Experiment, Adopt, Achieve On Innovation in Software Engineering

2Apr/100

Successful Innovation

This is an academic essay written for my Msc in Management at Birkbeck University, London.


Why some enterprises become successful innovators
and why others do not.
by Mark Gibaud

Today's organisations have to take into account a number of different aspects when attempting to deepen their capacity for, and evolve capabilities facilitating, innovation. Distilling the most relevant academic literature results in several organisational capabilities that must underpin several distinct phases of innovation if the firm is to achieve sustainable economic rents and ongoing growth from it's efforts in this direction. These capabilities are separated broadly into those supporting the identification of potentially lucrative innovations and those that support the exploitation of those innovations along lines that maximize their opportunity for profit. This essay will attempt to enumerate the most important of these capabilities together with said phases and summarise the operational details of each giving examples where possible.

Mastering innovation requires mature capabilities in several phases identified by Professor Joe Tidd (2005). The first of these are concerned with searching or scanning the environment for "signals" (Tidd 2005) that indicate an opportunity for innovation. These could form new technological advances in the market place; for example, the success of the iPhone presents many brands with a more compelling opportunity than ever before to represent themselves on a mobile platform. Signals could also be changes in legislation or changing behaviour in a competitor (who perhaps themselves are reacting to signals). Signals can also appear simply "in the wild", an example being on the Facebook page of Contiki Holidays (http://www.facebook.com/contiki), where users are indicating a strong desire to make contact with other travellers sharing their specific tour departure. Successfully innovating organisations have developed sophisticated methods for continuously capturing signals from a broad range of sources.

While signals might originate from outside the firm, the opportunities for innovation that they represent might not be immediately obvious. The right information in the right place at the right time can spark a profitable innovation that would otherwise delay coming to market if at all. Organisations naturally amplify knowledge through the efforts of their workers collaborating on projects (Nonaka & Takeuchi 1995), and firms should put resources and practices in place that support capturing and codifying what would otherwise remain less accessible but valuable tacit knowledge (Polanyi 1966). Referencing Knowledge Management best practices, creating a knowledge repository with an emphasis on collaboration, such as an enterprise wiki solution or groupware, broadens the reach of the sum of organisational knowledge and can quickly become a breeding ground of innovative ideas, evolving from signals captured from outside the firm. The paper and packaging group Mondi have a web-based system named the "Innovation Zone" through which employees can share and improve ideas (Koudal 2005). A dedicated team evaluates especially innovative ideas and creates plans to develop them further. In this way Mondi managers can enable the entire company to contribute to it's innovation efforts, with a team possessing the required authority and resources to facilitate the commercialization of ideas into new products or processes.

If an organisation is successful in it's search for and processing of innovation signals, it may well identify more opportunities than it can realistically afford to commit to. Thus, selection of the correct opportunities is critical to maximising return on investment in innovation efforts. It quickly becomes apparent that successful innovation is an interactive process between what the organisation can supply as per it's technological competences (technology push) and the demand it may identify from signals in the market (customer pull) (Tidd et al 2001). The organisation should select opportunities that are likely good answers to one or more marketplace questions, achievable in terms of it's current capabilities (though a little stretching of current capabilities is desirable, as this presents the opportunity for learning), and finally, well aligned with the broader strategy of the business. A mark of a successfully innovating firm is a mature mechanism for the "coupling and matching process" (Tidd 2005) of innovation supply and demand. A secondary point here is the implication that an organisation should be constantly deepening it's technological capabilities as this will result in the potential for diversification and thus more opportunities to map supply to demand regarding innovation efforts.

Following from actually preparing the market (this could be advertising for a new product or evangelising for a new process), successfully launching an innovation should be accompanied by mechanisms by which feedback can be both gained and acted upon rapidly. Customer feedback on products and services, especially those characterised by higher novelty and frequent change such as fashion and high technology, has become an especially valuable source of 'sustaining' innovation (ie. incremental improvements) (Christensen 1997). Efforts in this area range from the more loosely connected, such as the ever popular anonymous feedback forms, to a much more tightly integrated collaboration with "lead users" (Von Hippel 1986) that steer ongoing incremental improvements to existing products or services as they typically experience needs before more mainstream users. To pick an example from midway along this continuum, Zara store staff are equipped with PDA's and are able to gather information from browsing customers about what more they would like to see in store, like existing designs in different formats or colours. Once the store doors close, information is also gathered from the shelves that are more depleted than others and the stock of clothes that customers tried on but didn't buy. All this data is linked up to the point of sale system which allows branches to issue re-buy orders based on hard data instead of hunches and guesswork. The qualitative data gained by the PDA users makes its way back to Inditex  (Zara's parent company) headquarters in La Coruña, Spain, where the hundreds of designers employed there are tasked to respond to the data in designing their future products. Innovations like these have spurred Inditex to grow from $2.43 billion in 2001 to $13.6 billion in 2007 (Gallaugher 2010) and fueled massive global expansion, opening hundreds of new stores around the world. Inditex's ability to continuously launch new products and then refine them rapidly using customer feedback has paid dividends.

Finally, it is recommended that after an innovation is successfully brought to it's target, the firm retrospects on the entire development process and draws lessons that may be used in future innovation efforts (Tidd 2005). Furthermore, management is compelled to create new processes and routines around lessons learnt such that the organisation can form new behaviours that eventually make innovation-inducing practices the new norm. But what gives firms the ability to carry out the Tidd's phases of innovation successfully?

Successfully innovating companies put full time resources behind innovation endeavors (Koudal 2005). Whether individual employees are tasked with a few weeks of dedicated research and experimentation, new middle management teams are created with innovation-centric remits, or perhaps entire departments spun off as new innovation-chasing entities, organisations are learning that they can no longer concern themselves with sustaining the status quo and flirting with the odd idea on the side. Following the examples of 3M and Google, more and more companies are formally dedicating a percentage of their employees time to innovation to better incentivise ideation. This practice leverages the growing agreement that "front-line staff" are in the best position to generate ideas (Poppendieck & Poppendieck 2006, Mesaglio 2010) since usually they are regularly exposed to the customer and have most of the information available with which they might think of a better or entirely novel way to satisfy customers' needs. Van de Ven (1999) suggests that employees be given sufficient time to experiment with new ways of doing the work, while Tidd (2005) recommends that employees have the opportunity to work cross-functionally. A compelling method for gaining new organisational resources for innovation is put forward by Geoffrey Moore in his book Dealing with Darwin: that of "extracting resources from context to repurpose for core" (Moore 2006). Moore defines context as the efforts of the organisation concerned with continuing to provide existent products and services to customers, whereas core is the effort behind new products and services which seek to further differentiate the organisation. Moore investigates how the networking infrastructure products company Cisco goes about extracting resources from existing operations to apply to new ventures, enabling them to innovate on their own products but also quickly regain parity with any products from competitors who attempt to disrupt Cisco's market. Moore suggests that firms perform a "context/core analysis" followed by a resource allocation strategy that complements this analysis with the goal of setting a path to a more innovative future. It is clear that successfully innovating companies both allocate sufficient resources to innovation and also make it easier to do so by innovatively driving down the resource cost of day-to-day overhead.

Clayton Christensen articulates another innovation management question to be answered: The Innovator's Dilemma. In his 1997 book of the same name, Christensen discusses the question facing every innovating organisation: What is the most beneficial distribution of resources between sustaining or incremental innovation efforts and efforts behind disruptive or radical innovation? Essentially, organisations need to develop an "ambidextrous capability" (Tidd 2005) that allows them to effectively pursue both courses of innovation, with considerable allowance made for their different risk/reward profiles, the different paths they follow and the different "innovation architectures" (Tidd et al 2001) they require. While it's likely that sustaining innovations can be facilitated by relatively established routines, disruptive innovations will require innovation management that is highly flexible, tolerant of ambiguity and uncertainty, and seeks to hedge risk by limiting commitment (Tidd 2005).

In a discussion of how enterprises become successful innovators it is also prudent to discuss how enterprises might stay successful innovators. Mastering the complexity in their value-chain and innovation capabilties has gained successfully innovating firms the ability to sustain their competitive advantage as their operations and infrastructure is characterised by several attributes evident in the resource-based view of the firm (Wernerfelt 1984, Penrose & Pitelis 2009). Firm resources can include highly-skilled personnel, valuable branding, intellectual property rights, an advanced ICT infrastructure, and even customer loyalty (Wernerfelt 1984).  Possibly the most compelling attribute is that their operational configuration and infrastructure is difficult to imitate. Referring back to the example of Inditex, other fashion organisations may attempt to copy their infrastructure wholesale but this is a high risk strategy since Inditex regards people (specifically, the store managers and designers) as key resources. These employees are empowered to make decisions that drive Zara's rapid response to customer trends in fashion. Also present in successfully innovating firms is a managerial capability required to achieve rewarding innovations in the first place, and these managers are supported by a corporate culture that allows them to do their best work. Perhaps the best example is that of Jonothan Ive, who joined Apple in 1992, became VP of Industrial Design in 1998 and Senior VP of Design in 2005, and has been the main proponent in the design (and thus success) of the PowerBook G4, the Macbook, the unibody Macbook Pro, the iPod, iPhone and now the iPad. Apple doing their best to retain Jonothan and his team is a major contributor to Apple's ongoing successful innovation. Finally, it is worth remembering that no firm is an open book, and there are likely many more innovative processes and practices at work inside Inditex and Apple that have not found their way to the public domain but are central to sustaining each their competitive edge. This is the idea of 'causal ambiguity' (King 2007) and it represents a major problem for imitators in that they cannot exactly articulate how Inditex, Apple, etc remain successful innovators. Indeed, Tidd asserts (2005) that any successful "innovation management routines" are difficult to copy simply because they represent the accumulation of a long line of lessons learnt along the way. This essentially means that firms should seek to forge their own learning path to successful innovation and avoid the temptation to copy "fashions" if they are to sustain their competitive edge through successful innovation management.

