Watson and The Future of ECM

In the past, I have whipped out my ECM powered crystal ball to pontificate about the future of Enterprise Content Management.  These are always fun to write and share (see Top 10 ECM Pet Peeve Predictions for 2011  and Crystal Ball Gazing … Enterprise Content Management 2020).  This one is a little different though …  on the eve of the AIIM International Conference and Expo at info360, I find myself wondering … what are we going to do with all this new social content … all of these content based conversations in all of their various forms?

We’ve seen the rise of the Systems of Engagement concept and number of new systems that enable social business.  We’re adopting new ways to work together leveraging technologies like collaborative content, wikis, communities, RSS and much more.  All of this new content being generated is text based and expressed in natural language.  I suggest you read AIIM’s report Systems of Engagement and the Future of Enterprise IT: A Sea Change in Enterprise for a perspective on the management aspects of the future of ECM.  It lays out how organizations must think about information management, control, and governance in order to deal with social technologies.

Social business is not just inside the firewall though.  Blogs, wikis and social network conversations are giving consumers and businesses a voice and power they’ve never have before … again based in text and expressed in natural language.  This is a big deal.  770 million people worldwide visited a social networking site last year (according to a comScore report titled Social Networking Phenomenon) … and amazingly, over 500 billion impressions annually are being made about products and services (according to a new book Empowered written by Josh Bernoff and Ted Schadler).

But what is buried in these text based natural language conversations?  There is an amazing amout of information trapped inside.  With all these conversations happening between colleagues, customers and partners … what can we learn from our customers about product quality, customer experience, price, value, service and more?  What can we learn from our internal conversations as well?  What is locked in these threads and related documents about strategy, projects, issues, risks and business outcomes.

We have to find out!  We have to put this information to work for us.

But guess what?  The old tools don’t work.  Data analysis is a powerful thing but don’t expect today’s business intelligence tools to understand language and threaded conversations.  When you analyze data … a 5 is always a 5.  You don’t have to understand what a 5 is or figure out what it means.  You just have to calculate it against other numeric indicators and metrics.

Content … and all of the related conversations aren’t numeric.  You must start by understanding what it all means, which is why understanding natural language is key.  Historically, computers have failed at this.  New tools and techniques are needed because content is a whole different challenge.  A very big challenge.  Think about it … a “5” represents a value, the same value, every single time.  There is no ambiguity.  In natural language, the word “premiere” could be a noun, verb or adjective.  It could be a title of a person, an action or the first night of a theatre play.  Natural language is full of ambiguity … it is nuanced and filled with contextual references.  Subtle meaning, irony, riddles, acronyms, idioms, abbreviations and other language complexities all present unique computing challenges not found with structured data.  This is precisely why IBM chose Jeopardy! as a way to showcase the Watson breakthrough.

IBM Watson (DeepQA) is the world’s most advanced question answering machine that uncovers answers by understanding the meaning buried in the context of a natural language question.  By combining advanced Natural Language Processing (NLP) and DeepQA automatic question answering technology, Watson represents the future of content and data management, analytics, and systems design.  IBM Watson leverages core content analysis, along with a number of other advanced technologies, to arrive at a single, precise answer within a very short period of time.  The business applications for this technology are limitless starting with clinical healthcare, customer care, government intelligence and beyond.

You can read some of my other blog postings on Watson (see “What is Content Analytics?, Alex”, 10 Things You Need to Know About the Technology Behind Watson and Goodbye Search … It’s About Finding Answers … Enter Watson vs. Jeopardy! … or better yet … if you want to know how Watson actually works, hear it live at my AIIM / info360 main stage session IBM Watson and the Impact on ECM this coming Wednesday 3/23 at 9:30 am.

BLOG UPDATE:  Here is a link to the slides used at the AIIM / info360 keynote.

Back to my crystal ball … my prediction is that natural language based computing and related analysis is the next big wave of computing and will shape the future of ECM.  Watson is an enabling breakthrough and is the start of something big.  With all this new information, we’ll want to use to understand what is being said, and why, in all of these conversations.  Most of all, we’ll want to leverage this new found insight for business advantage.  One compelling and obvious example is to be to answer age old customer questions like “Are our customers happy with us?” “How happy” “Are they so happy, we should try to sell something else?” … or … “Are our customers unhappy?” “Are they so unhappy, we should offer them something to prevent churn?” Undestanding the customer trends and emerging opportunities across a large set of text based conversations (letters, calls, emails, web postings and more) is now possible.

