IT complexity:model, measureand masterThoughtsCover statement this is dummy copy, for an opening statement. This is an exa...
IT complexity: model, measure and masterBy Dr. Peter Leukert, Chief Information Officer, Andreas Vollmer, Chief Architect,...
Today algorithmic trading using Greeks is an                  will replace system X because the economics indicateinstanta...
them. Consciously taking complexity into account,              Complexity drives cost, and it also is a good indicatorvia ...
IT                                        ComplexityDecisions                                                             ...
“Measurement is the first step that leads to control and eventually to improvement.If you can’t measure something, you can...
Top-level view on aggregated                                                                               complexity metr...
• Interface. Interface complexity is determined                  For example, think about how risk measures improve   thro...
Similar to the evolution of other analytics-driven metrics as they were appliedto different solution spaces, the complexit...
extensions of the complexity model. While this               Conclusion   advancement will require expansion of inputs to ...
Dr. Peter Leukert is the                                             Mat Small is a Partner in                            ...
About Capco    Capco, a global business and technology consultancy dedicated solely to the financial     services industry...
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IT Complexity: Model, Measure and Master

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This Capco Thoughts white paper, <a>IT Complexity</a>, describes a groundbreaking initiative underway by Germany-based Commerzbank and Capco to develop a model for measuring IT complexity in the financial services industry. Individual financial institutions can gain value from this new model through immediate application to their existing environment, while reaping long-term benefits through contribution to an industry database of results.

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IT Complexity: Model, Measure and Master

  1. 1. IT complexity:model, measureand masterThoughtsCover statement this is dummy copy, for an opening statement. This is an example of how it wouldlook if it ran more than one line deep.
  2. 2. IT complexity: model, measure and masterBy Dr. Peter Leukert, Chief Information Officer, Andreas Vollmer, Chief Architect, Commerzbank AG and Mat Small and Pete McEvoy,Capco PartnersWhat if complexity was a discreet, measurable metric rather than a discretionary, ambiguousterm? Could a complexity metric reshape the decisions and activities of a CIO?IT complexity: A new metric to will be able to derive value from this new modelevaluate the impact of change through immediate application to their existing environment, while reaping long-term benefits throughWhat if complexity was a discreet, measurable metric contribution to an industry database of results.rather than a discretionary, ambiguous term? Coulda complexity metric reshape the decisions andactivities of a CIO?The information technology field is filled with quotesand anecdotes about organizations trying to contain, The power of quantitative metricsexplain and manage complexity. Often these words Today, CIO decisions are tied almost exclusively toreflect an inclination to assume that if complexity experience and straightforward financial analyses,exists, we should try to reduce it. As computer such as project costs and estimations. Somescience pioneer Alan Perlis once said, “Fools ignore companies also apply scenario analysis to technologycomplexity. Pragmatists suffer it. Some can avoid it. decisions for risk management purposes.Geniuses remove it.” But if a quantitative metric for complexity wasPure genius, however, rarely exists. And with our world available to complement experience and the typicalin a state of constant change, we need to master, financial metrics, how might those decisions change?not remove complexity. The reduction of complexitycan reach diminishing returns, and the existence Historical parallels from other industries help illuminateof complexity can allow greater business flexibility. the possibilities. A mid-20th century auto assemblyWithout a doubt, an appropriate level of complexity line manager could not have imagined the possibilityis necessary to maximize return. of Six Sigma and Lean techniques delivering five- nines production quality. The pharmaceutical industryLeading financial institutions recognize the need to has made stunning advancements in statisticalacknowledge, embrace and harness complexity. analysis to prove drug effectiveness.They understand that the many layers and connecteddependencies of today’s IT environments cannot be Securities trading offers an illuminating examplemanaged with simple heuristic, or experience-based, in financial services. Trading has come a long wayapproaches alone, but instead require objective, since a century ago when curbstone brokers tradedquantifiable measurement of their origins and effects. small and speculative stocks outside the New York Stock Exchange. Back then brokers did not standThis white paper describes a groundbreaking initiative on the street with a computer in hand. They had nounderway by Germany-based Commerzbank and notion of mathematically valuing an instrument andconsulting firm Capco to develop a model for quantitatively evaluating the risk associated withmeasuring IT complexity in the financial services price movements.industry. Importantly, individual financial institutions 2
