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Consider the Organisation as if it Were Granular Sand

24 Feb

Being Amended

Earlier group posts concerning performance management have taken a two strand approach. Firstly, some key business methodologies have been evaluated and compared. Secondly, the relationship between information/commentary media have been concerned in terms of meaning, abstraction, scale and complexity. This has been done with the purpose of reconciling the clarity of clear, reference-able breakdowns of organisational challenges and opportunities with the seismic shifts that big data will provide business models, strategies and tactics. In particular, the importance of language and social media to future BIS orientated models of governance, knowledge acquisition and communication will be most deliberated on.



Concerning Executive Decision Making

It is worth emphasizing that executives in the modern age are usually swamped informatically. They are too limited by their finite time and focus and potentially distracted by seemingly infinite demands (both internally and externally).

Whether actively or passively two key soft levers are used to build individual or macro level resistance points. These are in regards to how value is perceived  (in this example through transaction costs and how policy intersects with semiotics in the form of language


Transaction costs can be divided into three broad categories:

  • Search and information costs are costs such as those incurred in determining that the required good is available on the market, which has the lowest price, etc.
  • Bargaining costs are the costs required to come to an acceptable agreement with the other party to the transaction, drawing up an appropriate contract and so on. In game theory this is analyzed for instance in the game of chicken. On asset markets and in market microstructure, the transaction cost is some function of the distance between the bid and ask.
  • Policing and enforcement costs are the costs of making sure the other party sticks to the terms of the contract, and taking appropriate action (often through the legal system) if this turns out not to be the case.

Commons, J.R (1931). “Institutional Economics”.
American Economic Review

Organisations have to make tradeoffs between the differing transaction cost categories when it comes to deciding upon, searching for, agreeing upon, implementing, using, maintaining and upgrading information systems.

Communication in Organisations The Heart of Information Systems

Communication in Organisations The Heart of Information Systems
Roland Holten and Christoph Rosenkranz; Sprouts (2008)

Language and Semiotics and Governance

Similar to wider or similarly specialist reform(s), there would exist certain norms (either explicit or otherwise) in the social culture, vision and outcomes. This is a complex interplay between individual, component and aggregate entities. This operates collaboratively, competitively and symbiotically, with pulses, resonance bleeding. As a method of institutional/collective expediency beyond professional clusters people develop and enforce (to varying levels) language codes, norms and understandings. These loose standards can be done to widen communication and also/simultaneously stifle/undermine it.

To understand this better and build on the previous posts [I] [II] on language and media it is best to give a breakdown of key language schema examples:




Globe - DNA - D1.1

Public Affairs issue category

public consciousness public attention public support Popular support public rejection public anger pressure cause


Globe - DNA - B1.1

General initiatives category

little help arrangements cross roads comparison situation dangerous game


Globe - DNA - F1.1

General events category

poll tax riots Equality Impact Assessments technetronic era world war


Globe - DNA - E1.1

People types category

couple sociable friendly community protected group poorest members friends vigilante activists


Globe - DNA - H1.1

General organisations category

Spartacus group Resolution Foundation ATOS Atos BT BBC Guardian


General individuals category

Globe - DNA - G1.2

Christopher Thomond Hooper family Stuart Holden Lord Freud Steve Webb IDS

Product Types

Globe - DNA - C1.1

Finance products category

receipts overheads negative equity non payment arrears


Globe - DNA - A1.1

Fear keywords category

No-one poor pity problem gripe astonishing effect



Reconciling Roland Holten and Christoph Rosenkranz’s model for understanding language ease/barriers and the aforementioned schema one can imagine an organisational structure similar to the activity beteen differing molecules in a space offering multiple/overlapping environments:

Colour Pallette - 1c- first

The model displays an organisation with a communicative executive core, as well as a (slightly?) disjointed outer layer comprised of medium and lower tier employees or external communication. With the ontological schema, it represents a membrane and distance that limits proximity to decisionmaking for individual commmunications/policies coming from outside.

Organization”, understood in this sense, is closely related to the concept of “control”.
Control in big systems is defined as stable communication between sub-systems, meaning a
stable organization. Therefore, control is precisely the stable state of the variety interactions
between the nominated sub-systems

Beer, S. (1965) “The world, the flesh and the metal,” Nature205, pp. 223-231

Colour Pallette - 1c- second

Colour Pallette - 1c- second - b

Naturally, the failure of and organisations facets in regards  processes, artifacts or people can widen (or reduce) “communications power distance” between senior and lower level decisionmaking.

In this example the disharmony stems from Type categories and Keyword categories.




When it comes to organisational habits the total distance as well as the outcomes of velocities as communications are improved or hindered in order to encourage strategic alignment. When it becomes too one sided, asymmetrical or overly confrontational between one or different camps reciprocal issues grow This is a sure sign that disharmony and alignment is being forgone increasingly for ulterior motives.

Colour Pallette - 1c- second - mix

Weick (1988) describes the term enactment as representing the notion that when people act they bring structures and events into existence and set them in action. Weick uses this term in the context of ‘sensemaking’ by managers or employees. He also describes how they can enact ‘limitations’ upon the system to avoid issues or experiences. It is also seen as a form of social construction. To date enactment is related to organizations and their environment and strategic management.

In the diagram above, to counter increasing communications gaps from strategic groups to outside communications flows added core competence regions were added to provide ground up solutions and create a mid point using interdisciplinary stakeholders/emphases (notice the three coloured cluster in the top right direction of the image).



Ball of Confusion

Screenshot from 2013-02-17 21:11:11

For organisations operating on a significant level of complexity or sophistication a wider range of dimensions and components require consideration:


A system that adjusts its way of behavior relative to changing internal or external conditions is termed self-organizing

Ashby, W. R. (1947) “Principles of the self-organizing dynamic system,” Journal of General Psychology (37) pp. 125-128.
Ashby, W. R. (1962) Principles of the self-organizing system, in H. von Foerster and G. W. J. Zopf (Eds.)
Principles of Self-Organization: Transactions of the University of Illinois Symposium, London, UK: Pergamon Press, pp. 255-278.


