BIG DATA INITIATIVES WHY EA SHOULD DRIVE

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1 WHY EA SHOULD DRIVE BIG DATA INITIATIVES TABLE OF CONTENTS 1 Introduction 2 EA s role in big data: Innovation Planning Governance 2 Innovation: Providing value in using big data effectively 5 Planning: Harmonizing business and IT big data strategies 7 Governance: Ensuring positive business outcomes from big data initiatives 9 Summary 10 Recommended resources 11 Alfabet Enterprise Architecture, IT Planning and Portfolio Management 11 Benefits Big data is here. It s a technology trend that needs your attention, a business demand that needs your support and a potentially bewildering concept that needs your expertise. Enterprise Architecture (EA) needs to be in the driver s seat to steer business initiatives in the right direction and get the most out of today s big data technologies. The Age of Information, spawned in the late 70 s with the advent of microcomputers and proliferated with the Internet in the 90 s, heralded a new era for business. Vast amounts of data became available to get information on consumers, machines and the environment. The key to business success was no longer to just produce efficiently but to understand and use available data to build commercial models to market efficiently. Technological advances have ushered in the Big Data era: there is so much data that turning it into meaningful information is a daunting task. Company strategists, product developers and marketers struggle to obtain meaningful insight that can be used to deliver better products and services. Big data has the potential to change the very marrow of an enterprise: its business model, its operating model, its business processes and, accordingly, its IT. Orchestrating the transformation of these pieces is the realm of EA. As an EA professional, you have expertise that s indispensable for big ambitions for leveraging big data. Your big picture view of the enterprise can bring together siloed information reservoirs to deliver content, context and continuity. Your hard-won savvy in risk and compliance in IT can help business avoid regulatory landmines in data usage. Working within budget constraints is nothing new to you. And, of course, as the compass for technology innovation for the enterprise, enterprise architects have the wherewithal to show business where to apply big data for true market differentiation. In the digital business age, enterprise architecture plays a critical role in determining how the company s usage of information will drive better business results. BUSINESS WHITE PAPER

2 Between two otherwise evenly matched competitors, the firm that exploits more available data for business insight will have a competitive advantage. Brian Hopkins Q&A: The Top Five Strategic Big Data Questions, Brian Hopkins, Forrester Research, July 8, 2014 But can your EA today provide business the support it needs fast enough? Do you have the ability to bring business, technology, cost and risk aspects together in one cohesive picture? Do you know which technologies will meet the firm s needs best? Key to your success will be your knowledge of available technologies and how well you communicate with your business peers. An information architecture (and the newest software and hardware) will serve you well but won t be very enlightening for the business. But relate it to the company s business capabilities, operating model and business processes and it becomes a conversation about market differentiation, business automation and digital customer engagement. This white paper shows how the business opportunities big data offers creates new demands on EA to help the enterprise leverage it effectively. You ll see how to attain the insight into the information architecture that is required by the new focus on the architecture landscape in terms of regarding data not as the by-product of process and applications but as the foundation and catalyst for architecture changes. You will also learn to guide business as it is moving forward with its demands for innovative solutions for digital business. EA s role in big data: Innovation Planning Governance Forrester s EA capability map (see Figure 1) frames our discussion. These capabilities enable enterprise architects to expand their focus from internal IT issues to what Forrester calls the Business Technology (BT) agenda, including such topics as strategy alignment, customer experience, digitization, mobile and big data. In particular, the three EA value streams planning, governance and innovation help structure the discussion according to the value EA can bring to the enterprise in the context of big data. Figure 1: Forrester s EA Capability Map, EA Capabilities Must Change To Accelerate The BT Agenda, August 13, 2015 Innovation: Providing value in using big data effectively Your company already has a lot of data and there s a lot more outside of your company just waiting to become useful. There are certainly a lot of areas in your company where more data or better insight into data could be beneficial but just as certainly there are also resource limitations. This is where EA can first help: helping business to understand where big data can truly improve business outcomes and thus identifying where to spend the effort. 2

3 Big data can be used to improve Customer Experience (CX), achieve operational excellence, create new service offerings and acquire differentiating capabilities. EA has many tools in its arsenal to provide the insight needed to decide what is currently most important. One of these is the business capability map, a vehicle increasingly being used by architects as an instrument for enterprise IT planning and management. Different from the EA capability map in Figure 1, a business capability map describes the business capabilities a company needs to achieve its mission, such as channel management, product design or procurement. It prescribes a view of the enterprise based on business activities that are independent of specific business processes and organizational silos and unfettered by historically given circumstances. By associating architecture elements (business processes, applications, technology components) and KPIs to business capabilities, IT has the business context for IT transformation decisions. Using a language that is meaningful to business, IT and business can collaboratively plan transformation. EA can work with business to assess appropriateness for big data solutions, answering questions such as: Would the business capability benefit from capturing single or multiple events, such as a customer interaction on a website or a status change in production machinery, and responding to them in real time? Would the business capability benefit from improved analysis of available data to make predictions on, for example, customer behavior, likelihood of production failure or price levels? Would the business capability benefit from analysis of data not currently available to make predictions on customer behavior, likelihood of production failure or price levels? Would the business capability performance improve significantly if certain applications performed better for example, with quicker response times, reports and KPIs made available sooner? Figure 2: This business capability map is configured with KPIs measuring the big data benefits for each capability (dark blue = high benefit potential) and big data risk (red = high risk potential). According to this map Direct Marketing Management would be a good place to look into how big data could benefit this capability. Drilling down into supporting applications, EA can look for applications that would benefit from big data such as applications that: 3

