Improving Business Outcomes with Big Data Analytics in Communications, Media and Entertainment, by IDC

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  • 1. WHITE P APER Improving Business Outcomes w ith Big Data and Anal ytics in Communications, Media, and Entertainment Sponsored by: HP Debra Osswald Greg Girard September 2012 IDC Information is emerging as the new currency of business and the basis for sustainable competitive differentiation, innovation, value creation, growth, and risk mitigation. If communications service providers (CSPs), cable operators, and communications/media/entertainment companies (CME companies for short) are toF.508.935.4015 survive the pressures exerted upon them by their dynamic and challenging new market environment, they must deliver consistently high quality of service (QoS) and personalized customer experiences while efficiently operating their networks at the highest available capacity. They must also innovate more frequently and cost effectively, uncover new business models, and create new differentiated servicesP.508.872.8200 valued by their customers. All of this requires that they manage the full life cycles of the vast amounts of customer, network, and usage data streaming from their operations and analyze this data for actionable insight — in real time, near real time, or offline, depending on the business context and objectives. Emerging Big Data management and analytical technologies, business processes, and decisionGlobal Headquarters: 5 Speen Street Framingham, MA 01701 USA management frameworks can help these organizations achieve their goals. SITUATION OVERVIEW Todays CME market and technology environments are characterized by:  An increasingly harsh competitive climate  A profusion of varied, high-volume, and high-velocity data streams  Enterprise barriers to managing and analyzing new Big Data assets From the perspective of this white paper, the systems supporting CME companies CSP and content delivery network (CDN) operations (operational support systems, or OSS) and the systems supporting their customer, content, and partner assets (business support systems, or BSS) come to the fore as the key information technology (IT) barriers to managing Big Data assets for extracting actionable insight from them. However, additional barriers thwart these efforts as well — in particular, siloed organizational structures and incentives, disconnected cross-functional and multibusiness unit processes, and maladapted decision management frameworks.
  • 2. Competitive ClimateTodays competitive CME climate is harsh — characterized first and foremost bydeclining revenue from large traditional product categories (e.g., wireline voice, basiccable TV service, and entertainment content such as music and videos). In addition,many forms of desirable content and services are readily available to the generalpublic at very low prices or free of charge and often on an ad hoc basis without acontractual subscriber relationship. Moreover, CME industry incumbents confront newindustry participants drawn from varied corners such as consumer electronics(Apple), retail (Amazon), and technology (Microsoft as owner of Skype), as well asover-the-top (OTT) providers and niche players. Core service markets are saturated,and there is little opportunity for geographic expansion beyond home markets. As aresult, revenue and margins are under pressure, subscriber bases are eroding, thechallenge of competing for new customers and retaining existing customers isheightened, and service management and delivery are increasingly complex.The most pressing challenges CME companies face in their roles as CDNs and CSPsinclude: Slowing revenue growth with flat or declining ARPU worldwide Revenue risk from increasing rates of costly B2B and B2C customer churn Heightened service expectations for traditional and innovative product offers Dramatic growth in capital demanded for bandwidth requirements A mishmash of physical and operational system infrastructures Merger of complex legacy organizational structures and operating silosData Here, Data There, Data EverywhereCME companies are characterized by five enterprise management domains —services and products management; device management; B2B and B2C customersales, provisioning, and services management; network management; and digitalcontent management — that generate copious volumes of high-velocity data ofvarious types in critical aspects of their business, as depicted in Figure 1.Each intersection of the five management processes of CME enterprises generatescontinuous streams of Big Data characterized to one extent or another by three Vs —volume, velocity, and variety. Drivers of the three Vs include: A tidal wave of connected mobile devices (e.g., intelligent vehicles, smart building systems, and media tablets) New session patterns for digital media content consumption New service offerings and network usage patterns2 #237013 ©2012 IDC
