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.

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!

 

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.

Sep 192015
 

contextual%20intelligence-technologyThis all started during a conversation I had with a colleague (Baron Murdock of GreenBox Ventures, LLC) and he mentioned the term Contextual Intelligence. Due to the fact that we were talking about knowledge management and big data I believe that I understood what he was talking about. However, I had never heard of the term. Not long after our meeting I began to do a little research on the concept of contextual intelligence.

What is Contextual Intelligence?

It is during my initial research (consisting of a series of internet search queries) where I began to understand that the term Contextual Intelligence is not new. As a matter of fact it’s a term that has been used in graduate business schools since the 80’s.

Contextual Intelligence is, according to Matthew Kutz “a leadership competency based on empirical research that integrates concepts of diagnosing context and exercising knowledge”; Tarun Khanna states that ”understanding the limits of our knowledge is at the heart of contextual intelligence” and Dr. Charles Brown states that “Contextual intelligence is the practical application of knowledge and information to real-world situations. This is an external, interactive process that involves both adapting to and modifying an environment to accomplish a desired goal; as well as recognizing when adaptation is not a viable option. This is the ability that is most closely associated with wisdom and practical knowledge”

While there are several positions on what contextual intelligence is. I align more to Dr. Brown’s assertion of Contextual Intelligence. When it comes to knowledge management (KM) and contextual intelligence, context matters! Understanding that contextual intelligence is link to our tacit knowledge, I immediately thought of what is the connection between KM and Contextual Intelligence. Knowledge management among other aspects is concerned with the ability to understand knowledge and adapt that knowledge across a variety of environments (cultures) different from the origin of that knowledge.

To enable the flow of knowledge to the right person in the right time and in the right context, it is essential to understand the context of that knowledge. Information Architecture (IA) is the backbone of delivering knowledge in the right context to users of Knowledge Management Systems (KMS). IA focuses on organizing, structuring, and labeling content (information and knowledge). IA enables users to find relevant content in the right context, understand how content fits together, connects questions to answers and people to experts. It is the incorporation of IA that contributes to giving knowledge its context.

Understanding the context of knowledge consists of:

  • Understanding the intent of the knowledge
  • Understanding the cultural and environmental influences on the knowledge
  • Understanding the role (or who) the knowledge is intended to be used by
  • Understanding the relevancy of the knowledge (The knowledge could only be valid for a specific period of time)
  • Understanding the origin (lineage) of the knowledge

Big Data

Without context data is meaningless, this includes structured and unstructured data. Big Data resources contain a proliferation of structured and unstructured data. Knowledge management techniques applied to big data resources to extract knowledge will need to understand the context of the data in order to deliver pertinent knowledge to its users. 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.

We know that context matters. Especially when it comes to what we know (our knowledge). Being able to adapt our knowledge with others is at the heart of successfully communicating, sharing what we know and to fuel innovation.

Obtaining contextual intelligence for your organization consists of leveraging or hiring people who are fluent in more than one culture, partnering with local companies, developing localized talent and enabling your employees to do more field work to immerse themselves in other cultures (tuning in to cultural and environmental differences).

A couple of great resources to read on Contextual Intelligence are “Contextual Intelligence” by Tarun Khanna from the September 2014 issue of Harvard Business Review and “Understanding Contextual Intelligence: a critical competency for today’s leaders” by Matthew R Kutz and Anita Bamford-Wade from the July 2013 Emergent Publications, Vol. 15 No. 3.

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.

Jan 302013
 

Knowledge Management TrendsNow that we are firmly into 2013 lets take a look at what is trending in Knowledge Management (KM) this year.

With the proliferation of mobile devices (iPhone, Chromebook, iPad, Android devices) Personal KM is moving front and center. In the enterprise, as more and more content and knowledge gets created and the need to access and use that knowledge and content to address day-to-day knowledge needs of workers and customers (see Big Data), providing knowledge quickly to address internal and external users, as well as search and findability, are getting much attention within organizations implementing KM.