Below is a framework for encouraging eGovernment projects using a large and diverse range of stakeholders. It is particularly helpful in environments where operating in ‘silos’ with different approaches to artifacts, processes and  people exist. Its value is that the breakdown of complex problems into components can allow focus and harmonisation.

M. Wimmer A European perspective towards online one-stop government: the eGOV project (Electronic Commerce Research and Applications ) 2002

M. Wimmer A European perspective towards online one-stop government: the eGOV project (Electronic Commerce Research and Applications ) 2002 University of Linz (2002)

One of the disadvantages of this technique are the more complex abstraction requirements to handle complexity. As part of the tradeoff it may be more difficult to engineer consensus or even understanding for groups (even at an executive level.

Globe - Clolours1.1

To overcome this approaches need to be built in to ensure that individual perspectives and requirements are built into procedures and that this crystallizing is built into a cataloging that not only provides distinction between entities but also empathy.

One useful mechanism to deal with this is to embed a semantic framing of key policy and measurement communications. Sentiment analysis permits dashboards of keyword search for a variety of formats. However, most conventional approaches seem geared towards the tactics then strategies of organisations and how they relate to their/external communities.

An effective system for executive or senior level managerial decisions should be framed around the guiding strategic drivers that motivate direction and change.

Given the sophistication and limitations of human and computing logic as addressed in a previous post it is appropriate to draw from the logic that a single blog post and its responses is capable of generating hundreds of key terms, all which can be delinerated by the semantic schema explained above.

To extract and analyze ten pieces of concern and motivation of individual entities in regards to an organisational problem/opportunity could provide the starting point for articulating:

  • What are the overriding
    • visions
    • priorities,
  • What are the available
    • threats,
    • benefits;
    • limitors;
  • Who the key community stakeholders are
    • internally,
    • externally
  • What competences exist contextually
    • intenally
    • externally

Using human/and or algorithm techniques teams of specialists or lay researchers would be able to generate knowledge and/or communications competences as a scale previously unimaginable without the mixture of Internet community and machine learning sophistications (which is why big data is so important).

Returning to the keyword analysis of a social housing blog (creating a keyword list of around 500 unique terms) using a mixture of techniques involving:

  1. Artifacts Search: Wide keyword category search to identify user profiles,
  2. Process Search: Extract of specific terms (such as “bedroom”) within profiles,
  3. People Search: Extract of relationships/contexts within individual identified media.

Globe - Clolours1.2

Doing this intensely over a short period is not only able to generate homogenous tweets (over 800) from a large user population (over 300) (accounts [I] [II] [III]) but also contextual, filtered [I] [II] or broader information flows (albeit with requirements in these instances for reinterpreting/synthesizing).

Given the complexity and significant time, cost and communications expenses involved in a major information systems project it is appropriate to build in appropriate necessitating of data mining and representation to engineer communications harmonizing or demarcation within/without an organisation.

Having a tight data set using a wider population has its advantages for allowing data drift, as well as timeline style benchmarking of processes, systems and infrastructures to highlight where disharmony ebbs or recedes (either internally, between rival organisations or between industries or technologies). The adaptive potential for using an information community for complementary analysis and engagement.

Returning to the frameworks our group has already analyzed, below is an evaluation of the perspectives focus on a semantic level, graded up to five for relevancy:

Description Department for Trade and Industry Balanced Scorecard Framework Activity Basesd Costing Economic Value Added OBRiM Cresswell’s ROI Process Oriented BSC
Processing Systems 3 3 2 2
Alert Systems 2 2 3 3 1
Inventory Systems 2 2 2 2 2
Management Information Systems 4 3 3 4 3
Decision Support Systems 3 3 3 3
Accounting Management Systems 3 3 4 4
Financial Management Systems 3 3 4 4
Payment Systems 2 2
Expert Systems 2 4 3 3
Databases 3 3 4 4
Human Resource Information Systems 3 4 3 2
Marketing Information Systems 3 2 5
Technology 3 3 2 3
Computer Science 3 3 2 2
Electronics 2 2
P2P 2 2 4 2
Information Technology 4 4 3 3
Internet Technology 3 3 2 2
Internet of Things 2
Software 2
ICT Change 3
Knowledge 4 4 3 3 3 5 5 3
Information 4 4 2 3
Meaning 4 3 3 3
Statistics 3 3 4 4
Data Integrity 3 5 4
Virtualisation 1
Cloud 1 1 1 1
Cloud Technology 1 1 1 1
IT Reliability 3 4 4 3
IT Quality Performance 3 4 4 3
Knowledge Management 3 4 4 4 3
Statistical tools 3 5 3 3
Analysis 4 5 2 2
Sentiment Analysis 5 4 3
Standards 4 4 4 4
Front End 3 2 4 4
Re/engineering 3 3 2 2
Security 3 4 3 3
networks 4 3 4 2
Relationships 3 4 2 3 4 3 1
Clusters 2 4 3 5
Social Businesses 4 3 2 2
Collaborative Working 4 3 4 4 3 4 5 4
Communication 4 4 3 2
Knowledge Share 4 3 4 3
Openness 4 4 3 2
Open Source 3 3 2 3
Internet 2 3 2 1
Globalisation 2 3 2
Mergers 2 3
Asymmetries 4
Innovation 4 4 3 3
Competition 4 4 4 2 4
Competitive Advantage 3 4 4 4
Cost Leadership 4 3 3 2
Quality Leadership 4 3 3 3
Differentiation 3 2 3 4
Cultural Issues 4 4 3 2 5
Strategic Drivers 3 4 2 4
Business Change 4 4 3 2 4
Disruptive Technology 3
New Markets 3 4 4 3 3
New Territories 3 3 3
Fads and Trends 5 5 3 3
Changing Roles 3 3 3 3 1
Macro Economics 3 3 3 2
Micro Economics 4 4 3 2 5 3 2
Risk 3 4 4 2 2 2 5
People 3 2 3 2
Organisation 4 4 3 3 4
Multinational 4 4 4 3 4
SMEs 5 4 4 4 3 2 2
Individuals 3 3 4 4
Business 4 4 4 3
Entrepreneurship 5 3 3 3
Government 4 4 3 3
Society 3 4 3 1
Social Enterprises 4 3 4 3
Professional Types 3 3 4
Executives 4 4 4 2 4
CEO 5 5 4 3
CTOs 4 3 4 3 3 2 1
CIOs 4 4 3 3 5 4 2
Leadership 5 4 3 3 3 2 1
Governance 4 5 4 3
C Level Commitment 4
Orientation / Focus / Vision 4 4 4 3
Value Systems 3 3 4 2 2
Gut Instinct 4 4 3 3 3 4 3 4
Strategy 5 5 4 4 5
Strategic Alignment 5 5 4 4 4
Executive Strategy 4 4 4 3 4
Business Strategy 5 5 4 4 4 3 2 5
IT Strategy 3 3 3 2 4 3 2 4
Strategic Planning 4 5 4 4 3 3 2
Business Development 5 4 3 3 5 3 3 4
Accountability 4 4 4 4 2 4 3
Transparancy 4 5 3
Regulation 4 4 4 3 4 5 2
Consulting 4 5 3 3 3 4 4 3
Business Models 5 4 3 4
Free 5 5 4 4
Business Intelligence 4 4 3 4 2 3 2
Business Plans 5 5 4 4 5 2 3
Organisational Flexibility 4 4 4 4 1 2 1
Outsourcing 2 2 1 1 3 4 3
Mesurement 5 5 5 5 4 4 4
Objectives 4 4 4 3 2 3 3
Concerns 3 4 6 4
Goals 5 5 5 5 4 3 2
Mission Statements 4 3 4 4
Stakeholders 4 3 4 4
B2B 4 4 4 4
B2C 4 4 3 3
Distributers 4
Employees 4 5 2 5
Performance 5 5 5 5
Deployment 4 3 4 3 4
Planning 4 4 4 4 2 2 5 4
Process Management 3 4 3 2 5 4 2
Division Management 4 4 4 4 3 4 5
Length of Time 4 4 3 4
Supply Chain Management 4 4 4 2
Total Quality Management 3 3
Just in Time Processes 3 3 4 5 4 5 3 4
Six Sigma 3
Management 4 4 4 3
Front Line 2
Human Resources 4
Customer Centricity 4 4 3 2
Marketing 4 3 4 3
Sales 2 3 3 4
Distribution 3 3 3 3 4 2 5
Financing 4 4 4 4
Accounting 2 2 3 4
Legal 2 1 1 1
Information Technology 4 3 3 4 5
Bring Your Own Device 1
Investment 3 2 2 4
Venture Capital 4 2 3 2
Capital Projects 4 3 3 4 3 2 5 4
Costs 3 4 3 2
Costing 2 2 4 4
Expenditure 4 3 2 3
IT expenditure 3 4 3 3
Revenues 2 4 3 4
Services 4 3 4 3
Service Provision 3 3 4 4
Products 2 2 2 1
Observation 3 3 3 2
Methology 5 5 5 5
Administration 1 1 1 1 2 4 3
Efficiency 3 2 4 5 5 3 2 4
Operational Efficiency 5 4 3 4
Decision Making 3 4 3 2
Evaluation 2 3 4 4
Informal Evaluation 2 5 3 3
Metrics 4 4 4 4 4
Benchmarks 4 4 3 2
Quality 3 3 2 3 5 3 3
Service 4 4 4 4 3 4 2 5
Flexibility 2 5 3 5
Scorecard 5 5 4 4 3 5 3 5
Key Performance Indicators 5 5 5 5 5 5 4
Measurement 5 3 3 3 4 4 4
Financial Measurement 5 4 4 4
Multi Criteria Measurement 4 4 4 4
Ratio Measurement 4 4 4 4
Portfolio Measurement 3 4 4 4
Net Present Value 4 5
Internal Rate of Return 4 5 4 5 4
Economic Value Added 4 4 3 5 3 4 4
Return on Investment 4 4 2 4 2 5 3
Payback Analysis 1 2 3
Game Theory or Role Playing 4 4 5 2
Simulation 4 3 4
Quantification 2 2 4 3 4
Qualification 2 3 4 3 3 2 4
Intangibles 4 4 4 3 5
Tangibles 4 4 4 4 4
Outcomes 4 4 4 4
Communication 4 4 4 4
Messages 1
Social Media 1
Online Communities 1
Military 3
Mining Industry 3
Healthcare Industry 4
Pharmaceutical Industry 4
Travel Industry 4
Finance Industry 4
Banking Industry 4
Computing Electronics Industry 3 2 3 2
Consumer Electronics 4 2 3 2
Technology Industry 4 3 4 3
IT Industry 4 4 4 2
Internet Industry 3 3 3 3
Internet Search Engines 4 3 3 3
Internet Forums 3 4 3 2


The weightings from the combined methodology could be built to provide rank and contextual parameters based around the motivations of the stakeholders providing material (and therefore weighting depending on submissions and feedback.


Logic, Computation and (f*(k?) Meming: On2logi+k,ing

10 Feb

Our human impulses are both sources for an solvers of random behaviour , chaotic order and clean representation. For organisations trying to measure what is happening online is still often unclear, as an individual mix of human and computational logic failures. What is curious about the relationship between organic and circuit based thoughts and actions is that the desire to overcome our own deficiencies and extend our reach leaves us vulnerable to the weaknesses of computing logic.  On a societal level this leaves many questions. For organisational governance it poses the question: should we be trusting our own judgement or should we ‘outsource it to machines’?

The #bigpaper example given in the previous post would to many have seemed a woefully creative and/or academic exercise. Merely to organise rewteeted material, who applauds a workflow which includes?:

  • Scrolling ones own collection of Tweets;
  • Copying a body of tweets into a word document;
  • Printing off that word document;
    • Going to a public environment;
    • Emailing it to the present peer given failure to bring wallet;
    • Printing the document and waiting for it to be printed;
  • Cutting the document into ‘Tweet sized chunks’ to include only image and message (trying to avoid cutting too close);
  • Reading each tweet again, pushing thematically each tweet into an appropriately themed pile;
  • Finding a table and pushing Tweets evenly across 2D plane to try and balance contexts and relationships;
  • Photographing Tweets both as a population, localised and at an angle;
  • Packing away Tweets into representative piles;
  • Examining photos (not nearly enough definition, repeat process with higher resolution);
  • Unpack Tweet piles and rearrange;
  • This time with improved iterative reordering of Tweets;
  • Include token signposting to provide order and visual signposting;
  • Photograph again;
  • Repack again.

