Knowledge Management Cases in Asia/Knowledge Management in a Law Enforcement Unit/Literature Review

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In the knowledge economy, we see more knowledge firms emerging. And some existing knowledge firms redefining themselves to exploit and explore their knowledge resources. In public sector, law enforcement unit in many different countries has been already aware the significance of knowledge management in the past.

Governments have become increasingly focused upon the setting of targets in efforts to improve the efficacy of law enforcement units’ performance. The primary mission of any law enforcement units in the world is to protect life and property, preserve law and order and prevent and detect crime (Luen & Al-Hawamdeh, 2001). Investigation units of a law enforcement unit represent a knowledge-intensive and time-critical environment (Chen et al., 2002). The activities and work carried out by law enforcement units are primarily in the areas of crime prevention, incident management, investigation and community policing. Crime prevention implies the detection, and hence prevention of crime. These activities can be carried out through both reactive and proactive means. Reactive measures such as roadblocks, spot-checks and showing police presence are routinely carried out by law enforcement officers as part of their investigation duties. Proactive measures include public education to help prevent crime. In Singapore, one of the law enforcement units’ officers also reach out to the community via grassroots and community agencies to educate the public on the latest crime trends and threats. Law enforcement officers performing both reactive and proactive measures effectively will need to know the latest legal and organisational directions regarding these functions as well as the latest information on crime trends and the corresponding knowledge about the detection and prevention of crime.

Luen and Al-Hawamdeh (2001) find that the amount of information that law enforcement officers come into contact with in the course of their work is astounding. The needs of vast knowledge showed the growing importance for law enforcement officers to be a proficient knowledge worker, and they should able to access, assimilate and use knowledge effectively to discharge their duties. Presently, information and knowledge are captured within law enforcement units in various forms, ranging from computer records, to documented institutional orders, to the personal experiences of its officers. The crux of the issue is how to surface such knowledge and bring it to bear on the problems faced by law enforcement officers in a timely and effectively manner. This is where knowledge management principles and practices can help. It is thus imperative that law enforcement units such as the one in Singapore develops a coherent knowledge management strategy to ensure that such knowledge and information are made available to officers in a timely and effective manner, so as to enable them to perform their duties at an optimal level. In short, in such a complex and dynamic working environment information must be enhanced by an effective knowledge sharing system. (Luen and Al-Hawamdeh, 2001)

With the increased adoption of information technology within law enforcement units and the increasing of overall quality and information technology competence of law enforcement officers, law enforcement units are well positioned to leverage knowledge management principles and practices. This complemented by the enhanced skills, equipment and empowerment given to the officers that will enable them to perform their duties at an optimal level. In discussing the scope of knowledge management in law enforcement units, Luen and Al-Hawamdeh (2001) mentioned two definitions of knowledge within the context of knowledge management. There are two types of knowledge that need to be managed within law enforcement units, explicit knowledge and tacit knowledge. Explicit knowledge is used as guidance for law enforcement and decision-making. This type of knowledge is captured in the form of document (e.g. doctrines, law enforcement general orders and standard operating procedures) that have been verified and ascertained to be of value to law enforcement officers. The second type of knowledge is implicit or tacit knowledge. This includes the competence, experience and skills of law enforcement officers. Tacit knowledge is usually dynamic and fast changing as compared with documented knowledge. Regarding tacit knowledge, the scope of knowledge management in law enforcement units is primarily in the areas of creating and sharing knowledge and information. It has long been recognized that the most valued law enforcement knowledge has been acquired and organized around situational or street experience (Rubinstein, 1973). According to Luen and Al-Hawamdeh (2001), the more difficult issue to tackle is that of the willingness of law enforcement offices to create and share knowledge. There is a need for a culture characterized by openness, collaboration and sharing among law enforcement officers. This will require that law enforcement officers recognize the importance of collaboration and sharing knowledge with others. The responsibility to surface knowledge lies with everyone in the law enforcement units, as knowledge is generated in all phases of work.

