Tony Rhem

May 312017
 

AI and KMThis is the first of a three (3) part post on the connection between Artificial Intelligence and Knowledge Management.

Artificial Intelligence (AI) has become the latest “buzzword” in the industry today. However, AI has been around for decades. The intent of AI is to enable computers to perform tasks that normally require human intelligence, as such AI will evolve to take many jobs once performed by humans. I studied and developed applications in AI from the mid to late 1980’s through the early 2000’s. AI in the late 1980’s and early 1990’s evolved into a multidisciplinary science which included expert systems, neural networks, robotics, Natural Language Processing (NPL), Speech Recognition and Virtual Reality.

Knowledge Management (KM) is also a multidisciplinary field. KM encompasses psychology, epistemology, and cognitive science. The goals of KM are to enable people and organizations to collaborate, share, create, use and reuse knowledge. Understanding this KM is leveraged to improve performance, increase innovation and expand what we know both from an individual and organizational perspective.

KM and AI at its core is about knowledge. AI provides the mechanisms to enable machines to learn. AI allows machines to acquire, process and use knowledge to perform tasks and to unlock knowledge that can be delivered to humans to improve the decision-making process. I believe that AI and KM are two sides of the same coin. KM allows an understanding of knowledge to occur, while AI provides the capabilities to expand, use, and create knowledge in ways we have not yet imagined.

The connection of KM and AI has lead the way for cognitive computing. Cognitive computing uses computerized models to simulate human thought processes. Cognitive computing involves self/deep learning artificial neural network software that use text/data mining, pattern recognition and natural language processing to mimic the way the human brain works. Cognitive computing is leading the way for future applications involving AI and KM.

In recent years, the ability to mine larger amounts of data, information and knowledge to gain competitive advantage and the importance of data and text analytics to this effort is gaining momentum. As the proliferation of structured and unstructured data continues to grow we will continue to have a need to uncover the knowledge contained within these big data resources. Cognitive computing will be key in extracting knowledge from big data. Strategy, process centric approaches and interorganizational aspects of decision support to research on new technology and academic endeavors in this space will continue to provide insights on how we process big data to enhance decision making.

Cognitive computing is the next evolution of the connection between AI and KM. In future post, I will examine and discuss the industries where cognitive computing is being a disruptive force. This disruption will lead to dramatic changes on how people will work in these industries.

Mar 312017
 

CognitiveThere are approximately 22,000 new cases of lung cancer each year with an overall 5-year survival rate of only ~18 percent (American Cancer Society). The economic burden of lung cancer just based on per patient cost is estimated $46,000/patient (lung cancer journal). Treatment efforts using drugs and chemotherapy are effective for some, however more effective treatment has been hampered by the inability of clinicians to better target treatments to patients. It has been determined that Big Data holds the key for providing clinicians with the ability to develop more effective patient centered cancer treatments.

Analysis of Big Data may also improve drug development by allowing researchers to better target novel treatments to patient populations. Providing the ability for clinicians to harness Big Data repositories to develop better targeted lung cancer treatments and to enhance the decision-making process to improve patient care can only be accomplished through the use of cognitive computing. However, having a source or sources of data available to “mine” for answers to improve lung cancer treatments is a challenge!

There is also a lack of available applications that can take advantage of Big Data repositories to recognize patterns of knowledge and extract that knowledge in any meaningful way. The extraction of knowledge must be presented in a way that researchers can use to improve patient centric diagnosis and the development of patient centric treatments. Having the ability to use cognitive computing and KM methods to uncover knowledge from large cancer repositories will provide researchers in hospitals, universities, and pharmaceutical companies with the ability to use Big Data to identify anomalies, discover new treatment combinations and enhance diagnostic decision making.

Content Curation

An important aspect to cognitive computing and Big Data is the ability to perform a measure of content curation. The lung cancer Big Data environment that will be analyzed should include both structured and unstructured data (unstructured being documents, spreadsheets, images, video, etc.). In order to ingest the data from the Big Data resource the data will need to be prepared. This data preparation includes applying Information Architecture (IA) to the unstructured data within the repository. Understanding the organization and classification schemes relating to the data both structured and unstructured is essential to unifying the data into one consistent ontology.

Are We Up for the Challenge!