There is no sure way to guarantee value-creating, growth-inducing innovation. Ultimately, to 'manage innovation' is to establish the resources and develop the capabilities to merely increase the chances, radically or less so according to the skill of management, that successful innovation will flow from the organisation. Organisations must evolve capabilities to scan the marketplace for signals, select high-potential ideas, resource and manage their execution effectively, quickly gain and react to customer feedback, and in the final stages, retrospect on the initiative and learn as much as possible regardless of success or failure. In parallel, firms must constantly broaden their resources for knowledge management, cross-functional communication and collaboration of employees, effective collaboration with customers, suppliers and partners, and leverage advanced ICT infrastructures to support all of the above. This represents a major challenge for organisations, but one that cannot be ignored, because to ignore the challenge of innovating successfully is to doom the organisation to disruption by another and eventual extinction.

References:

Christensen, C.M., 1997. The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail illustrated edition., Harvard Business School Press.

Gallaugher, John., Information Systems: A Manager's Guide To Harnessing Technology. Retrieved Mar 19, 2010 from http://www.flatworldknowledge.com/node/41126 .

King, A., 2007. Disentangling Inter-and Intra-Firm Causal Ambiguity: A Conceptual Model of Causal Ambiguity and Sustainable Competitive Advantage. Academy of Management Review, 32(1), 156–178.

Koudal, P., 2005. Mastering Innovation–Exploiting Ideas for Profitable Growth. Deloitte research.

Mesaglio, Mary., IT-Enabled Innovation, lecture given at Travel Corporation luncheon, Rubens Hotel, London. 24th March 2010.

Moore, G., 2006. Dealing with Darwin: How Great Companies Innovate at Every Phase of Their Evolution, Capstone.

Nonaka, I.A. & Takeuchi, H.A., 1995. The knowledge-creating company: How Japanese companies create the dynamics of innovation, Oxford university press.

Penrose, E. & Pitelis, C., 2009. The Theory of the Growth of the Firm 4th ed., Oxford University Press, USA.

Polanyi, M., 1966. The tacit dimension. New York.

Poppendieck, M. & Poppendieck, T., 2006. Implementing Lean Software Development: From Concept to Cash (The Addison-Wesley Signature Series), Addison-Wesley Professional.

Tidd, J., Bessant, J. & Pavitt, K., 2001. Managing Innovation: Integrating Technological, Market, and Organizational Change, 2nd Edition 2nd ed., John Wiley & Sons.

Van de Ven, A.H. et al., 1999. The innovation journey, Oxford University Press New York.

Von Hippel, E., 1986. Lead users: A source of novel product concepts. Management science, 32(7), 791–805.

Wernerfelt, B., 1984. A Resource-Based View of the Firm. Strategic Management Journal, 5(2), 171-180.

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15Feb/100

Fostering Innovation: Repurposing Context for Core

I’ve just finished reading Geoffrey Moore’s Dealing with Darwin and while there is a fair amount of content that, as far as I can see, doesn’t necessarily reflect a lot of what is to be found in the academic literature regarding innovation, there is one very important concept tackled that is at the heart of firms’ ongoing desire to actually benefit from innovation initiatives undertaken. This is the concept of “repurposing context for core”.

Context is that required effort to “keep this thing going”. It’s the overhead involved in keeping already existing services and products getting to market. Most obviously it’s the Operations department in most service organisations and the Marketing and Sales department in product organisations. But it’s also everything that supports those departments: Finance, HR, IT, etc. 

Moore talks about the organisational inertia created when increasingly more resources are invested in context than in core. Although he says inertia is not the enemy of innovation (since the inertia of the previous innovation allowed the firm to stay it’s course), it does resist things at the point of change. It is at this point where executive management needs to pay special attention to be able to deconstruct organisational inertia and repurpose the resources it consumes in favour of more innovative undertakings. To this end, companies create new departments with the aim of completely freeing them up from context. Sometimes they go a step further and create an entirely new spinoff company. Read Meeting the Challenge of Dispruptive Change by Christenson and Overdorf for more.

On the other hand, core “is that which differentiates your company to create sustainable competitive advantage”. Moore indicates that while context might outweigh core by organisational resource allocation, but core outweighs context in strategic importance. Putting resources into context pays off next quarter; putting resources into core pays off next year and hopefully for the next few years.

This whole situation can be applied to a software development team as well. We are constantly looking to “repurpose context for core” (or at least reducing the effort and attention required by context) by automating testing, automating deployments, reducing process friction, refactoring to a more agile codebase and reducing wasted effort like not building the right thing or the thing right. Doing these things successfully buys us the ability to spend more time and attention focusing on things that can increasingly set us apart from the mediocre, like better usability and quicker response time to market of newly developed features and products. Of course it is common to find that driving down the effort required by overhead is often done “to make life easier” or to “cut out mistakes” rather than with the explicit goal of freeing up resources to focus on differentiation.

I think it is a compelling argument to begin using time gained by doing things in better ways, to doing things that differentiate your product or service.

 

“There is no new technology in the iPod.”

- Geoffrey Moore

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7Feb/100

Five Goals for 2010

new-years-money-goalsWith January safely put to bed, and with it the threat of making goals that get taken less seriously and have not much chance of survival, I thought I’d blog five sufficiently woolly (read achievable) goals for myself, with the aim of retrospecting come December 2010.

 

  1. Write more: They say writing is a muscle, and I intend to train that muscle more this year. I intend to blog both here and (more frequently) my work team blog to practice writing coherent, readable and perhaps even interesting content.
  2. Read more: I was never really a reader until a few years ago but since moving to London where books are a lot more affordable (vs South Africa), it seems counter-intuitive not to make good use of Amazon. Also very compelling but ‘recent’ is  the utterly trivial effort one has to put in to access the top 1% of any particular topic making it so easy to read only the best rated stuff. I am hoping that my Msc will only keep me down to 1 book every month or so.
  3. Pick an interesting dissertation subject and start on the research: At the moment I’m thinking about doing something related to Evidence-based Management. Starting a dissertation in the first year of a two-year Msc is ahead of schedule though so this strikes me as a good goal to have.
  4. Health and Fitness: Last summer I was going pretty well with sport and gym until I tore my calf muscle playing a tough game of squash. The 3 month layoff after that made me lazy and the Winter has delayed any real come back. This year I want to regain that fitness and stay injury free.
  5. Learn more French: I have done some basic courses but I want to attain the next level in the summer with another course. In a few years when I have more time for different things I plan to become conversational, but I’m happy to limit it to 1 step towards that this year.

 

Well that wasn’t so hard. I guess the hard part is sticking to them! Let’s return in 11 months time to see how I’ve done.

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15Dec/090

On the Nature of Knowledge, Public and Private

The following is an academic essay prepared for my Msc in Managment at Birkbeck University.

[Update: This essay received 70%]


The Nature of Knowledge as an Economic Good, Public and Private
by Mark Gibaud

In the 19th century industrialist society, the capacity to generate wealth was inextricably linked to physical property rights. This means that wealth generation was implicitly excludable. In the new intellectually-powered economy knowledge is the source of wealth but must be afforded a special mechanism of protection since new knowledge is expensive to create but often (though not always) easier and cheaper to imitate. It is in society's interest to reward these creators of new knowledge so as to incentivise their ongoing efforts such that new knowledge is continually created. However, society also benefits when knowledge is freely diffused, disseminated and leveraged as shown by the Open Source Software movement. This dilemma has given rise to the debate of knowledge being an economic good, but should it be public or private, or both? This essay attempts to answer this question by further analysing the nature of both public knowledge and private knowledge and qualifies the role of intellectual property rights (IPRs). A deeper analyses the nature of the relationship between public and private knowledge is followed by the policy implications suggested by that relationship.

A 'pure' public good by definition is non-excludable. That is, one's consumption of it does not prohibit another's ability to also enjoy it. Also, it is non-rival, meaning, as more people enjoy it, there is no reduction in supply which may cause others to go without it (public goods exhibiting only one of these characteristics are not noted as 'pure' public goods) (Kaul and Mendoza 2003). Air, for breathing, is an example of a pure public good in that it is neither excludable nor rival, since my breathing the air does not leave less of it for you, nor can I do very much to prohibit you from enjoying it. Though there are kinds of knowledge that do not have these characteristics, the majority of scientific knowledge (including economics and the social sciences) does enjoy these characteristics and is thus a prime public good. Public knowledge generally refers to knowledge coming from academics and researchers in universities, but can also include industry 'best practices' like Total Quality Management or Capability Maturity Model Integration (Matusik 2002). Private knowledge on the other hand is knowledge unique to particular firms and can be wrapped up inside company policies and processes (for eg. Google's "20% time"), and also embodied in services and products (Nelson 1992). Keith Pavitt argues compellingly for the distinction between science and technology, where technology "ecompass[es] both physical artefacts themselves, and the person-embodied knowledge to develop, operate and improve them." (Pavitt 1987). However, the real-world actualisation of that distinction is slightly more difficult to locate. For instance, two researchers may be performing the same basic undertaking of research into a particular topic or field, but one might be working at Google Research and the other at Stanford University (Nelson (1992) makes a similar observation of engineers engaged in research at IBM, AT&T and DuPont at that time). The university researcher is motivated to publish his research and contribute to the stock of knowledge, while the Google researcher is bound to keeping the results of his research private, and allow Google to benefit from the Schumpeterian rents associated with leveraging private knowledge (Nelson 1992). This is done either through patents, in which case the knowledge is public but protected, or through secrecy, by which the knowledge stock is left bereft of the Google researcher's new knowledge altogether (Nelson 1992). This is the distinction between science and technology implicitly proposed by the economists Sir Partha Dasgupta and Paul David when they argued that science contributes to the stock of knowledge, while technology does not (Dasgupta & David 1985). Finally, Dasgupta and David also reason (1985) that science produces knowledge that is more "general and fundamental" in nature and lacking in "immediate practical applicability" than what technological research tends to pursue. A distinction then, not so much of nature, but of goals, and a distinction that is illuminating when considering what direction public policy should take.