4 Have problems with reports that take too long to complete Have problems with calculations or other analytics which take too long to complete Have insufficient performance to support predictive analytics Are expected to experience performance problems because data volumes are increasing Having identified with business peers which areas of the business could produce better outcomes using big data tools and techniques, the next step would be to examine the issues and potential hurdles of using big data in those areas. EA certainly has experience in introducing new technologies into an organization and is well aware of the potential landmines and pitfalls. Regarding big data, EA can advise business on the technological, regulatory, organizational and financial aspects. EA will know what technology and data stores exist and can be used for culling data or gaining better insight and what can be combined with new technology to provide true business benefit. With its insight into the IT landscape and its understanding of how the elements relate to each other, EA is often turned to when compliance questions arise. Mature EA organizations will know which applications and data stores are compliance-relevant and will have established data security and privacy policies. They also understand dependencies between applications and the data flows between them so will be able to identify knock-on effects of using data in newer ways. These will need to be revisited as new sources of data arise and new legislation targeting data security is passed. Figure 3: Enterprise architects have the tools and techniques to understand the movement of data and its relationship to applications. They can thus advise on data compliance issues and effects of changing the IT landscape. Here we see an information flow diagram for the project Web Interaction Analytics containing current (blue) and future (linen) solutions. Also included are the information flows and business objects they are transferring. Newly proposed information flows are shown in magenta. Another area where EA has cut its teeth is in company culture and politics. With its mission of providing transparency into why and how transformation should occur, EA is in the role of company mediator. In regards to data, knowledge has always been wielded as an instrument of power. In organizations where business units are siloed and information is hoarded no matter how bad or good that information is sharing that information is a big challenge business leaders need to confront to cross department boundaries and have a holistic view of the customer for better CX and greater operational efficiency. EA knows its stakeholders and is practiced in breaking down silos to transform the IT landscape for greater effectiveness and more efficiency. A stakeholder analysis related to data could reveal where the cultural roadblocks exist. 4

5 Working under budget constraints when developing solutions are nothing new for EA. EA has the advantage in its overview of the architecture: all processes, applications, technology platforms and deployment locations. This makes it easier to find synergies and alternatives for creating the best solutions for a given budget. As for helping business decide what tools and techniques are best suited for achieving the big data insight business wants, EA may be challenged at first but with its understanding of many kinds of technology, it will be able to see through the hype of technology vendors. Innovation management is a growing practice in many companies and EA is often the practice owner or, at a minimum, important counsel to the practice owner. Using best practice innovation management approaches for big data, EA can help business to: Understand where big data truly improves business outcomes Understand the issues and potential hurdles of big data Create effective big data business solutions Choose the right big data processing and analysis tools Planning: Harmonizing business and IT big data strategies Probably the most difficult challenge the C-level board of a large company faces is aligning its diverse and dispersed business units to overall company strategy and ensuring business execution is according to strategy. With today s fast-moving markets and quickly changing market demands, companies need to ensure they move quickly to implement new strategies and tactics across the whole company. Yet often, companies don t have the tools and strategic planning processes set up to do this. As Forrester states: Without an adequate corporate toolbox, advice on strategic direction from a business strategist, strategy-focused enterprise architects, or portfolio managers, companies become tied to an onerous manual exercise that takes too long they have to chase down information and decisions from disparate stakeholders, resulting in risk because they do not have visibility into critical information. (The Forrester Wave : Strategic Planning For The BT Agenda, Q1 2015, Gordon Barnett and Margo Visitacion) The increasing scope of EA to cover strategy, portfolio, and architecture management enables it to better engage with the business. Techniques and tools that support them are critical for ensuring that business and IT are in total alignment moving forward and that a line-of-sight for short-, mid- and long-term planning is maintained. We ve already discussed business capability maps as a tool for business and IT collaboration. The enterprise operating model is also a part of the business architecture that facilitates the conversation between business and IT on initiatives and portfolio decisions (see Figure 4). Questions such as What part of the enterprise will need to transform its processes because a more data-driven approach to process will benefit the business? and How can we harmonize business processes across the enterprise with specific emphasis on using common data reservoirs for our CX initiatives? can be answered using the enterprise operating model as a basis for discussion. To bridge the gap between business strategy and IT when contemplating big data initiatives, EA can, as a first step, assess the changes required to the IT landscape. It will be necessary to operationalize the business strategy as typically the business strategy is defined at a high level of abstraction that isn t readily relatable to the discussions and activities in EA. Yet architectural considerations are an important part of any strategic transformational program thus operationalizing the strategy into EA requirements is an important activity (see Figure 5). This involves: Firstly, breaking down general strategy into the business drivers that are defining it Secondly, breaking these down into the business requirements they necessitate Thirdly, finally translating business requirements into architecture requirements and initiatives This helps to see what the impact on IT will be to be able to understand delivery and cost issues and reconcile the new strategy with the current IT strategy. 5