Even if a Big Data source was available and content curation was successful, the vast amounts of patient data is governed by HIPAA laws which makes it difficult for researchers to gain access to clinical and genomic data shared across multiple institutions or firms including research institutions and hospitals. According to Dr. Tom Coburn in his January 14th article in the Wall Street Journal ‘A Cancer ‘Moonshot’ Needs Big Data; gaining access to a big data repository all inclusive of patient specific data is essential to offering patient centered cancer treatments. Besides the technology challenges, there are data and regulation challenges. I’m sure that many of these challenges are being addressed. Thus, far there have been no solutions. Are we up for the challenge? Big Data analysis could help tell us which cancer patients are most likely to be cured with standard approaches, and which need more aggressive treatment and monitoring. It is time we solve these challenges to make a moonshot a certain reality!

Jan 312017
 

AJ Rhem Logo with Tag LineKnowledge is recognized as a valuable asset in organizations across many industries. How knowledge is shared, leveraged, obtained and managed will be the difference in how successful and sustainable an organization will become. The use of knowledge management principles, practices and procedures has expanded enormously in recent years. This expansion has also brought about the proliferation of knowledge management systems in its many forms, Contact Center Knowledge Repositories, Expertise Locators, Content Management, Document Management, Knowledge Repositories/Libraries, Social Media Applications, Decision Support Systems, to name a few. The inclusion of KM from a strategic point of view to streamline revenue, increase revenue, improve performance, attract/retain customers and manage human capital have enabled organizations to maintain and/or improve their competitive edge. Knowledge Management in Practice is a resource which presents how KM is being implemented along with specific KM Methods, tips, techniques and best practices to get the most out of your KM investment.

This blog post features two videos from the presentation of my latest book: Knowledge Management in Practice. This presentation was conducted at the Knowledge Management Institute (KMI) Certified Knowledge Manager (CKM) training class held in Washington DC.

The second video features the question and answer session that followed. Feel free to ask questions regarding the book here on this blog and/or make comments on YouTube. I look forward to hearing from everyone!

 

 

 

 

Jan 112017
 

KM Wizard2As we enter into 2017, I am dedicating this first blog post to answering some of the pressing KM questions presented by my clients.

Do you recommend any standard model of KM to follow/implement? If so, please describe the model in summary.

There are several models of KM that I have worked with at various organizations to implement KM strategies, methods, processes and solutions, these include; The SECI Model (knowledge capture); The Continuous Knowledge Model (Connect, Collect, Catalog, Reuse, & Learn); KM Maturity Model (Maturity Level 1 – Initial: – Knowledge management is a one-time process with no formal KM practices within the organization, Maturity Level 2 – Repeatable: – KM processes are implemented and tested, Maturity Level 3 – Defined: KM roles are created, defined, and filled, Maturity Level 4 -Managed: – KM is more standardized and Organization-wide KM practices are defined and measured regularly, Maturity Level 5 – Optimized: – KM is mastered and flexible to external and internal changes ) for assessment, understanding knowledge gaps, implementation of KM and the evolution of KM within an organization.

How has the evaluation of effectiveness of KM actions been accomplished, such as readiness assessment, maturity assessment and ROI?

When my firm is engaged with an organization to assess KM we tailor the KM Maturity Model activities to assess where the organization is with KM as well as develop activities in which to resolve gaps that have been identified. This leads to the development and operationalization of a strategy/roadmap to achieve a desired level of maturity.

What are the main reasons of KM success in an organization?

There are many reasons (or factors) for KM success. These reasons include:

Implementing a KM Strategy: The KM Strategy must be positioned to drive specific initiatives that align with the mission and objectives of the organization. The KM Strategy includes formal procedures, methods and processes to collect knowledge throughout the organization, a well-established infrastructure, networks for transferring knowledge between employees, and tools to facilitate the process. The KM Strategy will lay the foundation to align specific tools/technology to enhance individual and organizational performance.

Besides implementing a KM Strategy, other reasons for KM success are:

  • Having Executive Leadership/Sponsorship
  • Having adequate Budgeting and Cost Expectations
  • Having participation from all levels of the organization
  • Having adequate (or developing) processes and technology that support KM
  • Having adequate (or access to) Resources
  • Having adequate education and understanding of KM
  • Implementing sufficient metrics to measure the impact of KM on the corporation
  • Having adequate monitoring and controls in place to ensure the knowledge is relevant and is current and accurate
  • These reasons can be applied to all companies implementing KM and the absence of one or more of these factors may cause the KM effort (i.e., KM Program or KM Project) to fail.

