Category: Knowledge Management

Shadow IT and Information Optimization

This post sponsored by the Enterprise CIO Forum and HP.

Following up my Data Disconnect and Shadow IT post from yesterday, I wanted to talk about the 2nd area that is often overlooked when people undertake their own Shadow IT initiatives.

In my previous post, I talked about the Data Disconnect. That space where the data in your Shadow IT applications is disconnected from the rest of the organization.

This disconnect is something that requires the IT group to educate the rest of the organization as highlighted by Christian Verstraete in the his Enterprise CIO Forum titled Shadow-IT, it’s forbidden to forbid.   In some instances, the Data Disconnect isn’t a big issue…but many times, the disconnect is a huge risk for the organization.

Today, I want to talk about another aspect of Shadow IT related to Data  and Information…the optimization of data.  The world today is ruled by data.  That data is turned into information and sometimes that information is converted into knowledge.

When data lives outside the enterprise in the cloud or within a local ‘shadow’ database, it’s disconnected.  To be able to use the data within your organization’s applications, they need to be connected. Therefore…the first step is solving the Data Disconnect problem.

Once you know how you’ll solve that disconnect problem…whether by using internal systems, API’s to access cloud app data or simple scripts to dump/convert data…then you need to think about the Optimization and Conversion problem.

The optimization problem is a big one.

There is a ton of useful (and useless!) data in every organization living as structured and unstructured data.

Structured data is quite easy to access and use and is fairly easy to connect when you face yourself with a data disconnect. Find the data. Access/Dump the data. Use the data.  Repeat.

Unstructured data is different. This is the data that is growing exponentially these days. Its your email, text messages, twitter messages, blog posts, images, videos etc.   The data stored within these mediums is unstructured in that it is text based and or audio/video. Optimizing and using this data is difficult when its stored inside enterprise applications and its even more difficult when this type of data is stored in applications that aren’t managed by the IT group.

This unstructured data is what you find in collaboration tools. Its the information that your team’s share and knowledge that your team’s create.  If its stored in a third-party system with little to no access to retrieve the data, its not only disconnected, but useless.

Imagine that you work with a virtual team that is  ‘in the cloud’.  You use something like Basecamp or some other web based project management and collaboration tool to manage your projects.  In addition, your team uses email and an instant messaging platform like Skype to keep in touch throughout the day.

A great deal of knowledge flows through your collaboration platforms….but what happens to that knowledge after the first creation  and share?  Does it sit out in ‘the cloud’ forever and is never revisited…or do you somehow grab that knowledge to ‘share’ with the rest of your organization.

You can’t optimize the information and/or share the knowledge if it isn’t held within the organization’s systems in a manner that use usable and accessible.  This is the challenge of information optimization in the world of Shadow IT. There’s a lot of data / information / knowledge created that might be lost ‘in the cloud’ when these things aren’t considered.

So…CIO’s and IT groups…take the time to educate your organization on the pro’s and con’s of Shadow IT.  If people are adamant about using a cloud service that doesn’t fit into the IT Strategic roadmap, make sure you understand why they are so adamant about it and what they and you must do to make sure the Data Disconnect and Information Optimization problems are considered and addressed.

Image Credit: Information By heathbrandon on flickr

This post sponsored by the Enterprise CIO Forum and HP.

Data Driven…or Data Informed?

data slide By bionicteaching on flickrI just finished reading Eric T. Peterson’s post titled The Myth of the “Data-Driven” Business.

I don’t talk or write much about ‘data’…mostly because I’ve always taken it for granted as something that was always ‘there’.   If the data I needed wasn’t available in an easy to consume format, I’ve always found a way to get what I needed through data collection, data manipulation or by hacking together data to get what i needed.

To me, data has always been something that I’ve used to do my job. Data is something that I’ve used to help inform myself, my teams, my organizations and my clients.

I’ve often heard people and companies talk about being ‘data driven’ and have always felt like I was missing something as I never really understood what they meant by being ‘data driven’.

In my world, data has always been the building block of services and platforms but data isn’t driving me, my business or my teams. Data is the base level of the business. Data is the business in its rawest form…but its also meaningless without context  and meaning.

Most of my thinking towards ‘data’ comes from my systems thinking and knowledge management education and training in the form of the Russell Ackoff model. The Ackoff model claims that  there are five ‘buckets’ that content in the human mind can be classified into. These buckets are:

  • Data
  • Information
  • Knowledge
  • Understanding
  • Wisdom

In the systems thinking and knowledge management world, the “Data -> Information -> Knowledge” model is quite prevalent…or maybe more accurately, its been the prevalent filter that i’ve used in my work.

