Adapted Balanced Scorecard Framework

22 Feb


For our framework, we decided to base our idea on the well established and highly successful Balanced Scorecard framework. After conducting research for our individual blogs we found that the Balanced Scorecard was very prevalent among academics and professionals involved in the performance measurement field. However, we have made an alteration to the framework in order to focus it more towards the IS investment performance. Our framework consists of five different parts which we feel are vital to any company trying to establish the contribution of their IS investments to business performance. These five parts are: Financial, Users, Quality, Internal Business Processes and Transformation.

Framework: Adapted Balanced Scorecard


(1) Financial

As aplusk22 has mentioned, the financial element is a crucial part of effectively measuring the business performance of an IS investment. Ultimately, the goal of any company is to make a profit. This can be achieved through IS investment but the only way to determine this is through the process of measurement. Financial ratios are a simple, yet effective way of measuring the business performance of an investment in Information Systems. Perhaps the most relevant ratio is the Return On Investment (ROI). Simply put, the ROI establishes the revenue earned against the initial cost of the investment. A high ROI shows that investment gains compare favourably to the investment costs. If the detailed information is available, a comparison against competitors provides a useful way for management to assess relative performance with regard to IS investment.  It’s important to consider the following: information systems are intended to provide relevant information for decision-making which ultimately contributes to better decisions and as a result increases the return on investment [1]. Evaluation of the information systems is a multi-dimensional and multi-criteria task. ROI is a financial measure and does not provide information about efficiency or effectiveness of the information systems themselves [1]. We must also remember that the Financial element will play a part in each of the other four elements of our framework.

(2) Users

Customer service and satisfaction are becoming increasingly more important to businesses today. The concerns of users and their satisfaction are now incorporated into many companies’ mission plans. Therefore the user’s perspective of how a company is performing has become a main priority for management in many firms. It is for this reason we feel is it important to include the area of the customer in our framework for measuring IS business performance. To implement this framework, companies must articulate goals according to their mission and vision for their company, and then translate these goals into specific measures. An identification of measures that answer how a customer perceives a company is of vital importance to any company, and they seek to develop an ongoing relationship with the user from evaluating the results of these measures. These measures can include – customer retention rate, customer satisfaction rate, delivery performance to customer, quality performance to customer and customer percentage of market.  The main concerns of users generally fall into the four main categories of time, quality, performance and service and cost. Many IS investments provide intangible benefits, which resist traditional measurement techniques, and so the full potential of them is not always realised. IS customer measures measure the quality and cost effectiveness of IS products and services. As cdat2 mentioned in her blogs, when attempting to assess the impact of these information systems on business performance the following questions should be considered:
1) How well are business unit and IT staff integrated into IT systems development and acquisition projects?
2) Are customers satisfied with the IT products and services being
3) Are IT resources being used to support major process improvement efforts requiring information management strategies?

(3) Quality

Although the measurement of quality is a feature in many business performance frameworks, we believe it is of such importance that it should be an entire section of its own. We believe that the quality of the information systems impacts greatly on a company’s performance and so it is an important part of our framework. In IS quality can be grouped into different metrics such as system quality, software quality, Information quality, and service quality. Of these, system quality and software quality are closely related as both relate to the technical aspects of a software system. [2]

Information Quality: This relates to the desirable characteristics of the system outputs including: relevance, understandability, accuracy, conciseness, completeness, understandability, currency, timeliness, and usability. A way to measure this would be using the “User Information Satisfaction (UIS)” this method has been used for a variety of information systems quality measures. The User Information Satisfaction (UIS) is a seventeen-item questionnaire, which employs the use of scales to assess the user’s level of satisfaction with an information system it includes thirteen specific items, broken into three factors of Information Systems Personnel, Information Product Quality and Knowledge and Involvement.
System Quality/Software quality: The desirable characteristics of an information system, such as: ease of use, system flexibility, system reliability, and ease of learning, as well as system features of intuitiveness, sophistication, flexibility, and response times, ways of measuring the effectiveness are:
•          Completeness: Which part of the needed features are actually implemented
•          Asking users: What is the feeling of typical users about the software?
•          Metrics: Some metrics can give you a good idea about the quality of the code
•          Process: The use (or not) of certain processes is a good hint about the quality of a development process. Bug tracking, automated tests, versioning tools… [3]

