Findability and Innovation #IKNS

Columbia University Crown Jeff Carr is  senior productivity technology specialist for Microsoft Canada. He works with clients to help them understand how to use the Microsoft productivity tools. His background is in information architecture and information management. His experience is 50% as a consultant, 40% working in an organization, and 10% working for a vendor. Jeff is joined in this session by (1) Ralph Poole, a consultant with Iknow LLC (Iknow focuses on how to use metadata and text analysis to help with findability); and (2) Susan Baktis (Social Learning Strategy & Advisory at Accenture), who began in consulting and now focuses on knowledge management. She has experience with taxonomy and knowledge strategy.

[These are my notes from Columbia University’s 2013 summer residency program for its Masters of Science in Information and Knowledge Strategy. Since I’m publishing them as soon as possible after the end of a session, they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • Knowledge-Enabled Innovation. The great benefit of findability is that it enables innovation. Examples of knowledge-enabled innovation are prevalent. Google Glass allows you to have the world’s information displayed right in front of you at the moment of need. Initial uses were information retrieval, but now other uses are emerging. For example, Dr. Rafael Grossmann is a surgeon who used Google Glass while he was doing surgery. He streamed the surgery to people watching the surgery via a Google Hangout on an iPad. This facilitated knowledge transfer with people who otherwise could not have watched the surgery as closely if they had attended in person. MedRefGlass is an application that does facial recognition and helps the doctor identify a patient and then dictate her patient notes.
  • Embedding Knowledge. Stipple allows you to embed your content into images you publish to the web. Each image contains “dots.” When you click on a dot, it can display other content such as a website or a twitter stream. These dots are persistent tags that travel with the image regardless of the distribution channel (e.g., Facebook, Twitter, Flickr, etc.). Now you can use these dots to link to shopping sites so that you can purchase something you see outside a shopping site by activating the dot in the image. Better still, Stipple uses an automatic metadata tagging capability so no one has to manually tag an image.
  • Findability Depends on the Organization of Data.  You cannot embed knowledge until you have gathered and organized the requisite knowledge. Further you need good information governance protocols to make sure the knowledge gathered is accurate, current and fit for distribution.
  • Further Reading.

*Disclosure: This link is through my Amazon affiliate account and may generate income to me.

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Making a Case for Knowledge Management #IKNS

Columbia University CrownThe panelists in this session are: Jeff Carr (Senior Productivity Technology Solutions Professional, Microsoft), Ed Hoffman (CKO at NASA), Tom Stewart (Chief Marketing and Knowledge Officer, Booz and Company, and author of Intellectual Capital: The new wealth of organization*), and Bob Libbey (Head of Digital & Social Communications, Pfizer)

[These are my notes from Columbia University’s 2013 summer residency program for its Masters of Science in Information and Knowledge Strategy. Since I’m publishing them as soon as possible after the end of a session, they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • What’s the Key to Good Decision Making?  The most critical element to effective decision making within an organization is knowledge sharing. But this requires a culture that encourages knowledge sharing as a matter of policy AND gives people the necessary support to take the time to seek out knowledge and then share it. This kind of organizational culture helps me overcome the fear of asking and it gives my counterpart reasons to answer.
  • Knowledge Management as a Discipline. One of the great challenges is that the name “knowledge management” can be misleading. However, if you can get past the name, the practices it encompasses can be hugely helpful for an organization. KM is the single best antidote to the greatest threat to good corporate decision making: information hoarding. Helping people understand the value of knowledge sharing and collaboration is a huge part of the role of KM professionals. In addition, they need to help people in the organization handle the constant pressure of information overload.
  • Where should KM Live? Much depends on the organization.  In a balkanized organization, KM should live within the part of the organization that has the ability to take action. Ideally, KM should be a center of excellence with the power to provide KM goodness on an enterprise-wide basis. In addition, there should be KM competency within each business unit. It’s important that prudential functions (e.g., risk, HR, audit, knowledge) report up to a CXO, even though personnel may be embedded in business units. Without the vertical reporting lines, it can be hard to maintain enterprise-wide standards.
  • KM and IT. The relationship between knowledge management and IT is critical. They need to be close collaborators, but the panel agreed that KM function should not be buried inside the IT function. IT’s focus is primarily on the tools. KM’s focus in more on methodology. That said, if you have a generous view of each other’s areas of expertise and don’t get too hung up on turf warfare, it is possible to bring out the best in your collaborators in other key functions. One panelist pointed out that there is (or should be a difference) between thinking about the organization’s information (CIO) and thinking about the organization’s tools (CTO).