So…from my filter, Data is the rawest level of ‘stuff’. Its the baseline that you build from.  Data leads to information, which leads to knowledge…but data is nothing until you build something on top of it…until you add some form of context or meaning.

Therefore, it was always hard for me to understand the ‘data driven’ people who’ve been popping up everywhere over the last few years.  I’ve never really given much credence to the ‘data driven’ mantra.

So you can imagine my surprise when I saw the The Myth of the “Data-Driven” Business headline in my RSS reader today.

In the article, Peterson makes a fairly convincing plea to stop using the term ‘data driven’…rather, he says, use something more like ‘data informed’.

Eric writes:

My concern arises from the idea that any business of even moderate size and complexity can be truly “driven” by data. I think the right word is “informed” and what we are collectively trying to create is “increasingly data-informed and data-aware businesses and business people” who integrate the wide array of knowledge we can generate about digital consumers into the traditional decisioning process. The end-goal of this integration is more agile, responsive, and intelligent businesses that are better able to compete in a rapidly changing business environment.

Emphasis Mine.

I can get behind ‘data informed’.

I can get behind using data to make better decisions. At the end of the data, thats why you collect data…to make better decisions.  But…you’ve got to put meaning, context and definition around that data to make it useful.

I’m keeping an eye on Eric’s post to see what discussions come out of it but I’d love to hear your thoughts on how you view ‘data driven’ vs ‘data informed’.

Image Credit: data slide By bionicteaching on flickr

Flexible tools and platforms for a changing world

146/365 square peg into a round hole By rosipaw on flickr
square peg into a round hole By rosipaw on flickr

In the IT world, we tend to take a single-minded approach to our technology platforms.   We have email systems. We have web systems. We have HR and Finance systems.

Many organizations are implementing collaboration tools and social tools in the enterprise.  But…most organizations are implementing these platforms with blinders on without long-term plans for how those tools might need to adapt for how users really want to use it.

As we’ve seen in recent days/weeks in events around the world….technology is being used for much more than that. Technology is being adapted for their situation.  They are using the tools at hand in ways that weren’t really considered when those tools were created.

Linda Tucci had a great comment on this in her recent post titled Egypt’s CIO lesson: We use IT tools in ways unintended by toolmakers. She writes:

The truth is that tools take on a life of their own once put in the hands of human beings, who, by nature, are innovative. People are hard-wired to adapt tools in ways the toolmaker never intended — sometimes for the good and sometimes for the bad.

Very true.

How many times have you seen a technology platform implemented within a company to find that nobody uses it…or….people use it differently than planned?  It happens often.

If you are planning a new technology implementiation, are you thinking about how your people will use that technology? Are you thinking about how that technology might be used (or not used) once implemented. Are you thinking about the culture of your organization and how the technology fits with that culture.

You know people will attempt to use a technology differently than originally planned…so are you planning for those changes to come in the future? How will your technology strategy & platforms accommodate these changes.

Something to keep in mind during your next technology assessment / technology selection project…you don’t want to build a square peg today and find that you have a round hole next year, do you?

Image Credit: square peg into a round hole By rosipaw on flickr

A Social Approach to Knowledge Management in Projects – A White Paper

I recently submitted a paper to be considered for an academic conference on the topic of IT Project Management.

The conference uses a double-blind review process to review papers and provide feedback.  In this double blind-review, reviewer’s aren’t provided with author(s) information and author’s aren’t provided information about the reviewers.

Good and fair process….and one that I’m about to completely tear apart today. 🙂

My submission, titled A Social Approach to Knowledge Management in Projects, was conditionally accepted for inclusion if I were to address a major concern on the part of the reviewer.

The main concern was a claim of plagiarism.

The reviewer believed that the author (me) had plagiarized a good part of the paper.  They pointed to a website that they claimed proved that the author had used content from and note cited.  That website was mine – https://ericbrown.com.

Plagiarism is defined as:

the unauthorized use or close imitation of the language and thoughts of another author and the representation of them as one’s own original work.

I can see where the reviewer might have thought plagiarism existed as some of the work in the paper has been previously published here on my blog.  I’m actually quite excited that someone out there found my site interesting enough to cite as the original source of something that might have then been used in a plagiarism matter.

While this could be considered a case of self-plagiarism (if you believe in such an oxymoron), it’s not plagiarism.  The conference organizer requested that I cite my own work published on this blog within my article and also rework the article to ensure that the majority of the paper was significantly different than any other paper / article I’ve written.

Because I don’t believe in ‘self-plagiarism’, and because I’m feeling a bit rebellious this morning, I’ve decided to withdraw the paper from the conference and publish it, in its entirety, as a PDF here.  You can download the full paper using the link at the bottom of this post.

