Over the years I have felt extremely frustrated with the so-called knowledge repositories, such as SharePoint, and the many other solutions for collaboration that exist around an intranet. Many years ago I joined an engineering consultancy firm in London called Fulcrum (which a few years later merged into Mott MacDonald). That was back in 2008 and we were around 150 employees, with small offices in Edinburgh, Madrid and Hong Kong. Those were the days were sustainable building design was going strong. The six directors were (and are) an extremely cool and forward-thinking lot and they put together a great team of sustainability consultants and building engineers. I was one of sustainability guys.

As you can imagine, sustainable building design touches on many aspects of the building; insulation, air-tightness, energy efficiency, daylight, building controls or thermal comfort, to name a few. Knowledge was very important and we had a Knowledge Base (SharePoint). As we were constantly researching new technologies and design principles, we were continuously coming across very interesting documents and articles. We were devouring them and uploading them on the Knowledge Base. We had categories and tags and all the rest, and we were not too bad at applying metadata to the files. But nonetheless, it was a phenomenal mess.

Soon it was obvious that we were uploading stuff much more frequently than downloading files. The main reason for this was that any ‘search’ would yield a large number of results and there was no way we could obtain anything which actually matched what we needed in the moment without opening and reading a lot of documents. Now, many years later, I have a better understanding of the problems we were suffering then, but the truth of the matter was that we all had our own repositories of knowledge on our computers, and any time we had a need or an itch, we would turn to our reliable contacts (for instance, Tom, just across from my desk) who would send us an email with the document in an attachment.

We had built a platform which was to be a knowledge sharing platform, but we did not know the difference between a library and a collaboration environment. As a result, we ended up doing none, because we could not tell information from knowledge. To illustrate this, I will reproduce here the definition of Knowledge Management by Kimiz Dalkir and Jay Liebowitz: ‘Knowledge management develops systems and processes to acquire and share intellectual assets. It increases the generation of useful, actionable, and meaningful information, and seeks to increase both individual and team learning. In addition, it can maximise the value of an organisation’s intellectual base across diverse functions and disparate locations.’ Our knowledge base had tons of information with little use, relatively low meaning, and it was certainly not actionable.

KM is the Supermarket and your Project is the Kitchen

I often use this analogy. A knowledge-sharing platform is the supermarket you go to find the ingredients to take home to your kitchen. Once there, you can mess around with the alchemy of your project. I still work in the construction industry, sadly not anymore at Fulcrum, but at Werner Sobek, which is another very good firm. We are building engineers and designers doing pretty much all the things that architects do not do: structural engineering, façade engineering, heating and cooling, etc. As you can imagine, our kitchen can get pretty messy and we have all sorts of things going on at once.

I’ll give you a small example. We were recently approached by an architectural firm in Philadelphia to support them in a cool and confidential competition in Hamburg. It’s something like a museum and it will be small-ish, 2,500 m2 of net floor area. We have three weeks to cook up our magic and there are no fees involved, so we don’t want to spend too many hours cooking.

After a few days we received the architectural drawings, showing the exhibition areas, back of house offices, circulation, toilets, and so on, but there isn’t a single technical room for us to put our equipment in. This is quite common, by the way. One of the dishes on our menu takes priority and has to come out of the kitchen really fast, as all starters should. -This is: To Tell The Architects How Many and How Big Our Technical Areas Should Be-. Speed is key, because everybody is working away and the sooner we get our foot in the door, the easier our life will be for the next two years.

Now that you know the context, let’s go back to Knowledge Management.

So now that we know the breakdown of areas in the building, we rush to the supermarket and check out the different aisles and shelves. Navigating the supermarket is very easy and we quickly find an aisle call ‘Spatial Allowances’ (that’s the lingo). We walk along the aisle taking a look at the different products on display. It is very clear in our minds what the final dish shall be, so we easily identify the ingredients we can use:

• Template booklet for spatial allowances
• An excel spreadsheet with benchmarks for other museums
• A tool to estimate the loads (power demand, heating, ventilation, water, etc)

Furthermore, while looking around, we find other related ingredients that we did not know existed and which will give our dish extra flavour such as case studies of technical areas in museums we did in the past and a couple of diagrams we can adapt to fit our project. In fact, the architects won’t notice this, but we also took a couple of ready-made meals from the freezer, but hey, economies of scale, right?

Three Principles of Good Practice

In order to provide such an experience (navigating the supermarket), we had to establish a few requirements. Or rather, define a brief which is not too abstract nor too narrow; as Tim Brown puts it in his book ‘Change by Design’. The way I see it, the knowledge-sharing platform should conform to the following three principles.

