Ten principles of information management

Defining the principles of information management has never been easy; those of us in the field know what we do, and appreciate the value of our knowledge, but defining what we do to people outside our field can be challenging. This lack of clarity is not a reflection of any weakness in the area of information management but, rather, a reflection of the breadth of its scope and relevance. In this article, James Robertson outlines the key features of information management, which he draws from a number of “critical success factors” from various information management programs. Robertson makes a point of emphasizing that information management is not about just information technology; those of us in the field understand the frustration of having all our skill sets subsumed under the umbrella of technology: From the outset, it must be emphasised that this is not an article about technology. Rather, it is about the organisational, cultural and strategic factors that must be considered to improve the management of information within organisations.

Robertson’s 10 principles of information management:

  1. Recognize (and manage) complexity
  2. Focus on adoption
  3. Deliver tangible & visible benefits
  4. Prioritize according to business needs
  5. Take a journey of a thousand steps
  6. Provide strong leadership
  7. Mitigate risks
  8. Communicate extensively
  9. Aim to deliver a seamless user experience
  10. Choose the first project very carefully

Robertson does an excellent job of explaining the scope and breadth of information management, and I will be sure to incorporate this article in my courses.

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Sir Tim Berners-Lee reflects on 28 years of the Web

In this post, Sir Tim Berners-Lee reflects on the development of the Web since he first proposed it 28 years ago. Sir Tim expresses concerns about the increased amount of personal data that people surrender to the Web, to the point at which he believes we have lost control over this data. Sir Tim points also to the inherent dangers of the ease with which misinformation can be spread, and to the increased use of the Web by governments to surveil their citizens. Sir Tim makes mention of a five-year plan for delivering digital equality, created by his Web Foundation. The goal of this plan is to use the open Web to build a more equal digital world:

Because despite the wave of creativity, innovation and collaboration unleashed by the web, the reality is that today, the web is not for everyone. In fact, the digital revolution is creating new patterns of privilege and discrimination. It is causing job losses and wage polarisation as well as productivity gains; it risks taking away our privacy and autonomy even as it gives ordinary citizens new powers; it is isolating us in filter bubbles as well as connecting us across borders; and it is amplifying voices of fear and hate just as much as voices for tolerance and rationality.

This plan has three foci:

  1. Power: All People Can Make Their Voices Heard Equally
    We will fight to ensure people’s rights on the web are legally protected. This means enshrining in law your right to freedom of expression and privacy online and ensuring that you have control over the collection and use of your personal data.
  2. Accountability: Citizens Hold Governments and Companies to Account
    We will continue to push for policies that open up key information online, and equip public interest groups to use this data to hold governments and companies accountable.
  3. Opportunity: Women and Other Excluded Groups Gain Economic and Social Opportunities and Resources. Digital equality means more inclusive public services and fair opportunities in the digital economy. Examples of policy outcomes we will be pursuing here are affordable broadband for all; expanded and enhanced free public WiFi schemes and digital skills programmes; and increased financial inclusion for women through digital financial services

Knowledge management tools that aren’t tools

This article by Neil Olonoff discusses the conundrum that can be faced with the implementation of knowledge management tools that are supposed to make managing knowledge assets easier but which, in reality, can create more complicated workflows. Olonoff focuses particularly on SharePoint, which is the system we use in my institution. Olonoff argues that:

We call software a “tool,” even though you can’t turn a screw or lever a log with it. That’s how symbolic and abstract work has become. But the basic idea of a “tool” — a utility external to our minds and bodies — remains. It’s still something that’s supposed to make work easier. So this becomes a very useful heuristic for gauging the effectiveness of knowledge management methods, and, dare I say it, tools. When something demands more effort and time and expense than the way we did things earlier, i.e., before [the] introduction of the New Tool, then that utility is simply Not a Tool!

Certainly, in the case of my institution, the roll out of SharePoint has not been what I would call particularly successful. Many units do not have a SharePont site, even though the institution adopted the software three years ago.  I’m always a little leery when implementation and maintenance of knowledge management software resides primarily in the hands of information technology departments, who might not have sufficient understanding of how to manage knowledge assets, implement proper metadata, ensure proper flow of records, maintain retention schedules, and so forth. I have encountered a fair degree of resistance to using SharePoint amongst colleagues because, to quote Olonoff, the new tool doesn’t meet the basic definition of a tool. It makes them work harder.