In the paper, I try to look at ways to answer this question:

Can a project team use Web 2.0 / Enterprise 2.0 platforms to communicate and share knowledge during a project? Can this communication be indexed and mined to capture relevant knowledge about the project, project team members and project technologies without adding additional burden to the project team members?

Download a PDF copy of A Social Approach to Knowledge Management in Projects today

Enjoy.

Mining for knowledge in a social word

A segment of a social network
Image via Wikipedia

Last week I published a post titled Mining for Knowledge where I discussed some of the research that I’ve been doing in my doctorate program.

One of the favorite lines from the article, and one that resonated with a few others as well. The line was:

…converting tacit (i.e., internal) knowledge to explicit (i.e., external) knowledge is one of the most difficult things to do.

I’ve been thinking about this (and reading A LOT of articles, papers and books on the subject) and have come to the conclusion that trying to force someone to convert tacit knowledge to explicit knowledge is a wasted effort.

Why?

Can I truly convert 100% of my knowledge into the written form?  Will the context of my knowledge be converted?  Perhaps a good portion of my knowledge can be converted, but can my experiences, thoughts and believes that shaped that knowledge be converted?  Can I ‘write down’ the knowledge that I have and truly make it meaningful to others?  I don’t think (feel free to disagree here).

Does that mean that an organization should stop trying to gather an individual’s internal knowledge to add to overall organizational knowledge-base?  Nope…. definitely not.

Rather than forcing a conversion from tacit to explicit (which is darn near impossible), are there ways to manage the internal knowledge of people?  Managing that knowledge is a much easier process that converting that knowledge.

Knowledge is best internalized when wrapped in context

Nonaka and Takeuchi, the godfathers of Knowledge Management, argue in their book The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation (affiliate link) that tacit knowledge can be converted into explicit knowledge only through externalization and describes this process as being one of dialogue, discussion and reflection.

Basically, they’re saying that in order to share internal knowledge, you’ve got to start a dialogue with others.  That’s why activities like storytelling, mentoring and other forms of social interaction can play a huge role in knowledge managment…they help to start and maintain dialogue and discussion on various topics.  These activities help to provide context around knowledge, which helps a person internalize that knowledge and make it their own.

In my previous article I talked about ‘mining for knowledge’. I talked about using web 2.0 platforms to capture knowledge and to share knowledge. All good stuff (and still interesting to me) but I’m looking at other methods to make these platforms more social.  Make dialog and discussion a more active portion of these tools.

If we can find ways to create dialogue and discussion within the enterprise, knowledge sharing would happen much more naturally.    This is why I like the idea of Enterprise 2.0.  While some people hate E2.0, I think there’s some real value there. Of course, E2.0 won’t solve world hunger and probably will never truly win over its detractors, there are many aspects to the idea that make sense.

What would it mean for an organization’s knowledge managements capabilities if a system could be implemented that found indexed the many disparate repositories of structured and unstructured data sources found throughout the enterprise and then provided that information in a socially aware platform that could wrap context around the indexed knowledge as well as provide a mechanism for dialogue, discussion and reflection?   You’d have a platform that could capture and share explicit and tacit knowledge.

Anyone know of any companies with products in this space?  I know SocialText is out there but I don’t think they have a platform as robust as the one above. SharePoint also has some aspects to this but not everything.

Mining for Knowledge

Mining for KnowledgeIn my doctoral research, I’ve been researching ways to improve knowledge capture and sharing methods, specifically within project teams but the ideas can be dissemenated around the organization.

One of the biggest issues I’ve found while working as a consultant is the amount of knowledge that I walk away with after a project is complete.  Sure, I try to share this knowledge in every way possible but converting tacit (i.e., internal) knowledge to explicit (i.e., external) knowledge is one of the most difficult things to do.

Let’s assume though, that some portion of the knowledge that I hold in my head is converted into some form of writing at various periods throughout a consulting project.  Where does that explicit knowledge live?  In an email?  In some document stored on a server?  In a knowledge repository somewhere?

In the past, this problem has been attacked using centralized knowledge repository platforms.  These systems require users to log in and ‘enter’ their knowledge into the system.  Many of these platforms have been well built and some have been successfully used in organizations, but the success stories are far outweighed by the stories of KM repositories sitting idle and unused.

So…how can we get that tidbit of knowledge from my brain into some form of knowledge repository without me logging in and ‘entering’ it into the system?

Web 2.0 as knowledge repository

The use of Web 2.0 tools (blogs, IM, wikis, etc) has become ubiquitous..  If incorporated into a project environment, these tools might allow an easy and efficient method for capturing and sharing knowledge throughout project teams and project organizations.