For example, in Norway, the Police Security Service replaced the Police Surveillance Service. In the U.S., a clearinghouse for foreign and domestic terrorism analysis – the Terrorist Threat Integration Center – was located at the Central Intelligence Agency (CIA) compound at Langley, Virginia, reporting directly to the Director of Central Intelligence. The center will fuse all appropriate information and send a summary report to the Department of Homeland Security. The reason behind these arrangements is that a special branch of police work, which seems extremely knowledge-intensive, is police intelligence. Lahneman (2004) suggests that intelligence agencies were the world’s first knowledge companies. Managing knowledge has always been the primary mission of the intelligence community’s leadership. Accordingly, the intelligence community can benefit substantially from knowledge management approaches. Several agencies have embarked on innovative, large-scale projects on upgrade their IT capabilities. The intelligence community has also experienced several high-level organizational changes and proposals for organizational changes.

Knowledge collection activities require coordination to make sure that collected information gets to the right person at the right time. They also need oversight to ensure that each agency’s collection assets are so employed that the collection of potentially useful information is optimized. Optimized knowledge sharing where intelligence analysis is concerned can be more difficult. It is because unlike collection efforts, coordination is increasingly interagency in nature. Analysis related to terrorism and, in particular, terrorism against the U.S. homeland, is particularly dependent on fusing information from disparate sources. (Lahneman, 2004).

According to Grover and Davenport (2001), most knowledge management projects in organizations involve the use of information technology. Identifying, nurturing and harvesting knowledge is a principal concern in the information society and the knowledge age. Effective use of knowledge-facilitating tools and techniques is critical, and a number of computational tools have been developed (Housel & Bell, 2001). While technology can be used with knowledge management initiatives, Ward and Peppard (2002) argue that it should never be the first step. Knowledge management is primarily a human and process issue. It has been argued that IT-based systems used to support knowledge management can only be of benefit if used to support the development and communication of human beings.

Grover and Davenport (2001) found that by far the most common objective of knowledge management projects in Western organizations including law enforcement units involves some sort of knowledge repository. The objective of this type of project is to capture knowledge for later and broader access by others within the same organization. Common repository technologies include Lotus Notes, web-based intranets and Microsoft’s Exchange, supplemented by search engines, document management tools and other tools that allow editing and access. The repositories typically contain specific types of information to represent knowledge for a particular business function or process, such as:

  • “Best practices” information within a quality or business process management function;
  • Lessons learned in projects or product development efforts;
  • Information around the implementation of information systems;
  • Competitive intelligence for strategy and planning function; and
  • “Learning histories” or records of experience with a new corporate direction or approach.

According to Davenport and Prusak (1998), more and more companies have instituted knowledge repositories, supporting such diverse types of knowledge as best practices, lessons learned etc. Moffett and McAdam (2003) illustrate the variety of knowledge management technology tools by distinguishing between collaborative tools, content management and business intelligence. Collaborative tool include groupware technology, meeting support systems, knowledge directories and intranets/extranets. Content management includes the internet, agents and filters, electronic publishing systems, document management systems and office automation systems. Business intelligence includes data warehousing, decision support systems, knowledge-based systems and workflow systems.

With the aids of modern information technology (e.g. the internet, intranets, extranets, browsers, data warehouses, data filters, software agents and expert systems) knowledge creation, sharing and exchange in an organization and between organizations can be supported. Modern information technology can collect, systematize, structure, store, combine, distribute and present information of value to knowledge workers. (Nahapiet & Ghoshal, 1998).

Two examples of knowledge management technology in law enforcement units will be presented in the following. The first example is COPLINK described by Chen et al. (2002, 2003). COPLINK Connect is an application for information and knowledge sharing in law enforcement. The system uses a three-tiered architecture. The user access the system through a Web browser. The middle tier connects the user interface and the backend databases and implements the work logic. COPLINK Detect is targeted for detectives and crime analysts. The system shares the same incident record information as the Connect module and utilizes the database indexes it generates. However, the Detect system has a completely redesigned user interface, and employs a new set of intelligence analysis tools to meet its user needs.

Much of crime analysis is concerned with creating associations or linkage among various aspects of a crime. COPLINK Detect uses a technique called concept space to identify such associations from existing crime data automatically. In general, a concept space is a network of terms and weighted associations within an underlying information space. COPLINK Detect uses statistical techniques such as co-occurrence analysis and clustering functions to weight relationships between all possible pairs of concepts. In COPLINK Detect, detailed criminal case reports are the underlying information space, and concepts are meaningful terms occurring in each case. These case reports contain both structured (for example, database fields for incidents containing the case number, names of people involved, address and date) and unstructured data (narratives written by officers commenting on an incident, for example, witness A said he saw suspect A run away in a whit truck).