Service Quality: The quality of the support that system users receive from the IS department and IT support personnel, such as: responsiveness, accuracy, reliability, technical competence. This can be measured using the SERVQUAL method, this consists of two section, both containing 22 questions. The first section measures service expectations of companies within a certain industry. The second section measures the customers’ perception about a particular company in that industry. [4]

(4) Internal Business Processes

As le1008 mentioned in her blog, an organisation’s internal business processes are a very important part when measuring the performance of IS investments in a company. These processes are critical for satisfying both the customers and shareholders of a company. IS investments can contribute greatly to the improvement of business processes within a company and this in turn leads to a company achieving its objectives. It is therefore important to include this aspect in our framework. The business processes of a company is an area where measurement takes place on things managers know and manage on a daily basis. Business processes include measures such as cost, throughput and quality. These are for business processes such as production and order fulfilment. Activities in which the company excels and also in what it must excel in the future should be identified. Metrics for measuring business processes have to be carefully designed by management in order to measure performance. These could include a reduction in unit costs, reduced waste, improvements in morale within the company and increased productivity.

(5) Transformation

As cdat2 previously mentioned an IT performance management system should consist of a diverse set of measures, which in turn need to be assessed in varying manners. To critically view the transformation the firm has undergone it is vital to clearly map out the firms state before implementation, the goals set out and the actual results attained. Comparing the three sets of figures will clearly display to executives the effectiveness of the IT investment. Positive figures will act as motivators for the firm to reach their maximum capabilities and less optimistic ones will enable firms to alter methods and drive the company to reach their potential abilities.

The most effective way to measure the firms’ transformation and progression is through simple performance measures such as input measures (number of IT workers, number of computers), output measures (number of projects completed, helpline call duration), outcome measures (customer satisfaction, cycle time reduction) and also a combination of single measures. Combinations of single measures combine output, outcome, and/or input measures into measures designed to demonstrate improvements in efficiency or effectiveness. Efficiency IT metrics measure the performance of the IT system itself including throughput, speed, and availability. Effectiveness IT metrics measure the impact IT has on business processes and activities including customer satisfaction, conversion rates, and sell-through increases. Wide ranges of measures provide a balance for different decision maker needs. The key point is that the right measure is used at the right time and for the right reason. [5]
Input and output measures are absolutely vital for measuring how well a process to deliver IT products and services is performing.

Conclusion –

Having factored in the usefulness of the Balanced Scorecard, we felt our adaptation of the framework is more suited and geared toward assessing the impact of IS investments on the overall business performance of an organisation. It is our belief that the framework should consist of five parts and each part is of equal importance in terms of contributing to the impact of IS investments on business performance. We believe that keeping the framework simple and easy to understand is of paramount importance.





[4] An Examination of Information Systems Service Quality Measurement: Texas A&M University( 2005)

[5] Daniels, H. C. (1993) Information Technology: The Management Challenge, Addison- Wesley Longman Publishing Co., Inc.

Context Adaptation of D&M IS Success Model (2003)

21 Feb

In researching IS success models for our individual blogs, it was clear to see to all that the framework or model put forward by DeLone and McLean in 1992 and revised in 2003 was the basis for the majority of other academics when they were creating their own IS success framework. With that in mind and since the majority of our blog posts were either about the DeLone and McLean model or related to it, we decided to use that as our foundation.

Context Adaptation of D&M IS Success Model (2003)

Information systems success within an organisation can depend on the culture within the organisation and that’s why culture is the first dimension on our framework as mentioned in AndrewFitz22’s blog “How culture can impact on information systems success
According to Ismall [1] in regards to information systems, culture is one of the determinants in its success. Also culture can impact on how innovation within the organisation can improve information technology practices and overall organisation performance.
Culture impacts on an organisation in the following three ways
1. Provides unspoken guidelines to employees on how to get along with each other in the organisation and enhance the stability of the social system in the organisation.
2. Enabling the ability to deal successfully with problems from internal integration and external adaption.
3. Culture also enables differentiating between in-group and out-group people.

Organisational Structure
Decision Making Structure: There can be two sides associated with implementing a proper decision making structure. If a company decides to choose a decentralisation process studies have shown that it is “one of the strongest facilitators for the adoption of customer-based inter-organisational system and IT system in large and complex organisations”. Studies have also shown that there are benefits of a centralised organisation. Results have highlighted that a “better management effectiveness for end user computing” exists and also that there is a greater chance of successful “strategic information systems applications” (Hussein et al, 2007). These both in turn would have an impact on IS Success.

