The enterprise social computing scene is all about incentivizing, building and demonstrating – often with use cases – the benefits of socializing computer based activities.
Most of social computing consultant are thrilled by the possibilities offered to organisations to deliver superior results when it comes to collaboration, knowledge sharing and engagement with customers (or audience).
At the same time, and despite the positive and impressive growth in the industry, one still have to confront more traditional people, who have not had the opportunity to embrace social computing, by accident or design. The trick is that those people are the one in command, allocate budget and resources and at the end of the day make things happen … or not. This is a source of dissatisfaction for social computing consultants, evangelists and internal champions. My post that Luis Suarez kindly highlightedlast year originated from that dissatisfaction: I really had a hardwith the IT guy of a prospect company earlier that afternoon 🙂
Yesterday, while reading Patrick Lambe‘s Organising Knowledge: Taxonomies, Knowledge and Organisational Effectiveness (see Jack Vinson’s dedicated post), I stumbled upon a visual framework that helped me understand a bit further this reality.
Making sense through taxonomies: Marchand’s strategic information alignment framework.
The underlying idea in Marchand’s taxonomy is that there are four fundamental ways of creating value within IT.
In theory, IT policies are to address the four elements evolving in a sequence “manage risks” > “reduce costs” > “add value” > “create new reality”.
In reality this taxonomy displays two distinct (and often non-compatible) behaviours:
– manage risks and reduce costs
– add value and create new reality
While social computing is today clearly in the “add value, create new reality” side, most managers stick to “manage risks, reduce costs”. The ROI debate on 2.0 apps last year, right when social computing was getting attention to boardrooms, is a clear signal.
One reason is laziness, another one from Andrew McAfee is busyness and a third one is about sense-making. As Patrickwrites: “managing costs usually requires an intimate knowledge of yourinternal process and constant information flows to monitor and controlthem”. Trick is that social computing addresses knowledge activities (knowledge, not information).
1. Knowledge is immaterial;
2. Measure is only applicable to material elements;
3. Knowledge is not measurable;
4. “What you can’t measure, you can’t manage”;
5. Knowledge is not manageable;
6. Knowledge is not managed.
This is a reason why:
1. I consistently insist on reframing and enriching our metrics and reporting systems
2. There is effectively a breach in Marchand’s theoretical sequence between “reduce costs” and “add value”
3. Social computing finds it difficult to enter the organisation.
However, when you look carefully the “manage risks, reduce costs” is all about rationalisation (exploitation), while “add value, create new reality” is all about innovation (exploration).
This rationalisation / innovation divide sheds new light on the conversation few of us had some time ago around the specificities of social computing consulting and why some people like Dennis Howlett think it really differs from traditional IT consulting (to a point where traditional IT can’t make social computing consulting). The idea behind is that traditional IT consultancies are structured (organisation, competencies, offers) to service cost reduction and risk management, while social computing consultancies service value addition and new reality design.
Personally, I’m a bit more cautious: traditional IT consultancies are moguls that have bright people and room for small, hidden, yet efficient teams dealing with social computing.
In addition, Marchand’s taxonomy helps us also understand that only commoditization would help social computing move from innovation to rationalisation. The more early adopters, the more measures are accessible, the more manageable are such tools. Hence the current trend for use cases and projects containing feature description such as “facebook-like”, “youtube-like”. Great, but this “best practice” way of implementing things is good for the adoption curve, but not that good for building differentiation that fuels competitive advantage to attract new clients or new associates or improve existing online collaboration spaces.
Incidentally, we also get a sense of the major difference between social computing and cloud computing. Social computing is about creating social, computer-based environments to address specific communities of clients or teams. Cloud computing is about providing a new IT infrastructure that helps organisations rationalise their IT environment and budgets. It’s about hosting, software update and maintenance. Cloud computing can display benchmarkable figures (usually confirming cost reduction) and technical architecture that help waive risk perception, not social computing. The reason is that social computing is valuable in context (a posteriori evaluation) and impacts so many aspects of computer related work that it would require in-depth time-consuming analysis (which no one really does).
Playing with taxonomies to make things happen: Short run average cost curve and the long tail
If we want that organisations embrace social computing and as such innovation in IT that delivers both value and new ways of working and interacting with customers, there is a long list of things to be implemented, starting with a different way of managing organisations and interacting with people.
But there are simpler ways and here again taxonomies can be helpful in drafting a new way of making sense of reality.
Take two very visually similar taxonomies: the short run average cost curve and the long tail.