  3. 3. Today algorithmic trading using Greeks is an will replace system X because the economics indicateinstantaneous activity that leverages risk metrics as lower operational cost and a positive payback.”a core component of calculation. What was viewedas hard to measure 10 years ago has been made Wouldn’t that exercise be more productive, and mightroutine by the availability of models and data. that scenario unfold differently, with the introduction of a model-driven complexity measure? “Based onSimilarly, IT leaders need a transparent, objective the IT complexity metric in our business case, we’veframework to augment the experience they bring determined that if we replace system X, the resultingto decision making. Such a framework can aid in system will likely be just as complex because ofarticulating and communicating decisions both across underlying process and integration issues, and we willand outside the organization, an increasingly important never realize a positive return.” This type of thoughtrequirement as corporate directors and regulators innovation allows for an examination of other methodsexpand their scrutiny of technology decisions. to address the issue, such as reengineering the system. CIOs with a lot of experience in complex decisions are arguably in a better position, as they can subjectively associate future change with historical observations. However, if CIOs supplement their hard-earnedHow decisions related to experience, native intuition, and traditional financialcomplexity are made today – analyses with an IT complexity metric, they will haveand could be made tomorrow all of the pieces needed to make critical decisions that benefit both their IT department and the enterprise.Complexity has become an overworked word inthe IT field. It is used with increasing frequencyin publications and elsewhere to describe howmanagement views decision making broadly, aswell as in relation to specific functions across andwithin industries, such as IT management and How a complexity metric fitsrisk management. into the CIO agendaAll CIOs have biases based on experience. Their Whether thought about consciously or not, everyunderstanding of the familiar forms the basis for decision a CIO makes influences overall IT complexity.the gut decision they inevitably must make. The Complexity in turn drives up cost, makes qualityintroduction of a complexity metric allows for harder to achieve and affects flexibility. Thus the corean exploration of alternatives that experience may dimensions that dominate a CIO’s agenda – cost,not shed light on. quality and flexibility – are all influenced by complexity, and IT leaders have to make daily tradeoffs betweenWhen faced with decisions related to delivering ITchange, CIOs must categorize the situation, usuallyresulting in a subjective measure of complexity: “We 3
  4. 4. them. Consciously taking complexity into account, Complexity drives cost, and it also is a good indicatorvia a complexity metric, will improve the effectiveness of unexpected cost increases. Modeling howof CIO decisions – and make them easier to explain complexity increases in the two examples aboveand defend (See Figure 1 on page 5.) would have alerted IT managers to the cost impact. Based on this exercise, managers might mitigate cost increases or at least make more informed choices.The cost impactCost containment has been one of the most pressing The quality impactissues for CIOs in recent years. IT is continuouslyexpected to increase efficiency. CIOs of large financial The issue of quality has also become more importantinstitutions preside over significant IT budgets – on the CIO agenda. There are clear correlationsoften US$1-2 billion – and, by extension, substantial between quality and long-term operational costs. Andcomplexity. The decisions they make can influence the maturation of technologies has led IT end-usersdirection for many years to come and have potentially to be less forgiving of quality issues. Complexitylarge financial consequences. correlates to quality intuitively, as the following examples highlight:Clearly, complexity drives cost. One or both of thefollowing examples will be familiar to any CIO: • Technology and interface complexity – Production stability is one aspect of system• Technology complexity – A new software quality. A more complex application landscape package offers great functionality to the business. is more prone to suffer from incidents after Unfortunately, it runs on technology that requires deploying changes because there can be different skills from those of existing IT employees. unexpected, and thus untested, interdependencies Consequently, people need to be retrained, with systems that were not supposed to be additional upgrades need to be made for the affected by the change. new technology components and expensive external expertise has to be contracted for. • Functional and interface complexity – Error analysis and resolution is another example.• Interface complexity – A major new development In more complex environments it is harder to is well underway. Then integration testing starts. identify the root cause of an error and more risky Suddenly a number of interfaces are affected to fix it without introducing other errors. and need to be tested that were not part of the original scope. There are unexpected effects With a complexity metric, IT executives can manage on the downstream systems, and testing expense quality more effectively. climbs exponentially. 4
  5. 5. IT ComplexityDecisions Cost Dimensionsregarding • FunctionalIT change • Interface Qualitye.g. projects, • Dataarchitecture, • Technologytransformation Flexibility Figure 1. Complexity framework Consider IT complexity to make more informed decisions 5
