A Prescription for Healthy Learning Supply Networks

If we can begin in agreement that a Supply Chain is a dynamic network with a constant flow of material, information and finances we might be able to imagine it as a living entity.  We are not trying to introduce anything extra terrestrial here but rather make the critical point our supply chains need to be actively learning to survive.   Central to the organization managing its supply network is the ability to learn and manage knowledge in and across the supply chain. While the movement of physical products or services is the tangible outcomes of the supply network, these movements are predicated on how well information, knowledge, and learning is conducted by members of the supply chain, both within their operations, and also across the various partners. In this article, we will highlight some prescriptions on how to build learning programs for healthy supply chains, which will expand on the typical flow of information between supply partners.  Recommendations are structured under five major subjects that contribute to cumulative success in keeping supply chains alive and competitive.

#1: Appreciate the fact that learning supply networks are truly a competitive advantage. Today’s competitive supply networks are often characterized as both efficient and agile. They leverage assets from suppliers to  customers to sustain their advantage.  In order to manage these networks effectively, organizations need to appreciate the fact that the information that moves within and across these networks is as critical as inventory. Information movements, for example product demand, need to be put in the appropriate context for organizations to be able to act appropriately.  Adding content translates information into knowledge.  For example, unless an organization is able to do trend analysis, and learn from each and every demand request in order to improve future activities, its planning will be problematic. Similarly, learning must also occur in terms of performance by members with networks. Are some organizations more likely to demand on time and have raw materials available in real-time compared to others? To answer these questions, organizations must take information, put it in a reliable context, and interpret and act on it. Moreover, it is not simply the ability to learn that is important but the ability to do so in an agile manner. Learning needs to take place at a near real-time pace and must be occur under a wide assortment of conditions. Learning supply networks will outperform their traditional counterparts.

# 2: Have an adequate organizational learning program before you engage in inter-organizational learning. Similar to the quest for supply chain maturity, migrating from functional to process orientations, beginning internally and expanding externally, an organization’s learning initiatives must concentrate on cleaning their own "house" first. Time and time again organizations attempt to develop knowledge management and learning programs with their business partners before getting a handle on their internal processes and learning. Doing so is a futile exercise and leads to major calamities. For one, unless an organization knows its internal learning processes, it will be unable to define these, manage these, and be able to integrate these with those of external entities. Second, unless one cleans up their own backyard and straightens out their processes it will be a waste of time and effort, not to mention reputation and opportunity costs, to engage with external partners. The flow of knowledge between these organizations is critical to the success of the supplier network.   This becomes more difficult when each organization in the supply chain has disparate Customer Relationship Management (CRM) and Enterprise Resource Management (ERP) systems and other business knowledge based applications.  Disconnections between these disparate systems can minimize the amount of information that is able to flow between the links in the chain and will result in an unsynchronized supply network. It is absolutely essential that an organization first ensure that it has an adequate supply network in place and all systems within the organization are effectively connected prior in a desirable manner.

#3: Develop sound knowledge acceptance behavior. Knowledge Acceptance Behavior is the perception and acceptance of knowledge by the receiving function.  Consider the correlation here to the product design function at the front end of any supply network.  The product in this case is knowledge and must satisfy a need and be perceived valuable. Whatever the quantity and quality of the knowledge inputs, for a function, the inputs must be in correct mapping with the functionality of the receiver in order to gain value before being reused within the function and/or processed for delivery to the output end. Otherwise knowledge becomes a burden for the function. If the receiving functions don’t perceive and accept any knowledge input as a workable one or worthy to process, the particular input won’t have any value in the system. However this sense of perception is highly volatile, as the specifications of workability or worthiness changes in a dynamic business environment. To develop learning supply networks it is important to identify the knowledge needs of each member of the network. Knowledge needs should encompass the type of knowledge required, the time periods when knowledge is needed (i.e. the frequency), and the format in which knowledge is needed. These details should be made known and shared with all members of the supply network to promote the effective and efficient sharing of knowledge, leading to improved learning efforts in the supply network.