We have established that knowledge can be a public good. The fact that it is non-excludable and non-rival, means that it is effectively free, and no profit can thus be generated from public knowledge in and of itself (transmission costs of knowledge is a separate issue). This in turns means that there is no financial incentive to contribute to the stock of public knowledge. Thus, if left to the open market, any contribution will likely not occur and lead to a "tragedy of knowledge", where players might deplete the stock of knowledge (as it is still profitable to embed and evolve ideas from public knowledge into private products) without any replenishment of new knowledge into that stock taking place (David 2001). For an analogy, the same problem affects pollution, where no one company will curb its carbon emissions as it then puts itself at a disadvantage with competing companies in terms of manufacturing output. In matters like these, it is a compelling argument for the state to get involved, as can be seen by the recent lobbying activity in Copenhagen recently for climate change. As knowledge itself is an input to new knowledge (Stiglitz 1999, David 2001), this public good is critical to fostering ongoing innovation, and thus it is imperative that the state facilitate the cultivation of knowledge as a public good, as it does with other public goods. But the state does not directly incentivise this creation process. Rather, academia centres around a compelling code of conduct relating to publication, scientific priority and reputation building. Scientific priority is the phenomenon whereby fame and recognition is accorded to that discoverer who published his discovery first, irrespective of whether one or more other researchers made the same discovery independently at the same or similar times. In Robert K Merton's seminal discussion of scientific priority  (1957), he tells of some fierce battles of priority such as Galileo who, in The Assayer, "flayed four other would be rivals" in aid of protecting his discoveries. Notwithstanding with this winner-takes-all approach for scientific discoveries, a steady building of reputation is also very important to scientific researchers. Charles Darwin, the first to develop the theory of evolution through natural selection, is quoted as saying "My love of natural science . . . has been much aided by the ambition to be esteemed by my fellow naturalists." (Barlow 1958). It would appear that the state only has to facilitate this self-promotion of the academic community in order to safeguard a continual contribution to the public stock of knowledge.

Knowledge can also be a private good. Successful companies seek to employ effective strategies to cultivate the generation, capture and dissemination (Nonaka and Takeuchi 1995, Senge 1991) of their private knowledge as this contributes directly to an organisation's competitive advantage (Teece 2000) and is key to providing new products and services (Kessels 2001). Nelson (1992) pointed out that firms make use of intellectual property rights (mainly patenting) and secrecy to pursue profit from their organisational private knowledge. But Mansfield (1985) found that secrecy is often not very effective. He noted after studying 100 American firms that "information concerning the detailed nature and operation of a new product or process generally leaks out within about one year". The argument that the state must safeguard some kind of reward for innovators and their product and process breakthroughs is unassailable, though precisely how and what is the subject of increasing debate. Still dominant in these times though, is the patenting system.

The patenting system intends to encourage innovation and technological breakthrough by firstly creating a temporary monopoly for the inventor or inventors such that they are rewarded for their efforts, and secondly by requiring disclosure of the knowledge that led to the new product or process, such that that knowledge may be diffused to the benefit of wider society (Griliches 1990). It asserts that firms will not invest in innovation activities if they cannot reasonably expect profits to be generated from innovative breakthroughs. If imitators should come into possession of knowledge that innovative firms have invested heavily to develop, these "free-riders" will negatively affect the motivation of firms to invest in innovation (Gault and Von Hippel 2009). It is argued that any abolition of IPRs risks a "tragedy of knowledge", as it might benefit society at the present, since their would be an influx of new knowledge that may well be leveraged usefully. However, without any legal monopoly afforded by IPRs, there would no longer be a strong incentive to engage in expensive research and development and the creation of new knowledge would ebb away, leaving us at a relative standstill before long. Attention must be drawn, however, to the alternatives presented by, among others, Paul David (2001) such as "fair use" exclusions to the public research sector, and "compulsory licensing" which would enable the inventor to be rewarded but also society to benefit from the diffusion of the innovation. Gault and Von Hippel (2009) also cite government R&D subsidies and tax credits as helpful mechanisms to "lower innovator's private costs" and go on to point out the Open Source Software phenomenon, where source code contributors act under agreement to engage in 'free-revealing' of their privately-generated knowledge in an effort to build reputations in their communities which would in turn lead to more income-generating opportunities for both that individual and their full-time employer. Products and processes that are subject to free-revealing also generate valuable feedback from the wider community so that a company might improve that product or process improving its quality and thus potentially improving profitability. De Jong and von Hippel (2009) also present 'free-revealing' to have similarly rewarded innovation in the process equipment industry for high-tech SME's in Holland. It is clear that there is increasing innovation in reward systems for inventiveness and the current debate in IPR circles may well begin a steady journey towards revolutionizing the system.

Leonard-Barton asserts that "few if any companies can build capabilities without importing knowledge from outside its boundaries" (Leonard-Barton 1992). Remembering that firms on the whole seek to retain their own private knowledge, any company wanting to begin to deepen its capability has only one recourse: the public stock of knowledge. It can thus be said that in this aspect, private enterprise depends both initially and continually on the 'communal well' of public knowledge. In addition to the broadly applicable research that is generated in public academia, Nelson (1986) and Levitt et al (1984) found that across a wide range of sectors, there exists a dependency on the public academic infrastructure itself, in that the private sector directly values the training and research-orientated skills acquisition of future industrial researchers, as well as the academic "hive-mind" they bring with them in the form of a network of academic colleagues. It would appear that the nature of the public-private knowledge relationship is largely one of public creation and private consumption. Furthermore, it seems that there is no real risk of a confusion in roles as the institutions are, as discussed earlier, geared towards fundamentally different goals and outputs. Although he notes computer programs (Google Search started life as a university research project) and biotechnology products as exceptions, Nelson (1992) suggests that, "in most fields of technology what gives advantage to a company is a particular manifestation of a generic technology that is tailored to its own circumstance, products and processes." Although de Solla Price (1965) sums up the intent by stating that "scientists are highly motivated to publish but not to read, whereas technologists read assiduously but are not motivated to publish", it must be said that companies occasionally do also publish papers that contribute to public knowledge (Hicks et al. 1996).

Paul David tells us (2001) that the public good nature of public knowledge asserts that the free market cannot responsibly price that commodity such to align with the maximum benefit to society. Thus, the state has to engage in "public patronage for fundamental, exploratory research". This is a noble endeavour but one that subject to fiscal pressure on an ongoing basis, since any 'oversupply' of public knowledge could be wasteful in terms of taxpayer's money. On the other hand, the state must also govern the innovation-reward institution with an even hand. If governments overstate the benefit of innovation to private companies, the scales will tip in favour of turning public knowledge into private profits and we could advance the journey toward a "tragedy of the public knowledge commons". Furthermore, governments would be well advised to pay close attention to the research uncovering new ways by which innovators and inventors could be rewarded, but in addition, downstream innovation is further infused than it is currently, under the contemporary IPR system.

Conclusion:
In summary, given that the over-arching goal is the betterment of society generally, through the continual upgrading of existing, and the invention of new technology, it would appear that a public-private partnership where researchers and academics "push" knowledge of a more fundamental nature and of more general applicability to the stock of public knowledge, and in turn the private sector be incentivised to "pull" from this common stock, perhaps adding it to their internal research (which is of a more focused and specified nature) to then internally develop products which embed the science into new technology, this societal goal is served the best. Consequently, public policy needs to centre around maintaining this balance. By way of simple analogy, it falls to the state to ensure that the tree of knowledge is adequately watered, such that its trunk and branches, the public knowledge, may support the growing of new leaves of private knowledge to the benefit of society at large.



References:



Barlow, N., 1958. The Autobiography of Charles Darwin. London: Collins, 119–120.

Dasgupta, P. et al., 1997. On Institutions that Produce and Disseminate Knowledge. Fondazione Eni Enrico Mattei, Nota di lavoro, 68.

Dasgupta, P. & David, P., 1985. Information Disclosure and the Economics of Science and Technology, C.E.P.R. Discussion Papers. Available at: http://ideas.repec.org/p/cpr/ceprdp/73.html [Accessed November 22, 2009].

David, P.A., 2001. A tragedy of the public knowledge ‘commons’? Global science, intellectual property and the digital technology boomerang. Research Memoranda, 3.

Debackere, K., Clarysse, B. & Rappa, M.A., 1994. Science and industry: a theory of networks and paradigms.

Gault, F. & Hippel, E.A.V., 2009. The Prevalence of User Innovation and Free Innovation Transfers: Implications for Statistical Indicators and Innovation Policy. SSRN eLibrary. Available at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1337232 [Accessed December 15, 2009].

Griliches, Z., 1990. Patent Statistics as Economic Indicators: A Survey. Journal of Economic Literature, 28(4), 1661-1707.

Hicks, D.M., Isard, P.A. & Martin, B.R., 1996. A morphology of Japanese and European corporate research networks. Research Policy, 25(3), 359-378.

de Jong, J. & Hippel, E.A.V., 2009. Free Transfer of User-Developed Process Innovations to Producers: A typical behavior among Dutch High-Tech SMEs. Forthcoming.