Goal Alignment: This factor outlines the effect of linking up both Business and IT goals. If both these goals are aligned and have a clear direction in which they both are headed it can help in achieving IS Success.

Resources Allocation: This factor categorises resources into money, people and time. These three should then be managed properly by ensuring that sufficient money is available, the right people are in place and there is enough time to complete a IS project thus in time helping to lead to IS Success.

Top Management Support : “Top management support is defined as: devoting time to the [IS] program in proportion to its cost and potential, reviewing plans, following up on results and facilitating the management problems involved with integrating ICT with the management process of the business. “It’s important to consider the role which top management support plays in Information System success. Despite its relevance, “Practitioners and Researchers alike have focused their attention o factors they can more directly control and appear to only pay lip-service to TMS.” Young and Jordan, (2008), examined IS projects as due to their high costs it is critical for organizations to achieve success. “An issue demanding board level attention because of the high levels of investment and the strategic consequences of failure.” The work of Young and Jordan, (2008) highlight the importance of TMS, and declare it the most important critical success factor. While Young and Jordan present a concise argument in favour of TMS as the ultimate CSF, there are additional organizational factors that play a role in determining IS success.

Management Style: “Management style deals with the way in which management tends to influence, co-ordinate and direct people’s activities towards a groups objectives.” Hussein et al, (2007). A review of the literature would suggest that management styles impact on communication within the organization, and ultimately on the productivity of the users. “Lu & Wang’s study (1997) seems to support the major finding in Igbaria et al.’s study(1990) on the relationship between leadership style and user satisfaction. Both studies found that leadership style and system success are correlated significantly and positively.

Managerial IT Knowledge: Another organizational factor which is important to consider is Managerial IT knowledge. “Managerial IT knowledge refers to senior management experience and knowledge concerning information technology.” Logically it makes sense for senior management to understand the technology behind IT projects, in order to realize the benefits an organization can accrue through successful implementation of IS. Research has revealed that the IT knowledge of senior managerial staff directly and positively impacts on IT utilization, Boyton et al (1994). Therefore it is in the interest of organizations to employ those with a background in the related field. A manager who is aware of the technology, value and risks may then manage the project accordingly.

Our model has removed the direct relationships, drawn as arrows in the D&M model, between the six dimensions of IS success. Instead, lines connect five dimensions; service, information, and system quality, use, and user satisfaction. This is intended to demonstrate that these five dimensions interact and ultimately impact upon the net benefits of the information system, shown by a double arrow. The arrow is double sided to indicate that these benefits feed back into use and user satisfaction, like in the D&M model (2003). The arrows have been removed given the lack to support to date for the direct relationships between the dimensions at an organisational level. Neither is the model intended to be a process or causal model explaining the determinants of success, but instead is aimed to communicate that each of these dimensions impacts upon the success of an information system. If a system is not deemed a success, through an IS balanced scorecard for example, then each dimension can be examined to identify in what area the system is weak. Although this may satisfy practitioners, academics will still question the relationships between the dimensions of IS success.

Dimensions of IS success
When examining the success of a system, it appears to be necessary to look at more than just the benefits that the systems can offer. Considering the six dimensions of IS success present in the D&M model (2003) appears to provide a more complex evaluation of IS success and identification of elements of the system that are weak. As advised by Petter et al. (2008) success measurement programs can be attached to each dimension of the system together with weights depending on the relative importance of each.

There are six dimensions of IS success: system quality, information quality, service quality, system use, user satisfaction and net benefits. System quality is the ideal characteristics of an IS. Information quality is the ideal characteristics of an IS outputs. Service quality is the quality of the support received from IS. The three qualities would influence the using of the IS and affect user satisfaction. By using IS companies can achieve net benefits such as improving decision-making, increasing sales and so on. On the other hand, companies decide IT investments according the measurement of net benefits, which would affect the other dimensions in turn.

And Finally …
We found that the six dimensions set out by Delone and McLean in their 2003 model to be the most complete approach to measure the complex nature of IS success. We felt, however, that some elements were missing, namely organisational and cultural factors which all impact on the success of an organisation’s IS system.

Information Systems FAIL!