The key to retrieving knowledge from tools is to make the user experience as seamless as possible. For example, an employee creates a blog on an organization’s intranet and then uses this blog to write different topics, some that pertain to her project and some that don’t.

Perhaps this employee is participating in two projects within the organization and she writes about topics that might be of interest to a portion of the organization and project team members.  While she writes about interesting topics and at times, writes about her experiences on the projects that she’s worked on, perhaps her blog posts aren’t widely read.  This employee has attempted to convert a portion of her tacit knowledge to explicit knowledge but few people on the project team or within the organization find this knowledge because its tucked away in the intranet site (which is rarely used anyway).

In the above scenario, knowledge was converted from tacit to explicit but few people are able to absorb this knowledge and make it their own (i.e., perform the conversion from explicit to tacit knowledge).  What would happen if this knowledge were indexed, searched and shared with the rest of the project team in something akin to a project knowledge ‘journal’?

Since Web 2.0 platforms are ubiqutious, why can’t we use these tools as our knowledge repository?  Employees and project team members are already using them…so can we find a way to ‘mine’ these platforms for knowledge?

Could a system be built that ‘mines’ these web 2.0 platforms along with other unstructured data (documents, email, etc) to ‘build’ a knowledge repository available to the entire organization?

Mining for Knowledge

I’m currently looking at ways to use text mining methods and techniques to mine for knowledge. Text mining looks to be a good approach to solving this problem because it allows for knowledge to be gathered without additional work by project team members.

There are other approaches that could be used for gathering knowledge from project team members, but all require additional work to input information.  For example, a project team using a manual approach could ask team members to regularly update their blog and to ‘tag’ their posts with a special project tag or keyword so that a non-intelligent aggregation system (RSS, etc) could simply pull these tagged posts into a central repository.  While this is a good approach, it relies on the end-user to tag their content correctly, accurately and in a timely manner.  Tagging, and other categorization and taxonomic approaches, require the user to do something to allow their knowledge contribution to be categorized, indexed and found by aggregation systems and other users.

Using text-mining methods against pre-existing tools and platforms takes away the human fallibility issues found in current knowledge management repository platforms or by requiring a user to ‘tag’ a piece of content correctly as described above.

Using text-mining and other data mining approaches, I’m looking at ways to build semi-autonomous systems to index and organize both structured data and unstructured data pulled from blogs, email, IM, social networks, documents, spreadsheets and any other location / data sources. This system could aggregate knowledge found via text mining and social network analysis and build a project knowledge ‘repository’ that will contain all knowledge for any specific project. This repository will be searchable and will contain both manually curated content (e.g., content uploaded by project team members) and automatically curated / generated content based on text-mining and indexing techniques.

There are some major privacy issues here of course. How can you mine a users email and find the relevant knowledge without truly invading their privacy?  Not sure you can but I’m looking at it.

Trust & Mined Knowledge

One key element of this new inter-connected world that we live in is trust.   How can I trust that the information I read on a web page is worthwhile, honest and accurate?   If I want to know something about organizational behavior do I read go read a Wikipedia article on the subject or do I go look through the Harvard Business School’s Organizational Behavior faculty pages and find publications written by the faculty there?

Which of these two sources of knowledge would you trust to be more accurate?

The same can be said of knowledge captured and shared within an organization. How do you know that the white paper on your new API is true?  Is it because it was released? Is it because of the author(s) of the paper?   What if you had a knowledge-base generated by an autonomous agent using text-mining techniques…how would you know to trust the information contained in it?  Who wrote the content?  Were did it come from?

This is where trust comes into play. If you could ‘see’ the qualifications of the author or authors of the knowledge base articles would you trust the content more?  If I knew that the worlds leading authority on organizational behavior wrote the Wikipedia article on the subject, I’d tend to trust that article more.

This is another aspect of my research…building trust into the mined knowledge using social network analysis (SNA) methods & techniques.  Using SNA techniques, can the background, profiles, connections and knowledge of the users within an organization be automatically (or semi-automatically) generated to provide some form for initial trust metric to show that mined knowledge can be trusted?

I don’t know if it can…but I’m looking into it 🙂

Next Steps?

So what are the next steps for me and this research?

I’m working on a research paper now that I hope will outline the research in more detail.

Lots of questions still exist and there is quite a bit of research left to do.  I do believe I’m headed in the right direction as evidenced by an HBR video & Blog tilted How Knowledge Management Is Moving Away From the Repository as Goal which discusses a similar topic.

Look for more on this topic from me in the coming months.

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