• Knowledge should be very easy to create, share and rearrange 

The members of the organisation should be able to share their explicit knowledge in the easiest way possible, as any burden to the process of creating and sharing knowledge will dramatically reduce the level of engagement and the amount of contribution. Similarly, any knowledge domain is organic and will evolve with time, so the different domains and the different knowledge assets will need to be re-arranged (forgotten even). This process should also be extremely easy. In my experience, SharePoint and Wikis don’t fulfil this principle, especially when it comes to re-arranging.

• Knowledge should be organized as an ontology, not as a taxonomy

In case I am not using these big terms in the proper way; by taxonomy I mean a tree diagram, and by ontology I mean something like a network. A well-known taxonomy is the animal kingdom (or parts of it, rather). Under such organisation, any given species will only be in one place, and there is only one path leading to that species. So next time someone in your organisation needs to do some work about rabbits, he or she will have to access the folder of chordata (I just learned this word), then the folder of vertebrates, and so on until reaching the rabbit and accessing the knowledge your organisation holds on rabbits. But in reality, the way our brains reach different domains of knowledge is by navigating a network of domains, so different people will access their domain ‘rabbits’ by a myriad of different paths. Notably: carrots.

• Whatever the KM method, it should be built from the ground up 

Another barrier to a successful KM system is when the system comes from above. This now seems obvious to me, but not when we started implementing the KM platform back in the day. Back then we had a series of workshops between a bunch of senior guys where we devised the KM system including the major domains all on our own. We then passed it on to the wider company expecting them to start  populating and using it. It was not well received and it obviously failed.

This third principle is quite straight forward: whatever the KM system, it should be built from the ground up. Furthermore, I recommend building it around communities of practice and start small. The way I do it is as follows: first choose a specific company objective that is closely connected to knowledge (low hanging fruit), second define a small community of practice around it and give them a clear goal, and then start working on that specific domain for that specific target. By so doing, you will create a small but functional KM environment, which is useful for everybody from day one. People within this community will feel ownership, will look after their domains and will feel comfortable using the platform.

Knowledge Mapping on a Mind Mapping Platform  

Now, discussion on technology is unavoidable and so far I have only found a way to do this: communities of practice and collaborative knowledge mapping. In particular, we use mind mapping software. I don’t think there is much point in mentioning the particular software we use, since many commercial products out there provide the necessary functionality.

Mind mapping is a very simple and very powerful technique to organise your thoughts (and in our case, our collective thoughts). This is the Wikipedia description: “A mind map is a diagram used to visually organise information. A mind map is often created around a single concept, drawn as an image in the centre of a blank page, to which associated representations of ideas such as images, words and parts of words are added. Major ideas are connected directly to the central concept, and other ideas branch out from those.”

For the last six years we have been using collaborative mind mapping to manage our knowledge. It’s been the most successful platform I have ever used. It is simple, intuitive, easy to use and fully complies with the three principles of good practice. It provides an ontological navigation experience, so that different people reach the same domains following different paths. I can’t stress enough how important this is. Every now and then, when I have shared a new knowledge asset, I go for a walk and ask some random colleagues if it would be ok to carry out a test for me. I ask them to go to the knowledge map and see if they can find (or rather, access) something in particular. Invariably, they all find it in a matter of seconds. I observe the paths they follow and it is very interesting to see how different they can be.

The aim of this article is just to provide an insight into what I believe to be an effective knowledge sharing and collaboration platform, and what the principles should be to govern such an initiative. It all comes down to people and to influencing the organisation’s culture. I believe it should be down to the users to curate the experience of navigating the company’s knowledge. I do not want to overextend and lose your interest, and I hope you have found this story useful so far. I would be delighted to hear from you:

• What do you think?
• What is it like in your industry? What do you use?
• Is knowledge mapping a sensible solution only for engineering disciplines?

Following up from my last blog post: Too busy to get help? Take time to learn!

I hear from my Customers (our 20k+ Enterprise Services employees worldwide) almost every day, how hard it is “to find the stuff I need”, or “to find the good stuff”, out of a list of search results that sometimes spans tens of thousands of returns. And I totally get that. I feel the same way very often, whether I am looking for stuff internally, or trying to book flights for my next vacation.

But then I add some data insights to the equation, from the telemetry we capture on our Collaboration solution (https://aka.ms/Campus, for the “softies” among my readers) which shows that the average free text search query is 1.4 words long. And that is down from 1.6 words over the last 6 months.

This data is interesting in several ways to me, because knowing the information increase and rate of change required of all of us over the same time frame, seeing a decrease/limitation in search queries is not that odd, is it? I think it is a natural response that the more information is pushed on you, the more tunnel-visioned you get about the information you absorb, and the search query data is merely a reflection of that: Tunnel vision. Not a conclusion that “free text search queries” are not optimised (even though that is indicated as well).