10 Feb

 My series of blogs have been an attempt to perhaps look at the idea of a framework and the extraction of quality from an Information System from a different perspective & rather than approach it in an expansive way, that it could be better to have a pared down approach i.e: what do we really need & what would be a bonus if we can get it!

Unfortunately there are many examples of Information Systems failures however I have chosen an Irish example which I think represents a situation where the business needs were misunderstood and this in turn resulted in a low quality output.

The SUSI debacle came to light in October 2012, Student Universal Support Ireland, a new body which had been set up to centralise the student grants system which had previously been dealt with by individual Local Authorities had begun to flounder. Reports in the media of students having to drop out of college and being unable to pay for food,uncovered that thousands of students nationwide were still awaiting both tuition & maintenance grants. It was deemed a “bureaucratic nightmare” by a T.D in the Dáil. [1]

The system had been unable to cope with the amount of applications it received and had “underestimated the complexity of detail required from the students”[2]

As an applicant myself I was mystified that any time I rang to check on the status of my application I was dealt with promptly, unusual for an organisation which was under so much pressure, however I found through my research that in fact the helpline for SUSI had been outsourced & therefore the people on the phones were not involved in processing the applications, that to me is a huge misallocation of resources, the helpline was outsourced however they had not employed enough staff to process the applications! When looking at this example through the prism of IS Quality, does it really matter that the service level agreement with the outsourced company was producing the high quality required of the helpdesk when the Information System had clearly failed the end user.

I look forward to discussing these ideas with my blog group.

[1] James Bannon-

[2]Jacinta Stewart-

IS Quality and the Internet Revolution: The Arab Spring Uprising experience of 2011

10 Feb

The Arab Spring Uprising experience of 2011

Much has been talked about regarding Information System Quality, nonetheless, I would like to bring our attention to the role which Information System played in collaboration with computer aided Internet, and social networking in creating positive mobilisation for political and social change in the Arab world. I will support my view point with some relevant articles and the narratives from a scholarly publication in an international journal of communication (2011), bearing the title; “The Egyptian Experience: Sense and Nonsense of the Internet Revolution”, published by Miriyam Aouragh of Oxford University, and Anne Alexnder of University of Cambridge.

As part of Information System Quality; the Internet, Facebook, and other Social Media Network were used to disseminate information and mobilise the people in the Arab nations to rise against dictatorship government, operations, social injustice, and human rights abuse in the region. It all started with Tunisia in 2010 when the president Zine El Abidine Ben Ali was forced to step down by angry protesters due to the fatal self-immolation by Mohamed Bouazizi a street vendor who was protesting his mistreatment by local officials. This protest in Tunisia motivated people in Egypt to take to the streets demanding political reform which in turn forced President Hosni Mubarak to resign his 30 years of dictatorship rule. In the same manner, the strongest and most stubborn leader Africa in history- Colonel Muammar Gaddafi of Libya was ousted and killed in October 2011. This Arab protest had a chain reaction and thereby, spread through to Morocco, Yemen, Iraq, Syria, Bahrain, and Saudi Arabia respectively.

According to the writers, it is important to separate the use of Internet as a tool by people                                               seeking to achieve change from below, and the Internet’s role as a space to articulate collective dissent. They suggested three main points; the need to go beyond the debate between utopian and dystopian perspective regarding the role of Internet in political change, a change from perspectives that isolate Internet from other media by reviewing the synergy between social media and satellite broadcasters during the uprising, and also, to have an understanding of the dialectical relationship between online and offline political action.

They tend to agree with Morozov’s (2011) argument that, a government threatened with revolution would just pull the plug on the Internet, but that wouldn’t stop the protest either, and cannot prevent the protesters from communicating. The writers disagree with what they call false polarization of utopian/dystopian views of the Internet, rather they accept that  Internet is a product of imperialist and capitalist logics, and a thing that millions use in their efforts to resist those logics. They propose a dialectical relationship between online and offline political action. They finally supported their argument with a quote from Lenin that, “There are decades where nothing happens; and there are weeks where decades happen.”