Which solutions do you recommend be utilized in order to motivate and to increase the participation of people in KM?

The organizational culture plays an important role in motivating people to participate in KM. Creating an environment where informal networks are encouraged within the organization play a key role in the level of participation in KM activities. I have found the following solutions help increase participation of people in KM:

  • Incentivize people by awarding those who ideas create value for the organization
  • Highlighting those that participate in KM related activities (communities of practice, contributing to Wikis, active in blogs, learning a new skill important to the enterprise, attending conferences and presenting key learnings to the organization (knowledge transfer)
  • Tie participation in KM related activities to opportunities in which employee bonuses are increased
  • Communicating successful KM initiatives and the people who worked on them throughout the organization.

Creating knowledge-driven culture is one of the most important challenges of KM implementation, what is your suggestion for tackling this problem?

Here are some suggestions for creating a knowledge-driven culture:

The structure of the organization plays an important role in determining how knowledge is distributed, how decisions are made, the degree to which people feel comfortable sharing. It is important to remove barriers that exist between different groups and individuals. Organizational structure strongly influences the ability and willingness of people and communities to share and create knowledge, create an environment both physical and mental (open and trusting of individuals to share ideas) will help in developing your knowledge-driven culture.

Centralization: The degree to which decision making is centralized. In highly centralized

Organizations, decisions are made by few managers at the top of the organization. This puts a heavy demand on the cognitive capacity of these managers. Research and experience have identified that decentralized structures as being more suited for KM.

Formalization: The extent to which behaviors in an organization are governed by rules, policies, will have an effect on developing your knowledge-driven culture. In general, rigid, formal structures are regarded as being detrimental to KM.

A simpler organizational structure, which leads to less silos tend to make it easier for KM to be implemented. The complexity of the organizational structure also affects how it must be managed and what managerial roles are necessary to effectively implement KM.

What is your idea about trends and orientation of KM in 2017 and the near future?

One of the major areas in which KM will make an impact in 2017 and in the near future is within the customer service industry. Customer Service is the area in which most customers will have their only connection and interaction with your organization. It is this area where customers will form their opinions about the organization and determine if they remain a customer or move on to another competitor. Customer service is where organizations are investing a major portion of their revenue and attention to improving their customer service. Knowledge structures to support cognitive engagement in customer service is a future trend. Cognitive engagement solutions, interactive computing systems that use artificial intelligence to collect data, information and knowledge along with having the ability to understand and communicate in natural ways are all aspects of future customer service.

BIG Data continues to make an impact and present a challenge in the industry, which specifically points to how KM will be positioned to gleam knowledge from the various repositories of structured and unstructured data contained within the organization. Infusing Big Data with KM will provide organizations with a competitive edge to not only bring about significant innovations, but deliver knowledge across the enterprise to the right people at the right time and in the right context.

Social media is another future impact where KM will make a difference. Younger employees and customers having grown up in the social media era, and are more open to sharing information than previous generations. With adoption of enterprise collaboration tools on the rise, new streams, formats and sources of enterprise knowledge are being created. This consists largely of unstructured content (social chats, team forums, etc.) and this must be incorporated into a broader KM strategy, and be made easily accessible/findable by customers and employees. This will see a future impact of the use of Information Architecture in the delivery of knowledge.

Personal KM and Wearable Technology, with all of the advances in technology becoming accessories for us to wear is producing a multitude of data, information and knowledge accessible to the user. This includes Fitbits, Apple Watch, Google Glasses and more… all deliver and collect information that allow us to make personal decisions during the course of the day. What to eat, drink, wear, how much we’re exercising (or not) are all decisions in some part influenced by our wearable tech!

Wearable technology is gathering information not only about us but also the environment around us. Where is this all taking us? Will our physicians have the capability to tap into all of this personal information? How about potential advertisers? KM will be at the center of how can we capture the decisions we make from this information to improve our lives. Personal Knowledge Management the key to taking control of our personal information created by these devises.

What are your more pressing KM questions? Feel free to join the conversation here… and/or receive KM Mentoring and Guidance through the KM Mentor.