Several field user studies have been conducted to evaluate the COPLINK system. One of the studies is that a group of 52 law enforcement personnel from the Tucson Police Department representing number of different job classification and backgrounds were recruited to participate in a study to evaluate COPLINK Connect. Both interview-data and survey-data analyses support a conclusion that us of the application provided performance superior to using the legacy police records management system. In addition to the statistical data, these findings were supported by qualitative data colleted from participant interviews (Chen et al., 2003).

The other application to be presented here is concerned with geocomputation for geodemographics (Ashby and Longley, 2005). Geodemoraphic profiles of the characteristics of individuals and small areas potentially offer significant breakthroughs in clarifying local policing needs in the same way they have become an integral part of many commercial and marketing ventures. Ashby and Longley (2005) conducted a case study of the Devon and Cornwall Constabulary. They found that geodemographic analyses of local policing environments, crime profiles and police performance provide a significantly increased level of community intelligence for police use. This was further enhanced by the use of penetration ranking reports where neighborhood types were ranked by standardized crime rates, and cumulative percentage of the crime was compared with the corresponding population at risk.

Investigations of law enforcement units are complex undertaking that have both reactive and proactive dimensions to them. The knowledge required to effectively carry out an investigation is built upon “three pillars”, a team employed by the Singapore Police Force. These pillars are forensics, intelligence and interviews. A well-grounded forensic understanding of a crime scene is the foundation of any investigation. Intelligence gathering is a crucial activity for an investigation, particularly for proactive investigations into organized crime and/or terrorist related-operations. As regards interviews, the ability to derive relevant information from people through effective interviewing is seen by law enforcement units as an essential activity in any investigation.

One of the research conducted by Adhami and Browne (1996) concluded that knowledge management systems are more important in problem solving than in  other primary activities of law enforcement units. Dean (2000) noted that knowledge management systems are more important in the thinking styles of method and skill than in the thinking styles of challenge and risk. And so Dean specified that law enforcement research efforts should be focused on developing knowledge management systems that concentrate on enhancing the activity of how “problem solving” takes place within investigations. A set of five basic procedural steps are proposed: collecting, checking, considering, connecting and constructing.

According to Johnson and Scholes (2002), successful strategies are dependent on the organization having the strategic capability to perform at the level that is required for success. With different knowledge focus in the organization, different knowledge management strategies have to be adapted. Hansen (1999) mentioned knowledge strategies can be classified as: stock strategy, flow strategy and growth strategy. Stock strategy (efficiency- driven business) is used to solve known problems. The quality of the solution is found in fast and inexpensive application to meet customer needs. There is an accumulation of knowledge to improve efficiency. Competitive advantage is achieved in the ability to make small adjustments in existing goods and services at a low price it characterized by known problems and known methods for solution. Flow strategy (experience- driven business) solves large and complicated problems for customers, the problems are new, but they can be solved with existing methods in a specific context every time by effective adaptation. It is characterized by both new problems and existing methods for solutions. Growth strategy (expert-driven business) solves large, complex, risky, new and unusual problems for customers. There are continuous improvisation and innovation. Knowledge workers apply general high-level knowledge to understand, solve and learn. Learning from problem solving is important to be able to solve the next new and unknown problem for customers. So, knowledge of previous problems becomes obsolete. An expert-driven business is characterized by both new problems and new methods for solution. Knowledge is the most important strategic resource that law enforcement unit as a “firm” use to solve their particular crime problems. And the success of law enforcement work is positively related to stage of knowledge management technology and the extent of access to strategic knowledge resources.

In response to the September 11th terrorist attacks, major government efforts to modernize federal law enforcement authorities’ intelligence collection and processing capabilities have been initiated worldwide. At the state and local levels in many countries, crime and law enforcement report data have rapidly migrated from paper to automated records management systems in recent years, making them increasingly accessible (Chen et al., 2003). Investigations of law enforcement units are often dependent upon information from abroad. For example, the intelligence communities of different countries cooperate and share their information and knowledge, such as the Mossad with the CIA (Kahana, 2001). According to Lahneman (2004), knowledge sharing in the intelligence communities after 9/11 has increased rapidly. Knowledge management as a field of study is concerned with simplifying and improving the process of sharing, distributing, creating, capturing and understanding knowledge, it has direct relevance to the work of law enforcement.