising metrics to gauge an organization’s knowledge assets must begin with pricing individual knowledge pieces. Fourth, the lack of pricing schemes makes version control a problem. Since no rewards are attached to production of knowledge objects, there can be multiple pieces of the same knowledge object, which makes searching times for requisite knowledge unbearable.

Knowledge markets are usually facilitated through an intranet portal site. The knowledge management group in the company can act as a central clearinghouse for knowledge. Under this centralized regime, the group is responsible for both evaluating knowledge goods submitted for trading and for setting prices. Auction-based markets for knowledge goods are also a possibility. Here, a knowledge producer can offer licenses to his or her know-how to the highest bidder. Seller-based regimes are the most popular today. Here, sellers set the price of their knowledge product. The price can be determined by the time multiplying the time spent to create the knowledge by the agent’s pay per unit of time. In this scenario, agents must have the necessary amount of allowance points or monetary proxies to purchase a knowledge object. Agents get their purchase allotment through selling knowledge objects they created. This limits the free-riding problem of knowledge generated by few and consumed by many. Moreover, it enables the organization to track who is generating knowledge and whose knowledge is being sold.

The knowledge market addresses an important element — the destruction of old and outdated knowledge that makes the collection of knowledge easier to work with for the organization. Excessive knowledge on products, processes, and practices can actually have negative consequences. Problems can occur in terms of knowledgeoverload, in which case there are multiple versions of the same knowledge on aspects of products and services. Excessive knowledge also leads to poor search times when knowledge retrieval is conducted.

Much like a supply chain must regularly evaluate inventory and the return or write-off assets without value, old knowledge must be purged in a timely fashion or organizational change becomes difficult. Old routines and practices are institutionalized, which makes any efforts for future change and thinking creatively impossible. As such, the organization will make only incremental and minor improvements on this past knowledge without much hope for seeing and seizing the future of the marketplace. This consequence has been evident in the past with companies such as Polaroid, which lost ground in the advent of digital imaging, and Swiss watchmakers, which lost ground to leaner and more optimized Japanese competitors.

The knowledge network

Building, maintaining, and optimizing organizational knowledge networks is a critical agenda. Failure to have a viable knowledge network in place will result in poor attainment of organizational goals, limited innovations, erosion of market share, and perhaps even serious demise of the organization. A study of supply chains and their evolution to network management principles serves as a solid example, rich in strategy and tactics for optimal performance.