Who wouldn’t want to undertstand their customers, partners, constituents and employees better?  Beyond this, Watson will be applied to industries like healthcare to help doctors more effectively diagnose diseases and this is just the beginning.  Organizations everywhere will want to unlock the insights trapped in their enterprise content and leverage all of these conversations … in ways we haven’t even thought of yet … but I’ll save that for the next time I use my ECM crystal ball.

As always … leave me your thoughts and ideas here and hope to see you Wednesday at The AIIM International Conference and Expo at info360 http://www.aiimexpo.com/.

12 thoughts on “Watson and The Future of ECM

  1. Nice blog and valid points, as always, Craig. But you trigerred a thought: What if we’re over-analysing the social content out there? I feel another blog coming… 🙂

    1. Good point parapadakis, but that problem already exists. Was recently discussing some survey feedback on an intranet with the business owner. Less than 10% responded and it can be difficult to not give too much weight to one or two pieces of very negative feedback.

      However having this information allows you to direct your thinking and attention, even if it is just to ask further questions. NLP will open up huge interesting areas of knowledge representation and discovery.

  2. I agree that our customers are looking for more accurate to capture how their customers are feeling and not just the ones that fill in surveys. they are keen to know what has been their customer experience? how could it be improved? how do their current customers and potential customers want to be serviced / sold to / supported? ECM Content Analytics combined with Predictive Analytics will provide customers with some super-powerful customer insight!

  3. Craig, I couldn’t agree with you more about the importance of “all of this new content” and the use of analytical technologies to get at its business value, given that the content is “text based and expressed in natural language.”

    Yet one of the leading content organizations — the AIIM itself — agrees only weakly, judging both from the program and exhibit coverage at the info360 International Conference and Expo and from the report you cite, Systems of Engagement and the Future of Enterprise IT: A Sea Change in Enterprise , which calls “min[ing] community content to extract insights to enhance the business” an extension to collaboration — Is that really all it is? — and says “there is no need to rush into it… The business side of the house needs to catch up in terms of organizing the deep dives and staging the results to support future action.”

    There’s a lot of market education that needs to be done, including among folks such as the AIIM whom many look to for thought leadership!

  4. Federal election in full swing in Canada and to be our first social media election…14,000 tweets in the first afternoon of the campaign, politicians would love to analyse that data and get the pulse 🙂

  5. Most definitely Watson influences ECM. Everything “social” is about capturing conversations, establishing relationships, and engaging in series of activities in an online virtual space. Until recently, it was phone, email, and face to face meetings and there wasn’t a systematic way to capture, manage, learn, share, etc… and public sites like Facebook, Twitter, LinkedIn, and the general blog-o-sphere have provided different platforms to enable us to be “social” outside of traditional mediums.

    Both in the public web and within corporate intranets as more and more conversations (thoughts, ideas, Q&A, blogs, comments, etc…) are captured and managed across ECM platforms, the key is gaining some level of insight from all of this — not only within a single system like Watson but ACROSS platforms. No doubt we will see governments and other private industries use technology like Watson to also ensure security of information. Hopefully Google, IBM, or some other company will have the brain power to go beyond a closed and “trained” system Watson…

  6. Very relevant in an ECM point of view. Less relevant in a Search POV. There are huge differences between Search and ECM projects, you know that. Watson is based on a way for a machine to deal with enormous amount of specialized and dedicated info, structured into DB in a formated way. Search is a way to deal with enormous amount of info inside the enterprise, info which are only indexed and not formated.

    1. Fred – Watson is not exclusively based on a formatted database as you suggest. Watson uses DB2 for it’s structured data knowledge assets but most of the stored knowledge knowledge is unstructured and based on semantic relationships between extracted concepts and facts as processed through UIMA based NLP and other annotators … not unlike the way search technologies leverage concept based searching and ontologies.

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