Let’s take a look at what some others are indicating the trends will be for KM in 2013:

  • Matthew Whalley – ClientKnowledge Manager (Legal Services), talks about “helping clients to realize efficiencies and knowledge gains, the growing realization that KM delivers more than “documents” providing  “operational” efficiency, transaction delivery, knowledge re-use and transformation, and technology – social and mobile channels”.
  • SAP indicates that “defining a knowledge management strategy, structuring content and measuring business impact as well as reaching external leadership are becoming more and more important”.
  • KMWorld indicates that the focus is on sharing collective knowledge and on KM strategy more so than the technology.

These are some thoughts on what to expect regarding KM for 2013. So, what do you think? I look forward to hearing more about what other organizations and individuals are doing with KM in 2013!

Nov 292012
 

 

TimeDoin’ Time* somewhere south of Normal…

Time = KM Time

Similarities between Knowledge Management (KM) and “other kind of time”
      Confined to small space with other detainees…..

 

         Most others don’t know what you do (or why)…

 

         Time is not an enemy but a constant challenge…

 

         Unable to leave until requirements are fulfilled…

 

         Having done time, KMer will never be the same…
Are you doin’ time? We would like to hear from you….
Bruce Fransen
Knowledge Management Consultant
b_fransen@comcast.net

 

Sep 292012
 
knowledge management power directedIf knowledge is power, then knowledge management is “Power Directed”!

The essence of Knowledge Management comes through when we share what we know. When applied in its various forms (tacit and explicit) as well as in the specific types of knowledge (procedural, and propositional/declarative) it can have a lasting effect. The power being directed when leveraging knowledge management not only comes from sharing what we know but also from being experts in our chosen field. Being an expert in your field will distinguish you as a thought leader and key knowledge holder. These experts are to be utilized whenever possible and will be the catalyst for keeping order, providing effective decision making, and enabling organizations and its people to be successful.

If the recent NFL Referee strike and subsequent settlement taught us anything, it is that expertise counts and knowledge is power. In order to settle the NFL Referee strike that power (the referees knowledge and expertise) became the catalyst to drive the NFL Owners to come to an agreement.

In this season of political change throughout the world as seen through the Occupy Movement, and now the pending US Presidential elections, sharing knowledge and acting on this knowledge will influence the world for generations to come.

Briefing soldiers through lessons learned when one group returns from a mission to be replaced by another; when a parent teaches their children those “life lessons” from their experience; in the preparedness, response, and recovery by emergency personnel when a crisis or natural disaster strikes; in understanding what knowledge is needed to drive organizational decision making and response to customers; and when researchers combine what they know in order to discover cures and/or treatment to disease and sickness (I can go on and on!) are all examples of Power Directed! These examples illustrate the power of knowing and directing knowledge has the power to shape the world in which we live.

I am interested in hearing how you have directed your knowledge to make a positive change, provided an impact to your organization, and/or enhancing the knowledge of someone else to provide direction and/or to assist that person in making decisions.

Remember, knowledge itself cannot not exhibit power until it is put to use.

Aug 312012
 
Hurricane Isaac

As the US begins to recover from the aftermath of Hurricane Isaac, I am reminded of how knowledge management (KM) can be used to respond to disasters such as these.

The lack of response, or the inadequate nature of the response, has led to a need to increase the effectiveness and efficiencies of first responders.

Due to the nature of their work Disaster Response Teams (DRT), are usually first to arrive in a crisis situation.  KM applied to DRTs – in particular, first responders – will enable the DRTs to arrive at the scene in a more timely manner, be equipped with the right knowledge of the situation, and have the right tools and technology to execute their job, putting them in a position to save lives.

When a disaster occurs, first responders often do not arrive in a timely manner, are not fully aware of the situation and are not fully equipped to handle the situation.

Applying KM to DRT first responders will not only save the lives of the people in the community, but in many cases the response teams themselves. When fully knowledgeable of the situation they are responding to, the team will increase the confidence of the community by delivering a faster, more efficient response, assuring the community that they will receive the help they need. Applying KM must begin with a comprehensive KM strategy that promotes a proactive stance and preparation before disaster strikes!

Knowledge management is not a “silver bullet”, however I believe it will make a difference.

As always I’m interested in receiving and responding to all comments on this post…  be safe!