  • 3. FIGURE 1CME Big Data Generation Nodes Business Support Systems (BSS) Services and Products Management • Digital media • OSS/BSS metadata subscriber • Location and profile info B2B Customer Sales, Provisioning, time of usage Services Management CSP Operations Digital Content Device • Usage patterns, behavior Management • New business models Management profiles, churn data • Product/marketing offers • Network planning and operations B2C Consumer Sales, Provisioning, Services Management • Subscriber, • Real-time events network QoS • Data traffic and IP detail • Social media, records video, text, audio • Device usage behavior, session information, context Network Management Operational Support Systems (OSS) Key: Management Processes (Plain Text) • Big Data Examples (Italicized Text)Source: IDC, 2012Barriers to Effectively Managing Big Data andExtracting Actionable InsightsInformation Technology Barriers to Actionable InsightsWhile CSP companies have long-standing capabilities for managing largetransactional data sets, the legacy IT assets underlying these capabilities are largelyinadequate in todays environment. Increases by multiple orders of magnitude in thevolume of data and metadata, the profusion of unstructured data streaming withincustomer-generated text and digital media metadata in social networks, and new dataentities to organize customer-generated content represent three dimensions in whichlegacy IT assets come up short.Currently, most organizations rely on roughly one-third of the relevant informationavailable to their businesses for decision making. Such a low "data leverage rate" willnot allow an organization to survive, much less thrive, in the future, where we are©2012 IDC #237013 3
  • 4. certain to encounter unprecedented volumes and varieties of data and higher velocitiesof data generation.Many large carriers own multiple networks. Some inherited these networks throughacquisitions and mergers; others have allowed internal business units to invest inseparate IVR platforms over the years.This mixed bag collection of outdated IVR platforms from different vendors is slowingtheir efforts to apply necessary modifications to their services in a timely and cost-effective manner to gain or retain market share.Legacy infrastructures are likely to require extensive modernization/upgrade of ITsystems, including BSS/OSS, service delivery platforms, Web portals, customersupport operations, systems and processes, and more.Given their legacy context, existing infrastructures are typically incapable of miningthe latent value of Big Data. However, todays new, sophisticated Big Data, businessintelligence (BI), and analytics applications, tools, and technologies not only are moreeffective but also typically operate more efficiently and at a lower cost and cangenerally provide a rapid return on investment (ROI). Today, organizations of all sortsmust exploit technological advancements in the areas of information management,data storage and optimization, and business intelligence and analytics to fullycapitalize on the Big Data at their disposal. In particular, CSPs, cable operators, andother suppliers in the digital content realm must leverage automated ways to infusetheir operations and business processes with new intelligence and insight gleanedfrom the Big Data available to them. That means not only tapping into Big Data toprovide better customer service but also tapping into it and leveraging it throughoutthe entire customer and service life cycle — from more effective service innovation tobetter marketing and sales, pricing, trouble resolution, customer support, and more.Other Barriers to Actionable InsightsMost CME industry participants struggle with organizational silos across OSS andBSS processes. For example, customer, network, and service management oftenoperate as separate groups with different priorities — mirrored across disparateinformation technologies and business processes. Again, within the OSS domain, keypolicy-based decisions for the allocation of resources are not considered withindecision management frameworks reflecting the various business units, disparateoperating metrics, and incentive structures. In the BSS environment, responsibility forcustomer relationship management (CRM) functions, customer billing and financialmanagement, and marketing programs is diffused across several organizations —again mirrored in disparate systems.The types of barriers mentioned previously — extant within independent CMEenterprises — have been compounded by the recent wave of mergers andacquisitions as the industry has consolidated under severe market conditions.Such dysfunctional organizational structures and decision management frameworks— all mirrored in legacy system architecture — constrain the depth, extent, andtimeliness of OSS and BSS analytics to improve planning, investment, operations,and optimization of CME asset deployments and processes.4 #237013 ©2012 IDC
  • 5. FUTURE OUTLOOKBig Data– and Analytics-Enabled CompetitiveResponsesCME companies are pursuing — or perhaps more accurately, they are attempting topursue — a range of initiatives in each of the management domains illustrated inFigure 1. Key examples include: Managing customer experience to address growing customer expectations against vigorous competition Consolidating telecom, IT, and IP management to address the complexity and diversity of devices, services, and networks Developing new business models such as cloud delivery of on-demand business and consumer XaaS IT productsInitiatives of these sorts and a wide variety of others — in particular those reliant onBig Data management and analytics — now emerging as CME participants navigatetodays severe market conditions can be classified in three broad categories ofsuccessful strategic responses: Experience personalization (e.g., next best action CRM to monetize subscriber assets and improve customer intimacy and loyalty with real-time profile and usage analytics) Intelligent network management (e.g., centralized policy-based allocation of resources across network services with enforced cross-service compliance) Service innovation (e.g., application store aggregation, cloud services, and hosted voice service)In general, these initiatives commonly rely on historical and real-time contextual datamanagement and analytics across the dimensions of customer, device, network, andcontent management depicted in Figure 1.Each range of initiatives leverages various streams of high-volume, varied, and high-velocity data of the types depicted in Figure 1 to achieve key business outcomes inrevenue generation, cost reduction, and risk mitigation, as highlighted in Table 1.©2012 IDC #237013 5