Well done having the strength to get past that unexciting workflow!

Why did this need doing, let alone summarizing? Well firstly, when considering BIS, its important to have empathy concerning processes and the people that were/are confined with onerous, repetitive tasks (much in the same way with which a pilgrimage’s value comes from the journey as opposed to the destination). Secondly, it provides direct perspective concerning functions, challenging habits, providing insights and parallels for BIS environments. Thirdly, it provides the hunger for change and direction concerning what priorities and stages a solution should have.

The screencast in the other blog highlighted through photographic analogy informatics weaknesses concerning technology and processes and (seemingly) natural individual and organisational limiting factors (which may still exist as Big Data’s promises start to mature (but which hopefully appropriate BIS approaches would be able to mitigate)).

However, the frustration highlighted above downplays the fact that there were gains from using physical approaches (consideration time, treating information as a durable good and not a disposable resource). To reconcile these seemingly opposable approaches it is best to search for solutions which help to automate functions and logic steps (in a fully digital context, robots tooled with scissors are not quite within commercial reach…).

One of the challenges to implement functionality for ordering my material in a sophisticated way is that machines and computers are only pragmatically capable of operating within the functions trained by them. When arranging Tweets on a surface I had many complex and competing deliberations, which I either made with little effort (because the solution was clear) or considerable thought (because of ambiguities, complexity or too many choices). It is possible for computers to mimic these choices, let alone provide ones resembling (or improving upon!) human decision making was highlighted cleanly by Melanie Mitchell in the book Complexity: A Guided Tour:

Easy Things Are Hard
The other day I said to my eight-year-old son, “Jake, please put your socks on.” He responded by putting them on his head. “See, I put my socks on!” He thought this was hilarious. I, on the other hand, realized that his antics illustrated a deep truth about the difference between humans and computers.

The “socks on head” joke was funny (at least to an eight-year-old) because it violates something we all know is true: even though most statements in human language are, in principle, ambiguous, when you say something to another person, they almost always know what you mean.

Melanie Mitchell compared this human ease for distinction and interpretation with supposedly ‘state of the art spam filters’ which struggle to interpret V!a&®@ as spammer trying to vend. This computational challenge was expressed in terms of a computer being able to observe a pattern and then make the correct inference if the answer was not initially clear. To understand how much better computers can understand and solve analogies Mitchell worked for the AI researcher, Douglas Hofstadter on the “Copycat” program. This involved providing an example letter pattern jump and giving the computer exercises to make inferences. For example logic challenges could include:

“Consider the following problem: if abc changes to abd, what is the analogous change to ijk? Most people describe the change as something
like “Replace the rightmost letter by its alphabetic successor,” and answer ijl. But clearly there are many other possible answers, among them:

• ijd (“Replace the rightmost letter by a d”—similar to Jake putting his socks “on”)

• ijk (“Replace all c’s by d’s; there are no c’s in ijk”), and

• abd (“Replace any string by abd”).

An appropriate mathematical solution was found, involving a slipnet (network of concepts), a workspace (for the letters to reside), codelets (agents which explore possibilities) and temperature (a measure of organisation and control degree of randomness which codelets operated). Like performance management in the real world, the Copycat program had to identify the options, make an informed understanding as to how the decisions would be different and make a commttment.

Mitchell referred to a point earlier in the book, considering the activities of ants (insects which are dumb in isolation but which hold significant levels of intelligence once they reach a certain volume). Whilst ants would normally go for the most obvious food source (the place the other ants were going to or the direction returning ants with food were returning from) there would be a normal deviation involving ants taking new courses. This provides a unconscious balance between the short term expediency for food with longer term opportunities for sustainable food sources.

Screenshot from 2013-02-11 00:39:38

Identifying and implementing logical and mechanical solutions for organising social media paths do take time. However, they can pay dividends if the sheer cost of not automating functions exceeds the cost of either:

  • Outsourcing that functionality,
  • Buying an off the shelf solution,
  • Tinkering/customizing with available solutions,
  • Designing and implementing specific solutions.

To give a practical example, an analysis was taken of a recent Guardian article on the UK’s new spare bedroom tax for those on welfare and its corresponding 100 posts. Using a demo for a keywords text extractor  it was possible to create a breakdown of key terms for the article and each post. Entered into an excel spreadsheet, the exercise became more onerous than the Twitter arrangements. Although technically sifting through appropriate and inappropriate keyword solutions, the comments in isolation created variances that the tool was not going to deal with. The keyword list exceeded the Twitter population in terms of volume and diversity (this is partly because of the lack of a word limit), especially when considering duplicates. Here is one example covering taxes and benefits:

tax 11
tax.It 1
taxes 4
poll tax 2
Poll Tax 1
council tax 6
annual council tax 1
bedroom tax 14
new bedroom tax 1
extra bewdroom tax 1
percent beedroom tax 1
housing tax 1
Negligence Tax 1
window tax 2
tax avoidance schemes 1
tax planning rules 1
income/ benefits 1
pay/benefits 1
benefits 2
benefit 1
tax credits 2
council tax benefit 1
Employment Support Allowance 1
government pay 1
government assistance 1
Work Programme 2
programmes 1
Incapacity Benefit 0
basic benefit 1
Discretionary housing payments 1
Discretionary Housing Payment 1
housing benefit 6
Housing Benefit 2
HB 4
brand new HB 1
PIP conversion 1
decision 1
benefits measure 1
home allowances 1

Aggregating seperate analyses introduced problems in regards to multiple permutations from accidental or deliberate erring from standard explanation, emphasis, plural/singularity or spelling. Given that the process used or the tools analysis does not reconcile this we end up with upper case and lower case keywords being separate and descriptors and terms being welded together. In addition, parent child relationships between terms or titles do not appear strong (perhaps through conservatism of the software that could be tweaked). Terms such as coalition or Liberals are not carried or captured with cultural sensitivity (the UK’s government in this instance).

