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Technological Changes in the Organization: Some Insights

Important Note: After reading this article, please assess your organization in terms of its current technological changes.

Technological change refers to the development of an organization’s technology over time. In general, two types of technological change have been identified in the literature: continuous or incremental change and discontinuous or breakthrough change (Zyclidopoulos, 1999). Incremental technological change refers to gradual, often indiscernible technological flows, that improve on existing products or processes, but which one cannot usually attribute to any particular investor. In contrast, breakthrough change involves revolutionary technological advances due to the invention of new products or processes, and quite often is attributed to a particular inventor.

Technological change is thus the creation of new knowledge that is applied to practical problems. Sometimes this knowledge is applied to problems hastily, without full consideration of the consequences and alternatives. Schilling (2008) suggested that the subject of change management is approached as a strategic process. A firm’s organizational behavior should encourage the generation of innovative ideas while also ensuring efficient implementation. Organizational behavior refers to the study of the structure and functioning of organizations and the behavior of groups and individuals within them (Warner, 1994). The purpose of the post is to analyze and forecast the impacts of technical innovations on organizational behavior, intrarelationships, and interrelationships.

Technological Changes in the Organizations: Various Implications

Given the rapidly changing technology and increasing globalization of systems, implications are grouped into two areas: organizational and managerial implications.

Technological Changes and Organizational Implications

According to Regan and O’Conner (2002), the potential exists for an organization’s structure to undergo changes to accommodate changes in previous work processes. The type of organizational structure change could be minor (e.g. merging or separation of work groups) to major changes involving the creation of new divisions or spin-off companies. Technology may contribute to several changes as employing new methods to communicate may decentralize supervisory decision-making. As virtual teaming may make some office functions obsolete, new problems may arise that require the infusion of new technology or improved communications processes. Technological changes may cause irregularities in the skill sets of knowledge workers may require managerial intervention. Regan and O’Conner recommended five strategies to assist with organizational problems: combining fragmented tasks in one comprehensive task, the formation of natural work units, establishing client relations with workers, applying vertical loading techniques, and establishing direct performance feedback channels.

Technological Changes and Managerial Implications

According to McNurlin and Sprague (2006), several authors and researches posit that future organizations will be more virtual than physical as employees become parts of virtual teams that are connected by networks. Managers may need to change their respective focus from directing to leading. In a virtual workspace, managers may have more depth to draw upon by exchanging employees based on the purpose of the work and skill sets of the managed. A virtual workforce may become less employee-centric and more work-centric as employees adopt the mindset of working on projects that technically inspire the worker (McNurlin & Sprague, 2006).

Another implication for managers is related to the work environment of the knowledge worker. The organization is heavily reliant on the productivity of the knowledge worker. The creation of knowledge work is largely based on innovation. Knowledge workers depend on innovation to do their work. They are not doing a pre-established task, but rather they define and perform their task for the very first time. They create tools that will be used by other knowledge workers to do their jobs (Ramirez & Nembhard, 2004). Managers must work to create an environment that inspires and encourages innovation. As a result, knowledge workers will maintain productivity for the organization. Finding meaningful ways to measure the productivity of the knowledge worker would open the field to focus on means towards improving productivity. According to Ramirez and Nembhard (2004), “making workers productive will be the great management task of this century, just as to make manual work productive was the great management task of the last century.”

Workplaces and Strategic Management of Technological Changes

Technological changes have transformed the traditional workplace to agile (Joroff, Porter, Feinberg, & Kukla, 2003), virtual (Ware & Grantham, 2003), mobile, and collaborative workplaces (Schaffers, 2005). Today, knowledge work can be conducted at thousands of other physical locations such as airports, cars, and airplanes. Agile workplaces are constantly transforming, adjusting, and responding to organizational learning (Gunasekara, 2003). Agility, as Joroff and his colleagues noted, is the flexibility to increase and contract the workforce and all its support costs to meet dynamically changing needs in a rapid change and high uncertainty. Schaffers argued key aspects of technological changes are mobility, sharing of information and knowledge, and collaboration across organizational networks. Mobile workplaces include the mobility and flexibility of the corporate settings and constraints to adapt to the evolving needs and opportunities of the knowledge worker.