  • 6. TABLE 1 Big Data– and Analytics-Enabled Business Outcomes Business Outcomes Business Categories Revenue Generation Cost Reduction Risk Mitigation Experience  More effective targeted  Tailor customer support  Improve revenue personalization marketing campaigns via services commensurate assurance effectiveness customer segment with customer value to prevent/detect fraud, offer-response rates theft, and network leakage  Increased rate of resolving  Revenue management via customer inquiries and optimizing pricing by time, complaints on first call in geography, customer less time profile, and use  Contextualized and personalized real-time upsell and cross-sell recommendations presented through customer contact center scripts, during customer browsing sessions, or in SEO advertisements Intelligent network  CDN management to  Better infrastructure  Management of network management continuously stream planning and capital assets to consistently digitized multimedia allocation to networks, deliver improved QoS content from source to systems, datacenters, cell end users sites, and retail locations  End-to-end new product rollout — planning, fault  More effective real-time  Improved design and finding, rectification, and allocation of service utilization of network optimization capacity to high-value assets customers in the context  Proactive real-time of session type and usage capacity management — self-optimizing wireless networks via predictive analytics Service innovation  Development and ongoing  Rapid detection, accurate refinement of evaluation, and effective differentiated product and response to competitors service offerings tactics and actions (e.g., new pricing and  Application markets (app services) stores and development platforms)  Business voice as a service (VaaS) with ready-to-run call and conference management and extended IVR services Source: IDC, 20126 #237013 ©2012 IDC
  • 7. Competitive Imperative: Extract Value fromBig Data and AnalyticsAs Table 1 illustrates, effectively taming the three Vs of Big Data — volume, velocity,and variety — presents CME companies with the opportunity to create value fromactionable insights hidden in Big Data.It is essential for a CME company to extract the maximum value from Big Data inorder to achieve sustainable and profitable growth. Intelligent analysis of Big Data candramatically increase the insight a business has into its customers preferences,buying behaviors, usage patterns, and more. In addition, Big Data insights canimprove the organizations ability to make more informed decisions in productinnovation, pricing, bundling, promotions, and customer support, thus having thepotential to increase revenue and customer satisfaction while enabling theorganization to operate more efficiently and effectively to also reduce costs."Incumbent" service providers need to more effectively and rapidly monetize andgrow nascent product/service categories such as mobile data, and cable and mediacompanies need to better monetize content assets and any existing relationship theyhave with their customers. More specifically, digital service providers need tounderstand customer purchase and usage habits and consumption preferences (akacustomer insight). They also need to personalize the assortment of applications,content, and service offerings for each user (business or consumer) based on theusers needs and interests and at the same time simplify and facilitate the customersability to find the appropriate application/service/content — and do all that costeffectively while optimizing the monetization of all available products/content/titles,services, and resources (the network, bandwidth, employees, etc.).To tap into all of the latent business value of Big Data, a CME organization mustdeploy Big Data technologies in such a way that the new intelligence and insightsgleaned are embedded into the companys business processes and operations. Thereare many points of intersection in a service providers operations and businessprocesses where Big Data technologies and BI/analytics applications and tools canbe embedded so that new information with unique business value can be extracted.In addition, while BI and analytics are not new, with the growth and improved ability tocapture Big Data, there is a growing need to properly operationalize BI/analytics andBig Data technologies within an organization to harvest all insight available for use byboth employees and customers.Fundamental Shifts in CME InformationManagement and AnalyticsFour new paradigms are emerging as CME companies develop their Big Data andanalytics capabilities: Context-aware analytics (i.e., situational awareness of Big Data and analytics in the context of business conditions and decision imperatives based on transactional data)©2012 IDC #237013 7