Dec 152016
 

km-for-law-firmsLegal knowledge management is the driving force within law firms across the globe. The recent International Bar Association (IBA) conference in Washington DC attracted over 6000 legal professionals from around the world and Knowledge Management (KM) was prominently featured at the conference. In an article by Ron Friedmann of Fireman & Company in Bloomberg Law he indicates that legal knowledge management is on the rise as law firms realize that KM increases a lawyer’s productivity (Friedmann, 2016). This increase in productivity leads to delivering better value to clients. Ron Friedmann also indicates that The 2016 Citi-Hildebrandt client advisory expects “to see more focus on knowledge management” and The 2015 Altman Weil law firm report finds that 68% of firms with 250+ lawyers have incorporated KM initiatives to improve the firm’s efficiency (Friedmann, 2016).

In a Forbes 2014 article Micah Solomon indicates that creating true client loyalty is one of the most powerful and reliable ways to build a strategic, sustainable advantage for the law practice and that truly loyal clients are less price sensitive, and are less likely to be enticed by competitive entreaties from the firm across the street or across the continent (Solomon, 2014). Knowledge Management plays a key role in ensuring a high level of client support. KM staff operate smoothly between lawyers and a range of operational functions; ideally situated to increase intra-firm collaboration, communication, and understanding. Some KM programs have worked on operations for some time, but business conditions are now ripe for more extensive applications of KM to firm operations; arguably critical to keeping operational teams relevant and law firms profitable (Solomon, 2014).

Client support specifically focuses on dramatically improving the client experience. It is the expectation of all clients that legal professionals and law firms will provide high quality legal services and it’s that promise and demonstration of high quality legal services that are the intangibles that will set the firm apart. To read this full blog post access Globe Law and Business (The key ingredient for creating and sustaining law firm profitability). For more about Legal Knowledge Management see Knowledge Management in Law Firms – Expertise in Action and for a look at how other industries are leveraging KM pick up a copy of Knowledge Management in Practice. As always, I look forward to your comments and questions!

 

Nov 302016
 

chapter-13-figure-1-km-competency-model-rhemOver the last several weeks I have been in conversations with colleagues and clients about what are the specific Knowledge Management (KM) roles that are essential for a KM project and/or program to succeed. Since there could be a myriad of the types of KM projects that can be initiated, the roles needed to successfully execute the KM project will vary. In determining the role(s) that are suitable for your KM Program/Project you will need to know what responsibilities are associated with each role and the core competencies needed to be successful in executing effectively. Armed with this information you must match the KM role, responsibility and core competency to your needs. Once that is completed, assigning the right people is the next step and determining what gaps in personnel exist (if any). If there are gaps in the personnel needed for your KM initiative leverage the information detailing the KM roles, responsibilities and core competencies to fill the necessary roles.

The roles of KM professionals consist of but are not limited to Chief Knowledge Officer (CKO), KM Program Manager, KM Project Manager, KM Director, Operations KM Director, KM Author, KM Lead, KM Liaison, KM Specialist, KM System Administrator, Knowledge Engineer, Knowledge Architect, KM Writer, Knowledge Manager, and KM Analyst. Knowledge management has both soft and hard competencies. The soft competencies include ensuring that knowledge processing is aligned with the organization’s business goals and objectives, and is integrated into the organization’s everyday business and work. It also includes software development, business and systems architecture and workflow management. The hard competencies include elicitation and representation of knowledge (both tacit and explicit) and it also includes structural knowledge in the form of business rules and business process.

Note: The KM Roles, Responsibilities and Core Competencies originally appear in Knowledge Management in Practice, by Dr. Anthony J. Rhem, published by CRC Press.

The following is a snapshot of the KM Roles, Responsibilities and Core Competencies for Knowledge Manager and KM Specialist:

KM Role Role Description Responsibilities Core Competencies
Knowledge Manager Knowledge Manager works with the KM Program and/or Project Manager to implement KM initiatives. The Knowledge Manager has the following responsibilities: -Manages KM efforts (often serves as a KM Project Manager or Product Owner)

-Looks across KM processes to capture tacit and explicit knowledge

– Balances technology, information, processes and individual and organizational learning within a culture of shared values.·        Creates ways to maintain a sustainable competitive advantage