Blog Egypt protest 2011

Egyptians celebrate after President Hosni Mubarak resigned and handed power to the military at Tahrir Square on 11 February. (AP Photo/Khalil Hamra/PA Images)

To conclude on the above episode, I agree and disagree with some of the views expressed in the paper. I agree that Internet alone cannot mobilise people without the active presence of the activists and the folks who stormed the streets of Cairo Egypt. On the other hand, I disagree with the quote from Morozov (2011) as stated above. If any government pulls the plug of the Internet, they will automatically disable the flow of communication through the Internet, and that will create a huge impact in disrupting all plans towards action. It makes big news whenever America observes that Internet-Hackers have infiltrated their national or military classified documents through the Internet of course. Finally, I could recollect that during the revolution of 2011 in Egypt, it was reported that mobilisation of the folks to rise against the 30 years of dictatorship by Hosni Mubarak started with the Facebook. Egyptians responded to that call throughout the whole world, and the effect was disastrous to Mubarak and his allies.  The dismantle of Mubarak’s throne was a display of the good qualities Information systems can deliver.


  1. AOURAGH, M. Oxford University; ALEXANDER, A. University of Cambridge: The Egyptian Experience: Sense and Nonsense of the Internet Revolution.

International Journal of Communication 5 (2011), Feature 1344-1358 1932–8036/2011FEA1344

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:

Banking 24/7

10 Feb

In this blog & in an attempt to highlight my believe that IS frameworks should be more Industry specific, I will focus here on a particular industry which I feel demonstrates the viability of a ranking system of importance (as mentioned in my first blog- Context is King) when constructing a framework which will ensure the provision of outputs of high quality from the Information System.

In this age of technology, the efficiency & speed of an Information System is most likely a measure of quality for most organisations seeking to compete. These expectations are largely due to the amazing advances there have been in technology & the huge amounts of capital being invested by organisations in Information Systems. However it is accepted that the main aim of an Information System is to improve the overall efficiency and effectiveness of a process. The term ‘Real Time’ has entered the fold, particularly in the banking industry & also in the provision of Business Intelligence applications.

Internet Banking in particular could not function without real time updating of data, consider the implications of a delay in that information system, the chaos that could be caused if it was possible to withdraw cash from an ATM & due to a delay on the system that amended balance would not be recorded instantaneously & therefore the transaction could be attempted over & over before the system recognises that the account is in fact empty. It would be unfathomable that due to delays in processing transactions that billions could be lost.

But then of course data security would also be of huge concern, the loss of a customers’ data or ease of hack-ability to the sensitive information contained in an Information System would also be disastrous. We saw this with the Ulster Bank fiasco, what was a technical glitch triggered by a software upgrade has cost the bank millions & inconvenienced thousands of customers, the issue might have been an IT problem but it had an immediate effect on the IS, the information was now unreliable and therefore unusable.

This incident highlights the emphasis which must be placed on ensuring that the quality of what is seen as the more important elements of the information system are maintained at all cost and its seems logical that directing resources into achieving this will affect the quality of other elements of the IS such as ease of use which could be deemed less important due to its’ overall impact on the organisation.

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

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

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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.

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

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

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Third attempt: Close up on strategic related Tweets

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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)

Context is King

10 Feb

As I am entering the arena quite late & having read the comprehensive blogs which have been written by my colleagues on IS quality, my observation as I and my group move towards constructing a framework is the necessity of a ranking system of importance in terms of what the organisation requires from the Information System. If as reported between 50- 80% of Information systems are failing, perhaps it is due to trying to tick every box & trying to meet every need of the organisation. Perhaps it is necessary to focus on achieving higher quality from certain outputs/needs & a lower quality from others.

The use of resources when implementing a new IS system especially in these economic times must be paramount. There seems to be a general consensus in society & in what is a most definite shift in attitude from the  Celtic Tiger era that it is no longer necessary to have it all.

In terms of an Information system what does that mean? Well it means being realistic, assessing your business needs, and recognising that an Information System can bring huge advantages to your organisation while also recognising that to successfully implement an IS you will need to decide what really matters to you, For example on a scale of 1-10: If your business need is speed then  that ranks number 1 & if your system operates on an Intranet then having very secure data is most likely not a major concern and therefore ranks 10 and therefore could be seen as a bonus if you can achieve data security but in reality it is not a measure of quality for your IS.

The needs of organisations differ industry wide and I feel what is lacking in the frameworks which have been presented to us all in class in the last few weeks is the need for context, is it really possible to construct a framework which can be applied to all Information Systems, regardless of Who the organisation are, What they want from the information system and What can realistically be achieved. Could this be part of the issue with the high failure rate of Information Systems that in an attempt to gratify every need we are aiming too high & in a situation akin to Business Process Reengineering while the reward might be great perhaps the risks are too high.

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