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.
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!

 

Jan 132016
 

K15968-v2As we move into 2016 it is time to reflect on knowledge management and look at the future of this discipline. In my latest book: Knowledge Management in Practice I address what I believe is the future of KM in 2016 and beyond. An excerpt from chapter 18 follows.

Future of Knowledge Management:

One of the major areas in which KM will make an impact 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. Due to this scenario (and others) organizations invest a major portion of their revenue and attention to improving their customer service.

In an August 2014 Harvard Business Review article by Peter Kriss entitled “The Value of Customer Experience, Quantified” he states “Intuitively, most people recognize the value of a great customer experience. Brands that deliver them are ones that we want to interact with as customers that we become loyal to, and that we recommend to our friends and family”. Also, he states that the “value of delivering such an experience is often a lot less clear, because it can be hard to quantify” Delivering consistent and concise knowledge to provide answers to customer inquiries in an efficient way leads to providing value to the customer and improving the overall customer experience.

In support of this trend of KM in customer service, Forrester’s “Top Trends For Customer Service in 2015”, author Kate Leggett points out in trend #4, knowledge management’s impact when she states “Knowledge Will Evolve From Dialog To Cognitive Engagement. Organizations will look at ways to reduce the manual overhead of traditional knowledge management for customer service. They will start to explore cognitive engagement solutions, interactive computing systems that use artificial intelligence to collect information, automatically build models of understanding and inference, and communicate in natural ways. These solutions have the potential to automate knowledge creation, empower agents with deeply personalized answers and intelligence, scale a company’s knowledge capability, and uncover new revenue streams by learning about customer needs.”

IBM Watson is playing a significant role in the evolution of applications that automate knowledge creation by providing deeply personalized answers and intelligence. This technology will not only effect customer service, but a multitude of industries with its capability to extract knowledge from Big Data sources. The IBM Watson ecosystem will provide deep content analytics and intensive scientific discovery that will lead to improve cognition contributing to an organization’s knowledge capabilities. This supports Kate Leggett’s research and points out that KM will continue to play a significant role in delivering knowledge and decision making capabilities to the customer service industry for the foreseeable future (2016 and beyond).

Global View of KM

In reviewing the 2015 Global Knowledge Management Observatory Report, authors David Griffiths, Abi Jenkins and Zoe Kingston-Griffiths state “The Knowledge Management function in many organizations is in a state of general decline”. This as they indicate is due to the following factors:

  • “Satisfaction in Knowledge Management’s contribution to strategic and operational objectives within organizations is often poor.”
  • “Knowledge Management lacks maturity and integration within the vast majority of organizations.”
  • “Knowledge Management continues to be predominantly seen as a technology-led function.”
  • “Satisfaction with technology-led Knowledge Management solutions is not improving.”
  • “Many Knowledge Management professionals do not appear to have the necessary awareness and/or permissions required to respond to unmet demand for KM activities in organizations.”
  • “Knowledge Management, as a field or area of practice, is argued to be suffering from a lack of specialist practitioners.”
  • “The value and/or significance of Knowledge Management activities is still not being appropriately recognized or reported within most organizations.”

Solutions that address many of the findings of the 2015 Global Knowledge Management Observatory Report are essential for KM success in 2016 and as KM evolves as a discipline. This includes producing a comprehensive KM strategy, KM education options, adopting KM programs, project and systems, and addressing why KM programs/projects fail.

All of these aspects from the 2015 Global KM Observatory Report are addressed in Knowledge Management in Practice. This book should be leveraged as a reference/guide and presents a tremendous resource to support the growth of KM at your organization.

Nov 302015
 

Chapter 9 - Figure 2 - Model for KM in Healthcare

Healthcare is a knowledge intensive business. Making the best use of knowledge within any healthcare provider organization (hospital, clinic, pharmacy, physician private practice, etc.) is essential for optimal patient care as well as cutting and/or streamlining costs. Knowledge Management (KM) in healthcare is about sharing know-how through collaboration and integration of systems to enable access to knowledge. Applying knowledge sharing and collaboration to healthcare would include sharing medical research, giving visibility to patient decisions, and collaboration between physicians and healthcare provider organizations. Collaborative work environments will bring more effective communication and more physician responsiveness to patients.

Healthcare is also a massive industry, and every healthcare provider organization faces challenges where incorporating knowledge management would be beneficial. The processes and systems that enable the delivery and management of healthcare services to patients are faced with the prospect of failing to prevent (and can indirectly or directly cause) suffering and in some cases death to the various patients it serves. It is for this reason that knowledge management is attracting much attention from the industry as a whole. However, it is now time that the healthcare industry start to implement KM and begin realizing the benefits that it can provide.