Knowledge managers should also have a general understanding of knowledge architecture, but do not need an in-depth knowledge.Extensive experience and senior technical expertise in the field of Knowledge Management or Capacity Development preferably in an international development organization with a proven track record of successfully delivering KM strategies. Has worked in a developing country and has a good knowledge of international development issues, trends and approaches. Proven experience in the design and delivery of capacity development, coaching and mentoring activities, particularly adult learning techniques, replication of best practices. Strong knowledge and practice of Results Based Management (RBM), experience in performance measurement and program evaluation. Strong communication skills both written and verbal, excellent report writing and organizational skills. Leadership· Excellent communication· Time management/ability to prioritize· Development or management of information systems to support complex business processes· Project management of IT projects· Significant knowledge and use of relational database systems· Survey design· Finding assembling and analyzing verbal and numerical data from internet, databases and paper-based sources· Dissemination of information in a way that is accessible, manageable and which supports the work of individualism an organization· Experience of working effectively in a diverse team, maintaining good working relationships· Excellent information technology skills including relationship database programming and/or reporting skills
KM Specialist The Knowledge Management specialist is engaged in the support of the KM Policy, Planning Research and Metrics for knowledge management. KM Specialist Responsibilities Include:

Lead/contribute the development of a knowledge management strategy and associated implementation plan.

·Lead/contribute to the development and execution of the KM Governance Plan·        Develop a comprehensive mapping of KM information sources and knowledge, including processes

-Contribute to the develop and ongoing maintenance of the knowledge management system(s)

·Create a approach for guiding on going analyses needed to address observed KM gaps and for identifying opportunities for innovation, process, procedure and policymaking/adjustments

– Oversee capacity building and support for internal knowledge acquisition, management and sharing; ensure relevant communities of practice are developed and strengthened. Support development of staff, consultants and key partners and on all aspects of knowledge management

Knowledge engineers need in-depth competency as it pertains to Knowledge Architectures as well as Knowledge sharing, collaboration and transfer techniques and methods.
Oct 272016
 

ajrhem-italy-corp-meetingThe Central Knowledge Management Office (CKMO) is comprised of Senior Management and Core Team members and is the vehicle for implementing and keeping under review the KM initiatives that will be championed by the organization. The CKMO will support KM innovation, and enhance individual and organizational performance, by delivering improved learning, collaboration, and knowledge sharing into the culture of your organization’s environment.

The challenge of knowledge management is to determine what knowledge within an organization qualifies as “valuable.” All information is not knowledge, and all knowledge is not valuable. The key is to find the worthwhile knowledge within a vast sea of information. Oftentimes, knowledge management is misunderstood as simply maintaining websites or other technology. Besides what is mentioned above, the following list outlines what a CKMO delivers:

  • CKMO is orderly and goal-directed. It is inextricably tied to the strategic objectives of the organization. It uses only the knowledge that is the most meaningful, practical, and purposeful.
  • CKMO is ever-changing. There is no such thing as an immutable law in CKMO. Knowledge is constantly tested, updated, revised, and sometimes even declared obsolete when it is no longer practicable. It is a fluid, ongoing process.
  • CKMO is value-added. It draws upon a vast amount of knowledge located throughout many repositories across your organization.
  • CKMO is visionary. This vision is expressed in strategic business terms rather than technical terms, and in a manner that generates enthusiasm, buy-in, and motivates managers to work together toward reaching common goals.
  • CKMO is complementary. It can be integrated with other organizational initiatives such as KCS and ITIL.

Once the process captures the organization’s knowledge, the real power occurs when an organization’s members act on that shared knowledge.

The following are essential components to establish and maintain the CKMO (Vision, Mission and KM Governance)

CKMO Vision

The CKMO enables the retrieval, creation, sharing, collaboration and management of knowledge and through the implementation of workflow, search and collaboration capabilities, the CKMO vision is to quickly provide reliable solutions to questions and support the organization’s knowledge management needs.

CKMO Mission

The CKMO mission is to support the vision of CKMO and implement the initiatives that support the best practices identified by the CKMO strategy. The CKMO Team will execute a Knowledge Management program that embodies situational understanding, organizational learning and decision making by providing knowledge products and services that are relevant, accurate, and timely.

CKMO Governance

Knowledge Management Governance ensures policy adherence and provides controls to guarantee that the knowledge stored and accessed provides the best value for the organization. CKMO Governance describes the policies, procedures, roles, and responsibilities to successfully maintain the organization’s knowledge assets. Effective governance planning and the application of the governance plan are critical for the ongoing success of knowledge management within the organization.