Kaul, I. & Mendoza, R.U., 2003. Advancing the concept of public goods. Providing global public goods: Managing globalization, 78.

Leonard-Barton, D., 1992. Core capabilities and core rigidities: A paradox in managing new product development. Strategic management journal, 111–125.

Mansfield, E., 1985. How Rapidly Does New Industrial Technology Leak Out? The Journal of Industrial Economics, 34(2), 217-223.

Nelson, R.R., 1992. What is ‘commercial’and what is ‘public’about technology, and what should be. Technology and the Wealth of Nations, 57–71.

Pavitt, K., 1987. On the nature of technology. University of Sussex.

Matusik. S., 2002. An Empirical Investigation of Firm Public and Private Knowledge. Strategic Management Journal, 23(5), 457-467.

Senge, P.M., 1993. The Fifth Discipline: Art and Practice of the Learning Organization New edition., Random House Business Books.

Stephan, P.E. & Audretsch, D.B., 2000. The economics of science and innovation, Edward Elgar Publishing.

Stiglitz, J.E., 1999. Knowledge as a global public good. Global Public Goods: International cooperation in the 21st century, 308–25.

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5Dec/090

Knowledge Management Essay

The following is an academic essay on Knowledge Management prepared for my Msc in Management at Birkbeck University, London.

[Updated 15 Dec with final version]

Organisational Knowledge as One of the Core Assets of our Time:

Implications for Management

by Mark Gibaud

Knowledge is one of the key assets of the intellectually-powered "new" economy. Organisations can achieve critical competitive differentiation if they learn to leverage the collective and cumulative knowledge of their employees. Starting earnestly in the mid 90's, Knowledge Management (KM) has emerged as the key discipline to support this endeavour, but many organisations have not yet fully recognised the benefits of managing their knowledge due to a poor understanding of the nature of workplace knowledge itself and how to effectively manage its capture, storage and distribution within the organisation. This essay aims to explore the implications for management by illuminating the nature of knowledge in the workplace, how it is generated and how to further amplify its generation such that an organisation can be in a better position to capture and diffuse it. Also highlighted are the compelling reasons as to why knowledge should be managed. Finally, one leading strategy, of moving from "channels" to "platforms", is more fully explored through the analysis of a new type of "wiki" software.

Knowledge is defined by the Oxford English Dictionary as "expertise and skills acquired by a person through experience or education". One might think that simply by extending this definition to include the situational context of the workplace, one can then arrive at an accurate assessment of organisational knowledge. However, this is only a part of the story. Organisations amplify knowledge in a number of ways from the cumulative efforts of its staff (Nonaka 1994), potentially creating a knowledge repository contributed to and in turn leveraged by all employees. Michael Polyani popularised the nature of tacit or implicit knowledge which is embodied in an individual and not easily codified or transferred (Polanyi 1966). Later, Ikujiro Nonaka focused on the distinction between tacit knowledge and explicit knowledge, which can be written down and transferred (Ikujiro & Takeuchi 1991). Polyani also argued (1966:55) that all knowledge is either tacit or rooted in tacit knowledge.  Pairing this observation with the fact that the world is full of visible codified knowledge, it follows that tacit knowledge could be further broken down into that which is codifiable, albeit with more intensive effort and management, and that which remains uncodifiable, such as intuition gained from experience, vis-à-vis Polanyi's "We can know more than we can tell". Organisations have historically exhibited a high level of explicit knowledge codification such as operational manuals, process documentation and annual financial reports. However, it is the generation, codification and dissemination of knowledge further along the knowledge continuum (Leonard & Sensiper 1999) (that is, increasingly tacit knowledge) that represents the major challenge for contemporary organisations and thus becomes the primary opportunity for knowledge management solutions (Twentyman 2006) (see diagram 1). In turn, the term "Knowledge Management" has many definitions. The common elements of the most-cited definitions centre around defining a strategy for creating, capturing, storing, accessing, and distributing knowledge across individuals, teams and the entire organisation (and sometimes even outside it) in an effort to generate value (increased skill in employees, more innovative products or services, etc) from an organisation's knowledge-based assets (Stankosky 2005, Davenport et al. 2008, O'dell & Grayson 1998, Rumizen 2001, Brooking 1998).
Nonaka, through the development of his SECI model (Nonaka 1994), argued that organisational knowledge can take on a self-generative nature when knowledge is transferred between tacit and tacit, tacit and explicit, and explicit and explicit states. He argued, after closely studying Japanese firms, that organisational knowledge takes on a "spiral" nature when transferring between these states, inferring that this "knowledge conversion" process serves to continually increase the organisation's total stock of knowledge as learning becomes embedded in the organisation's culture. A deeper analysis of Nonaka's SECI model is beyond the scope of this essay, but the key implication for management is that in order to create a useful knowledge base from which employees may leverage value, an organisation must first take the necessary steps to begin to support and facilitate the generation of that knowledge.
Another useful lens through which to define knowledge is with reference to the Knowledge Hierarchy (Zeleny & von Hayek 1980) or DIKW (Data to Information to Knowledge to Wisdom) taxonomy, if only to assert that while an organisation might record data and make sense of that data turning it to information, gaining knowledge from that information is indeed the next level entirely. Consider when Google asked users in a survey whether they would prefer more search results per page (Millis 2006). Users responded that "more is better", so Google lengthened the results from 10 to 30 for some users. However, it turned out that the extra half-second that the page took to load drastically decreased user satisfaction such that users conducted fewer searches. Google took the data from the initial survey, turned it to information (a recommendation to provide more search results per page and thereby increase user satisfaction) but then, only after going forward with an experiment, did Google gain the knowledge that users actually far preferred faster load times than more results per page. The lesson here is that the management of knowledge, is very different to the management of mere data and information.
Much reference is also made to the dynamic nature of organisational knowledge (McInerney 2002), in that it is constantly being updated, upgraded and refreshed, and should be regarded and managed as a living entity rather than a static artifact.  Davenport & Prusak argue that knowledge is not only bound to "documents and repositories" but also "routines, processes, practices and norms" (Davenport & Prusak 2000). Knowledge is produced, captured and transferred in many ways, from formal mentoring arrangements, apprenticeships and training programs to informal workplace discussions. Since these workplace practices occur on an ongoing basis, it is imperative that any KM strategy and/or solution needs to facilitate the consistent and continual upgrading and improving of the organisation's knowledge.
There is broad and growing consensus that the strategic management of knowledge assets contributes directly to an organisation's competitive advantage (Teece 2000) and is key to providing new products and services (Kessels 2001). On the other hand, neglecting this need leads to organisations suffering redundancy in effort and repeating past mistakes (Garfield 2007). International Data Corporation, a technology research group, reported that a poor capability to manage knowledge cost the Fortune 500 $12 billion per year (Stewart 2001, cited by McInerney 2002). But knowledge cannot be bought in and of itself; rather, it has to be cultivated in-house (Teece 2000) before any opportunity to embed it into new products or services can be fully exploited. The more salient knowledge an organisation has, and the more accessible it is, the more opportunities employees will find to leverage that knowledge in the innovation of new products and services. This will not only  decrease time-to-market and increase quality, but also expand the potential for future improvements to said products and services. It would appear that executives can no longer afford to lack a strategy for managing the collective of their employees' knowledge.
There are many opportunities to both capture and diffuse knowledge already present in most organisations. Any design, development or engineering of a product is fundamentally a knowledge creation process, and the lessons of bringing a product to market are invariably valuable to future efforts (M. Poppendieck & T. Poppendieck 2006). Davenport and Prusak, in their book "Working Knowledge: How Organisations Manage What They Know", highlight the value of interpersonal communication when facilitating knowledge transfer (Davenport & Prusak 2000). Time should be allotted, they argue, to allow staff members to engage in spontaneous conversations, organised group KT (knowledge transfer) sessions, demonstrations, presentations and experience reports, and the idea of "productivity" should be broadened to include these activities. Swap et al. suggest (2001) that storytelling and mentoring are also powerful ways to diffuse knowledge if well managed, and highly recommend the practice of joint-problem solving involving a senior and junior practitioner (Leonard & Swap 2004). A good example of this is in the software development industry where two programmers engage in "pair programming" (Williams & Kessler 2002). Two programmers sit at one computer, taking turns to command the keyboard and mouse while the other reviews the code as it is written. The result is a higher quality piece of work, and a good deal of knowledge transfer between the programmers involved. Peter Senge also advocates creating learning situations (Senge 1993). In his book "The Fifth Discipline", he champions the creation of a "learning organisation" through five key disciplines including "team learning" through dialogue and group discussion. It is clear that there is already a wealth of key opportunities for the capturing of knowledge in the workplace, but the key is to institutionalise the culture of knowledge capture and sharing. Workers should not feel harried or rushed; rather, they must have the opportunity to constantly reflect and analyse how practices and processes might be improved (Garvin 2003). Projects should end with (or be punctuated by) "retrospectives" or "post-mortems" where questions such as "What did we do right?", "What did we do wrong?" and "How can we improve?" are asked and provoke discussion in their answers (Derby et al. 2006). Another key aspect to evolving towards a culture that facilitates KM is the breaking down of boundaries and isolated teams and individuals. Along with the aforementioned communities of practice, working groups provide an opportunity for individuals to share and collaborate with employees outside of their day-to-day teams. Management teams that cultivate this kind of culture will, in addition to fostering innovation, prime themselves for return on investment when engaging in KM practices.
But how exactly do we use these opportunities to capture a deeper set of knowledge? Andrew McAfee recommends that organisations move away from communication "channels" where knowledge is one-to-one, formulated haphazardly and expended quickly, to communication "platforms" where knowledge has a bigger audience (and thus often displays more care in its creation) and can be kept relevant, salient and accessible (McAfee 2006). An instruction sent in an email to a new employee detailing the tools, practices and processes of the organisation is redundant effort, likely to be incomplete, and loses accessibility and visibility rapidly after its immediate use has expired. But a web page on the corporate intranet titled "Things you need to know to start" that is both easy to find, and easy to update, is instantly accessible to anyone, likely to be kept relevant and updated, and also likely to be a product of a group of people rather than one individual, greatly increasing the chance that it is of a higher quality (Mader 2007). A "wiki" is a website that allows users to create and edit HTML pages with rich content for immediate consumption by potentially everyone with a web browser. Wikipedia has built its success and huge popularity on this model. Contemporary wiki products include features like configurable access rights, a WYSIWYG (what-you-see-is-what-you-get) text editor, document revision history and several more features that make it an extremely compelling KM tool for the enterprise. A number of organisations have identified wikis as an excellent tool to facilitate communication and collaboration (Grace 2009) and one of the easiest ways to move from the "channel" of communication (often email) to a "platform" of wiki documents, photo galleries and blog entries. Management teams should look keenly to this and other "Web 2.0" technologies that contribute in bringing people together, as Nonaka's spiral can be greatly infused when large groups of employees, who are otherwise distributed across the organisation, are brought together in the same virtual space.
However, it is important to note that the role of technology in Knowledge Management has historically been misdiagnosed and overstated. Consequently a number of organisations have missed the mark by focusing too much on the technology (Davenport et al. 2008). According to Teech (2000), IT solutions are only an enabler, and they should be implemented not to enable the storage and retrieval of knowledge, but the connection of people. This should be self-evident in today's Facebook dominated world, but as Joel Spolsky says, to promote the successful community-driven collaboration tool he helped create, "A successful Exchange [an installation of the product] depends on whether you [the product buyer] can supply the community", implying that even the best software solution will not create a useful knowledge base without the engagement of a community.
Microsoft chairman Bill Gates framed the challenge precisely in an interview for a Newsweek magazine article in 2006: “While information wants to be free, knowledge is much ‘stickier’ – harder to communicate, more subjective, less easy to define.” He continued that an employee's value to their firm is wrapped up in their tacit knowledge. “Your ability to combine it with the knowledge of co-workers, partners and customers can make the difference between success and failure – for you and your employer.” (Twentyman 2006) The message to management is clear: the cultivation and generation of strategic knowledge, followed by the effective capture, diffusion and consequent amplification will define competitiveness in tomorrow’s businesses. Organisations are highly advised to adopt strategies for the effective management of their employees' collective knowledge, as it is critical to survival in a knowledge-driven economy of the 21st century.
References:
Brooking, A., 1998. Corporate Memory: Strategies For Knowledge Management 1st ed., Cengage Learning Business Press.
Davenport, S.T., Prusak, L. & Strong, B., 2008. Putting Ideas to Work. Wall Street Journal.
Davenport, T.H. & Prusak, L., 1998. Working knowledge: How organizations manage what they know, Harvard Business School Pr.
Derby, E., Larsen, D. & Schwaber, K., 2006. Agile Retrospectives: Making Good Teams Great illustrated edition., Pragmatic Bookshelf.
Elinor Millis, 2006. Google says speed is king - CNET News. CNet News. Available at: http://news.cnet.com/2100-1032_3-6134247.html [Accessed November 16, 2009].
Garfield, S., 2007. Knowledge Management in the Real World. Lecture at Lawrence Technological University. Available online at
http://www.slideshare.net/SGarfield/knowledge-management-in-the-real-world [Accessed November 16, 2009].
Grace, T.P.L., 2009. Wikis as a knowledge management tool. Journal of Knowledge Management, 13(4), 64 - 74.
Kessels, J.W., 2001. Learning in organisations: a corporate curriculum for the knowledge economy. Futures, 33(6), 497–506.
Lave, J. & Wenger, E., 1991. Situated learning: Legitimate peripheral participation, Cambridge Univ Pr.
Leonard, D. & Sensiper, S., 1999. The role of tacit knowledge in group innovation. Knowledge and Strategy, 281.
Leonard, D. & Swap, W., 2004. Deep smarts. IEEE Engineering Management Review, 32(4), 3–10.
Mader, S., 2007. WikiPatterns, John Wiley & Sons.
McAfee, A.P., 2006. Enterprise 2.0: The dawn of emergent collaboration. MIT Sloan Management Review, 47(3), 21.
McElroy, M.W., 2003. The new knowledge management: Complexity, learning, and sustainable innovation, Butterworth-Heinemann.
McInerney, &., 2002. Knowledge Management and the Dynamic Nature of Knowledge. Journal of the American Society for Information Science and Technology, 53(12), 1009–1018.
Nonaka, I., 1994. A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5(1), 14-37.
O'dell, C. & Grayson, C.J., 1998. If Only We Knew What We Know: The Transfer of Internal Knowledge and Best Practice 1st ed., Free Press.
Polanyi, M., 1966. The tacit dimension. New York.
Poppendieck, M. & Poppendieck, T., 2006. Implementing Lean Software Development: From Concept to Cash (The Addison-Wesley Signature Series), Addison-Wesley Professional.
Rumizen, M.C., 2001. The Complete Idiot's Guide to Knowledge Management 1st ed., Alpha.
Senge, P.M., 1993. The Fifth Discipline: Art and Practice of the Learning Organization New edition., Random House Business Books.
Senge, P.M., 1990. The Leader's New Work: Building Learning Organizations. Sloan Management Review, 32(1), 7-23.
Spolsky, J., 2009. StackOverflow Podcast 70, IT Conversations. Transcript available at: http://blog.stackoverflow.com/2009/10/podcast-70/ [Accessed November 16, 2009].
Stankosky, M., 2005. Creating the Discipline of Knowledge Management: The Latest in University Research, Butterworth-Heinemann.
Swap, W. et al., 2001. Using Mentoring and Storytelling to Transfer Knowledge in the Workplace. Journal of Management Information Systems, 18(1), 95-114.
Teece, D.J., 2000. Strategies for managing knowledge assets: the role of firm structure and industrial context. Long Range Planning, 33(1), 35–54.
Twentyman, J., 2006. Capturing knowledge Knowledge capture is an area that has traditionally been poorly served by supporting software tools. INSIDE KNOWLEDGE, 9(6), 42.
Wenger, E., 1999. Communities of practice: Learning, meaning, and identity, Cambridge Univ Pr.
Williams, L. & Kessler, R., 2002. Pair Programming Illuminated, Addison Wesley.
Zeleny, M. & von Hayek, F.A., 1980. Management support systems: Towards integrated knowledge management. Management, 1(1), 7.