  • 8.  Pattern-based strategy (i.e., defining, assembling, and interrogating systems of factors relevant to a business strategy, objective, or decision by proactively detecting patterns evident only across multiple systems, processes, and organizations that can positively or negatively impact business outcomes) Shared information ecosystems (i.e., sharing and exchanging relevant information across business ecosystems — the exchange of information across business entities for improved decision making for better business outcomes) Monetization of information (i.e., the ability to derive new economic models based upon the availability of data or analytics as a service, offering, or components of an offering)When one considers the data-intensive nature of CME companies and the verycentral role that many of these information, communications, and entertainmentproviders play in the new digital economy, it seems quite clear that CMEs need toembrace Big Data technologies and leverage the fundamental shifts taking place inthe market in which they operate.For example, what industry participants are better positioned to know a customerslocation and context better than retailers and communications service providers? Witha phone in every customers pocket or purse and GPS and other location-basedtechnologies, CSPs are well positioned to capitalize on context-aware analytics thatcan infer a customers disposition to be presented with relevant merchandise and/orservices for purchase and much more.Similarly, from analysis of usage data in aggregate and on individual customers orcustomer segments, CSPs can discern many important patterns and incorporate thisknowledge into their planning process and develop new service offerings, businessstrategies, and pricing plans — and that is just the tip of the iceberg. Feworganizations are better positioned to monetize information and tap into a diverseecosystem of players to optimally capitalize on the data available to them than CSPs,cable operators, and select media and entertainment companies.In addition, consumers, small and medium-sized businesses (SMBs), and largeenterprises of all sorts are beginning to pursue more agile solutions and alternativeconsumption models such as cloud-based services. Given these shifts, organizationswill increasingly need an innovative end-to-end "information partner" that can providethem with best-in-class solutions consisting of both proprietary and open sourcetechnologies/capabilities so they can select the solution that best meets theirunique needs.8 #237013 ©2012 IDC
  • 9. CME Opportunities with Big Data andAnalyticsActionable insights from efficient Big Data management and effective analytics canaddress some of the main concerns and challenges CME companies face today.PrivacyCSPs, cable operators, and other CME companies will likely invest in BigData/analytics technologies and benefit from social media scans to gauge customersentiment and much more. However, due to privacy concerns, they may be reluctantto trawl for individual customer data and preferences on social media sites. Vendorsshould help CMEs understand how to do so in the most appropriate fashion, takinginto consideration customer privacy concerns, etc.Over-the-Top (OTT) CompetitionIDC believes CSPs and CME companies have a unique advantage in terms of dataavailability and accessibility, but this advantage will not last. We exist in aninformation-intensive society, and it will not be long before competing suppliers suchas the aforementioned OTT players are capturing even larger wallet share andmindshare from incumbent provider citizenry. In fact, we would contend that the OTTplayers already have greater mindshare than incumbent service providers such ascable operators and CSPs. How often do consumers seek content and hotapplications from their incumbent service provider? Not often enough is theresounding truth. In fact, if we go to the extreme negative posture and stipulate thatOTTs have already captured the bulk of consumers mindshare, then the challengesthe incumbent providers face are all the more pressing and real. Therefore, webelieve it is absolutely imperative to leverage all available data at the CME companysdisposal to improve the customer experience, increase new product innovation inboth timeliness and quantity, enhance operational efficiency and effectiveness, andgenerally reinvigorate pricing, bundling, and personalization capabilities.Additionally, many of the larger CSPs have a tremendous opportunity and positioningadvantage to offer SMBs a host of useful offerings such as Web-based videoconferencing, unified communications as a service (UCaaS), and other valuable andeasy-to-use (cloud-based and on-premise) business productivity applications andservices. Big Data technologies can go a long way to ensuring that the launch and thesupport of these offerings yield a rapid and acceptable ROI and customer satisfaction.CME Industry Position Within the IntelligentEconomy EcosystemThe convergence of intelligent devices such as smartphones and tablets; smart cars,smart buildings, and smart infrastructure; social networking; pervasive broadbandnetworking; and analytics ushers in a new economic system that is redefiningrelationships among producers, distributors, and consumers of goods and services.In the enterprise, these trends make it more difficult for business leaders to rely solelyon experience or intuition to make decisions. There is simply too much information to©2012 IDC #237013 9