The governance plan will establish the processes and policies to:

  • Avoid proliferation of unnecessary knowledge by defining consistent review process (workflow).
  • Ensure that knowledge quality is maintained for the life of the knowledge asset by implementing quality management policies.
  • Provide a consistently high quality user experience by defining guidelines for knowledge creators.
  • Establish clear decision-making authority and escalation procedures so policy violations are managed and conflicts are resolved on a timely basis.
  • Ensure that the solution strategy is aligned with business objectives so that it continuously delivers business value.
  • Ensure that knowledge is retained in compliance with organizational retention guidelines.

As always, I look forward to comments and conversation on this topic.

Aug 312016
 

Knowledge Management in Practice by Anthony J RhemKnowledge is recognized as a valuable asset in organizations across many industries. How knowledge is shared, leveraged, obtained and managed will be the difference in how successful and sustainable an organization will become. This book is a culmination of my years of experience within the knowledge management (KM) discipline. Since 1998 I have been involved in knowledge management, from researching, developing processes for capturing and codifying knowledge, developing knowledge management systems, developing and operationalizing knowledge management strategies across several industries, writing articles, books, developing and teaching KM curriculum and speaking at numerous KM conferences.

My latest book Knowledge Management in Practice covers how knowledge management is leveraged in several industries. An examination of the various uses of KM practices, policies, procedures and methods including tips and techniques to create a competitive advantage are presented. The industries that are covered include first responders, military, healthcare, Insurance, financial services, legal, human resources, merger and acquisition firms, and research institutions.

Essential Knowledge Management concepts are also explored not only from a foundational perspective, but from a practical application. These knowledge management concepts include capturing and codifying tacit and explicit knowledge, KM methods, information architecture, search, KM and social media, KM and Big Data, adoption of KM, and why KM Initiatives fail.

The following are the subjects that are covered and what you can expect from the various chapters:

  • The Case for Knowledge Management (KM): Chapter 2 – The Case for Knowledge Management details the factors you must consider to in order to make the case for your organization to start instituting KM and its various practices and policies. This chapter details what will be necessary for your organization to either launch a KM initiative/project, and/or establish a KM program.
  • Being Social – KM and Social Media: Chapter 3 – In this chapter KM and Social Media examines how social media tools and techniques are becoming facilitators of knowledge for the organization. In this chapter specific guidance and insight is given to develop your organizations social media strategy and to determine the social media tools, techniques and platforms that can be utilized to begin taking advantage of what social media can bring to KM.
  • Dude, where’s my car: Utilizing Search in KM: Chapter 4 – Utilizing search in KM details the importance of search in knowledge management and in particular a knowledge management system. Several aspects of implementing search are examined including the importance of having user centric information architecture.
  • The Age of Discovery: KM in Research Institutions: Chapter 5 – Research institutions play a key role in product innovation. Knowledge Management is a catalyst to stimulating and sustaining a high level of innovation. This chapter examines how KM is utilized; focusing on various KM methods that can and in some cases are being incorporated at research institutions.
  • Where has all my experts gone? – KM in Human Resources and Talent Management: Chapter 6 – When it comes to talent management KM can play a critical role in ensuring the knowledge assets are captured and made available to the enterprise. KM in talent management when applied holistically involves capturing and sharing employee knowledge from onboarding to exit interview.
  • Sound the Alarm! – KM in Emergency and Disaster Preparedness: Chapter 7  – Emergency and disaster preparedness is enhanced through the incorporation of knowledge management. Putting the right knowledge in the right context at the right time in the hands of First Responders could be the difference in saving lives and preventing casualties. It is important to begin with a comprehensive KM strategy in order to establishing a plan to deliver the knowledge in a timely manner.
  • Happily Ever After – KM in Mergers and Acquisitions: Chapter 8 – When organizations merge or are acquired there is a level of uncertainty both from a macro (organization) level and from a micro (employee) level. Applying KM to mergers and acquisitions will enable the organization to know what knowledge is important to retain, who those knowledge holders are, what are the knowledge gaps and how to quantify the knowledge of the organization. From an employee standpoint having the organization share knowledge about the pending transaction as well as incentify employees to share what they know and to assist employees in transitioning (within the new organization or to a new organization) will go a long way to ensure a smooth M&A transaction.
  • Is there a Doctor in the house? – KM in Healthcare: Chapter 9 – Healthcare has become focused on the individual. As the healthcare community moves to electronic record keeping and capturing patient information at the point of initial interaction; having accurate knowledge about that patient as well as having the patient knowledgeable about his/her own health is essential to the success of caring for that patient. KM is an essential ingredient for healthcare success, especially in the areas of drug interaction analysis, sharing of patient diagnosis between hospitals and doctors, and furthering the development of healthcare informatics.
  • Show me the Money! – KM in Financial Services: Chapter 10 – Knowledge Management in the financial services sector centers on being able to attract, serve and retain customers. By delivering the tools to customers that provide knowledge in order to make sound financial decisions is at the heart of what KM will provide. In order to bring innovative financial services and products to the marketplace and have an understanding of how it will best serve and benefit the customer; putting specific knowledge at the fingertips of employees serving the customer will also be critical component of what KM will bring.
  • Are you in Good Hands? – KM in Insurance Industry: Chapter 11 – In this chapter you will learn how KM in the insurance industry is used to communicate knowledge to customers, agents and customer contact centers while providing mechanisms for employees to share, capture and catalog knowledge. KM in the insurance industry will provide the knowledge to (among other things), complete applications, bind insurance, and service a claim.
  • Sign Right Here! – KM in the Legal Profession: Chapter 12 – In this chapter an examination of how KM can/should be used to enhance the management of a law firm and execute on client engagements will be presented. KM in law firms is primarily executed through the building and fostering communities of practice around practice specialties. This enables legal representatives to respond to a situation with the right expertise, equipped with the right knowledge to resolve a legal matter.
  • Get That Knowledge! – Knowledge Management Education: Chapter 13 – This chapter examines the state of knowledge management education. This examination includes KM certification programs, KM curriculum at institutions of higher learning, as well as KM education policies, procedures and future direction of KM education. In addition this chapter will present specific criteria to consider when selecting a KM education option.
  • Big Knowledge! KM in Big Data: Chapter 14 – In this chapter an examination of how KM can and should be used to gain knowledge from your Big Data resources will be presented. How KM will be used on Big Data to provide a rich structure to enable decisions to be made on a multitude and variety of data is the essence of this examination. Along with specific analysis of the various types of data and KM methods for examining this data, a detailed understanding of KM’s impact on Big Data can be realized.
  • What have you done for the War Fighter Today? – KM in the Military: Chapter 15  – There is a rich history when it comes to KM in the Military. An examination of how KM in the military is being used with special attention to such events as Base Realignment and Closures (BRAC) will be examined. In addition a look at the various branches of the military (Army, Air Force, and Navy) and their KM Strategies, KM systems and KM methods are presented.
  • Drinking the KM-Kool-Aid: Knowledge Management Adoption: Chapter 16 -Adoption of KM programs, policies, methods, and systems, is a challenge for all organizations. This chapter is all about adoption! If your organization does not adopt its KM principles, practices, processes, procedures or systems that deliver KM they may be recognized as a failure. This chapter will present specific guidance on how to improve KM adoption and how to position your KM initiatives for success.
  • Failure is not an option! – Why KM Projects Fail: Chapter 17 – With lofty promises come unrealized results. Knowledge Management gained widespread popularity in the 90’s, however many KM initiatives failed and this popularity has tapered quite a bit. Since the mid 2000’s a renaissance of KM began to occur, some disparate KM success started to be achieve (call centers, research, human resources, military ) and KM is now considered as a discipline to use as a competitive advantage. Although KM is being used with some success in this new knowledge economy, many KM initiatives still fail. This chapter details the factors that contribute to KM initiatives failing as well as measures to adhere to in order to achieve KM success.

Included in this publication is an in-depth synopsis of each chapter and an overall introduction to the book in chapter 1. The book concludes with chapter 18, which offers a summary of the book and insight on what’s next for knowledge management.

For those individuals and organizations who have purchased my book I would like to thank you and invite you to ask me questions about the material covered in the book and/or any KM questions that are on your mind.

Jul 312016
 

MentoringI want to start this blog post by asking a question.

Question: Once you complete a training class, a college course, and/or a seminar are you then ready right away to apply what you’ve learned to effectively do your job?

I believe in 90% of the cases that answer is NO!

So how do we begin to address this? One proven way is to have a trusted mentor with the expertise you need to work with your team or individual to implement what has been learned. Mentoring or instituting a mentor protégé program is a proven method to transfer knowledge. Knowledge Management (KM) like any other discipline, needs mentors (or experts) to assist organizations to properly carry out their vision and mission for implementing KM. To properly execute KM at your organization, no matter if your organization is new to KM or have a need to bring your team to another level of understanding, mentoring is the preferred method.