  6. 6. “Measurement is the first step that leads to control and eventually to improvement.If you can’t measure something, you can’t understand it. If you can’t understandit, you can’t control it. If you can’t control it, you can’t improve it.”–H. James HarringtonThe flexibility impact How do you measure complexity?The relationship between complexity and flexibility The observation offered above by the leadingoften forms a “vicious circle.” Flexibility gained by performance and quality expert H. James Harringtonadding new functionality and new technology quickly highlights the central role that measurement playsdrives up complexity. The more complex the system in addressing complexity. In its current state, thelandscape, the harder and more risky changes Commerzbank/Capco complexity model appliesbecome. As a result, flexibility decreases, as these to the application landscape: single applications,examples show: application clusters, application domains and the entire application landscape.• Data complexity – When implementing compliance regulations, many banks are hindered The model consists of several complexity indicators by the fact that they do not have all customer data covering the relevant dimensions of application stored consistently in one place in the enterprise. complexity. We have statistically validated these complexity indicators through quantitative research• Functional and data complexity – Product using Commerzbank data on approximately 1,000 introduction, considered to be a hallmark of applications over three years. (See Figure 2 on page 7.) flexibility, is more difficult in a highly complex environment because of the interdependencies A tacit inverse correlation exists between flexibility and effects of systemic changes. and complexity that is difficult to quantify. However, we have established a statistically significantIn summary, a complexity metric will increase correlation between the complexity indicators andtransparency and provide insights that help in both cost indicators, such as maintenance spend, andmanaging cost, quality and flexibility. A metric will quality indicators, such as the number of incidentsalso help uncover intelligence associated with every occurring during production.strategic decision, improving appreciation of thedelicate intricacies associated with the CIO agenda. The complexity indicators of the model cover four dimensions: functional, interface, data and technology. • Functional. One driver of functional complexity is the functional scope of an application cluster. The sum of weighted use cases serves as the figure to measure this. In each use case, a weight factor is assigned, from “one” for simple use cases, such as changing one data field, like address, to “four” for use cases with involved logic. Use cases have been classified by expert judgment. Other indicators measure the functional redundancy and standard conformity of the solution architecture. 6
  7. 7. Top-level view on aggregated complexity metrics – indicates areas for further analysis: High Implementation Quotient values for Investment Banking related groups – i.e. implementation of investment banking applications is more “complex” than comparable commercial banking applications (assuming an equal number of functions are covered) Functional group, Securities Processing, is characterized by a high number of applications and interfaces with other functional groups Data Warehouse Staging with “only” 8 applications shows the highest value for quantity of interfaces which reflects the number of source systemsRise against the quarter beforeDescent against the quarter before Figure 2. Complexity dashboard, a sample view 7
  8. 8. • Interface. Interface complexity is determined For example, think about how risk measures improve through the sum of weighted interfaces. The when a financial institution has more years of, for weights are calculated by type of interface, such example, defaulted bonds to model. as API, file exchange, database view and broker Web service. This indicator shows the interface Bottom line, the more companies that use the intensity. The ratio of internal to external interfaces complexity model and contribute to a standard data- is another relevant indicator. base over time, the higher the benchmarking quality.• Data. Data complexity is measured by the number of database objects in an application cluster.• Technology. Technology complexity is monitored through a number of drivers, including business Immediate application and benefits criticality and prescribed time for recovery The complexity model, as it stands today, can be of applications under consideration. Another applied to important IT decisions at any financial technology indicator is the variety of operating institution after some calibration and data gathering. systems employed in the application cluster. The model can also help educate IT leaders. And it should foster dialog between the IT departmentEach indicator measures a relevant aspect of and the business units it serves.complexity. In our experience, these measuresbecome most powerful if considered in conjunction. • Decision and trending analysis. IT executivesSometimes it is useful to aggregate them into one will immediately be able to use the complexityoverall complexity score to simplify matters, such as model to analyze the impact of decisions andtracking the complexity of legacy architecture over perform trending analysis. This will help themtime. For other problems and decisions, the