The paradigm shift to the diversity of workplaces described above is multidimensional because of its relationship with the flexibility of the knowledge worker needs, corporate settings and various constraints inherent of the knowledge-based economy. In an attempt to define a portfolio of mobile workplaces, Schaffers summarized these dimensions into two: the number of work locations (or workplace context) and the frequency of changing location. Schaffers’ portfolio of mobile workplaces is subdivided into four generic forms: full mobility workplace, micro-mobility workplace, multi-location workplace, and dynamic workplace. Besides the location and time, workplace context includes additional aspects such as the nature of the task, markets demands, and availability of corporate resources.

The realization of the various work environments presents complex managerial and leadership challenges. Schaffers had identified the following ones: work requirements, workers behavior and needs, organizational factors, industry developments, societal and cultural structures and policies, and technological opportunities and bottlenecks. Continued globalization, coupled with the technology revolution has changed corporate work settings. Abbott and Banerji (2003) noted that the change in environment has forced most firms to develop strategies based on dynamic systems that can adapt to the changing external environment.

Therefore, the future work setting will be the result of a balance between these different forces. Murray and Greenes (2006) have identified the four pillars framework for building an enterprise of the future. The framework covers leadership, organization, learning and technology. Murray and Greenes added that the ability of an organization to compete with these future workplaces is enhanced when all elements of the enterprise are in close alignment. A leader’s role of the enterprise of the future is to find solutions to the challenges; also to create and maintain the alignment between all the elements.

Future Workplace, Tools, and Work Patterns

A traditional structure in an organization is defined as the manner in which its specific work activities are divided and the way the coordination among these activities are achieved (Bratton, Grint, & Nelson, 2005). The labor is subdivided into two dimensions. The horizontal dimension involves grouping different work activities into subunits, or departments, and into jobs. Horizontal division of labor is associated with specialization of workforce. The vertical dimension of division of labor is concerned with distributing authority for planning, decision making, and monitoring.

Future firms will require more flexibility, quick responsiveness, and mutual accountability. They need sophisticated, adaptive, empowered workers in a fractal organizational structure, that is, a distributed network of leaders with innovative organizational core competencies adapt to the new context (Prewitt, 2004). The new dynamic environments are driven by technological revolution and economic globalization, resulting in rapid and continuous changes, diminished product life cycles and the need to turn large amounts of data into useful information (Schreiber & Carley, 2006).

Business in the new century is not a physical thing, but a network of relationships that spans the globe and is increasingly mediated by telecommunications instead of face to face transactions. Rindova and Kotha (2001) have examined the coevolution of form, function, and competitive advantage in the dynamic, hypercompetitive in a particular context and have developed, using the grounded theory methods, a framework within which organizational continuous changes can be understood and managed. In this framework, they proposed that firms rely on continuous morphing to regenerate competitive advantage under conditions of rapid change.

Dynamic capabilities and strategic flexibility are two organizational mechanisms that facilitate continuous morphing. As Rindova and Kotha (2001) pointed out, whereas dynamic capabilities are defined as a firm’s ability to achieve new forms of competitive advantage, strategic flexibility is referred to a firm’s ability to respond to the demands of dynamic competitive environments. As firms change what they are and what they offer through the continuous morphing process, they migrate into a new strategic and competitive domains. This requires an inherent flexibility of the resources available, including IT resources, to a firm and its flexibility in applying those resources. Corporate structural features and patterns can be more complex within multinational corporations. Indeed, research on the organization of multinational corporations has projected the emergence of complex internally differentiated structures (Malnight, 2001). Characteristics of these structures include a global dispersion of operations, interdependence and tight coupling of subunits, and an emphasis on cross-unit learning and structural flexibility. 

Conclusion

The purpose of this post was to analyze and forecast the impacts of technical changes on organizational behavior, intrarelationships, and interrelationships. Technological change is the creation of new knowledge that is applied to practical problems. Sometimes this knowledge is applied to problems hastily, without full consideration of the consequences and alternatives. The subject of change management should be approached as a strategic process. A firm’s organizational behavior should encourage the generation of innovative ideas while also ensuring efficient implementation.