Knowledge is defined by the Oxford English Dictionary as "expertise and skills acquired by a person through experience or education". One might think that simply by extending this definition to include the situational context of the workplace, one can then arrive at an accurate assessment of organisational knowledge. However, this is only a part of the story. Organisations amplify knowledge in a number of ways from the cumulative efforts of its staff (Nonaka 1994), potentially creating a knowledge repository contributed to and in turn leveraged by all employees. Michael Polyani popularised the nature of tacit or implicit knowledge which is embodied in an individual and not easily codified or transferred (Polanyi 1966). Later, Ikujiro Nonaka focused on the distinction between tacit knowledge and explicit knowledge, which can be written down and transferred (Ikujiro & Takeuchi 1991). Polyani also argued (1966:55) that all knowledge is either tacit or rooted in tacit knowledge.  Pairing this observation with the fact that the world is full of visible codified knowledge, it follows that tacit knowledge could be further broken down into that which is codifiable, albeit with more intensive effort and management, and that which remains uncodifiable, such as intuition gained from experience, vis-à-vis Polanyi's "We can know more than we can tell". Organisations have historically exhibited a high level of explicit knowledge codification such as operational manuals, process documentation and annual financial reports. However, it is the generation, codification and dissemination of knowledge further along the knowledge continuum (Leonard & Sensiper 1999) (that is, increasingly tacit knowledge) that represents the major challenge for contemporary organisations and thus becomes the primary opportunity for knowledge management solutions (Twentyman 2006) (see diagram 1). In turn, the term "Knowledge Management" has many definitions. The common elements of the most-cited definitions centre around defining a strategy for creating, capturing, storing, accessing, and distributing knowledge across individuals, teams and the entire organisation (and sometimes even outside it) in an effort to generate value (increased skill in employees, more innovative products or services, etc) from an organisation's knowledge-based assets (Stankosky 2005, Davenport et al. 2008, O'dell & Grayson 1998, Rumizen 2001, Brooking 1998).

Nonaka, through the development of his SECI model (Nonaka 1994), argued that organisational knowledge can take on a self-generative nature when knowledge is transferred between tacit and tacit, tacit and explicit, and explicit and explicit states. He argued, after closely studying Japanese firms, that organisational knowledge takes on a "spiral" nature when transferring between these states, inferring that this "knowledge conversion" process serves to continually increase the organisation's total stock of knowledge as learning becomes embedded in the organisation's culture. A deeper analysis of Nonaka's SECI model is beyond the scope of this essay, but the key implication for management is that in order to create a useful knowledge base from which employees may leverage value, an organisation must first take the necessary steps to begin to support and facilitate the generation of that knowledge.