individual understand how their decisions might affect thedimensions need to be considered – for example future cost, quality and flexibility of IT projects.the trade-off between functional scope and interface To achieve these results, a phase of data gatheringintensity in defining application domains. and calibrating the model is necessary. Depending on the availability of relevant information, suchTo date, we have measured time series of statistically as data on the interfaces of applications undervalidated complexity metrics for Commerzbank. consideration, this process will take a few weeksWe believe that, ultimately, a single company cannot to a couple of months. Again, this type of analysisdevelop a comprehensive approach to complexity will become more precise and robust over timemodeling on its own. Models evolve when multiple as collected data is enriched.organizations contribute data and experience. 8
  9. 9. Similar to the evolution of other analytics-driven metrics as they were appliedto different solution spaces, the complexity model will offer a number ofpossibilities in the not-too-distant future.• Educating IT leaders. The numbers produced from across the financial services industry. This ever through use of the complexity model will vary improving precision will continue to add value for across organizations. Also, similar to other IT executives. analytics-driven metrics, the definition of thresholds for the model will be set over time A complexity metric will help CIOs articulate short- as both IT leaders and business units gain better and long-term implications of initiatives, costs appreciation of its merits. Each scenario modeled, over time, impacts on existing operations and the coupled with the passing of time to observe the business as a whole, and strategic implications and outcomes of a metric-driven decision, will enable justifications of high-risk projects. By articulating IT executives to test their own hypotheses and complexity in this way, CIOs will be able to strengthen build a stronger foundation of knowledge to intercompany partnerships and create new support future decisions. opportunities to achieve measurable results.• Bridging the gap between business and technology. In addition to informing decision making within the IT organization, a complexity measure should help IT executives to better explain and defend their decisions to the business. Expansions and possibilities An objective measurement of complexity will be a While the complexity model at present is focused monumental step toward addressing the concerns primarily on IT applications, it is not difficult to of business unit managers and other executives envision how it might evolve and be extended regarding IT systems development. CIOs will no to a broader set of technology decisions. Similar longer need to rely on soft, subjective explanations to the evolution of other analytics-driven metrics supported by experience. Instead, they will be as they were applied to different solution spaces, able to produce a quantifiable metric that provides the complexity model will offer a number of a new level of transparency. possibilities in the not-too-distant future, including:To date, the complexity model leverages data from • IT architecture. Perhaps most interesting to ITa single firm: Commerzbank. Ultimately, the model leaders is the notion of looking for complexitywill improve over time as data from more institutions across not just the application stack but theallows for more accurate benchmarking. Making the overall architecture. This will support conclusionsmodel available to others will enable benchmarking regarding the impact of change on the entireacross multiple organizations, increasing the credibility infrastructure, including networks and otherof the metric based on comparative data points aspects, and is perhaps one of the most natural 9
  10. 10. extensions of the complexity model. While this Conclusion advancement will require expansion of inputs to the model, such as indicators on infrastructure and The notion that you can’t manage something you middleware components, the output will provide can’t measure has been ingrained in business for IT executives a more rounded perspective. many years. The creation of a complexity model presents an extraordinary new opportunity to• IT processes. Extensive work has been done understand the levers that drive cost, quality and over time on IT supply chain modeling. In the flexibility. Importantly, such a model becomes future, incorporating this thought leadership could stronger as more data is added to it. produce a complexity metric that is oriented to the process dimension of IT decisions, which could aid We hope this white paper has helped stimulate your in decisions relating to the software development interest in exploring complexity and how you can life cycle – for example, determining the right harness it to improve your organization. We also allocation of time and resources to each leg of the invite you to join the conversation as we continue SDLC. This concept could be extended further to to explore complexity issues. Among topics we include complexity aspects of sourcing decisions. plan to address:• Business processes. It is easy to intuit a • How is complexity calculated, and how would relationship between a business process and the an organization embark on a complexity technical complexity needed to support it. In many measurement program? instances, the technology cannot be simplified • How does the complexity metric influence the without corresponding simplification of the strategic decision process? business