Copying and then breaking down the keywords into manageable or personalized themes or categories was onerous (although this is partly a lack of tools for reprocessing). Reordering the material takes time on a human level (although ironically resembling the process of disk defragmenting, see image of extracted keywords with markers to post author below after part of the keywords were moved to another excel sheet for clarity).

Screenshot from 2013-02-11 01:34:33

To capture the whole chain of appropriate keywords using this technique although imperfect (it is like considering the world as if it is a grain of sand and then commencing an audit of the universe). It is amazing however examining what keyword extraction is able to offer for just one discussion thread in terms of verbal emphases, especially when related to information, point, emphasis and debate (particularly when sources such as the Guardian offer quantifiable recommend numbers).

The keywords extracted cover the individual topic pretty comprehensively. Once interpreted effectively, especially with terms synthesized and broke down to base meaning and interaction it is capable of providing strong specialised meaning. At a rule base level once that sophistication point is reached scalable and sophisticated analysis, communications and campaigning is possible. As alluding to in my previous post, it is possible to map for solutions problems and issues. In many ways sentiment analysis is already offering this (although is still prone to errors similar to explained above). Getting to a more meanings based level that takes in human and computing errors would provide a clearer understanding regarding the topic (although it would be more consistent using personal judgement for many of the keyword themes in this example, given the cleaning required to counter the volume of computing keywords).

Perhaps it is apt to highlight the work of Joseph Weizenbaum, a member of GE’s team in 1955 to build the first the first computer system dedicated to banking operations and whose technical contributions includes the list processing system SLIP and the natural language understanding program ELIZA, which was an important development in artificial intelligence.

“…Named for the heroine of My Fair Lady, ELIZA was perhaps the first instance of what today is known as a chatterbot program. Specifically, the ELIZA program simulated a conversation between a patient and a psychotherapist by using a person’s responses to shape the computer’s replies. Weizenbaum was shocked to discover that many users were taking his program seriously and were opening their hearts to it. The experience prompted him to think philosophically about the implications of artificial intelligence, and, later, to become a critic of it.

In 1976, he authored Computer Power and Human Reason: From Judgment to Calculation, in which he displayed ambivalence toward computer technology and warned against giving machines the responsibility for making genuinely human choices. Specifically, Weizenbaum argued that it was not just wrong but dangerous and, in some cases, immoral to assume that computers would be able to do anything given enough processing power and clever programming.

“No other organism, and certainly no computer, can be made to confront genuine human problems in human terms,” he wrote.”

In order to circumnavigate historic failures of intelligent comprehension in computing logic the commercial providers online stuck to using “Recommended by…” algorithms comprising of aggregate or contextual navigation and consumption patterns. Perhaps, rather than reinforcing our human approaches online, perhaps we have become more like the ants?

Although the keyword analysis provided a more simple and one off demonstration, one should not discount the value of more complex and custom built analyses. However, the concerns regarding the processes and stages of a human analysis disappear once the reality of having to automate such functions kick in. There are tradeoffs concerning subtlety. For BIS approaches to performance management it is dangerous to assume that buying a machine solves the problems of the human functionality for some cost. Without knowing what is under the hood or at a bare minimum what are the qwerks then there is a risk that complexity will create unknown risks to organisational governance.


Other blog posts in the Order From Chaos miniseries include:

  1. Order From Chaos: Performance Management and Social Media Analytics in the Age of Big Data;
  2. Abstraction, Perspective and Complexity: Social Media’s Canon of Proportions;
  3. Logic, Computation and (f*(k?) Meming: On2logi+k,ing;
  4. Transposition, Catalysts and Synthesis: Playing with iMacwells eDemon.

More than just eCoal, eSteam and ePower: The Modernizing Dynamics of Change Series

  1. Introduction;
  2. Economic requirements: Catalyst for Invention, Innovation and Progress
  3. Not Just Invention: Change Through The Desire to Innovate, Reimagine and Expand;
  4. New Tools, New Patterns, New Thoughts: the Great Dialogue;
  5. Nobody Will Notice The Slow Death of Dissmeination, They Will Be Too Busy Listening;
  6. The frictions of competition and cooperation to strategic thinking;
  7. The Hot and Cold Wars: Relationships and conflicts between big and small, propriety and open source.


If you have any suggestions, relevant links or questions to add flavour to this series then please join the dialogue below or contact me via Twitter:

Abstraction, Perspective and Complexity: Social Media’s Canon of Proportions

10 Feb

One of the great failures of the Web 2.0 era is that its architects have built cathedrals centered around the self, the hooking of other entities that encourage aggregate as opposed to selective or contextual information and the informatic prioritisation of time over meaning. This often results in:

  • misalignment of priorities, as a result of individual or wider overvaluing of totems such as ‘followers’ quantities;
  • too much energy being dissipated by users running on a hamsters wheel, sifting through in time messages and updates;
  • cursory acknowledgement of information or signposts but not enough time to understand or revisit.

In many instance this can be unproductive, particularly as even obeying norms of usage is working within the inefficiencies of the ecosystems. Whilst it would be interesting to speculate on the economic and cultural reasoning as to why this outcome would emerge and ways of rectifying it in spite of economic drivers (such as the network effect) tethering many online actors and entities to inefficient processes and communities, it is perhaps better instead to highlight on failures of the current orthodoxy. This is done not only to highlight productivity and organisational failures of modern messaging tools, highlight clear and practical advice for current users but also provide positive direction for iterate improvements and destructive alternatives.

Screenshot from 2013-02-11 01:46:26

To provide an analogy covering challenges regarding information and communications a body of tweets collected from the Social+Informed Twitter account (used for earlier blog posts featured on sopinion8ed). It was created to highlight the need for organic approaches to categorization to manage complexity, as well as navigate tradeoffs that large data flows create. In particular it deals with the challenges regarding complex systems’ structures and approach to looking at bodies of information as if they are interlocking organs.

In this instance, the population evolved to exist into four main categories:

  • Strategic level Tweets (red);
  • Managerial level Tweets (green);
  • Processing level Tweets (blue);
  • Informatics components level Tweets (yellow).