Another useful lens through which to define knowledge is with reference to the Knowledge Hierarchy (Zeleny & von Hayek 1980) or DIKW (Data to Information to Knowledge to Wisdom) taxonomy, if only to assert that while an organisation might record data and make sense of that data turning it to information, gaining knowledge from that information is indeed the next level entirely. Consider when Google asked users in a survey whether they would prefer more search results per page (Millis 2006). Users responded that "more is better", so Google lengthened the results from 10 to 30 for some users. However, it turned out that the extra half-second that the page took to load drastically decreased user satisfaction such that users conducted fewer searches. Google took the data from the initial survey, turned it to information (a recommendation to provide more search results per page and thereby increase user satisfaction) but then, only after going forward with an experiment, did Google gain the knowledge that users actually far preferred faster load times than more results per page. The lesson here is that the management of knowledge, is very different to the management of mere data and information.

Much reference is also made to the dynamic nature of organisational knowledge (McInerney 2002), in that it is constantly being updated, upgraded and refreshed, and should be regarded and managed as a living entity rather than a static artifact.  Davenport & Prusak argue that knowledge is not only bound to "documents and repositories" but also "routines, processes, practices and norms" (Davenport & Prusak 2000). Knowledge is produced, captured and transferred in many ways, from formal mentoring arrangements, apprenticeships and training programs to informal workplace discussions. Since these workplace practices occur on an ongoing basis, it is imperative that any KM strategy and/or solution needs to facilitate the consistent and continual upgrading and improving of the organisation's knowledge.

There is broad and growing consensus that the strategic management of knowledge assets contributes directly to an organisation's competitive advantage (Teece 2000) and is key to providing new products and services (Kessels 2001). On the other hand, neglecting this need leads to organisations suffering redundancy in effort and repeating past mistakes (Garfield 2007). International Data Corporation, a technology research group, reported that a poor capability to manage knowledge cost the Fortune 500 $12 billion per year (Stewart 2001, cited by McInerney 2002). But knowledge cannot be bought in and of itself; rather, it has to be cultivated in-house (Teece 2000) before any opportunity to embed it into new products or services can be fully exploited. The more salient knowledge an organisation has, and the more accessible it is, the more opportunities employees will find to leverage that knowledge in the innovation of new products and services. This will not only  decrease time-to-market and increase quality, but also expand the potential for future improvements to said products and services. It would appear that executives can no longer afford to lack a strategy for managing the collective of their employees' knowledge.

There are many opportunities to both capture and diffuse knowledge already present in most organisations. Any design, development or engineering of a product is fundamentally a knowledge creation process, and the lessons of bringing a product to market are invariably valuable to future efforts (M. Poppendieck & T. Poppendieck 2006). Davenport and Prusak, in their book "Working Knowledge: How Organisations Manage What They Know", highlight the value of interpersonal communication when facilitating knowledge transfer (Davenport & Prusak 2000). Time should be allotted, they argue, to allow staff members to engage in spontaneous conversations, organised group KT (knowledge transfer) sessions, demonstrations, presentations and experience reports, and the idea of "productivity" should be broadened to include these activities. Swap et al. suggest (2001) that storytelling and mentoring are also powerful ways to diffuse knowledge if well managed, and highly recommend the practice of joint-problem solving involving a senior and junior practitioner (Leonard & Swap 2004). A good example of this is in the software development industry where two programmers engage in "pair programming" (Williams & Kessler 2002). Two programmers sit at one computer, taking turns to command the keyboard and mouse while the other reviews the code as it is written. The result is a higher quality piece of work, and a good deal of knowledge transfer between the programmers involved. Peter Senge also advocates creating learning situations (Senge 1993). In his book "The Fifth Discipline", he champions the creation of a "learning organisation" through five key disciplines including "team learning" through dialogue and group discussion. It is clear that there is already a wealth of key opportunities for the capturing of knowledge in the workplace, but the key is to institutionalise the culture of knowledge capture and sharing. Workers should not feel harried or rushed; rather, they must have the opportunity to constantly reflect and analyse how practices and processes might be improved (Garvin 2003). Projects should end with (or be punctuated by) "retrospectives" or "post-mortems" where questions such as "What did we do right?", "What did we do wrong?" and "How can we improve?" are asked and provoke discussion in their answers (Derby et al. 2006). Another key aspect to evolving towards a culture that facilitates KM is the breaking down of boundaries and isolated teams and individuals. Along with the aforementioned communities of practice, working groups provide an opportunity for individuals to share and collaborate with employees outside of their day-to-day teams. Management teams that cultivate this kind of culture will, in addition to fostering innovation, prime themselves for return on investment when engaging in KM practices.

But how exactly do we use these opportunities to capture a deeper set of knowledge? Andrew McAfee recommends that organisations move away from communication "channels" where knowledge is one-to-one, formulated haphazardly and expended quickly, to communication "platforms" where knowledge has a bigger audience (and thus often displays more care in its creation) and can be kept relevant, salient and accessible (McAfee 2006). An instruction sent in an email to a new employee detailing the tools, practices and processes of the organisation is redundant effort, likely to be incomplete, and loses accessibility and visibility rapidly after its immediate use has expired. But a web page on the corporate intranet titled "Things you need to know to start" that is both easy to find, and easy to update, is instantly accessible to anyone, likely to be kept relevant and updated, and also likely to be a product of a group of people rather than one individual, greatly increasing the chance that it is of a higher quality (Mader 2007). A "wiki" is a website that allows users to create and edit HTML pages with rich content for immediate consumption by potentially everyone with a web browser. Wikipedia has built its success and huge popularity on this model. Contemporary wiki products include features like configurable access rights, a WYSIWYG (what-you-see-is-what-you-get) text editor, document revision history and several more features that make it an extremely compelling KM tool for the enterprise. A number of organisations have identified wikis as an excellent tool to facilitate communication and collaboration (Grace 2009) and one of the easiest ways to move from the "channel" of communication (often email) to a "platform" of wiki documents, photo galleries and blog entries. Management teams should look keenly to this and other "Web 2.0" technologies that contribute in bringing people together, as Nonaka's spiral can be greatly infused when large groups of employees, who are otherwise distributed across the organisation, are brought together in the same virtual space.

However, it is important to note that the role of technology in Knowledge Management has historically been misdiagnosed and overstated. Consequently a number of organisations have missed the mark by focusing too much on the technology (Davenport et al. 2008). According to Teech (2000), IT solutions are only an enabler, and they should be implemented not to enable the storage and retrieval of knowledge, but the connection of people. This should be self-evident in today's Facebook dominated world, but as Joel Spolsky says, to promote the successful community-driven collaboration tool he helped create, "A successful Exchange [an installation of the product] depends on whether you [the product buyer] can supply the community", implying that even the best software solution will not create a useful knowledge base without the engagement of a community.

Microsoft chairman Bill Gates framed the challenge precisely in an interview for a Newsweek magazine article in 2006: “While information wants to be free, knowledge is much ‘stickier’ – harder to communicate, more subjective, less easy to define.” He continued that an employee's value to their firm is wrapped up in their tacit knowledge. “Your ability to combine it with the knowledge of co-workers, partners and customers can make the difference between success and failure – for you and your employer.” (Twentyman 2006) The message to management is clear: the cultivation and generation of strategic knowledge, followed by the effective capture, diffusion and consequent amplification will define competitiveness in tomorrow’s businesses. Organisations are highly advised to adopt strategies for the effective management of their employees' collective knowledge, as it is critical to survival in a knowledge-driven economy of the 21st century.

References:

Brooking, A., 1998. Corporate Memory: Strategies For Knowledge Management 1st ed., Cengage Learning Business Press.

Davenport, S.T., Prusak, L. & Strong, B., 2008. Putting Ideas to Work. Wall Street Journal.

Davenport, T.H. & Prusak, L., 1998. Working knowledge: How organizations manage what they know, Harvard Business School Pr.

Derby, E., Larsen, D. & Schwaber, K., 2006. Agile Retrospectives: Making Good Teams Great illustrated edition., Pragmatic Bookshelf.

Elinor Millis, 2006. Google says speed is king - CNET News. CNet News. Available at: http://news.cnet.com/2100-1032_3-6134247.html [Accessed November 16, 2009].

Garfield, S., 2007. Knowledge Management in the Real World. Lecture at Lawrence Technological University. Available online at

http://www.slideshare.net/SGarfield/knowledge-management-in-the-real-world [Accessed November 16, 2009].

Grace, T.P.L., 2009. Wikis as a knowledge management tool. Journal of Knowledge Management, 13(4), 64 - 74.

Kessels, J.W., 2001. Learning in organisations: a corporate curriculum for the knowledge economy. Futures, 33(6), 497–506.

Lave, J. & Wenger, E., 1991. Situated learning: Legitimate peripheral participation, Cambridge Univ Pr.

Leonard, D. & Sensiper, S., 1999. The role of tacit knowledge in group innovation. Knowledge and Strategy, 281.

Leonard, D. & Swap, W., 2004. Deep smarts. IEEE Engineering Management Review, 32(4), 3–10.

Mader, S., 2007. WikiPatterns, John Wiley & Sons.

McAfee, A.P., 2006. Enterprise 2.0: The dawn of emergent collaboration. MIT Sloan Management Review, 47(3), 21.

McElroy, M.W., 2003. The new knowledge management: Complexity, learning, and sustainable innovation, Butterworth-Heinemann.

McInerney, &., 2002. Knowledge Management and the Dynamic Nature of Knowledge. Journal of the American Society for Information Science and Technology, 53(12), 1009–1018.

Nonaka, I., 1994. A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5(1), 14-37.

O'dell, C. & Grayson, C.J., 1998. If Only We Knew What We Know: The Transfer of Internal Knowledge and Best Practice 1st ed., Free Press.

Polanyi, M., 1966. The tacit dimension. New York.

Poppendieck, M. & Poppendieck, T., 2006. Implementing Lean Software Development: From Concept to Cash (The Addison-Wesley Signature Series), Addison-Wesley Professional.

Rumizen, M.C., 2001. The Complete Idiot's Guide to Knowledge Management 1st ed., Alpha.