KM is a particularly complex issue for health organizations. The potential benefits knowledge-management implementation could bring are enormous. Some of these benefits include: better outcomes for patients, cost reduction, enhanced job flexibility, and improved responsiveness to patients’ needs and changing lifestyles and expectations and ensure more effective communication, leading to focused and (hopefully) seamless care interventions and a better patient experience.

In realizing these benefits it is understood that healthcare delivery is a knowledge driven process and KM provides the opportunity to incorporate knowledge management practices to improve the various healthcare processes.

To leverage knowledge management in the appropriate way to address the complex and process nature of healthcare, healthcare organizations should adopt a broad strategy to capture, communicate and apply explicit and tacit knowledge throughout the healthcare delivery process.

Healthcare Delivery Process

Delivery of healthcare is a complex endeavor. It includes primary organizations for healthcare delivery such as healthcare providers having inter-organizational relationships with other players (i.e., Blue Cross/Blue Shield and its member organizations, physician and hospital affiliations) to provide a foundation. The increasing cost of healthcare is putting pressure on access and quality of healthcare delivery and this is calling for increased accountability, because of high rates of medical errors, and globalization which leads to demands of higher standards of quality, are also putting pressures on healthcare delivery organizations.

The healthcare delivery process includes the following areas Patient Intake, Data Collection, Decision Support, Diagnosis and Treatment, and Patient Closeout. Each of these areas (depending on medical organization) have more complex processes, procedures and systems that enable them to integrate and function together. Below provides more details of each of the areas that comprise the healthcare delivery process:

Patient Intake Process: Due to the increase in patient demand partially caused by health reform initiatives that focus on broadening patient access to insurance, many medical practices are experiencing an increase in new patient enrollment. Whenever new patients use the services of a hospital or physician practice, they must complete forms that list their contact information, medical history, insurance information, and acknowledgement of various HIPAA regulations.

The patient intake process is the first opportunity to capture knowledge about the patient and his/her condition at the time of arrival at the healthcare facility. At this point the patient information is captured, along with method of payment, medical history and current vital condition. All of this data is transitioned to the facilities database. This presents an opportunity for the data to be shared, an opportunity for information to be processed from the data, and knowledge to be acquired from the information.

Data Collection: At this point of the process all the data that was taken during the intake process is collected and sent to the healthcare facilities’ database. The collection of healthcare data involves a diverse set of public and private data collection systems, including health surveys, administrative enrollment and billing records, and medical records, used by various entities, including hospitals, clinics, physicians, and health plans. This suggest the potential of each entity to contribute data, information and knowledge on patients or enrollees. As it stands now a fragmentation of data flow occurs because of these silos of data collection. One way to increase the flow of data, information and knowledge is to integrate them with data from other sources. However, it should be noted that a substantial fraction of the U.S. population does not have a regular relationship with a provider who integrates their care.

Decision Support System: This area of the healthcare delivery process involves integrating the Clinical Decision Support Systems (CDSS). The CDSS will enable the standardization and sharing of clinical best practices and protocols with staff, patients, and partners on demand, anywhere, and on any device. Physicians, nurses and other healthcare professionals use a CDSS to prepare a diagnosis and to review the diagnosis as a means of improving the final result. Data Mining (which will be examined later in this chapter) is conducted to examine the patient’s medical history in conjunction with relevant clinical research. Such analysis will provide the necessary knowledge to help predict potential events, which can range from drug interactions to disease symptoms. Some physicians may use a combination of a CDSS and their professional experience to determine the best course of care for a patient.

There are two main types of clinical decision support systems. One type of CDSS, which uses a knowledgebase (expert system), which applies rules to patient data using an inference engine and displays the results to the end user. Systems without a knowledge base, on the other hand, rely on machine learning to analyze clinical data. The challenge here is that a CDSS to be most effective it must be integrated with the healthcare organizations clinical workflow, which is often very complex. If a CDSS is a standalone system it will lack the interoperability needed to provide the knowledge necessary for healthcare professions to make a good determine of the best course of care for a patient.

However, the sheer number of clinical research and medical trials being published on an ongoing basis makes it difficult to incorporate the resulting data (Big Data). Additionally, incorporating Big Data into existing systems could causes a significant increase in infrastructure and maintenance.

Diagnosis and Treatment: Making a diagnosis is a very complex process, which includes cognitive tasks that involves both logical reasoning and pattern recognition. Although the process happens largely at an unconscious level, there are two essential steps where knowledge can be captured and applied.

In the first step, the healthcare professional will enumerate the diagnostic possibilities and estimate their relative likelihood. Experienced clinicians often group the findings into meaningful clusters and summarizes in brief phrases about the symptom, body location, or organ system involved.