#4: Manage noise in knowledge transfer. Between the supplying functions, medium and receiving functions noise gets in the way and complicates the entire knowledge processing in any organizational system. The noise equivalent in a supply network might be excess inventory but noise in this discussion can be visualized as the unintended, unplanned, unrelated extra knowledge that enters the transmission process and distorts or even breaks down the knowledge transmission in any system. In the real world a noiseless transmission does not exist. Noise can enter the process from the sender, the channel or the receiver. Noise in the system limits the quality and amount of desired knowledge transfer, but interestingly also adds new kinds of knowledge, which may enrich the system knowledge. Whether, this extra knowledge will be included as an input in the system, depends entirely on the receiving end.

#5:  Manage Bounded Thinking. Now the most common way whole systems are managed is working backwards from what a system is expected to produce. This process typically includes establishing overall goals (measured in terms of quantifiable outputs) for the system first, then setting and associating the smaller goals or outputs of the individual component functions and then identifying the inputs needed for each function to perform. A change in overall output of the system evokes a chain reaction of changes into the preceding outputs and at the end naturally demands functions to work on new set of knowledge inputs. In fact in the present uncertain, changing business environment, when the output of organizations is being challenged every day, the need to work on new and newer set of knowledge inputs for organizations grows exponentially. But for an organization as a whole, the capacity to deal with all the new knowledge sets produced within the organization is very limited. There is not much an organization can do taking all the knowledge into account. The organization practically may not have enough band-width to investigate every set of knowledge input for the desired output demanded by the changed business environment. Rather over time, the organization limits itself into a predefined smaller set of knowledge inputs and works on inputs only within the bounded limits to produce some satisfying outputs instead of optimal outputs.
 
Inconsistencies in knowledge management for an organization arise from this point only. As organizations grow, the organizational functions work with new and newer sets of knowledge and contribute more varieties of knowledge into the common organizational knowledge pool. However over time, as the organizational knowledge grows, these functions due to their bounded rationality do not investigate every set of new knowledge inputs that would be relevant within their domain of functionality and hence use a limited part of the organizational knowledge instead of exploiting the whole. This reduces the generation of newer sets of knowledge as the functions may not fetch the perfect set of knowledge and sooner or later the organizational knowledge pool stops getting newer varieties of knowledge and the organization as a whole looses its vigor to fight the changing business needs. In this way the worthiness of every new set of knowledge produced by the different organizational functions will be investigated by the respective receiving functions before being treated as new knowledge and gets a location in the repository. This will save the search cost and motivate every function to go for optimal decision-making by using all the new sets of knowledge in their repositories.

Like any reputable doctor might warn a patient, in order to remain healthy these prescriptions must be taken regularly.  This prescription as applied to supply chains must be taken along with a balanced diet of inventory and financial flows.  Adhering to this advise raises the status of one of the most valuable assets in any supply network; knowledge.  Good circulation in this context is a powerful competitive tactic for healthy learning supply networks.

Dr. Kevin C. Desouza is on the faculty of the Information School at the University  of Washington. He is a founding faculty member of the Institute for Innovation Management (I ³M) and is an affiliate faculty member of the Center for American Politics and Public Policy, both housed at the University of Washington. His immediate past position was the Director of the Institute for Engaged Business Research, a think-tank of the Engaged Enterprise, a strategy consulting firm with expertise in the areas of knowledge management, crisis management, strategic deployment of information systems, and government and competitive intelligence assignments. He has authored Managing Knowledge with Artificial Intelligence (Quorum Books, 2002), co-authored The Outsourcing Handbook (Kogan Page, 2006), Managing Information in Complex Organizations (M.E. Sharpe, 2005) and Engaged Knowledge Management (Palgrave Macmillan, 2005), and edited New Frontiers of Knowledge Management (Palgrave Macmillan, 2005). His most recent book is currently in press - Agile Information Systems - to be published by Butterworth Heinemann (2006) . In addition, he has published over 100 articles in prestigious practitioner and academic journals. His work has also been featured by a number of publications such as the Washington Internet Daily, Computerworld, KM Review, and Human Resource Management International Digest. Dr. Desouza has advised major international corporations and government organizations on strategic management issues ranging from knowledge management, to competitive intelligence, and crisis management. He is frequently an invited speaker on a number of cutting-edge business and technology topics for national and international, industry and academic audiences . Dr. Desouza is a fellow of the Royal Society of Arts.