The new dynamic environments are driven by technological revolution and economic globalization, resulting in rapid and continuous changes, diminished product life cycles and the need to turn large amounts of data into useful information. The realization of the various work environments presents complex managerial and leadership challenges: work requirements, workers behavior and needs, organizational factors, industry developments, societal and cultural structures and policies, and technological opportunities and bottlenecks. Future firms will require more flexibility, quick responsiveness, and mutual accountability. They need sophisticated, adaptive, empowered workers in a fractal organizational structure, that is, a distributed network of leaders with innovative organizational core competencies adapt to the new context.

 

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Two Types of Innovative Leadership: Application to Knowledge Management Initiatives

Amar (1998) observed that organizations whose success depends on innovation require a leadership style totally different from the one typically used by most leaders. Whereas leaders of traditional organizations succeed on their ability to artfully manipulate their environment, innovation leadership emanates from manager’s creative initiatives, intellectual preeminence, and technical or unique expertise that is of value to each individual in the group and which translates to direct benefit for all (Amar, 1998).

The literature distinguishes two types of innovation leadership: the transformational-transactional leadership model in the organizational behavior literature, and the leadership role model in the innovation management literature (Bossink, 2004). In the organizational behavior literature, leadership relates to: the personal traits of the leader such as intelligence, values and physical appearance; the leader’s behavior such as the use of power, the control of rewards and the delegation of authority; and the organizational situation the leader is in such as the structure, age and environment.

The innovation management literature presents leadership as a role to be performed by managers but also by employees. These roles are: inventor: the leader promotes the technological know-how that is translated into innovative products and services; champion: the leader promotes organizational adoption of innovations; entrepreneur: the leader initiates, drives and controls the innovation strategies and processes in the organization; gatekeeper: the leader gathers and processes information about changes in the organization and its environment; and sponsor.

Bossink (2004) identified four leadership styles in the innovation leadership roles: 1) charismatic: the leader communicates an innovation vision, energizes others to innovate, and accelerates innovation processes; 2) instrumental: the leader structures and controls innovation processes; 3) strategic: the leader uses hierarchical power in favor of organizational innovation; 4) interactive: the leader empowers other to innovate, cooperates with them to innovate and shows them how to become innovation leaders in the organization themselves.

My question is: How could we apply these two types of innovative leadership to a knowledge management initiative?

 

Thanks for sharing your thoughts.

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Knowledge Worker Tools

In the knowledge society the value-creating strategies and long-term viability of a firm depends on sustaining its competitive advantage. The resource-based view of competitive advantage suggests that organizations with valuable, unique and non-substitutable resources gain sustainable competitive advantage and superior performance (Moustaghfir, 2008; Zhang, 2007). Such firms can achieve these capabilities by developing new products and services that satisfy customers, and by restructuring and improvement their operational and strategic business processes. Tremendous amount of corporate data, information and knowledge that are related to operational and strategic levels in a firm are flooding into business (Lau, Ning, Ip, & Choy, 2004). The optimal use of corporate knowledge assets can improve the performance of decision makers and process workers (Moustaghfir; McGuff & Kador, 1998) and is a fuel that drives a firm’s engine of innovation (Henrad & McFadyen, 2008). Online transaction processing (OLTP) technologies and online analytical processing (OLAP) applications are useful for addressing the operational data needs (Sen & Sinha, 2005) and supporting strategic decision making (Jones, 2005) of a firm. The purpose of this essay is twofold. Fist, an identification of the categories of knowledge workers who could benefit from OLTP and OLAP systems is provided. Second, the relevance of these tools to the workers activities is discussed.