In the second step in the diagnostic process, healthcare professional would incorporate new data, information and/or knowledge to change the relative probabilities, rule out some of the possibilities, and ultimately, choose the most likely diagnosis. For each diagnostic possibility, the additional knowledge increases or decreases its likelihood. At this point the diagnosis and treatment is rendered by the healthcare professional and the patient records are updated.

Patient Closeout/Patient Discharge: In the case of a simple patient closeout from a routine/scheduled physician visit or simple visit to the local clinic, the patient receives medication (if applicable), sets follow up appointments if necessary and finalized payment arrangements and the patient records are updated. However if you have had a hospital stay the discharge process can be quite involved. In the case of a discharge a set series of tasks must occur prior to discharging a patient. These tasks include examination and sign-off by appropriate providers and patient education. For each patient, the time of discharge and the tasks that need to be performed will be provided one day ahead of time. This allows for everyone involved in the discharge to self-organize on the day of discharge to get the work done within the window necessary to meet the scheduled discharge time (Institute for Health Improvement, 2015). At the conclusion of the discharge, patients receive information and instructions for continued care and follow up, in addition all patient records should be updated.

The following was an excerpt from my latest book: Knowledge Management in Practice

 

Oct 312015
 

Fin ServFinancial service enterprises operate in a highly challenged market where consolidation, increasing regulation and economic realities are negatively impacting their ability to achieve key objectives. This has created a culture where there is a constant need to find more predictable revenue streams and cost efficiency gains.

Regulatory bodies such as the Financial Industry Regulatory Authority (FINRA), Securities and Exchange Commission (SEC), Commodity Futures Trading Commission (CFTC), and the various international bodies’ present challenges to financial service organizations to deliver fair and open products and services, while providing answers, and direction to the various customers interacting with their organizations. In order to address these challenges knowledge management is needed to streamline processes and deliver content at the right time, in the right way and in the right context to meet the demand of customers.

In meeting the demand for customers, it is increasingly important for financial services organizations to address customer needs. KM through the implementation of processes and technology (including Information Architecture – see Chapter 4) will ensure customer information is shared with the right people at the right time across the organization. By utilizing a customer-focused, integrated knowledge management system, all employees interacting with a customer will have up to date knowledge of that customer’s breadth of relationship and experience with the organization. This will assist the organization with cross selling, up selling and reporting on the effectiveness of any new customer initiatives.

In addition the staff must start (if they are not already doing so) working together using knowledge as a focal point to service the customer. With this emphasis, as more financial products and services become available through mobile devices the ability for those financial companies to respond rapidly to customer demands with the right answers, at the right time, and in the right context will be met. 

Empowering Employees to Satisfy Customers

The objective of knowledge management is to capture knowledge of different stakeholders of the organization and make it explicitly available to all employees. Sharing of knowledge will enable improved and quicker decision making. Employees empowered with improved decision making will increase the ability to address customer needs and create more satisfied customers. Empowering your employees through knowledge management will assist your organization in addressing competition driven by reduced barriers to switch companies, the proliferation of products and product commoditization, mergers and acquisitions and the ever changing product portfolios, and shifts in customer behaviors.

Financial services organizations (including banks) value of Knowledge Management as a business practice. From managing intellectual capital, to the vast array of customer data, one of the goals of KM is to enhance customer satisfaction and increase revenue.

Whether the organization is regional or global, a key aspect of your business and specifically your KM strategy must be to treat each client as an individual with individual needs. By implementing a comprehensive KM program and associated processes and systems a determination as to which customers are most likely to buy which products, who is at risk of leaving, which unprofitable clients are most likely to be profitable, and who is most likely to respond to which marketing campaigns based on their demographics, can start to be addressed and the organization will have a sustainable model for success!

Knowledge management practices, policies, procedures and applications all aimed at delivering financial services that enable people to build financial stability should be the focus of all financial services organizations. This chapter focuses on the use of Knowledge Management (KM) within the financial industry and will present how KM is being leveraged to increase sales through customer satisfaction, capturing and cataloging knowledge for a personal interaction, the advantage of creating and leveraging communities for improved employee performance and extending your knowledge to customers to provide self-service provides a competitive edge.