process. Business process simplification • What is envisioned for the executive dashboard for is evident in many initiatives, from reengineering to complexity measurement and scenario modeling, Six Sigma. In the future, a complexity metric could and how would the complexity metric be used in serve as a process measurement or a heuristic concert with other IT metrics? to measure the efficacy of business process • How is complexity modeling different across changes. These applications could allow for the various corporate paradigms (mid versus large quantification of business complexity and provide size, new versus old firm, single line versus a more holistic view of changes needed to drive multiline business, institutional versus retail)? the CIO agenda. For more information on participating inEmboldened by insights into IT, organizations might Commerzbank and Capco’s Complexityconsider measuring the complexity of business Working Group, please contact Pete McEvoy,architecture, as well. IT decision making on the Peter.McEvoy@capco.com or Andreas Vollmer,business side would likely benefit from more explicit Andreas.Vollmer@commerzbank.com.and quantitative consideration of complexity. 10
  11. 11. Dr. Peter Leukert is the Mat Small is a Partner in Chief Information Officer Capco’s Capital Markets of Commerzbank AG. He Technology practice. Mat brings is in charge of information over 20 years’ experience in the technology across all business capital markets industry as a units of Commerzbank and practitioner, technology leader, oversees approximately 4,000 and management advisor. He employees. Peter was co-lead focuses on client initiatives of the integration of Dresdner involving business, operations Bank into Commerzbank, which and technology transformationwas successfully completed in May 2011. Before joining strategy and implementation. Given Mat’s breadth ofCommerzbank, he was a partner at McKinsey & Company, experience he brings distinctive insights to solving large-serving financial institutions and the public sector on scale business and technology issues. Prior to joiningIT and operations topics. Peter studied mathematics Capco, Mat held execution and leadership positions in theand physics at the University of Bielefeld and obtained US and Europe ranging from front officea doctorate in financial mathematics at the Humboldt to technology across a myriad of traded products at firmsUniversity of Berlin. including Citi and the American Stock Exchange.Peter.Leukert@commerzbank.com Mat.Small@capco.com Andreas Vollmer is the Chief Pete McEvoy is a Partner with Architect of Commerzbank AG. Capco in the Capital Markets As head of IT Architecture & Technology Practice. Pete Services, Andreas has cross- brings over 15 years’ experience functional responsibility for the in the technology field as a overall IT architecture and is also thought leader in architecting the IT security and IT governance and delivering IT solutions to lead. Andreas has over 10 years’ business problems. Given Pete’s experience in IT strategy, IT knowledge across the myriad of architecture and IT management technologies in all aspects of thein the financial services industry. Prior to joining IT landscape, he provides balanced solutions strategiesCommerzbank he worked as a senior project manager with that align with the continuing evolution of technology. PriorBooz & Company. Andreas studied industrial mathematics to joining Capco, Pete held industry positions includingat the University of Kaiserslautern, Germany, and obtained a chief architect for one of the world’s largest Hedge FundsMBA from the Rotman School of Management, University of where he participated in the complete replacement of itsToronto, Canada. existing technology infrastructure.Andreas.Vollmer@commerzbank.com Peter.McEvoy@capco.com 11
  12. 12. About Capco Capco, a global business and technology consultancy dedicated solely to the financial services industry. We recognize and understand the opportunities and the challenges our clients face. We apply focus, insight and determination to consulting, technology andtransformation. We overcome complexity. We remove obstacles. We help our clients realize their potential for increasing success. The value we create, the insights we contribute and the skills of our people mean we are more than consultants. We are a true participant in the industry. Together with our clients we are forming the future of finance. We serve our clients from offices in leading financial centers across North America and Europe. About Commerzbank Commerzbank is a leading bank for private and corporate customers in Germany. With the segments Private Customers, Mittelstandsbank, Corporates & Markets, Central & Eastern Europe as well as Asset Based Finance, the Bank offers its customers an attractive product portfolio, and is a strong partner for the export-oriented SME sector in Germany and worldwide. With a future total of some 1,200 branches, Commerzbank has one of the densest networks of branches among German private banks. It has above 60 sites in 50 countries and serves more than 14 million private clients as well as one million business and corporate clients worldwide. In 2010 it posted gross revenues of EUR 12.7 billion with some 59,100 employees. Capco Worldwide offices Amsterdam • Antwerp • Bangalore • Chicago • Frankfurt • Geneva • Johannesburg London • New York • Paris • San Francisco • Toronto • Washington DC • Zürich To learn more, contact us at +1 877 328 6868 or visit our website at capco.com. Capco © 2011. All rights reserved. T1060-0611-02-NA

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