Mar 26

Knowledge as a Service (KaaS): A Proposal

I know, I know – the above sounds kitschy, corny, tacky, hyped-up thought leadership.  We are in the era of cloud – so of course, I am going to propose [A-Z] aaS as a solution.

But there is more to this proposition that the initial skepticism can see.

As I expressed in previous posts on this series exploring the new paradigms for Knowledge Management (KM) we are undergoing a tectonic shift in what knowledge is, how we use and store it, and even how we define it.  All these trends are leading us to see a new reality in KM that necessitates a new platform to address properly.

KaaS is that platform and I would like to explore in this installment what it is and how to approach it.

Defining KaaS

The trick to the definition of Knowledge as a Service is to not allow the improper definitions of cloud muddy the waters.  For the vast majority of people, but thankfully shrinking, the cloud means the internet.  Delivering applications on a browser over internet transport protocols is what is, inappropriately, called the cloud.

In reality, the cloud is a three layer model of distributed computing: the SaaS (software as a service) layer provides the interface and top-level functionality, the PaaS (platform as a service) layer provides the brunt of the processing necessary for applications to work, and the IaaS (infrastructure as a service) layer provides the low-level services (such as databases and communications) that are necessary for an application to function in an complex ecosystem.

KaaS has been defined (for better or for worse) mostly along the lines of proper-answer at the precise-time for the past 10 years or so, including being used by RightAnswers (a vendor of KM solutions) as a go-to-market name; even Salesforce.com uses the concept.

Alas, the lack of the open-cloud three-tier model pretty much precludes them for fully leveraging that which they tout – anytime, anywhere, anyone, best answer – without a complex set of integrations.  Organizations have not yet embraced the open-cloud, three-tier model – so it is impossible for them to deliver on that model.  Maturity is still needed in the organization in regards to cloud for KaaS to fully succeed – but the next two-to-three years will prove critical in those efforts.

The term KaaS does not refer to a fourth layer to be added to this model, rather to a platform for providing the best knowledge, in the best context, at the best time as needed.  This coincides well for the models I have been discussing, including the “Knowledge Nirvana” webinar I did last year.

KaaS is more about how to leverage the cloud to access and make available all sorts of knowledge – from static repositories to more interesting collective knowledge, to real-time SME (subject matter experts) contributions.  And delivering this on an open-cloud model in an open platform that is part of a larger cloud infrastructure is where Knowledge will be in the next four-to-eight years.

Approaching KaaS “Deployments”

KaaS is not a software package, a methodology, or a framework (well, closer to being a framework actually) – it is a model; a collection of lessons learned, best practices, proven workflows, and case studies that can help your organization leverage knowledge from anywhere, anything, and (more importantly) anyone in a distributed computing model.  The main advantage you will have from embracing components to deploy in a KaaS model will not be better management of the knowledge you have, but better access to knowledge all around.  There are three things you must understand before embarking on this new model:

1)      Platform Fit. To leverage a KaaS model the first thing you need to make sure is that the platform it will rely on fits in your cloud infrastructure plans.  Virtually all organizations, or all by the end of this calendar year, have a cloud plan in place or already underway.  Smart CIOs and organizations have been busy deploying or creating a cloud infrastructure that will support the organization’s operations for many years to come.  If not, that is at the top of the priorities list for this calendar year and into the next.  The time where any hosted application or on-demand application was called cloud is quickly coming to an end – the three-layer model of the open cloud is taking over the enterprise – and you must ensure that your KaaS deployment conforms to your corporate standards.

2)      Leverage.  Second, you must ensure that your KaaS deployment can be leveraged across many functions – both internal to the enterprise as well as external.  There are three core reasons why a platform deployment makes sense: infinite elasticity, unparalleled integration, and the ability to leverage it across ecosystems.  KaaS being a platform-model deployment must conform to all this – but the leverage is the one that provides the strongest justification. In the “old days” KM was relegated to one of two uses: internal sharing of knowledge in repositories and (in the form of knowledgebase) for customer service to power both agents and end-users (via self-service deployments).

The need was patent for organizations to acquire, maintain, and use different systems for each process they had that required knowledge.  There was no common standard to reach across the many needs and as a result each function was “forced” to find the best solution that worked for them – often resulting in many different solution deployed concurrently with no way to leverage what was done, the lessons learned, or the need to optimize deployments.