*Disclosure: This link is through my Amazon affiliate account and may generate income to me.

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How High Performers Compete – and Win – with Analytics #IKNS

Columbia University CrownJeanne Harris is executive research fellow and a senior executive at the Accenture Institute for High Performance in Chicago. She directs the global research agenda on information, technology, analytics and talent at the Institute. In the IKNS program, she is an instructor in the Business Analytics class.

[These are my notes from Columbia University’s 2013 summer residency program for its Masters of Science in Information and Knowledge Strategy. Since I’m publishing them as soon as possible after the end of a session, they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • Lessons from Peter Drucker. Jeanne Harris had the privilege of working with Peter Drucker early in her career. Here are some of the data-related lessons she learned from him:
    • Look for patterns. Analytics help reveal patterns, which in turn reveal what is happening below the surface of the organization.
    • Don’t settle for just a single insight. Businesses are complicated animals so it is rare for a single insight to explain everything about an organization. Look for several insights that shed light on the business as a system.
    • What gets measured gets done. Things don’t get implemented unless people and processes are measured and monitored.
  • The Value of Analytics. Early studies indicated that companies that implemented ERP systems rarely received any value from the system. When Jeanne Harris and Tom Davenport dug deeper into the research, they discovered that reality was a bit more nuanced that the research indicated. In fact, while some companies found ERP systems disappointing, the companies that considered analytics to be a key part of their business strategy received great value from their ERP systems. The main differentiator was a company’s approach to and use of data.
  • Competing on Analytics. People have been collecting data (and performing analysis) for centuries. What’s different is knowing how to use data analytics to (1) differentiate your company or product, (2) execute your business strategy, or (3) build data into your products. A perfect example of a company that competes on data analytics is Netflix. Data helps Netflix be a huge disruptor in its space. For example, Netflix initially used data via its Cinematch algorithm to help (1) customers choose films to watch; (2) Netflix manage its inventory; (3) Netflix negotiate its deals with movie studios (which are typically less data driven); (4) Netflix manage customers who tend to hold onto movies longer than average. (Netflix manages them by not sending them the first batch of new release movies.) In short, data analytics give Netflix a huge competitive edge.
  • How do you Build Analytical Capability in Your Organization?  It isn’t enough to use data to execute your strategy or achieve operational efficiency. In fact, the more effective use of analytics is to support better decision making.  Ultimately, you need to use analytics to stay ahead of your competitors. This requires cultural change within the organization. Harris told us how Progressive Insurance Company used data to differentiate the safe motorcycle owners from the reckless ones. Next they offered preferential rates to the safe customers and pushed the bad risks to their competitors. In another data-driven effort, Progressive offered customers the opportunity through its “Snapshot” program to install a device on the vehicles that collected data on their driving habits. This data was then analyzed to determine each participating customer’s likelihood of having an accident. With this information, Progressive could offer a more appropriate insurance rate.
  • Big Data. One definition of Big Data is “data too big to be analyzed by SQL.” Harris noted that we have only begun to scratch the surface of Big Data’s potential to realize major business outcomes. The technology is finally up to the task, but we don’t yet have enough people able to derive insights from that data. As a result, there is incredible demand for trained data analysts. The other problem is that many decision makers in organizations are essentially innumerate and, therefore, don’t understand how to use Big Data and the insights it can reveal. Harris quoted Tom Davenport who was concerned that “a lot of Big Data is low analytics” and, therefore, people are missing the great insights that could be attained by using more sophisticated analysis.
  • What Skills are Necessary? Harris recommends the following skills:
    • You need to be numerate. This means not only understand numbers, but also statistics.
    • You must understand scientific methodologies (e.g., forming a hypothesis,  A/B testing, the scientific method generally).
    • You must understand what the data are really telling you.
    • You must understand how the data relate to your strategy.
    • You must know how to translate the data analysis into operations/execution and, ultimately, how to use the data to change the organization itself.
  • Analytics Makes s Difference. Big Data isn’t only for Big Business. Even simple analytical applications can help small businesses and nonprofits. For example, Harris and her team helped a theater company use their sales data to materially improve their ticket subscriptions. For organizations large and small, there now is a drive to data monetization.
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Business Thought Leadership Strategy #IKNS

Columbia University CrownArt Kleiner is an editor-in-chief at strategy + business and Booz & Co. His talk is based on materials he developed with George Roth at MIT’s Organizational Learning Center (now the Society for Organizational Learning).