Senge, P.M., 1993. The Fifth Discipline: Art and Practice of the Learning Organization New edition., Random House Business Books.

Senge, P.M., 1990. The Leader's New Work: Building Learning Organizations. Sloan Management Review, 32(1), 7-23.

Spolsky, J., 2009. StackOverflow Podcast 70, IT Conversations. Transcript available at: http://blog.stackoverflow.com/2009/10/podcast-70/ [Accessed November 16, 2009].

Stankosky, M., 2005. Creating the Discipline of Knowledge Management: The Latest in University Research, Butterworth-Heinemann.

Swap, W. et al., 2001. Using Mentoring and Storytelling to Transfer Knowledge in the Workplace. Journal of Management Information Systems, 18(1), 95-114.

Teece, D.J., 2000. Strategies for managing knowledge assets: the role of firm structure and industrial context. Long Range Planning, 33(1), 35–54.

Twentyman, J., 2006. Capturing knowledge Knowledge capture is an area that has traditionally been poorly served by supporting software tools. INSIDE KNOWLEDGE, 9(6), 42.

Wenger, E., 1999. Communities of practice: Learning, meaning, and identity, Cambridge Univ Pr.

Williams, L. & Kessler, R., 2002. Pair Programming Illuminated, Addison Wesley.

Zeleny, M. & von Hayek, F.A., 1980. Management support systems: Towards integrated knowledge management. Management, 1(1), 7.

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20Aug/090

Netflix Culture

Netflix are one of the tech companies that ground through some sizable losses during the dotcom burst and the following stagnation, and have emerged, on the back of the popularity of the DVD player in US households, to be the biggest online DVD/Blue-Ray rental service in the world. The company has been managed well, and their stock price seems to show it.

Some insight as to how they achieved that can be found in a slide deck detailing their "culture".

There is a lot of good stuff here, but here are my favourites:

  • Company culture and set of values manifests itself in who gets rewarded, promoted, and let go; Big emphasis on "talent density" - I like that.
  • Leffort's Law: If you manage, it's your fault.
  • Effectiveness is far more important than Effort.
  • "Rapid Recovery" is the right model, rather than wasting too much time on preventative measures (exceptions exist).
  • Vacation policy: There is none - employees take what they need and are encouraged do take "what is good for Netflix" (Professionalism and self-discipline over process adherence).
  • Expense policy: "Act in Netflix''s Best Interest".
  • Annual salary review is also market-based, and not just hiring.

Not only do they have an inspirational vision, but they seemed to have worked out most of the details of how to make it a reality.

Netflix might have its detractors, but the important thing that these slides demonstrate is that management is recognizing what it takes to have a happy, productive, talented tech workforce producing value for business.

Enjoy.

[via Scott Berkun]

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26Jun/090

Solution to Combine, Minify and GZIP your JS and CSS

I've recently completed a fair bit of research and consequent development at work that goes quite far to improve the performance of our web application's front-end. I thought I'd share the basic solution here.

The first obvious thing to do is benchmark your site using Yahoo's YSlow and Google's PageSpeed. These will highlight the "low-hanging fruit" performance improvements to make. Unless you've already done so, the resulting suggestions will almost certainly include combining, minifying and gzipping your static content.

The steps we're going to perform are:

  1. Write a custom HTTPHandler to combine and minify CSS.
  2. Write a custom HTTPHandler to combine and minify JS.
  3. Include a mechanism to ensure that the above only do their magic when the application is not in debug mode.
  4. Write a custom server-side web control to easily maintain css/js file inclusion.
  5. Enable GZIP of certain content types on IIS 6.

Right, let's start with CSSHandler.asax that implements the .NET IHttpHandler interface:

using System;
using System.Collections.Generic;
using System.IO;
using System.Text;
using System.Web;

namespace WebApplication1
{
    public class CssHandler : IHttpHandler
    {
        public bool IsReusable { get { return true; } }

        public void ProcessRequest(HttpContext context)
        {
            string[] cssFiles = context.Request.QueryString["cssfiles"].Split(',');

            List<string> files = new List<string>();
            StringBuilder response = new StringBuilder();
            foreach (string cssFile in cssFiles)
            {
                if (!cssFile.EndsWith(".css", StringComparison.OrdinalIgnoreCase))
                {
                    //log custom exception
                    context.Response.StatusCode = 403;
                    return;
                }

                try
                {
                    string filePath = context.Server.MapPath(cssFile);
                    string css = File.ReadAllText(filePath);
                    string compressedCss = Yahoo.Yui.Compressor.CssCompressor.Compress(css);
                    response.Append(compressedCss);
                }
                catch (Exception ex)
                {
                    //log exception
                    context.Response.StatusCode = 500;
                    return;
                }
            }

            context.Response.Write(response.ToString());

            string version = "1.0"; //your dynamic version number 

            context.Response.ContentType = "text/css";
            context.Response.AddFileDependencies(files.ToArray());
            HttpCachePolicy cache = context.Response.Cache;
            cache.SetCacheability(HttpCacheability.Public);
            cache.VaryByParams["cssfiles"] = true;
            cache.SetETag(version);
            cache.SetLastModifiedFromFileDependencies();
            cache.SetMaxAge(TimeSpan.FromDays(14));
            cache.SetRevalidation(HttpCacheRevalidation.AllCaches);
        }
    }
}

Ok, now some explanation:

IsReUsable property:

We aren't dealing with anything instance-specific, which means we can safely reuse the same instance of the handler to deal with multiple requests, because our ProcessRequest is threadsafe. More info.

ProcessRequest method:

Nothing too hectic going on here. We're looping through the CSS files given to us (see the CSSControl below for how they're coming in) and compressing each one, using a .NET port of Yahoo's YUICompressor, before adding the contents to the outgoing response stream.

The remainder of the method deals with setting up some HTTP caching properties to further optimise the way the browser client downloads (or not, as the case may be) content.

  • We set Etags in code so that they may be the same across all machines in our server farm.
  • We set Response and Cache dependencies on our actual files so, should they be replaced, cache will be invalidated.
  • We set Cacheability such that proxies can cache.
  • We VaryByParams using our cssfiles attribute, so that we can cache per CSS file group submitted through the handler.

And here is the CSSControl, a custom server-side control inheriting the .NET LiteralControl.

Front:

<customcontrols:csscontrol id="cssControl" runat="server">
          <CustomControls:Stylesheet File="main.css" />
          <CustomControls:Stylesheet File="layout.css" />
          <CustomControls:Stylesheet File="formatting.css" />
</customcontrols:csscontrol>

Back: 

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Web;
using System.Web.UI;
using System.Linq;
using TTC.iTropics.Utilities;

namespace WebApplication1
{
    [DefaultProperty("Stylesheets")]
    [ParseChildren(true, "Stylesheets")]
    public class CssControl : LiteralControl
    {
        [PersistenceMode(PersistenceMode.InnerDefaultProperty)]
        public List<Stylesheet> Stylesheets { get; set; }

        public CssControl()
        {
            Stylesheets = new List<Stylesheet>();
        }

        protected override void Render(HtmlTextWriter output)
        {
            if (HttpContext.Current.IsDebuggingEnabled)
            {
                const string format = "<link rel=\"Stylesheet\" href=\"stylesheets/{0}\"></link>";

                foreach (Stylesheet sheet in Stylesheets)
                    output.Write(format, sheet.File);
            }
            else
            {
                const string format = "<link type=\"text/css\" rel=\"Stylesheet\" href=\"stylesheets/CssHandler.ashx?cssfiles={0}&version={1}\"/>";
                IEnumerable<string> stylesheetsArray = Stylesheets.Select(s => s.File);
                string stylesheets = String.Join(",", stylesheetsArray.ToArray());
                string version = "1.00" //your version number

                output.Write(format, stylesheets, version);
            }

        }
    }

    public class Stylesheet
    {
        public string File { get; set; }
    }
}

HttpContext.Current.IsDebuggingEnabled is hooked up to the following setting in your web.config: 

<system.web>
    <compilation debug="false">
</system.web>

So, basically, if your site is in debug mode you get HTML markup like this: 

<link rel="Stylesheet" href="stylesheets/formatting.css"></link>
<link rel="Stylesheet" href="stylesheets/layout.css"></link
<link rel="Stylesheet" href="stylesheets/main.css"></link>

But if you're in production mode (debug=false), you'll get markup like this: 

<link type="text/css" rel="Stylesheet" href="CssHandler.ashx?cssfiles=main.css,layout.css,formatting.css&version=1.0"/>

The latter will then obviously invoke the CSSHandler, which will take care of combining, minifying and cache-readying your static CSS content.