Naturally this solution was not elegant for Tweets containing a message covering more than one of these main categories. In such instances a parent category was chosen but a coloured token for the second choice category was given to signify association. Additionally, given that one of the guiding themes of the Social+Informed account was for social social business generated important information on open source technologies and social entrepreneurship extra tokens were additionally created (white and brown). Similarly, to highlight GIS and visualisations coins were used and for cloud computing buttons.

Within mini clusters of similar themed tweets an effort was made to coordinate twinned Tweets in the closest directions. As intentioned and improved with each ordering iteration the mini clusters became more homogenous and neighbouring clusters more complementary to each other. For example, category borders would be similar in themes and corporate/organisational activities were at the borders whilst more general themes tended to be closer to the core. Perhaps naturally, information systems themes Tweets resided closer to the very centre, given the general nature of the themes and the mix of technology, process and peoples that such messages would cover.

The consequence of this synthesis is not only to create an archive of old material in a now more accessible format than what date the Tweets were created or what a common ‘find’ search query can offer. It helped offer:

  • A clarification of overriding themes that have already been explored and how they interrelate or are dissimilar;
  • An overview of themes and experts for this sample;
  • A framework for mapping out and quantifying/qualifying based around context and parameters future initiatives;

Whilst of value, such explorations emphasize the inefficient nature of Twitter as basic tool needing more sophisticated interpretations than the following/follower dynamic. As a simple method of mitigating this (for internal efficiency or external efficiency (ie, less ‘white noise’ for followers)) it is advisable to be operating multiple accounts dealing with specialist themes (which can be managed by either multiples browsers with multiple Twitter accounts running or an excel sheet to ‘bank’ into differing category themes Tweet urls of interesting messages until those user accounts are activated again. Here are some examples:

metr1c1de, covering benchmarking

secureitie, covering security

datam1n1ng, covering data and statistics

managechangeit, covering management, change and IT

[Screencast to come. For now, please use right click images below for satiation to see definition, using ctrl+ to zoom in and understand detail]

01 - DSCN6994

‘Database’ of Tweets

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Tweets laid out into starting categories

04 - DSCN6988

First attempt at positioning Tweets into spread thematic plane. The camera quality results in too poor an image level for legibility

07 - DSCN7002

Second attempt at positioning Tweets into spread thematic plane. The lighting, camera quality and higher abstraction level as a result of further spaced out Tweets renders the messages unreadable.

08 - L1130338

Third attempt at positioning Tweets into spread thematic plane. Notice how the tradeoff for an aggregate view makes legibility of Tweets too difficult

09 - C-B - L1130343

Third attempt: Close up on management related Tweets. On closer inspection notice sunlight’s effect on readability of Tweets

09- C-R - L1130344

Third attempt: Close up on strategic related Tweets

09 - C-B -  L1130361-2mb

Third attempt: Close up on analytic related Tweets

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Third attempt: ‘Specialists’ viewpoint


Other blog posts in the Order From Chaos miniseries include:

  1. Order From Chaos: Performance Management and Social Media Analytics in the Age of Big Data;
  2. Abstraction, Perspective and Complexity: Social Media’s Canon of Proportions;
  3. Logic, Computation and (f*(k?) Meming: On2logi+k,ing;
  4. Transposition, Catalysts and Synthesis: Playing with iMacwells eDemon.

More than just eCoal, eSteam and ePower: The Modernizing Dynamics of Change Series

  1. Introduction;
  2. Economic requirements: Catalyst for Invention, Innovation and Progress
  3. Not Just Invention: Change Through The Desire to Innovate, Reimagine and Expand;
  4. New Tools, New Patterns, New Thoughts: the Great Dialogue;
  5. Nobody Will Notice The Slow Death of Dissmeination, They Will Be Too Busy Listening;
  6. The frictions of competition and cooperation to strategic thinking;
  7. The Hot and Cold Wars: Relationships and conflicts between big and small, propriety and open source.


If you have any suggestions, relevant links or questions to add flavour to this series then please join the dialogue below or contact me via Twitter:

Information Systems Quality – Design

10 Feb

The Future of Design:

As the world is becoming more computerised the need for more and more systems will grow. The design process needs to evolve as new systems and mediums are developed. Ten years ago the idea of using tablet devices and the complexity of our smartphones was only a thing of science fiction and Palo Alto research labs (PARC). The internet is now at the fingertips of over a billion people and growing by millions every day. It is only in the last few years that Africa has been wired for high speed internet, who knows what these new users will create. The range of applications is also growing, from specialised weapon systems to everyday smart phones and gaming consoles.  There is a growing need to match the right systems to the right users. There is also a growing degree of expertise, users are more selective than they used to be and more understanding of what they are buying. The growth of the gaming industry into the mainstream has led to a need for more interactive or fun experiences, users no longer like the traditional text based approach.

Due to all of these advances in the marketplace the need for a competitive edge will led to new design features. Here are a few many experts believe will be used;

  • Distributed Systems: The development of innovative user interfaces is increasing access to distributed information sources. People ‘surfing’ the net are no longer just programmers looking for interesting pieces of code.
  • Multimedia Interfaces: Text is still the most significant form of interaction with computer systems. Increasingly, however, we have the problem of integrating it into graphical, video and audio information sources. The technology is relatively straightforward, the design is not.
  • Advanced Operating Systems: Many of the changes described above are being driven by changes in the underlying computer architecture. Increasing demands are made upon processing resources by graphical and multimedia styles of interaction. [1]
  • HCI Development Environments: On top of the new generations of operating systems, there are new generations of interface development software. Many of these environments extend the graphical interaction techniques of the Apple desktop to the construction of the interface itself. For perhaps the first time, users may be able to customise their working environment. This creates opportunities but also carries high risks if many different users must all operate the same application at different times.


Other Sources:




IS Success Canvas?

10 Feb

Success is a lousy teacher. It seduces smart people into thinking they can’t lose.  –  Bill Gates

IS Success Canvas?

The DeLone & McLean IS success model was instrumental in identifying the key dimensions of IS success, and remains robust in most regards, as outlined in Petter et al (2008). However, Gable et al (2008) have excluded the constructs “Use” a consequence of IS Impact and not a dimension, and “User Satisfaction” which is measured indirectly under the other variables.

