IT’S YOUR DATA, AND THIS IS YOUR BLOG

Welcome to the Collibra Blog, where CDOs, data stewards, and data citizens go to learn about true data governance.

subscribe

Looking Beyond Data to Knowledge Governance

Share: Share on FacebookShare on Google+Tweet about this on TwitterShare on LinkedInEmail this to someone

Looking Beyond Data to Knowledge Governance

The best input and challenges always come from customers. And, I’ve been thinking about a big challenge I hear consistently: trying to define the long term roadmap and strategy for their data governance program.

To be clear, my target audience is organizations who have seen success with data governance and are moving up the governance maturity curve.  Typically, they have already conquered foundational capabilities such as active stewardship, glossary management, data quality and issue management, compliance reporting, and more.

The key question I pose to those considering their long term roadmap is why stop at data governance?  Data is a core corporate asset, but aren’t there other corporate assets that could benefit from the same governance principles and approach?

To start answering that question, let’s first revisit the definition of governance itself.  According to wikipedia:

“Governance is the way the rules, norms and actions are structured, sustained, regulated and held accountable. The degree of formality depends on the internal rules of a given organization and, externally, with its business partners. As such, governance may take many forms, driven by many different motivations and with many different results.”

There are also numerous academic research papers to be quoted such as:

“ the governance process is a framework of authority that ensures the delivery of anticipated or predicted benefits of a service or process” (source)

The theme is that the value of governance is not limited to only data governance.  So, if we are not limited to data governance, then where do we go?  My search for an answer led me back to the accepted knowledge hierarchy depicted below.  It shows how data is transformed into information, and information into knowledge.

Looking Beyond Data to Knowledge Governance

Figure 1 – Knowledge Hierarchy

Sources: Nissen, M.E. (2000), ‘‘An extended model of knowledge-flow dynamics’’, Communications of the Association for Information Systems, Vol. 8, pp. 251-66 and Davenport, T. and Prusak, L. (1998), Working Knowledge, Harvard Business School Press, Boston, MA

The really interesting thing is that additional research has yielded variations on the model.  Tuomi [1] proposes an inverted model to drive the idea of knowledge creator and seekers.  Richard C. Hicks, Ronald Dattero and Stuart D. Galup also extended the model to five layers to include the personal aspect of knowledge that includes personal knowledge and innovation.  All of this points to the fact that social and collaborative aspects of human interaction are being more widely accepted as a part of the knowledge framework.

The impact of considering the knowledge hierarchy in the context of governance is that it has the potential to move governance further into the core of the enterprise and provide a different level of value compared to only focusing on the data layer and its derivatives.  In fact, when you take a hard look at the research, you see that the experts see knowledge governance as being critical to the success of knowledge management programs.  Here are some examples:

‘…greatest acknowledged obstacle to the implementation of a KM [knowledge management] strategy is the management culture of the organization [2] [3]’. These obstacles reveal a problem in the implementation of an organizational KM strategy. The problem lies not in the implementation of a given strategy per se, but in thelack of governance of that strategy.

‘While the importance of having enunciated knowledge management strategy has received considerable attention in the literature, little have been known about how the governance of knowledge management strategy is acted upon. Knowledge governance is meant to ensure the delivery of knowledge management strategic benefits. It broadly deals with the framework of decision rights, organizational structure, policy guidelines, risk management, performance measurement, and feedback mechanisms in relation to knowledge management deployment.’ (source)

So, there is an opportunity to apply governance to knowledge management and explore new frontiers. But there is a catch.  From a pragmatist’s point of view, there are issues with gaining sponsorship and deciding on an approach.  By sponsorship, I simply mean finding someone at a high enough level to champion this effort and get budget approved.  Let’s face it, knowledge management has been around for a long time. Most have not done it well and proving the bottom line value is difficult. So finding senior leadership to drive buy-in may be tough.  This point is reinforced below:

‘The terms knowledge champion, leader or sponsor are used interchangeably in the knowledge management literature. The terms variously indicate a person who initiates a KM strategy, or one who supports and promotes the initiation of such a strategy. Therefore the person or persons responsible for the implementation of a KM strategy may have the sole responsibility for the development and implementation of a knowledge management strategy. This cannot ensure buy-in from the organization as a whole.’ [2] [3] [4].