All of the above can then also be duplicated for your static JavaScript content:

`JSHandler.ashx:

using System;
using System.Collections.Generic;
using System.IO;
using System.Text;
using System.Web;

namespace WebApplication1
{
    public class JSHandler : IHttpHandler
    {
        public bool IsReusable { get { return true; } }

        public void ProcessRequest(HttpContext context)
        {
            string[] jsFiles = context.Request.QueryString["jsfiles"].Split(',');

            List<string> files = new List<string>();
            StringBuilder response = new StringBuilder();

            foreach (string jsFile in jsFiles)
            {
                if (!jsFile.EndsWith(".js", StringComparison.OrdinalIgnoreCase))
                {
                    //log custom exception
                    context.Response.StatusCode = 403;
                    return;
                }

                try
                {
                    string filePath = context.Server.MapPath(jsFile);
                    string js = File.ReadAllText(filePath);
                    string compressedJS = Yahoo.Yui.Compressor.JavaScriptCompressor.Compress(js);
                    response.Append(compressedJS);
                }
                catch (Exception ex)
                {
                    //log exception
                    context.Response.StatusCode = 500;
                    return;
                }
            }

            context.Response.Write(response.ToString());

            string version = "1.0"; //your dynamic version number here

            context.Response.ContentType = "application/javascript";
            context.Response.AddFileDependencies(files.ToArray());
            HttpCachePolicy cache = context.Response.Cache;
            cache.SetCacheability(HttpCacheability.Public);
            cache.VaryByParams["jsfiles"] = true;
            cache.VaryByParams["version"] = true;
            cache.SetETag(version);
            cache.SetLastModifiedFromFileDependencies();
            cache.SetMaxAge(TimeSpan.FromDays(14));
            cache.SetRevalidation(HttpCacheRevalidation.AllCaches);
        }
    }
}

And its accompanying JSControl:

Front:

<customcontrols:JSControl ID="jsControl" runat="server">
    <customcontrols:Script File="jquery/jquery-1.3.2.js" />
    <customcontrols:Script File="main.js" />
    <customcontrols:Script File="creditcardpayments.js" />
</customcontrols:JSControl>

Back: 

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Web;
using System.Web.UI;
using System.Linq;

namespace WebApplication1
{
    [DefaultProperty("Scripts")]
    [ParseChildren(true, "Scripts")]
    public class JSControl : LiteralControl
    {
        [PersistenceMode(PersistenceMode.InnerDefaultProperty)]
        public List<Script> Scripts { get; set; }

        public JSControl()
        {
            Scripts = new List<Script>();
        }

        protected override void Render(HtmlTextWriter writer)
        {
            if (HttpContext.Current.IsDebuggingEnabled)
            {
                const string format = "<script src=\"scripts\\{0}\"></script>";

                foreach (Script script in Scripts)
                    writer.Write(format, script.File);
            }
            else
            {
                IEnumerable<string> scriptsArray = Scripts.Select(s => s.File);
                string scripts = String.Join(",", scriptsArray.ToArray());
                string version = "1.0" //your dynamic version number
                const string format = "<script src=\"scripts/JsHandler.ashx?jsfiles={0}&version={1}\"></script>";

                writer.Write(format, scripts, version);
            }
        }
    }

    public class Script
    {
        public string File { get; set; }
    }
}

Enabling GZIP:

As Jeff Atwood says, enabling Gzip on your web site server is a no-brainer. After some tracing, I decided to enable Gzip on the following file types:

  • .css
  • .js
  • .axd (Microsoft Javascript files)
  • .aspx (Usual ASP.NET Web Forms content)
  • .ashx (Our handlers)

To enable HTTP Compression on your IIS 6.0 web server:

  1. Open IIS, Right click Web Sites, Services tab, enable Compress Application Files and Compress Static Files
  2. Stop IIS
  3. Open up IIS Metabase in Notepad (C:\WINDOWS\system32\inetsrv\MetaBase.xml) - and make a back up if you're nervous about these things :-)
  4. Locate and overwrite the two IIsCompressionScheme and one IIsCompressionSchemes elements with the following: 
<IIsCompressionScheme    Location ="/LM/W3SVC/Filters/Compression/deflate"
        HcCompressionDll="%windir%\system32\inetsrv\gzip.dll"
        HcCreateFlags="0"
        HcDoDynamicCompression="TRUE"
        HcDoOnDemandCompression="TRUE"
        HcDoStaticCompression="TRUE"
        HcDynamicCompressionLevel="9"
        HcFileExtensions="htm
            html
            txt
            css"
        HcOnDemandCompLevel="9"
        HcPriority="1"
        HcScriptFileExtensions="asp
            dll
            exe
            aspx
            js
            ashx
            axd"
    >
</IIsCompressionScheme>
<IIsCompressionScheme    Location ="/LM/W3SVC/Filters/Compression/gzip"
        HcCompressionDll="%windir%\system32\inetsrv\gzip.dll"
        HcCreateFlags="1"
        HcDoDynamicCompression="TRUE"
        HcDoOnDemandCompression="TRUE"
        HcDoStaticCompression="TRUE"
        HcDynamicCompressionLevel="9"
        HcFileExtensions="htm
            html
            txt
            css"
        HcOnDemandCompLevel="9"
        HcPriority="1"
        HcScriptFileExtensions="asp
            dll
            exe
            aspx
            js
            ashx
            axd"
    >
</IIsCompressionScheme>
<IIsCompressionSchemes    Location ="/LM/W3SVC/Filters/Compression/Parameters"
        HcCacheControlHeader="max-age=86400"
        HcCompressionBufferSize="8192"
        HcCompressionDirectory="%windir%\IIS Temporary Compressed Files"
        HcDoDiskSpaceLimiting="FALSE"
        HcDoDynamicCompression="TRUE"
        HcDoOnDemandCompression="TRUE"
        HcDoStaticCompression="TRUE"
        HcExpiresHeader="Wed, 01 Jan 1997 12:00:00 GMT"
        HcFilesDeletedPerDiskFree="256"
        HcIoBufferSize="8192"
        HcMaxDiskSpaceUsage="99614720"
        HcMaxQueueLength="1000"
        HcMinFileSizeForComp="1"
        HcNoCompressionForHttp10="FALSE"
        HcNoCompressionForProxies="FALSE"
        HcNoCompressionForRange="FALSE"
        HcSendCacheHeaders="FALSE"
    >

And that's it! This saved us heaps of bandwidth and resulted in a more responsive web application throughout.

Enjoy!

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19Feb/090

Illegitimate Affecters

I've long been searching for a succinct noun phrase for that certain annoying thing that seemingly requires you to do something in a less-than-perfect way. Something that you know can and should be done better. You curse having that 'requirement', you loathe having to create a 'workaround', and you dream of a better world. Whether it's the tardiness of the web standards world requiring CSS browser hacks, or the less-than-stellar API of an enterprise system with which you have to integrate, or perhaps being forced to browse in IE because of corporate bureaucracy, you've probably become annoyed at having to contend with this thing that, if the world was a better place, would not otherwise be detrimental to your work or productivity.

Having failed at finding the correct phrase for such a thing, I've done what I usually do and made one up. I now consider something like the above to be an illegitimate affecter. Having this succinct term is useful when identifying individual constituent parts of the system that can then be factored out by function and treated to an increase in quality (refactoring/rewriting) on a part by part basis.

For example, I sometimes stumble on poorly named properties only to trace their source back to the (poorly named) property of an outside API. The developer that first created the property in our application used the property name of the API object as an affecter but failed to recognize it as illegitimate, unnecessarily causing that little bit of extra confusion to all developers consequently working with that property.

I've also been in design discussions when reasons are brought up against making some architectural/design change to the system, only to be carefully exposed as illegitimate affecters, often temporary in nature, and sometimes actually even lending more weight to the argument to undertake the change proposed.

When they are outside of your control, illegitimate affecters should be kept at bay by abstraction layers. When inside your control, they themselves should form part of the redesign and refactoring discussions.

What illegitimate affecters can you think of?

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2Feb/090

Lean and Mean

IMG_0214 A couple of weeks ago I presented at an internal company conference on Lean Software Development and what we can learn from Lean Manufacturing. As I am still a neophyte at presenting, the PowerPoint notes are prosaic and should be a coherent read.

I also included a slide discussing the Estimation Fallacy and Optimism Bias in an attempt to provide some insight into why software estimation is so often inaccurate.

The last thing I wanted to slip in was a slide on The Alignment Trap as presented in a Bain Consulting industry research publication released back in 2007. Briefly, the conclusions of this study put companies in four distinct quadrants: Well-aligned/Effective; Less-Aligned/Effective; Well-aligned/Ineffective and Less-aligned/Ineffective. The sales figures of the companies in the less-aligned/effective quadrant were better than the sales figures of the well-aligned/ineffective companies. The lesson there being that companies should avoid the alignment trap by letting their IT departments become effective at what they’re doing, before aligning IT operations more accurately with the business strategy.

It’s all in the presentation in better detail here!

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20Jan/090

The Importance of Meritocracy

When trying to get developers of a project invested in what they are doing on a day to day basis, few practices go so far as the establishment of an informal meritocracy in the team.

Traditionally in software, meritocracy is talked about with relation to initially giving a developer a small amount of time and trust to contribute something outside of his or her traditional area. The product of that time is then evaluated by the team leader or project manager, and if that mini-project was deemed to be valuable, the developer is given additional time and trust the next time he has an idea (when time permits so as not to negatively affect the main development project). This process works successfully in open source projects.

Now, I think it would be good to extend this phenomenon, contrary to the usual rules of social correctness in the workplace, to informal benefits in and around the workplace itself. Senior developers should get to work from home more, more relaxed internet surfing rules and even free coffee (if not already standard) so as to get juniors to aspire to be just like them. We are not all rewarded in equal financial terms for the value we contribute towards the project, so why should we all be subject to the same office environment rules? People should associate responsibility, accountability, and good performance with benefits beyond just their salary.

Conversely, employees who abuse the trust given to them to perform their job can have their perks reduced or taken away entirely. Is Gerald Facebooking too much? Fine, restrict him and only him to free surfing in lunch hours and after 5pm. If he's gives a damn, he'll soon get the message and shape up. If he doesn't, well, taking away his perks will hopefully be the first few steps to warnings and then a dismissal, because you don't want anyone like that on your software team.

I am aware that this kind of thing could get messy with the wrong people around, but then again, software development in general gets messy with the wrong people around! I would concede that an informal meritocracy would work best in a mature workplace where the hierarchy is accurately based on experience, qualifications and merit to the project, however rare that may be!

So let's drop the egalitarian charade and tell it like it is. All software developers are not created equal, and differing perks for juniors and seniors would be a good thing!

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