Fortunately, for any practitioner seeking to evaluate IS success within an organisation, it is not necessary to invent the wheel. Many valid measures have been identified tested and refined. Sedera et al’s Multi-dimensional IS Success Instrument for example, takes into account many of the concerns outlined in Seddon (1999), and has collected and tested success measures, combining them into a comprehensive 27 measure IS Success Instrument from an initial 37 items in total.  –  (See Gable et al (2008) for list of measures.)

In my previous post (Relatively Successful IS) I presented some of the concerns raised with regard to type of IS, stakeholder perspective and organisational context etc. in determining IS success. In particular, the context matrix presented in Seddon et al (1999) stands out as identifying the challenges and providing direction in tailoring an evaluation to a particular perspective of success. However, it remains doubtful that all of these contingencies will ever be entirely controlled for.

The challenges of relating an (ideal) IS success model concept to a practical context are reminiscent of Osterwalder, A., Pigneur, Y., & Tucci 2005, and so many others’ quest to establish the dimensions of the “Business Model”. While in academia the research continues, in practice, Osterwalder’s “Canvas” provides a framework, informed by the research, into which various users/stakeholders from various contexts etc., can input their own specific content. I would suggest designing a framework much like the Business Model Canvas, whereby all perspectives etc, can be accommodated. The IS Success Canvas framework would be informed by the knowledge gained through DeLone & McLean, Seddon et al, and Sedera’s modeling and research.

Success consists of going from failure to failure without loss of enthusiasm.’ –  Winston Churchill


Gable, Guy G. and Sedera, Darshana and Chan, Taizan (2008) Re-conceptualizing information system success : the IS-Impact Measurement Model. Journal of the Association for Information Systems.

Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236-263

Seddon, P. B., Staples, S., Patnayakuni, R., & Bowtell, M. (1999). Dimensions of information systems success. Communications of the AIS, 2(3es).

Osterwalder, A., Pigneur, Y., & Tucci, C. L. 2005. Clarifying business models: Origins, present and future of the concept. Communications of the Association for Information Science (CAIS)

Information Systems Quality – Design

10 Feb

In my last few blogs I wrote about the change in perception of design towards that of major importance over the last thirty years, on design processes, Design Science and of Human Computer Interaction. I this blog I want to write about the gains that investments in design can give your business, and how Google changed the way we design websites. Many experts today believe that design is the only distinguishing factor between items, many businesses can easily copy other people’s ideas but their designs may be why they sell better.

Design Investment:

£20 billion is spent a year in the UK on design, leading the UK to be on the forefront of most design frontiers, design is also the largest the biggest single source of intangible investment in the UK. In the video below they refer to the relationship between the clients and designers as the most important, you might have the best architects or designers in the world but your client really decides what they need and how they need it. If the client knows what they want and they are paired with an accomplished designer then they will have a very prosperous relationship. Design will encourage innovation, creates competitive advantage and drives growth.

David Frost,Director General of the British Chambers of Commerce said;

“Anybody now can turn out any product, what will differentiate is that unique design flare that’s built into a product, that’s what creates the value.” [1]

IS Design and Minimalism:

 It’s very obvious how much the design of websites has changed in the web 2.0 years when compared to the earlier years of the net. Today websites try to be simple and direct, why bug your viewers with annoying graphics and distractions. Google I believe has led the way in this new era, when they launched at the turn of the 21st century their homepage was so bare in comparison to Yahoo etc. Google realised that people preferred to see their site because it was simple and easy, the search bar is in the middle and there are no distractions.



IS systems today are also trying to be easier to use, SAP one of the world’s largest business intelligence systems is very bright and menu friendly, with home buttons and easy to navigate screens. Your customer should always be given what they want and judging by the success of these simpler designs, they may be the future of IS design.


“Making the simple complicated is commonplace; making the complicated simple, awesomely simple that’s creativity” Charles Mingus [2]

Information Systems Quality – Design

8 Feb

In this blog I wanted to outline two very important approaches to the design process, both are very successful at leading developers to better design and information system quality. They are 1) Design Science 2) Human-Computer Interaction;

Design Science:

A paper by A. Hevner et al. called ‘Design Science in Information Systems Research’ published in the MIS Quarterly in 2004 has been an excellent source for me when researching this topic. The paper describes design science essentially as a problem solving tool, if the design process wasn’t part of IS development process then the problems would undoubtedly leek into the system and a of course a fall in quality. The paper recommends following a seven step guideline to avoid your system leaking problems, see the figure below.  Hevner et al, outlines why they conducted their research;

 “Our purpose for establishing these seven guidelines is to assist researchers, reviewers, editors, and readers to understand the requirements for effective design-science research.”[1]

 They also recommend researchers and developers to use their creative skills and best judgement to determine when and how to apple these seven guidelines.


Within the paper the authors propose to two fundamental questions for design science, 1) What utility does the new artefact provide? 2) What demonstrates that utility? I believe that these questions will prove very useful in future research into the area of design implantation.

Human-Computer Interaction (HCI):

Another well published design process method is Human-Computer Interaction (HCI), this method places the design in the middle and asks what tasks, technology and human interaction will my system need to be able to handle, see the diagram below. This HCI method factors in organisational and social issues as well by distributing the factors amongst the three inputs. [2][3][4]


Within this process in the user interface development process, this is another guideline to design, then, evaluate and finally execute your idea or system. This includes using storyboards, proposals and prototypes; each test/re-test phase eliminates errors and leads to better design and in turn better quality. There is a sense of cyclical process within HCI, at every stage you design, prototype and finally evaluate. Only when you are happy then should you move onto the next development stage.


Taking from the old to create a new.

8 Feb

The attempt of creating a modern framework which contributes to BPM must draw off the older frameworks and use the knowledge which they created and expanded on. Then move forward from that point.  As “the measurement mantra continues to reverberate throughout nearly every corridor of business life” [1]. In the light of drawing information from old ideas and building on them I will draw firstly from information gathered from the department of trade and transport UK. According to the UK’s department of industry and trade (for the case of this blog I will coin the department of trade and industry as DTI) there are four key steps in a performance measurement framework.