The short run average cost curve’s main driver is economy of scale: most of the decrease in per part cost occurs at the low end of the volume scale. Even an increase of one or two units ordered can significantly decrease per unit cost. This calls for volume strategies that favour very low diversity. The taxonomy shows it is the most efficient way of managing things both in terms of costs and risks. It is taught within every basic economy class so that it is very common to have the economy of scale in mind when managing things. This is the reason why people are happy with IT environments where everything is rationalised, where one set of tools are implemented, no matter they are locally relevant. They implement or accept the “manage risks, reduce costs” approach to IT.
This taxonomy works fine in an economy where supply dominates demands, where competition is not fierce. The trick is that this economy is the economy of the Great Mr Ford, not the one of you and me. Today’s economy is all about fierce competition, fast and radical innovation and picky consumers (and employees). This is the long tail economy!
And what does the long tail taxonomy craft as a vision of the world? Quite the opposite to the short run average cost one: “a very, very big number (the products in the Tail) multiplied by a relatively small number (the sales of each) is still equal to a very, very big number” (Chris Anderson). The taxonomy shows it is most efficient to address niche related topics. In today’s economy it’s all about managing exceptions. In fact it’s been decades that it works like that, the wild wild web only increased this reality by becoming a platform. It makes profitable what were previously unprofitable transactions.
As a consequence, maintaining the short run average cost approach today usually generates in reality diseconomies of scales. These later materialise by unsuitable IT frameworks, dissatisfied users and decrease in competitiveness and profit generation. The inflated debate (see for example Jon Husband’s) over having “Millennials” joining the organisation goes down that road.
Shifting from the short run average cost curve to the long tail one offers a different vision of the world and opens up to new understanding of creating value within IT. The value is in locally relevant IT settings that help deliver specific work. What’s important here is to support and serve employees by implementing situated IT environments that facilitates social interaction (between them, with customers), knowledge sharing and day-to-day work, but also facilitate exploration and change. That’s what we do for a living at Headshift. Given the fact that the bigger the organisation, the more entropy (complexity, peculiarity), creating value in IT today means embracing what looks like “chaos”. Big work ahead and no surprise decision makers can be cautious.
Making sense of “chaos”: Applying the long tail behind the firewall
It’s just what you define as “chaos”, because chaos is already there. Map your IT systems and have a look. It’s probably going to be worse than anticipated.
In fact, reluctant decision makers need to reframe their vision of the world and the long tail is an interesting taxonomy for that. Organising IT “chaos”, recreating coherence (organisation that makes sense – cosmos) in this long tail world implies shifting from system centricity to user centricity. Quality Management is all about that and Knowledge Management is getting down that road too (the link is the “learning organisation”), so that there is nothing new in the shift. Coherence is to be created at user level by providing him/her with a relevant set of tools so that s/he can manage exceptions, not by implementing a an organisation-wide one-size-fits-all set of tools and prohibiting situated initiatives (typical of economy of scale approach).
That’s where social computing is relevant: it helps creating user tailored content.
Wiki and blog farms, such as Confluence or Movable Type, help securing a group perspective while facilitating local implementations.
RSS servers, such as NewsGator, helps delivering the right information to the right people. This is particularly the case when users can subscribe the feeds they consider professionally relevant.
(Social) Tagging helps users reference the bits of info that are relevant to them in a way that is relevant to them. Compared with classical classification works, you save actually quite a lot of time. No need to venture into endless facet classification analysis; the facets will emerge naturally. KM people can classify information in an official (socially negotiated and organisationally specific) way. Folksonomy will help users accommodate and help KM people get a sense of which facet is dominant in reference to a specific set of information nuggets. The social functionality enables serendipity.
Social Networks help map and locate collaborators, providing both rich profiles and content associated to the person. They also may help materialise real interactions that happens to have jobs done.
Great, but so far end users still have to manage social computing tools and legacy tools. They often have to navigate in between systems via a long string of clicks or different toolbars to access all the information they need to perform properly. The result is that coherence is not complete, yet.
That’s where personalized (start) pages solutions, such as PersonAll, are helpful. In a corporate environment, they are user tailored portals where one can surface both social computing and professio
nal corporate tools (such as ERP, CRM, ECM and likes) thanks to widgets and portlets. All information is few clicks away and both worlds are unified. A user tailored portal creates personalised working environments where information flows (via notifications) seat behind more traditional / corporate tools. This creates more meaningful and efficient working environments, without perturbing legacy systems, but fostering knowledge worker productivity. The coherence of the IT environment is recreated, but gives room and flexibility for adding tools … and not insulting the future.
So don’t hesitate to play with taxonomies if the road toward adding value through social computing is blocked. In the great majority of cases, people need new maps to navigate into new seas. The shift between the short run average cost curve and the long tail is only one example.