The second challenge is deciding on an approach.  Simply stated, it can be difficult to know where to start with knowledge management when most have a vague definition of what it is.  This lack of clarity makes it hard to pin down ownership and stakeholders, let alone gain agreement and secure their time to assist with the application of governance to it.  What sparked an idea for a solution for me was this passage:

‘There are two categories of strategies – deliberate and emergent strategies. Deliberate strategies must be articulated in a plan that must then be implemented. Emergent strategies are those that emerge in the organization as part of the process of learning what works well and what does not.’

I was inspired to forget about a top down deliberate strategy and think about how an emergent strategy might work.

I propose you start by first thinking about the form knowledge management has taken in your organization.  By form, I specifically mean content.  Almost every organization started on the knowledge management journey by implementing portals, document libraries, video libraries, and more.  The truth is that most stalled here and now have piles of virtual artifacts.  Also think about the new emerging forms of personal knowledge and collaboration that are being driven by social technology as mentioned above.  Taking these things into consideration, I believe you could apply these three steps to execute on an emergent governance strategy:

  • Classify and cross associate content with corporate policy, process and drivers.  Then offer traceability and search based on business context.
  • Apply stewardship to the management/curation of the content.
  • Offer collaboration and capture new personal knowledge by group, communities, and domains.

This idea may sound very abstract, so here is a practical example.  You could substitute any number of technologies, but let’s consider Microsoft SharePoint.  It has a vast array of capabilities including classifying content in libraries by terms and termsets, metadata navigation & services, search, workflows, and more.  A lot of organizations start with the idea that it will serve as a knowledge portal. But the reality is, most of those features never get put to use and it simply becomes a content repository with a search engine on top.  No matter how it’s deployed, what it lacks is an association of the content to corporate processes and policies and a way to intelligently curate this association. In essence, it lacks governance.  It would be a very valid bottom up (emergent) strategy to simply link the terms and termsets to governance glossaries by domain and then associate the libraries and documents to governance communities and domains.  And then later, continue with the other two steps I suggest above.  This type of approach is fairly simple, low cost, and should be fairly quick for an already successful governance program. The impact, however, could be tremendous for both the business and the governance organization.

Returning to the original challenge of the roadmap, I think leaders of governance programs must be willing to step back and consider the applicability of governance beyond only the data domain.  I’ve considered the area of knowledge management but there are undoubtedly countless other possibilities.  Finally, it is important to take promising possibilities and fully consider the practicalities of execution as I’ve done here.  After doing that, your roadmap should start coming into focus.

Sources:
[1] Tuomi, I. (1999), ‘‘Data is more than knowledge: implications of the reversed knowledge hierarchy for knowledge management and organizational memory’’, Journal of Management Information Systems, Vol. 16 No. 3, pp. 103-17.
[2] Chase, R. L. (1997). The Knowledge-Based Organisation: An International Survey. Journal of Knowledge Management, 1(1), 38-49.
[3] S. Zyngier and F. Burstein, “Knowledge management strategies: leaders and leadership,” presented at Constructing the Infrastructure for the Knowledge Economy; Methods and Tools, Theory and Structure’ Proceedings of the 12th International Conference on Information Systems and Development (ISD’03), Melbourne, 2004.
[4] Davis, S., McAdams, A., Dixon, N., Orlikowski, W., & Leonard, D. (1998). Twenty Questions on Knowledge in the Organization, Business Intelligence and Ernst & Young Center for Business Innovation.

John has 25+ years of business intelligent and data management experience in a number of diverse leadership roles including responsibility for consulting, sales, marketing and product development. During this time he worked with a number of pioneers of data warehousing, has been a frequent public speaker and developed deep expertise in BI methods, data warehouse design, analytic techniques, master data management and meta data management. He has been a principal at several silicon valley software startups and consulting organizations that where acquired at separate times by both IBM and HP.