  1. The strategic objectives of the organisation are converted into desired standards of performance.
  2. Metrics are developed to compare the desired performance with the actual achieved standards.
  3. Gaps are identified.
  4. Improvement actions are identified. [2]

The UK DTI demonstrates simple and intuitive steps to creating a framework for BPM where they also state that for a simple framework/methodology keep it simple and smart. The DTI created a very intelligent little acronym which is to be applied to the development of a simple framework i.e. Specific, Measurable, Achievable, Relevant and Timely = SMART. The application of these attributes to the strategy will lead to direct returns from the framework in terms of measuring performance. The simple performance measurement framework described by DTI is like the EVA and ABC frameworks because it acts as a complimentary addition to the Balanced Scorecard framework.

Simple Measuring Framework


The Balanced Scorecard Framework

The balanced Scorecard is the most adopted framework in business performance measurement and it was introduced by R. Kaplan and D. Norton in 1992. The Balanced scorecard approach was to focus on leading indicators of a business rather than the lagging indicators. Lagging indicators are the measurement of actions, sales and data recorded which have already taken place i.e. past performances whereas leading indicators are the measurement of future performances such as financial performance, customer satisfaction, customer growth, customer defection and other business related predictions. The Balanced Scorecard was redesigned to measure the components which make up a business’s strategy in 2001 and it is composed of four perspectives i.e. 1. The financial perspective 2. The customer perspective 3. The Internal Business  and 4. The Learning and Growth perspective.

“The financial perspective The strategy for growth, profitability and risk from the shareholder’s perspective.
The customer perspective The strategy for creating value and differentiation from the perspective of the customer.


The internal business perspective The strategic priorities for various business processes that create customer and shareholder satisfaction.
The learning and growth perspective The priorities to create a climate that supports organizational change, innovation and growth.”


Image of the Balanced Scorecard



Economic Value Added ( EVA); EVA is a metric of financial performance  and according to its developers at Stern Stewart Company, “ it is directly linked to the creation of shareholder value” [4]. Stern Stewart Co. developed a formula for EVA which is EVA = (Net Operating Profit After Taxes) – ( Capital *Cost Of Capital). The advantage of using the EVA framework is the information and motivation it gives to managers in relation to making decisions  to create the most shareholder wealth. The EVA framework is complimentary to the balanced scorecard framework and according to Kaplan “Using EVA alone can cause managers to invest in less risky, cost-reducing activities rather than in growth activities and as a pure financial model, EVA cannot serve as a vehicle for articulating a strategy. But coupled with the BSC, the trade-offs between short-term productivity improvements and long-term growth goals can be managed (Kaplan 2001)”[5]. The EVA framework is an excellent model for the internal measurement of a business. Therefore when it comes to determining the contribution of information systems to business performance, the results would be clear and precise direct returns from IT.

Image detailing the aspects of the EVA framework.




Activity-Based Costing 

ABC like EVA can be complimentary to the balanced scorecard framework. When applying the ABC methodology companies will gain valuable knowledge in relation to which business activity and which business activities are profitless. “ABC, then is a way of measuring which of the firm’s activities generate revenues in excess of costs and as a result, provide keen insight into what is really providing value for customers (Meyer 2002).”( Meyer, Marshall W. (2002). Finding performance: The new discipline of management, in Business Performance Measurement: Theory and Practice. Neely, Andrew, editor. Cambridge University Press.)[6] The activity based costing like EVA can be of benefit to assessing IS/IT contribution to business performance, due to the fact that it’s a financial related measure and that it looks at it activities within the business to determine which are performing and which are under performing. The reason it is of benefit is that ABC highlights certain activities of financial measures and when then the determining looked at under a microscope IS contribution is made evident.





3 The Balanced Scorecard. 2001, R, Kaplan and D, Norton.

5. The Balanced Scorecard. 2001, R, Kaplan and D, Norton

6.  Meyer, Marshall W. (2002). Finding performance: The new discipline of management, in Business Performance Measurement: Theory and Practice. Neely, Andrew, editor. Cambridge University Press.


Building Business Performance

7 Feb

This video shows why measuring Information Technology can pay off for a company
I got this off youtube and the video was made by ATT Enterprises
This video shows the importance of not just measureing how new technology investment benefit a companies performance but managers need
to look at at there hole entire technology platforms.
In the video they mention a couple of very important areas or Business Enablers,that need to be in place to make investment in new technologies payoff these are as follows:
1. Skills
3.Digital Platform
So a company thats thinking of investing in new technologies needs to also invest in these business enablers to make it increase company performance
All the Frameworks in the world can be in place to measure buiness performance from investment in new Information technology and alot of these frameworks have been covered in previous blogs not just by myself but by others, there is a need by managers to take a look a there existing Informations Systems and work from there, while i do feel the video above covers this point well it also shows the benefits that a company can recieve from measuring IT and business performance.

Information Technology and company Performance

6 Feb

I Came across this article which I feel offers great insight for managers to help them understand why Information technology measurement is so important, this article is called
“Information Technology and Organizational Performance An Integrative Model of IT Business Value” and is written by NIGEL MELVILLE, KENNETH L. KRAEMER AND
VIJAY GURBAXANI, I found it on a website…1… – United States”
It Cleary states that there is a clear importance of researchers ,managers and policy makers on the way information technology can benefit a company’s performance, a certain degree of uncertainty lies about what we know and don’t know. The authors of this article have completed a review and came up with the association between information technology and organisational performance and how there are differences in how companies see key elements and there interrelationships.
They then go onto building a Model of IT business value based in a resource based veiw of the firm, this model goes onto integrate the different strands of research into a single framework. From this they then look at how other researchers have modelled IT business value, they concluded that the locus of IT business value generation is the company that has invested in and deployed IT resources, they go on to call this the “focal firm”, But the point that I found to be most interesting in terms of the use managers will get from this is that they have looked at external factors also and how they play a major role in shaping the extent to which IT business value can be generated. They seem to focus in on one area in particular and that is the area of competitive environment- this will include industry and characteristics and trading partners, also they used the macro environment, from this the researchers then derived a integrative model of IT business value that is made up of three domains 1.focal firm,2. Competitive enviromnet 3.macro environment, they then used a resource based view between each of the 3 mention above and how they shape the relationship between IT and Organisation performance see model below-


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