OLTP and OLAP

 Online transaction processing (OLTP) systems are web-based transaction processing systems (TPS). TPSs are databases that process transactions within an organization (Haag, Cummings, & McCubbrey, 2005). Payroll, inventory, and sales systems are few examples of TPSs. OLTP tools are useful for addressing the operational data needs of a firm (Sen & Sinha). OLTP applications, with their online nature, decentralize computing power in an organization by placing that power in the hands of customers; hence they are characterized as customer self-service systems. The latter are integrated to databases and database management systems (Post & Kagan, 2001) to support the operational role of the knowledge worker. Various functionalities of the integrated system assist in the gathering of input, processing, and updating existing knowledge according to specific business rules. However, OLTP systems are not well suited for supporting decision-support queries or business questions that managers typically need to address. Such questions involve analytics that include aggregation, drilldown, slicing or dicing of data, which are best supported by online analytical processing systems.

The term OLAP was coined by Codd et al. in the 1990s (Davenport & Sena, 2004; Hedelin & Allwood, 2002). The OLAP system helps to manipule information to support strategic decision making. Jones (2005) defined decision making as the process of selecting from a set of options the alternative(s) that are most likely to lead to desired outcomes. He added that the decision making process is a knowledge-intensive activity which is subdivided into four phases: intelligence, design, choice and implementation. The knowledge needs of decision makers drive the knowledge derivation process (Davenport & Sena) and are supported by categories of technologies  such as executive information systems, expert systems, agent-based modeling, data mining, and decision support systems (McNurlin & Sprague, 2006).

OLAP applications are decision support systems that enable the knowledge worker to make better and faster daily business. These applications are supported by data warehouses. The concept of data warehouse was developed to circumvent the limitations of operational databases for decision support systems. Lau et al. posited that data warehouse has excellent capabilities to integrate data from multiple transactional systems and improve their quality. OLAP enables various types of analyses of data organized as a star design (central fact table and dimensional tables) with average response times of OLAP that are lower than 20 seconds (Lau, Chan, Fun, & Wong, 2004).

Although OLAP technologies are powerful, Hedelin and Allwood argued that they also have some limitations. OLAP allows the knowledge worker to elaborate and test perceptive hypotheses about associations in the data. However, the existing information in the database remains unexploited if appropriate queries are not executed. Data-mining tools circumvent this shortcoming by looking for significant patterns without requiring the formulation of a specific hypothesis. This technology enables, as Hedelin and Allwood noted, knowledge discovery in addition to knowledge verification and provides sophisticated analyses to support decision making.

Process Workers and OLTP

The OLTP and OLAP applications users’ needs are different from one another (McGuff & Kador, 1998). An OLTP is useful for addressing the operational data needs of a firm (Haag, Cummings & McCubbrey, 2005). Some examples of OLTP include worldwide airline customer reservation systems, online banking systems, or financial applications including ledger, accounts payable and accounts receivable, payroll, manufacturing, inventory and human resources. These operational systems demand procedural specificity and support corporate mission-critical processes. Process workers (McGuff & Kador) using these systems perform day-to-day operations following specific business operational needs. 

Although they cover a wide business functions, ERP systems are typical examples of operational systems. Sumner’s (2005) defined ERPs as software tools used to manage enterprise data as they are built with an integrated systems approach that establishes a common set of applications supporting business operations. An ERP system provides an enterprise database where all business transactions are entered, processed, monitored, and reported. Examples of ERP systems include SAP, PeopleSoft and Oracle. These systems cover different corporate functional areas such supply chain, receiving, inventory management, customer order management, production planning, shipping, accounting, and human resource management.

Decision Makers and OLAP

Contrary to OLTP technologies, OLAP applications have different set of characteristics that include generalization, aggregation, adaptability and long retention period (McGuff & Kador). Database content and structure tend to be more generalized and usually include several operational applications. The level of detail may be at a much higher level of aggregation. This aggregation creates a level of difficulty that the operation systems do not have to deal with. The data retention period for decision maker’s use is much longer, often measured in years. If the business strategies or structures change, then all the data must be modified. By using an OLAP system, the knowledge worker can manipulate enterprise dimensional data models to understand changes that are occurring in the firm and take appropriate business decisions (Lau et al.).