  • 10. assimilate, and change happens too rapidly. The old cause-and-effect mental modelsbecome outdated quickly, while the demand to respond faster and with greater insightto ongoing internal and external events is increasing, particularly for CME companies.For many years, people wanted to move to the "intelligent economy," but the toolswere lacking. In this new economy, not only access to information but also the abilityto analyze and act upon information creates competitive advantage in the market andcontinuous innovation in new product development, packaging and bundling, pricingand billing, and more. Today, the discussions extend to a broader set of data andwhat CME organizations can do with the data once they gain access to it. Theintelligent economy produces a constant stream of data that must be monitored,analyzed, and acted upon. The data management and analytics challenges of theintelligent economy are likely to overwhelm CME organizations that are unpreparedfor these changes.Also, as weve said, CME companies are uniquely capable of capturing data from allavailable data sources: the "smart" network (call detail records, IP events/transactions,customer and service interactions with systems and CSRs, etc.), DPI, end-user devices,M2M modules, RFID chips, sensors, security cameras, social media, internal systemsand networks, and external sources such as partners and their systems and customers.Accordingly, CME companies are well positioned to unlock insights from all availabledata. Via an enterprise approach, they can harvest, organize, and analyze data andapply insights in the decision management context of each relevant business process.In addition, they can leverage Big Data technologies and advanced analytics andbusiness intelligence tools and applications to mine their vast warehouses of valuablecustomer, service, network, and operational data.OVERVIEW OF HP BIG DAT A AND AN AL YTICSOFFERINGSHP offers a wide range of information management and analytics (IM&A) capabilitiesdrawn from its enterprise services, software products, and cloud and securityplatforms to address Big Data challenges and opportunities in the CME space.HP IM&A services include information strategy and organization, informationmanagement and architecture, business analytics and information delivery, and socialintelligence. HP provides these consulting services around its own Big Data softwareassets, Autonomy and Vertica, and third-party software assets, in particular SAPHANA and Microsoft SharePoint/BI platform. HP supports this with a variety ofsoftware and solution delivery models including on-premise installation, hosted,software as a service (SaaS), cloud computing, and multitenant SaaS (clouddeployment).HP focuses its capabilities to enable CME organizations to proactively manageinformation-related business risk, enhance customer experiences, and optimizebusiness performance to maintain reliability, reduce the costs of operation, andprotect revenue.10 #237013 ©2012 IDC
  • 11. HPs Autonomy software asset helps CMEs develop connected intelligence fromstructured and unstructured data for actionable decisions that improve businessperformance.HPs Vertica analytics database delivers scalable performance on Big Data queriesenabling real-time decision making to be embedded in utility processes in order tooptimize business performance.Vertica and Autonomy deliver a powerful combination for real-time analytics anddecision making using structured and unstructured data across the enterprise.HP CMS OfferingHP CMS provides a broad portfolio of products and solutions from core network tohandheld devices. This includes a suite of convergent IT and telecom solutions withsoftware assets to address areas such as OSS/BSS, SDP, SDM, cloud, M2M, CDN,and telecom Big Data and analytics as well as professional services such as businesstransformation consulting, integration, enhanced support, and managedservices/outsourcing. The HP CMS Actionable Customer Intelligence (ACI) portfolioof products and solutions supports CSPs with: Building a single and secure customer profile Analyzing trends over time and in time for a better understanding of each customers preferences and behavior Acting with personalized offers to improve the customer experience and managing real-time charging and policy controlsHP ACI helps telecom operators gain control of their customer intelligence and let itwork for them to monetize enriched services, conduct targeted promotions andcampaigns, as well as control network congestion and enable new business modelsfor partnerships with over-the-top players.Strengths and ChallengesHP offers a solid product portfolio to CME companies in the Big Data and analyticsarena and also possesses a knowledgeable and experienced services organizationwith a good understanding of CME business processes and systems. In the Big Dataand analytics arena, it is critical that these two sets of assets (products and servicespersonnel) come together for CME companies. HP can leverage its strong embeddedbase of CME customers to upsell Autonomy and Vertica offerings, but IDC believes itis important that HP recognize that the Big Data game should not be driven only bytechnology. It is vitally important that HP retain staff/expertise from Vertica andAutonomy and give these important teams of people and the related assets the abilityand autonomy (pun not intended) to lead their own marketing, sales, and deliveryefforts in the manner that is appropriate for these sorts of engagements and generallyto be empowered to deliver business value in the same manner that they did prior tobeing acquired by HP. With all of the management turmoil that has been taking placein HP over the past several years, it is critical that the significant investments HP hasmade into the Big Data and analytics space not be squandered.©2012 IDC #237013 11