6 Figure 4: The operating model can be assessed for improving efficiencies with better information management. Here we can see how the operating model is related to the enterprise architecture (organizations, applications and service centers). With this capability, IT planners and strategists can contribute to the assessment of the operating model to identify potential for using information differently in pursuit of process and resource simplification, harmonization, homogenization, re-use, and reduction in redundancy. Figure 5: This strategy operationalization grid centers on the business requirement Identify Complementary Product Offerings. To the left we see the business drivers from which this requirement was derived and on the far left the corresponding external trends that trigger the business drivers. To the right of the business requirement we see the architecture requirements that are derived from the business requirement and on the far right the defined initiatives to satisfy the architecture requirement. The user can move through this grid to understand the relationship between business strategy and architecture impact. Change and migration roadmaps are key to keeping the organization synchronized on change. Road-mapping provides the vehicle for ensuring that everyone relevant to the success of business and IT initiatives is informed, involved and in sync, understanding the pace, required resources and milestones of enterprise change. It can reduce costs associated with project rescoping by providing visibility into road-map impact and increase IT agility with better insight into implications of change. 6

7 Figure 6: Here we see the road maps for all architecture objects associated with the project Web Interaction Analytics : the business change, information capability, application and technology roadmaps. And when talking about a big data strategy and not just short-term tactics, master planning and IT portfolio assessments can chart the course moving forward. IT master planning is a key concept of EA management. It consists of defining the strategic target architecture and developing a master plan that is, a road map to get from the current situation to the desired target landscape. More than just another IT management approach, master planning is business-driven, while most other approaches are IT-driven. The core idea is to ensure business-aligned IT. Defining an organization s strategic target architecture has an important prerequisite: a business strategy. Master planning is a method that enables business to achieve its strategic goals and ensures that IT and business strategies for example, on using big data are harmonized. Figure 7: This master plan map shows a company s organizational units (far left-hand column), the processes they execute (top row) and the applications that support them (cells). This shows business how it is being supported with IT. In this case the map is showing the current IT that is associated with the project CRM Big Data Analytics Center. The same map generated for a date in the future would show the IT support at that point in time, i.e. how the project will be changing the landscape to incorporate big data analytics capabilities. 7

8 Governance: Ensuring positive business outcomes from big data initiatives EA plays a big role in enterprise governance. It is, or should be, EA that defines the targeted business outcomes that IT should be working towards and as Gartner states: EA processes must reinforce and enact business leaders decision-making rights, information governance (stewardship processes as well as data standards), application governance and strategy directions, and IT infrastructure investment and risk priorities. (Hype Cycle for Enterprise Architecture 2015, 30 July 2015, Betsy Burton and Philip Allega) How can EA best govern enterprise transformation? By implementing portfolio management, for one thing. Integrated IT portfolio management provides a high-level view of the various IT portfolios strategies, demands, applications, technologies, projects and services and how they interlink to be able to understand the impact of change on all areas of the enterprise. Integrating these views enables IT leaders to see the cost, effort, technical complexity, feasibility and interrelated effects of a proposed IT change or initiative. As a governance approach, Integrated IT Portfolio Management (IIPM) aligns portfolios to business strategy, capabilities and demand, manages changes to portfolios in a consistent and clear manner and exposes dependencies and impacts between portfolios. In the context of big data, portfolio management will help guide and manage the transformation of the IT landscape when implementing big data solutions. Delivery roadmaps Costs and risks Business strategies Tactical demands IT change portfolios Road maps Portfolio strategies Tactical demands Business strategy portfolios Metrics on performance of IT support Business assessments of IT support IT asset portfolios Figure 8: The many portfolios that make up the IT portfolio must be synchronized in order to govern transformation effectively. In its governance capacity, EA will also need to monitor investments and results by ensuring that big data projects are aligned with the business capabilities big data is supposed to help. Here again, a portfolio management tool can help by associating projects to business capabilities. Having already determined which capabilities could benefit from big data insights, it s then easy to identify whether there are big data projects associated to those capabilities or not. EA will need to work with business to define KPIs that measure whether a big data implementation project results in the business outcomes hoped for: is the right information (the actors, actions and other variables) being captured in the right amount (to be statistically relevant and meaningful) and being analyzed quickly enough to enable an agile reaction in business operations? In short: Does more insight really equal more revenue? 8

