What is knowledge management? Well, it’s like information management, if that helps. No?
So what is information management? Well, really it all starts with quality management. (Get to the point!)
This is a slightly re-digested and expanded version of a little snippet I previously wrote, which appears in Principles of Festival Management (Chapter 10: Research & Evaluation).
Start with an arts & crafts, handmade mode of production. Here, the person making the product manages the quality of the product directly. Then you’ve got mass production, where the management of quality is shifted to managers rather than individual assembly-line style workers. With a proliferation of consumer choices, quality management becomes both a competitive advantage and a method of cost saving, given the high volumes being produced.
Does quality management apply to the arts? Err, in some parts, not others. (*cough quality metrics cough*).
You may have heard of standards and systems like: Six Sigma, Total Quality Management, Kaizen/Continuous improvement, ISO9004, ISO9001 in regards to quality management. They all seem on the face of it, like your typical big money, executive-level, boardroom type words that “shouldn’t” fit in the arts world, but it’s also clear that management theory has percolated its way all over the place – public sector and charities alike.
Really, it’s not cutting edge thinking, when nearly 30 years ago now, people were saying things like this:
“In the new information society, the key resource has shifted to: information, knowledge and creativity” (Naisbitt, Global Paradox, 1994)
It’s an extension of quality management principles, moving from manufacturing processes to information. We can generally grasp the idea of improving quality of physical objects, but what’s the bottom line impact of poor quality information? We’ve all lost spreadsheets every now and then. We’ve all wasted time entering data that didn’t turn out to be particularly valuable. One quote from 1999 I found, suggested that poor information management could cost a company as much as 10-25% of its revenues. (L. English, 1999… but I can’t remember where , hey that’s a good example of the risks of bad information management actually, do you know what I’m leaving it in.)
Knowledge management and The DIKAR model
The ‘DIKAR’ model (Venkatraman, 1996 – Managing IT resources as a value centre) is a commonly used way of abstracting the Knowledge Management process.
Very briefly this shows the more technology driven side (DI: Data, Information) meeting the business value side (AR: Action, Results) with Knowledge (K) in the middle. Business decisions create demand for knowledge, while data and information supply the raw material to inform knowledge.
- Data has to be interpreted in order to render information.
- Information has to be understood in order to emerge as knowledge.
- Knowledge allows managers to take effective decisions.
- Effective decisions have to lead to appropriate actions.
- Appropriate actions are expected to deliver meaningful results.
On the supply side, there are clearly many options to explore and evaluate for collecting data and processing it into usable information. This is not to say everyone is doing so efficiently or effectively. Given the proliferation of data, it is easy to rapidly amass a wide variety of seemingly authoritative information that does not inform any particularly important business decisions (Action) or generate value, however this is determined (Results).
If we do have to borrow anything from the software developers, let it be the phrase:
“Garbage in, garbage out”.
I would hope improving your approach to ‘KM’, the benefits are three-fold:
- Reducing time required on the ‘Supply’ side (Data & Information)
- What you do (Actions & Results) can be improved, delivered better/faster
- Ongoing history or legacy (Knowledge) is built up and retained
The cultural sector can clearly struggle with organisational continuity and building institutional knowledge. In the public sector, it is more likely that individual organisations will have some of their Knowledge Management approach determined for them by funding bodies, though networks or sector support organisations have a similar role across all sectors.
Maybe the thing about instrumentalism (for whatever purpose) Is the disconnect between organisations and funders is that that for the most part they are expected to do the “DI” bit but it is the funders who end up driving the “KAR”?
For most applied research & evaluation, the ambition is usually to answer a relatively proscriptive question: Who attends? Were they satisfied? What is our impact on X, Y or Z? I think
It is relatively easy to identify the work involved with data collection and analysis; and to learn more about the tools and practices that improve and simplify this essential research ‘legwork’. It is less likely that we could describe these (nevertheless valuable) stand-alone projects as consistently fitting into, or replacing the need for, an overarching strategy for Knowledge Management within the organisation.
It is hard to say what the difference a single point of data (questionnaire, transaction, social media) makes but we can at least have a shared and conscious decision about what is most useful/most interesting to us (as well as that which our funders oblige us to collect anyway). Technology can help and be a part of this but it probably shouldn’t be your first instinct.
What can I do about it?
Anyway, here’s a nice list for you to think about, pinched from this consultancies list of ‘Barriers to Knowledge Management’
- Knowledge is power: people hoard knowledge instead of sharing it
- The individual work bias: teamwork is more valuable that doing it all yourself
- Local focus: “This is just how it works here”, not sharing knowledge further
- Ownership: “This is someone elses system”, no buy in, no trust
- No room to fail: Errors will be penalized, incentives to hide failures
- Not paid to share: No budget for writing up or dissemination
- No time to share: I’d love a tidy spreadsheet, but it’s not a priority right now!
Specific technologies are not inherent to ‘KM’ practice, though it is hard to argue that reduced barriers have made some approaches possible that would have previously been cost-prohibitive. There is plenty of work and value to be realized from taking a step back to consider how you could simply manage existing data, information and knowledge resources more effectively. Substantial trust is needed within organisations for individuals to relinquish ownership of knowledge, or methods of working, which will likely be encoded in very individualised ways. If nothing else, this can also identify where tacit, personal and flexible decision making should start and where more data-driven or formulaic decision making should end.
(Also see Appendix 1: the ‘Template Evaluation Commitment’ in this RSA handbook)
In conclusion, a Knowledge Management strategy tries to not emphasise any one form of data, or research method over any other. Instead, it provides a model for addressing the whole spectrum of knowledge supplying and demanding processes, giving appropriate place and consideration to each. Few festivals would want or need to employ a full time archivist of course, but this approach is worth bearing in mind the next time you pull together sales reports, survey results or web analytics; with only a vague idea of what organisational knowledge this is actually feeding into, or what demand-side decisions can be informed by this. Equally, you may save considerable time and effort, being reassured that some questions are less urgent than others, or have already been satisfactorily answered by previous efforts.
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