To add to that, 80% of the searches on our solution are free text searches, although we offer two more search options: parametric search and catalogue browsing. I would hypothesise that is also a result of simply “running to fast” to even see there are more ways to find the stuff you are looking for.

And please, do not read this short piece as “industry research” or “statistically verified data” – these are trends combined with my own thoughts, based on taking a long hard look at my own behaviours as much as anybody else’s!

But to come back to my last post, about “taking time to learn”, I honestly believe that we can do a lot ourselves, before we ask the tool/process/company to fix the problem for us – no tool can find what we are looking for, unless we take time to (learn how to) look!

Many times we are very quick to jump into “solution mode” and we think the fix is to buy a new tool and throw out the old one, change the existing one, or even add a few more to the already rich tool box we have. I am going to go out on a limb here and say that, in the name of Pareto, 80% of the time this is not the right way to address the problem(s). Or at least not the right first step.

We have shared some of our own experiences in the 5+ year KM-journey that we have been on in Microsoft Enterprise Services in this 2-pager: Microsoft Services Reimagines Knowledge Collaboration with Cloud-Based Platform. One key conclusion was the same conclusion many others have drawn, that it is 80% a “people & process-problem” and not a “tools problem”.

Investing some time in understanding our organisation’s/team’s search behaviours and “teach ourselves/them how to fish”, instead of telling us/them to “go fish”, or sending someone out for “new fishing tools”, is usually time well invested for most organisations.

Are you too stuck in the "I don't know but I don't have time to learn!" dilemma?

In my last post I talked a bit about Digital Transformation and how the multi-faceted and extremely high-paced transformation that most of us are in the midst of right now, is rapidly increasing the need for us all to “work smarter”. To some of you, this is a bit of a cliché and something that some managers/leaders repeated more often than actually applicable, some 7-8 years back. It was one of those buzzwords that got abused to the point of ridiculousness.

So why am I dusting the old "work smarter" slogan off then?

Because today, more than ever, I actually think it is finally becoming a necessity and a game changer for every high performing individual to “work smarter”. I am not saying work faster, longer, harder, or more. I think we have reached the point where that is no longer an option. A bit like how Moore’s law has finally reached saturation and after decades of accelerating has now started to slow down.

In "To Social, or Not To Social?" I touched upon how productivity and efficiency improvements used to be all about optimizing processes and essentially cutting costs.  But as most companies are as lean as they’re ever going to get already, streamlining further isn’t really a viable option anymore. In the same way, working faster, more or harder really isn’t either. I think we may have reached saturation, or we are at least very close to reaching it, in terms of how an individual’s performance can be enhanced or stretched much farther.

“Collaboration is the new black” they say…

Sure, I buy that but, perhaps it isn’t quite that simple?  Have you ever found yourself in a situation where you are desperately looking for something, or desperately trying to figure something out, and you are under so much pressure that your brain starts shutting down and you keep adding more things to your plate?  You just don't have time, to ask someone to explain it to you - at least you feel like you don't have that time!

You are trying to juggle so many things and still meet all the deadlines, and most people can manage for a few days or weeks to keep up appearances, but eventually reality hits: you realize that you'll have to start resetting expectations, altering delivery dates, pushing milestones. Now you are starting to feel like you can catch your breath a little, as the pressure lightens up, but since you still haven't delivered anything, all you really have achieved is pushing things in front of you. The more stuff you push and the further out you push it, all the while new things are coming onto your plate, the worse and the heavier the load gets. It builds like a wave in front of you and it keeps getting heavier and heavier...

I call it "snow plow"-mode, courtesy of my Swedish heritage I guess.

Don't get stuck in the "I don't know but I don't have time to..." dilemma!

It is nothing but a vicious circle and the quicker you realise you're moving into that cycle, the quicker you can do something about it. You can "Get Help" . . .   the title of my next article.

PLEASE NOTE: The views and opinions expressed here are my own and do not necessarily reflect those of my employer.
 

When developing knowledge management systems (KMS) there exist the need to deliver the right knowledge to the right people at the right time and in the right context. Easier said than done… Right? Well, if you incorporate a sound information architecture (IA) in your design and implementation of your KMS, this will be exactly what you need to correctly facilitate the flow of knowledge.

IA connects people to their content (information & knowledge) that includes the high level rules that govern the manner in which information concepts are defined, related, realized and managed by the enterprise. The major IA components are the Content Model, Metadata Schema and Taxonomy.