3)      Knowledge Flows. Third, you need to understand what knowledge means for your organization, where it comes from, and how you use it.  Decisions like real-time SME (subject matter expert) access or stored knowledge in knowledgebases, timeliness to access the information needed while retaining the critical aspects of each processes, and alternatives to knowledge that would make the process still functional.  These are questions that must be answered for virtually all processes that use knowledge.  The answers to these questions will give you the information you need create a knowledge-flow.

Most organizations don’t want to tackle this work as it sounds extremely confusing and daunting; in reality, it is not.  Generating a knowledge-flow map for your organization is an easy part of any process documentation initiative and should be done as an early step to adopting any knowledge methodology or model.  If you know where the knowledge comes from, where it goes, and how it is used – you are far more likely to end up with a proper solution that meets your needs.

In addition to existing vendors trying to adapt their solutions to this model (including eGain, Intelliresponse, KANA, Moxie, and I am sure others that will chime in the comments below) , there are a couple of I came across this past year that are going in this direction: Coveo and Mindtouch.

Of course, these are early steps to adopting the concept of KaaS – but if you can answer the questions in these first steps, the rest is far easier.

Is the model of KaaS something that interests you?  Are you seeing the cloud as the next step in knowledge management? Please let me know what you think in the comments – good discussions are always welcome…

disclaimer: as with any other post that mentions vendors, I have to make the disclaimer.  Virtually all of the vendors mentioned are either current, past, or future clients.  If you think I am being nice to them because they are/were/will be clients you don’t know me.  Having being in this business for over 15 years it would be impossible to mention vendors that have not been or are clients.

image source: http://thespiritscience.net/spirit/2011/09/21/types-of-knowledge/
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  • http://twitter.com/gonikhil gonikhil

    Great post Esteban and thanks for the mention. Yes, we at Moxie Software are furiously wokring towards this goal of making knowledge aka ‘answers’ available to ‘customers’ when they need it.

    ‘Customers’ could be internal employees or partners or end consumers looking for the answer to thier question; we believe the best way is to connect the question to the answer regardless of it being available in a knowledge repository or in the head of the right expert. As you say, it really is simple and we believe in keeping it that simple for our customers. Thats why we are taking on the complex task of making this all work together magically – public cloud, private cloud, security, mobile (did i miss any buzz words?).

    We call it ‘Social Knowledge’ and its coming soon…

  • http://www.facebook.com/fuzesocial Chuck Van Court

    Greetings Esteban:

    You have provided a thought provoking post, indeed.

    I agree with much of what you say, especially your thoughts on how quickly knowledge goes
    stale and the importance to not silo knowledge between different organizational stakeholders
    and instead to selectively extend different content to different people.

    However, unless I misunderstood you, where I don’t buy your concept is when it comes to
    answering questions of customers or staff with little time or interest to extract desired answers
    from content not specifically created to answer a question. Search engines have some
    success interpreting a question’s intent and surfacing relevant content from unstructured and
    disparate data, but the AI smart enough to extract and craft thorough, succinct and easy to
    understand answers from said content is still many, many years away.

    Until which time AI has massive advancement, It will take knowledge sharing platforms that
    bring together and motivate contributions from the right people along with participation
    from other people with the responsibility and skills to curate and edit this
    vast knowledge into quickly consumable answers. If done correctly, these answers should
    also perpetually evolve and mature giving them a much longer shelf life and better value than
    the transitory knowledge duplicated throughout most communities to answer some form
    of the same question.

    Beam me up Scotty…Ok, I’ll just walk real fast, instead.

    Chuck

  • http://www.facebook.com/fuzesocial Chuck Van Court

    Greetings Esteban:

    You have provided a thought provoking post, indeed.

    I agree with much of what you say, especially your thoughts on how quickly knowledge goes
    stale and the importance to not silo knowledge between different organizational stakeholders
    and instead to selectively extend different content to different people.

    However, unless I misunderstood you, where I don’t buy your concept is when it comes to
    answering questions of customers or staff with little time or interest to extract desired answers
    from content not specifically created to answer a question. Search engines have some
    success interpreting a question’s intent and surfacing relevant content from unstructured and
    disparate data, but the AI smart enough to extract and craft thorough, succinct and easy to
    understand answers from said content is still many, many years away.

    Until which time AI has massive advancement, It will take knowledge sharing platforms that
    bring together and motivate contributions from the right people along with participation
    from other people with the responsibility and skills to curate and edit this
    vast knowledge into quickly consumable answers. If done correctly, these answers should
    also perpetually evolve and mature giving them a much longer shelf life and better value than
    the transitory knowledge duplicated throughout most communities to answer some form
    of the same question.

    Beam me up Scotty…Ok, I’ll just walk real fast, instead.

    Chuck

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