9 Figure 9: Big data initiatives can be assessed as to their effectiveness on business capabilities using KPIs and reports such as these. The role of information architect is changing fast with big data. No longer just responsible for building and communicating the enterprise information model, information architects now are expected to and can provide solution guidance by assessing available data s ability to satisfy business requirements, embracing and modeling various sources of data and understanding where data can trigger new processes. As the worlds of data and content collide and organizations implement systems of engagement and systems of automation along with systems of record, information architects have never been more important. Information architects stand at the nexus of all these dimensions to coordinate the flow of the fuel of your business your information. ( Define The Shifting Responsibilities Of The Information Architect, Forrester Research, 31 December, 2014, Gene Leganza) Figure 10: This diagram of the target architecture proposes the introduction of a streaming analytics engine generating predictions of account movement information. The streaming analytics engine should be built on a new architecture pattern (standard platform) Big Data Streaming Analytics Core. The big data lead an information architect is taking a closer look at this architecture pattern. Another important aspect in governance for big data strategies is data integrity and security. EA can contain risk pertaining to data by defining ownership and responsibility for data, establishing data security policies and monitoring adherence and by maintaining clean metadata on stored data. 9

10 Summary In short, EA can and must support business in its endeavors to use big data for greater customer insights and operational efficiency. It can do this by: Classifying business objects by the expected data proliferation and growth rates Assessing products and services that gain value from specific data (business object) and exposing potential beneficiaries Identifying products/devices that will in the future generate major data volumes for big data projects (e.g., engine part status, patient health reader) Identifying customer interactions generating data that is useful for sales and service models, along with identification of fraudulent behavior patterns to assist early detection Assessing business capabilities/market products with regard to them benefitting from big data categories Funneling ideas into an innovation management process in which business and IT jointly evaluate the potential value of big data Performing architectural impact analysis of big data initiatives Planning and monitoring the solution implementation Take the next step For more information on how EA can drive big data initiatives to assure the business gets the greatest value from them talk to your Software AG representative. For more information on Software AG s solutions for enterprise architects, visit Recommended Resources The Forrester Wave : Enterprise Architecture Management Suites, Q3 2015; The 10 Providers That Matter Most And How They Stack Up, Forrester Research, 1 September 2015, Gordon Barnett Magic Quadrant for Enterprise Architecture Tools, Gartner, 4 November 2015, Saul Brand Magic Quadrant for Integrated IT Portfolio Analysis Applications, Gartner, 18 November 2014, Daniel B. Stang and Jim Duggan White Paper: IT Strategy and Master Planning, Best Practice Models and Recommendations for Business-Aligned IT, Software AG 10

11 Alfabet Enterprise Architecture, IT Planning and Portfolio Management. All of the topics covered in this white paper are supported by Software AG s Alfabet product for business and IT transformation. Alfabet helps IT decision-makers make better IT investment decisions and reduce transformational risks by understanding when, where, how and why to make changes in the IT portfolio. It links the interdependent perspectives of IT, business, finance and risk for whole view analysis of how IT can support business change. Enterprise architecture capabilities build the necessary foundation with an accurate, real-time picture of the IT landscape including all applications and technologies, the inter-relationships between them, the information they exchange as well as the business capabilities and processes they support. Alfabet s portfolio management capabilities support independent portfolio decision-making for optimization of individual portfolios application, project, technology and demand portfolios - as well as portfolio-level strategy modelling to incorporate all portfolios into strategy formulation. Further, cross-portfolio analytics provide a high-level view of how the various IT portfolios interrelate to be able to assess the impact of change to any one portfolio on the others. Alfabet s collaborative planning platform enables all stakeholders to interface, communicate and consider multiple perspectives when making transformation decisions as well as prioritize project proposals based on alignment with buinsess strategy. Benefits: Well-founded and sustainable decisions on IT transformation due to accurate, current and complete information on the IT landscape IT structures aligned with business objectives and processes to ensure that IT transformation goes hand-in-hand with business transformation Streamlined IT portfolios that increase IT s agility in implementing business initiatives faster thus improving time to market for new business products Lowered project, application and data risk to safeguard IT project investment, ensure business continuity, and increase compliance with regulatory requirements Improved IT governance across federated environments through definition and enforcement of standard EA processes and components for projects A rich set of functionality and resources including frameworks such as ArchiMate and TOGAF * as well as reference content for diverse industries (Industry. PerformanceREADY) 11

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