Good decision making is imperative for the survival of firms (Jones, 2005). The process of identification of critical alternative courses of action and development of a decision-making used multiple criteria decision approaches (Figueira, Greco, & Ehrgott, 2005). According to Jones, this process forges the decision through a choice made from among available alternatives. The main goal of OLAPs is to improve the quality of a decision. The quality of data determines both decision quality and the quality of the OLAP. The integration of OLAP and OLTP technologies through a common data warehouse technology provides decision support to firms (Gorla, 2003). Data warehouses extract data from different operational databases to facilitate decision-making by management people by employing a set of user-friendly tools, like data mining and presentation techniques (Chowdhury, 2007). Traditional decision making phases take the decision maker through knowledge gathering, alternative formulation, and finally a selection of the alternative. The purpose of data warehouses is to enforce a centralized store-house representing a single source of truth for the entire organization. This centralization allows managers to access analytical databases through OLAP interface and analyze corporate data on various dimensions (Hedelin & Allwood). OLAP technologies allow decision makers to evaluate corporate changes over time, obtain an overview of the business operations and perform various analyses. A data warehouse project is usually business-driven and will work to improve the direction of the organization.  The first priority of the business-driven data warehouse approach, as Chowdhury noted, is the formulation of a lit of questions. This list is a set of analytical problems that managers consider as critical success factors for the future of the business. It evolves to a dimensional model which is combined to the data model OLAP cubes to build reports that answer managers’ questions.

Conclusion

 

In this post, OLTP and online OLAP were identified as two examples of front-end support tools that knowledge workers can employ to support organizational goals. OLTP tools are useful for addressing the operational data needs of a firm. They decentralize computing power in an organization by placing that power in the hands of customers. OLTP applications are useful for process workers in their day-to-day operations. However, OLTP systems are not well suited for supporting decision-support queries or business questions that managers typically need to address. By using an OLAP system, decision makers can manipulate enterprise dimensional data models to understand changes that are occurring in the firm and take appropriate business decisions. The integration of OLAP and OLTP technologies through a common data warehouse technology provides decision support to firms. This integration enforces a centralized store-house representing a single source of truth for the entire organization and managers to access knowledge bases and analyze corporate multidimensional data.

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Knowledge Management and Outsourcing Possibilities: Conflicting Strategies?

Knowledge management (KM) refers to the process of exploring all the capabilities of knowledge resources (Sabherwal & Sabherwal, 2005) or as a combination of knowledge and processes (Regan & O’Connor, 2002). These processes can help a firm improve its performance and effectiveness by employing purposefully designed strategies for creating, identifying, collecting, organizing, and sharing knowledge. KM processes can also be used to facilitate the integration of IT and business knowledge. Feng, Chen, and Liou (2005) identified knowledge generation, knowledge capture, knowledge codification, and knowledge transfer as the four main KM processes.

There are advantages and disadvantages of outsourcing the integration of new technologies into the organization (Haag, Cummings & McCubbrey, 2005). Outsourcing issues are usually handled by 1) identifying which services needed to be outsourced, 2) assessing the internal capacity in the company for these services, and 3) analyzing the potential strategic business values that can be obtained from the services.

Pati and Desai (2005) have identified five forms of sourcing: (1) insourcing, (2) selective sourcing, (3) strategic alliance sourcing, (4) outsourcing, and (5) off-shore outsourcing. While the insourcing relies on in-house resources, the authors argued that outsourcing use resources external to the organization. Whereas selective and strategic alliance types of sourcing are established on multiple suppliers and on joint venture partners respectively, outsourcing predominantly uses resources external to the organization at a local or regional level. Offshore outsourcing implies delegation of the selected business operations to an offshore location outside the country.

From IT perspective, the three variables that influence strategic outsourcing decisions are:  (1) Internal IT capacity, (2) IT services opportunity being contemplated, and (3) Potential strategic business values that can be obtained from IT service. The internal IT capacity comprises commitment of top leadership, provision and deployment of infrastructure, pervasiveness and sophistication of use, technological and managerial skills. Discrete IT functions and end-to-end IT enterprise wide solutions are the IT services opportunity being contemplated. Potential strategic business values that can be obtained from IT service are the following: service level, core competencies, alignment of goals, time to market, world class processes, industry on process knowledge, new business opportunities and overall competitiveness.