[These are my notes from Columbia University’s 2013 summer residency program for its Masters of Science in Information and Knowledge Strategy. Since I’m publishing them as soon as possible after the end of a session, they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • Thought Leadership. The goal of thought leadership is that when someone is exposed to your thinking, they can imagine putting it to use and they are different for having gone through that thought experiment. In other words, they came away more capable than before they encountered your views. Thought leadership is the connection between your thinking and the thinking of people you haven’t yet met.
  • Writing.  “Writing is iterating.” (Writing is rewriting.) It is part of your craft to know how to put things together so well that your readers can take it apart and understand it. It also means simplify your message until you cannot simply further. Kleiner describes this as “dancing up to the edge of reductionism without falling into the abyss.”
  • Initial Writing Exercise:  If you had to prepare a message for the world, how would you answer the following: (1) What’s its title? (2) What’s its lesson? (3) Why this message? (Clarification: the “world” means any group of people that contains at least one person that you do not know personally.) Once you have completed this exercise, analyze it using the “four ways to think about creative work” outlined below.
  • Four ways to think about creative work. (1) What’s your purpose? What’s the explicit reason for why you want to do this and are willing to devote the time necessary to do this? (2) How do you build credibility? How do you fit your work within the established canon? How do you substantiate your work so that it is unshakeable? (3) What is the story you are trying to tell? And how does it resonate? (4) Who is the audience and how can we prepare your message so that those who are ready to hear it will be moved to listen to it and act. Each of these ways of thinking require a different focus and a different approach. The problem is that when we mix these up, it leads to writer’s block. Therefore, isolate each way and focus on it until you have reached a satisfactory point.
  • Purpose. A lot of people are lackadaisical when it comes to thinking about the purpose of their ideas. This is in part due to a sense of politeness that stops us from asserting our purpose over the purpose of another person. So we need to train ourselves to engage in the iterative exercise that Peter Senge recommends: ask what’s my purpose? Then ask: if I achieved my purpose, what would that make possible? And if I achieved that further purpose, what would that make possible, etc.?
  • Research. If you are presenting thought leadership based on research, part of your credibility will depend on the originality of your research. (That research can be based on primary and secondary sources.) One key way to establishing credibility is overcoming traps of the mind: (1) the problem of confusing cause/effect versus correlation; (2) internal consistency (e.g., behind every great fortune is a great crime – this is true until it isn’t); (3) category correspondence (does the theory actually fit the case you are trying explain); (4) universality (i.e., assuming that one successful case will be successful in all cases); (5) does your work have face validity (i.e., does it make sense — even if it is initially counterintuitive?). How much of this substantiation is needed for your thought leadership piece to be valid? Just enough. To test this ask:
    • What research supports your piece of work?
    • Is it enough?
    • How might its substantiation be challenged?
    • Are you prepared to be openly challenge about the validity of your work?
  • Telling the Story. Behind everyone of your projects, something life-changing happened to someone that will stay with them for the rest of their life. Your job as a thought leader is to identify and cultivate the story of each of those life-changing moments. “The power of the story is in the connection between the way it makes you feel and the thing it makes you understand.” Chances are, you already know what the relevant story is. (Every thought leadership piece has a story. You need to tell it in a way that resonates with your audience.) What you may not have done is understood what you are going to do with that story. In what direction will you take that story?
  • The Audience. You need to consider how to meet at least some of the expectations of your audience. “In the age of the internet, every interaction is like a play in which the audience can declare an intermission and leave at any moment.” Therefore, you need to give your audience something close enough to what they expect so they are willing to stay, and far enough from their expectations so they are not bored.
  • Additional Crafts. The creation of your work of thought leadership also includes the crafts of copyediting, layout and marketing. Each of those crafts can benefit from the analysis set out above.
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