 

Jul 282015
 

KMandBigDataBig Knowledge! Knowledge Management and Big Data – Excerpt from Chapter 14: Knowledge Management in Practice:

A goal of knowledge management is to capture and share knowledge wherever it resides in the organization. Leveraging the corporate collective know-how will improve decision making and innovation where it is needed. The proliferation of data, information and knowledge has created a phenomenon called “Big Data”. Knowledge Management when applied to Big Data will enable the type analysis that will uncover the complete picture of the organization and be a catalyst for driving decisions. In order to leverage an organizations Big Data it must be broken down into smaller more manageable parts. This will facilitate a succinct analysis, which then can be regrouped with other smaller subsets to produce “big picture” results.
Volume, Velocity, and Variety are all aspects that define Big Data.
Volume: The proliferation of all types of data expanding many terabytes of information.
Velocity: The ability to process data quickly.
Variety: Refers to the different types of data (structured and unstructured data such as data in databases, content in Content Management and Knowledge Management systems/repositories, collaborative environments, blogs, wikis, sensor data, audio, video, click streams, log files, etc.).
Variety is the component of Big Data in which KM will play a major role in driving decisions. Enterprises need to be able to combine their analyses to include information from both structured databases and unstructured content.

Data, Information and Knowledge

Since the focus here is about leveraging knowledge management techniques to extract knowledge from Big Data, it is important to understand the difference between data, information and knowledge: Data, I often refer to as being represented by numbers and words representing a discrete set of facts. Information is an organized set of data (puts context around data). This can result in an artifact such as a stock report, news article, etc. Knowledge on the other hand emerges from the receiver of information applying his/her analysis (aided by their experience and training) to form judgments in order to make decisions. Erickson and Rothberg indicates that information and data only revel their full value when insights are drawn from them (knowledge). Big Data becomes useful when it enhances decision making, which in turn is only enhanced when analytical techniques and an element of human interaction is applied (Erickson and Rothberg, 2014).

In a February 26 2014 KM World article titled “Big Data Delivering Big Knowledge” Stefan Andreasen is Chief Technology Officer at Kapow Software indicates that “To gain a 360 degree view of their ecosystem, organizations should also monitor user-generated data, public data, competitor data and partner data to discover critical information about their business, customers and competitive landscape” (Andreasen, 2014). The user-generated data, public data, competitor data and partner data provides the variety of data needed to be analyzed by KM and it’s this type of data that will be examined more closely.

User-generated data
Customers are sharing information about their experience with products and services, what they like and don’t like, how it compares to the competition and many other insights that can be used for identifying new sales opportunities, planning campaigns, designing targeted promotions or guiding product and service development. This information is available in social media, blogs, customer reviews or discussions on user forums. Combining all this data contained in call center records and information from other back-office systems can help identify trends, have better predictions and improve the way organizations engage with customers (Andreasen, 2014).

Public data
Public information made available by federal, state and local agencies can be used to support business operations in human resources, compliance, financial planning, etc. Information from courthouse websites and other state portals can be used for background checks and professional license verifications. Other use cases include monitoring compliance regulation requirements, bill and legislation tracking, or in healthcare obtaining data on Medicare laws and which drugs are allowed per state (Andreasen, 2014).

Competitor data
Information about competitors is now widely available by monitoring their websites, online prices, and press releases, events they participate in, open positions or new hires. This data allows better evaluation of the competition, monitor their strategic moves, identify unique market opportunities and take action accordingly. As a retailer for example, correlate this data with order transaction history and inventory levels to design and implement a more dynamic pricing strategy to win over your competition and grow the business (Andreasen, 2014).

Partner data
Across your ecosystem, there are daily interactions with partners, suppliers, vendors and distributors. As part of these interactions organizations exchange data about products, prices, payments, commissions, shipments and other data sets that are critical for to business. Beyond the data exchange, intelligence can be gleaned by identifying inefficiencies, delays, gaps and other insights that can help improve and streamline partner interactions (Andreasen, 2014).
To comb through the various sources of user-generated data, public data, competitor data and partner data leveraging KM analytics (data analysis, statistics, and trend analysis) and content synthesis technology (technology that categorizes, analyze, combines, extracts details, and re-assess content aimed at developing new meanings and solutions) will be necessary.

Applying KM to Big Data
Knowledge Management has the ability to integrate and leverage information from multiple perspectives. Big Data is uniquely positioned to take advantage of KM processes and procedures.

These processes and procedures enables KM to provide a rich structure to enable decisions to be made on a multitude and variety of data. In the “KM World March 2012” issue it was pointed out that “organizations do not make decisions just based on one factor, such as revenue, employee salaries or interest rates for commercial loans. The total picture is what should drive decisions”. KM enables organizations to take the total picture Big Data provides, and along with leveraging tools that provide processing speed to break up the data into subsets for analysis will empower organizations to make decisions on the vast amount and variety of data and information being provided.

The emerging challenge for organizations is to derive meaningful insights from available data and re-apply it intelligently. Knowledge management plays a crucial role in efficiently managing this data and delivering it to the end users to aid in the decision making process. This involves the collection of data from direct and indirect, structured and unstructured sources, analyzing and synthesizing it to derive meaningful information and intelligence. Once this achieved it must be converted it into a useful knowledge base, storing it and finally delivering it to end users.