A Content Model provides the framework for organizing your content so that it can be delivered and reused in a variety of innovative ways.

A Taxonomy is a hierarchical classification or framework for information retrieval. Taxonomies represent an agreed vocabulary of topics arranged around a particular theme. A taxonomy can have either a hierarchical or non-hierarchical structure. However, typically taxonomies are presented in a hierarchical fashion

Metadata is an important aspect of the IA and in particular the Content Model. Metadata is primarily used for labeling, tagging or cataloging information or structuring descriptive records. Metadata (fields and attributes) are assigned to a content type to provide a means to describe it and provide the means in which to find content once it becomes part of a KMS.

The marriage between IA and KM is really a one sided affair. A KMS needs IA to be effective, but IA is not dependent on KM. When it comes to effectively labeling, structuring and categorizing explicit knowledge types within an KMS having the right information architecture is essential. The purpose of IA for a KMS is to ensure that the right people have access to the right knowledge at the right time… and in the right context.

The knowledge we are speaking about can be either explicit and/or tacit. Explicit knowledge is formalized, codified and easily expressed in words and symbols. This is often called the know-what. Explicit knowledge can take the form of, but not limited to lessons learned, knowledge articles, FAQs, Standard Operating Procedures (SOPs), Job-Aids, and Best Practices. Explicit knowledge can be represented by any tangible asset that conveys how to do something or describes how a decision was made about something. Tacit knowledge is knowledge found within the minds of the practitioner. This can consist of intuitive know-how, experience, learnings, and practices. This knowledge is difficult to capture and is usually passed on to others through mentoring, storytelling, and other socialization methods.

A Knowledge Management System usually involves just explicit knowledge. IA does a great job in providing the infrastructure in order to capture, catalog, store, retrieve, and find explicit knowledge. However, IA plays a significant role in bringing in tacit knowledge sources within the KMS. This is done primarily through the use of expertise locators and social communities. Expertise Locators leverage IA to provide the infrastructure (metadata schema) to capture attributes about the experts with the organization and associate the expert to social communities and explicit knowledge sources within the KMS. The attributes to describe the experts can include such things as areas of expertise, educational background, projects worked on, years of experience, and research material published. Essentially anything that will help describe the expert in order for a user of the KMS to understand what the expert may know and who can contribute to making a decision or has the ability to solve a problem.

When it comes to knowledge management, IA is essential to the adoption and success of any knowledge management system implementation.

Looking at a few keynotes from one of our internal, semi-annual technical conferences, and reflecting on some of the many Microsoft and Customer stories I heard on my recent travels in Europe, it doesn’t take a lot to see how they are all converging around one thing: Digital Transformation.

There are probably as many definitions of (and opinions on) the term “Digital Transformation”, as there are leaders, influencers, bloggers…. out there. And as many definitions as there are, as many are the business problems we are trying to solve with it, and as many (multiple times many more actually) solutions are there out there. So that is exactly where it should start: with asking ourselves not only “WHAT” we need to do but even more importantly “WHY” we need to do it? Are we really solving the right problems? Are we asking the right questions? Are you? Have you really isolated the problem you are trying to solve or are you throwing a solution/process/tool/consulting team at it, to fix the symptoms? The low hanging fruits? Or have you actually asked yourself “why”, as well as asking the “what”/how/who/when/where…?

Over the last few weeks I have had a ton of conversations with Customers and Microsoft teams (who work side by side with our customers every day) and everyone is working on some kind of “Digital Transformation” project or initiative – whether it is an internal project to implement our own New World of Work – concept at our offices in Stockholm or Prague, or sitting down with a Customer who is struggling to make users adopt Skype for Business, when all their work instructions are based on phone books and phone extensions. It is all “Digital Transformation” of some sort.

I like the idea of this transformation as the Fourth Industrial Revolution as e.g. referenced by the World Economic Forum, as the theme for their 2016 Annual Meeting in Davos, Switzerland. I think it puts it in a good perspective and I think, in many cases and for most of us, we have to be prepared to support anything from Industrial Revolution 3.5 (or at the very least 3.75) to 4.25, over the next 3-5 years.

How can we do that effectively, all the while we continue to perform, in a world that transforms so fast around us, on every level, that we can barely find the share button on our screen from one day to the next? We need to Work Smarter! Yup, I know, it is a total cliché and I know more than one of my former colleagues who has smoke coming out his ears reading those words: “WORK SMARTER”.

There is no way that one person can support every type of customer problem, at any point of scale of “Digital Transformation”/Industrial Revolution 3.0/4.0 on his or her own, so the only way to keep performing is by leveraging the Collective Knowledge of our Global Organisation(s)!