Mentor, Coach or Consultant (adapted from Afif Tabsh)

So what distinguishes a mentor, coach or consultant:

Mentor: Someone who has a considerable amount of experience in a specific field, topic, industry and uses it to guide others, to show them how to use it and understand why it’s used a certain way.

Coach: Someone who has the skills and know-how of asking the right questions to people to extract ideas, concerns and decisions from them. A coach works through others to get results rather than show them the way or guide them into a solution.

Consultant: Someone who has the knowledge and expertise in a certain field, topic or industry along with the skills of how to facilitate discussions and ask the right questions to be able to give you the best solution for a specific issue or problem you are facing.

A Mentor is a combination of both Coach and Consultant!

What we are doing at my firm A.J. Rhem & Associates is implementing an online mentoring environment for Knowledge Management. We are taking the idea of the mentor and creating an environment where those who are working with KM to execute KM projects and/or establish KM programs can receive the guidance needed to achieve success and deliver on what KM can do for you as a practitioner and your organization.

Knowledge Management Mentor – Online

The KM Mentor.com site brings essential KM concepts to all subscribers that are not only from a foundational perspective but also from a practical application. These concepts include but are not limited to, capturing and codifying tacit and explicit knowledge, KM methods, information architecture, search, KM and social media, KM and Big Data, and the adoption of KM.

KM Mentor provides access to:

  • Presentations by industry leaders on a variety of topics
  • KM templates and instruction on executing KM strategy, performing knowledge transfer, and KM assessments and audits
  • KM program and project implementation guidance
  • Insights and reviews on KM tools
  • Guidance on implementing and executing various KM Methods
  • Specialized KM publications
  • A private secure collaboration community for members to discuss ideas and get expert answers and advice

As always I welcome your comments!

 

Jun 302016
 

WCG Content ModelContent modeling is a powerful tool for fostering communication and alignment between User Experience (UX) design, editorial, and technical resources on a Information Architecture effort. By clearly defining the content domains, content types, content attributes (metadata) and relationships, we can make sure that the envisioned content strategy becomes a reality for the content creators.

The Content Model is a logical depiction of what an organization knows about things of interest to the business and graphically shows how they relate to each other in an entity relationship (ER) diagram or class diagram. An entity relationship diagram is an abstract conceptual representation of structured data.  It uses standard symbols to denote the things of interest to the business (entities), the relationships between entities and the cardinality and optionality of those relationships.  The Content Model, contains detailed characteristics of the content types or concepts, attributes or properties and their definitions.  It is a result of detailed analysis of the business requirements.

When starting a content modeling effort, it is important to begin with a high-level (conceptual content model). The conceptual content model is the first output from content modeling. After some initial work identifying, naming and agreeing on what content domains and content types are important within your problem domain you are now ready to structure them together into a conceptual content model.

It is essential that content strategists, information architects and business stakeholders engage with content modeling early on in the process. These are the people best positioned to find and classify content types that make sense for the business. They bring that understanding of why content needs to be structured, named and related in a certain way. In addition, the business subject matter experts bring knowledge of the rules about content that drives the naming and determining of relationships between content types.

Finding Content Types

Content types live in existing web sites, customer call centers (call logs), product documentation, communications, as input & output of processes and functions as well as in the mind of people performing various tasks. The mission is to find them, document and define them. here are other reasons to make something a separate type of content:

  1. Distinct, reusable elements. You might decide to create an Author content type that contains the name, bio and photo of each author. These can then be associated with any piece of content that person writes.
  2. Functional requirements. A Video might be a different type of content because the presentation layer needs to be prepared to invoke the video player.
  3. Organizational requirements. A Press Release may be very similar to a general Content Page, but only the Press Release is going to appear in an automatically aggregated Newsroom. It’s easier for these to be filtered out if they’re a unique type of content.

Content models progress along a continuum of constant refinement, there are three important stages in the content modeling lifecycle:

  • Conceptual: The initial content model which aims to capture the content domains, content types and high level relationships between content types.
  • Design: Adds the descriptive elements (metadata) to each content type and further refines the structural relationships between them.
  • Implementation: Models the content within the context of the target technology, e.g. CMS, Search Engines, Semantic Tools, etc.

Remember Content is KING!