Pati and Desai’s (2005) decision cube for IT sourcing engagements is used to determine whether or not an IT service should be outsourced. This model defines eight scenarios which guide strategic outsourcing decisions. Whereas the first two leads for in-sourcing, the other favors outsourcing. Forbath and Brooks (2007) noted that most companies have outsourced some portion of their business to lower costs and over time, have achieved cost savings in the outsourced portion of the business.

IT outsourcing (especially its off-shoring aspect) as a special type of outsourcing, began early in 1990s as a way to supplement in-house IT development activities. IT outsourcing became a growing economic phenomenon worldwide because of 1) the development of IT-related infrastructures in developing countries, 2) a surging demand for IT specialists in developed world, and 3) availability of a highly skilled pool of personnel in the developing world at a reasonable cost. Organizations that outsource their activities are expecting the followings benefits: 1) cost savings; 2) increased rate of returns on investments, and, 3) improved access to best practices in IT design, implementation and operations.

The IT offshore outsourcing has some pitfalls if not well plan and implement in both sides: client-side, vendor-side and client-vendor relationship problems (Shi, 2007). In addition to the problems mentioned, the three potential concerns related to privacy in information security raised by off-shoring data processing are related to:

          Legal aspects: legal perceptions may differ from one nation to the other and ambiguity could arise during a dispute

          Information security: employee credibility information security largely depends on the people who handle the information. Practice of the ethical rules and privacy policies of the organization like non-disclosure of trade secrets, secrecy and non-disclosure contracts with staff, third party service providers or visitors are difficult to enforce with the vendor

          Vendor reliability and dependability.

 

Therefore, my question is: what are the advantages and disadvantages for a knowledge organization to outsource its information system?

 

Please share your thoughts. Thanks.

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Knowledge-Based View of the Firm and Knowledge Management Systems

            The creation of a global society with possibilities of knowledge sharing is among the contributions of the IT revolution and globalization. In the knowledge society, the value-creating strategies and long-term viability of a firm depend on sustaining its competitive advantage. The knowledge-based view of the firm draws upon the resourced-based view (Levitas & Ndofor, 2006; Williamson, 1957; Chandler 1962; Stigler, 1961) and considers knowledge as a distinctively unique resource that should be managed. Organizational knowledge can be characterized as explicit and tacit (Regan & O’Connor, 2002), and embedded (Bourdeau & Couillard, 1999). Knowledge management (KM) refers to the ability to create and manage a culture that encourages and facilitates the creation, appropriate use, and sharing of knowledge to improve organizational performance and effectiveness (Walczak, 2005).

            Organizational KM includes the identification, acquisition, storing, and dissemination of tacit, explicit, and embedded knowledge. Conceptualizations of knowledge management (KM) as well as of intellectual and human capital in organizational design are usually guided by various perspectives such as information-processing theory (Tushman & Nader, 1978; Galbraith, 1973), organizational learning theory (Senge, 1990), knowledge creation (Kearns & Sabherwal, 2007), dynamic capabilities (Collis, 1991), and resource-based theory of the firm (Rugman & Verbeke, 2002; Wernerfelt, 1984; Penrose, 1959).

Good KM, as Charles (2005) noted, involves three elements: people, processes and technology. Organizational technologies that support KM initiatives and KWs are called knowledge management systems (KMS). KMS are IT-based tools developed to support corporate processes of knowledge management (Feng, Chen, & Liou, 2005). KMS are classified in terms of knowledge dimensions (tacit and explicit) and the extent of codifiability required (Becerra-Fernandez, 2000), codification versus personalization strategy (Hansen et al., 1999), KM processes that are supported (Alavi and Leidner, 2001; Tiwana and Ramesh, 2000). Benbya and Belbaly (2005) have provided a classification of KMS based on the tacit and explicit dimensions. Examples of such applications are knowledge bases, business intelligence services, corporate information portals, and customer relationship management services. Five indicators are used to measure their success (Benbya & Belbaly, 2005): 1) system quality, 2) knowledge quality, 3) use and user satisfaction, 4) perceived benefits, and 5) net impact.