Next-generation techniques for managing tacit knowledge

In this article, Kate Simpson, national director of knowledge management at Bennett Jones LLP, discusses new techniques for managing tacit knowledge. Simpson defines tacit knowledge as the personal experiences and deliberate practice by individuals built up over their 10,000 hours on the knowledge ladder of expertise. Knowledge managers have debated the best ways in which to extract tacit knowledge and convert it into recorded, explicit, knowledge for decades. Simpson discusses three new techniques that could be used for this conversion:

  • Guided Practice:  practice over the course of 10,000 hours is what creates experts… Deliberate or guided practice requires reflection and commitment to improvement as well as with an expert who can provide performance feedback throughout the learning process.
  • Guided Observation: to understand what someone actually does you must observe. There is a notorious gap between what people say they do and what they actually do.
  • Guided Experimentation: developing simulations allow lawyers to practice what they have learned and to test theories and experiment with different approaches (presumably, this approach could be modified for different environments).

 

Email addiction

This article by Naomi Schaefer Riley discusses email addiction amongst workers. I think most of us are aware of this phenomenon: The feeling that we must check our work email in the evenings, on weekends, and even on our holidays. We compulsively check our email several times a day, which can have a negative effect on our productivity. You can’t sit in any meeting without seeing at least half of the members checking their email. We are being told increasingly that most of us do not multitask well. I was a conference last week, where most of the audience during a plenary presentation had their necks down as they worked on their mobile devices; I doubt most of them were taking notes related to what they were hearing. It struck me as rude, in fact, that so few people were giving the speaker their full attention.

Riley mentions a French law passed recently that gives employees “the right to disconnect.” Companies with more than 50 employees must allow workers to go home in the evenings or on weekends without having to check in electronically. I’m not sure why companies with fewer employees were not included in this law, as this means that these employees would not enjoy the same privileges. While my email practices are not protected by law, sadly, I adopted my own policy over the past two years of not checking my work email after 6:00 pm, on weekends, and on holidays (I use an away message). Many people I know say that they check emails during their holidays because they want to avoid a full inbox when they return to work. I have disciplined myself not to do so. My away message makes it clear that I will not read my email when I am on holidays, so I find that many people do not send me a lot of emails while I am away. Further, from past experience, I know that once I read work emails during my holidays, I feel obliged to answer them, which means my relaxed state often goes out the window. I have learned that setting boundaries around my time is a sign of self-respect, and allows me to have a healthier perspective on work and life priorities. I would like to think that there is more to my life than my job, regardless of how much I love it.

 

Data anarchy vs. data governance

In this article, Robert Seiner talks about the difference between the states of data anarchy and governance. Seiner points to the large amounts of personal data that each of us generates, often without being aware of doing so, and the state of anarchy in which this data exists. This state of affairs exists similarly for business data. Seiner distinguishes between data anarchy and data governance as follows:

Data anarchy:

  • There is no clearly defined formal accountability for the definition, production, and use of data.
  • There is no one responsible for overseeing subject matters of data as a cross-business asset.
  • There is no formal process for escalating data issues to a strategic level that makes decisions.
  • There are irresponsible investments and management of high profile data-related projects.
  • There are inefficient/ineffective processes associated with leveraging data for decision-making.
  • People that handle data are uncertain of the rules associated with sensitive data.

Data governance:

  • People that [sic] define, produce, and use data are held formally accountable for following the documented and communicated rules associated with defining, producing and using the data.
  • There are people that have the responsibility for managing data across business areas, business functions, and major data integration projects.
  • There is formal accountability for following an agreed upon process to escalate data issues to the appropriate level of the organization.
  • Investments and high-profile data integration projects are strongly vetted with an intent focus on the data requirements of the organization.
  • Business and technical processes associated with managing data are formalized, and people are held accountable for following the processes.
  • People that [sic] handle the data are well-versed and audited in following the rules associated with protecting sensitive data.

Seiner suggests that many organizations are in a state of data anarchy: The truth is that many organizations know what they want but they don’t know how to get it. Organizations must move from data anarchy to data governance if they want to get the most value out of their data. It’s all in the data.