  • 12. Specifically, for companies in the communications (telecom and cable) and mediaand entertainment industries, knowing how their business operates andunderstanding their business processes, systems, and operations are criticallyimportant to the effectiveness of any sort of major initiative. Accordingly, for HP tofully leverage Autonomy and Vertica and its other industry-specific assets and domainexpertise, it must pull all these things together cohesively into solutions that will meetspecific business needs for CME companies. IDC believes the relatively recentacquisitions of Vertica and Autonomy strongly signaled to the market HPs intentionsto become a leading provider of data warehousing and analytics solutions; however,for CME companies to become believers and buyers, HP must combine the in-houseexpertise of these industries with the prized assets and expert personnel whoknow them.In addition to the software and services capabilities noted previously, HP provides thefollowing infrastructure components to enable Big Data application deployments: Cloud computing. HP can offer clients a variety of enterprise-grade cloud computing solutions, including public, hybrid, and private. The ability to offer private cloud to CMEs is considered a strength for a number of reasons, not the least of which is a tighter security model. Security. HP offers clients a security strategy through the HP Security Framework, designed to offer end-to-end information security plans and execution road maps. Because of the sensitive nature of customer data and the requirements and penalties imposed by the regulators, security is top of mind for industry IT executives. Mobility. HPs approach to enabling enterprise mobility is suited for organizations that wish to reach their constituents across multiple networks and devices by delivering applications, content, and services in a scalable, secure, and reliable way. This approach leverages HPs global applications services capabilities to provide the architecture, systems engineering, development, and support services. Combined, they help an organization simplify its applications and extend them where necessary as well as build mobile business-to-business, business-to-consumer, and business- to-employee applications. This approach also leverages HPs service-oriented architecture–based integration architecture and is enabled by development and security frameworks that help create componentized building blocks from monolithic legacy applications to develop and deploy mobile applications.HP faces several unique market challenges and some of the same market challengesas other leading IT vendors serving the CME communitys Big Data needs: Demonstrating leadership in the transition from information management to Big Data. HPs legacy information management solutions, including TRIM, Data Protect, and others, are not broadly implemented across the CME marketplace. HP must more effectively demonstrate leading capabilities at the component level with high-profile Autonomy and Vertica wins as well as highlight its ability to deliver end-to-end Big Data software, services, and hardware with both lighthouse and marquee CME companies.12 #237013 ©2012 IDC
  • 13.  Offering competitive, differentiated solutions portfolios. In the CME industries, many of these companies are traditionally early adopters of emerging technologies. Accordingly, they fully understand the potential value of the Big Data trend and are budgeting accordingly. HPs competitors are also focused on expanding their solution portfolios on the Big Data trend in terms of breadth and depth of product capabilities, IT infrastructure, and professional services. HP must leverage its industry position and demonstrate the value of a Big Data relationship with HP to gain Big Data market share.ESSENTIAL GUIDANCEWhile it is difficult to know how and where to start a Big Data/BI/analytics initiative,there is little question that doing nothing is not an option. Uncertainty about where togo for the best solution and solution provider and concerns over costs andrequirements and the like are only natural. However, several parties can help yourorganization recognize the value of untapped data assets and the implications ofoperating without the critical information that is available to your organization as wellas its employees, customers, and partners.To begin, you should conduct a data gap analysis using internal resources or workingwith a trusted IT partner, or both, which is probably best. This analysis will give yourorganization a prioritized list of functional areas, processes, and employee positionsthat would operate more effectively and be able to make more informed decisions ifthe users had all the data and information they needed to perform optimally.In addition, it is vital that the organization formulate a Big Data strategy — and thismust be done at the top level of the organization. Without an executive-led initiative,an organization has little opportunity for success with Big Data because it is an all-encompassing undertaking. Thus, it is critical that the organization engage itsstrategic leadership team to develop a Big Data strategy. The elements of thestrategy will address the organizational needs, both short term and long term, as wellas the goals for all the departments involved/selected and will prioritize eachdepartments requirements at the highest level. From there, it is best to engage aknowledgeable and experienced expert partner to vet the strategy and revise itaccordingly and not to go further than strategy development until the strategy isconfirmed. As you probably know, there are many suitable organizations able toassist a large CME company with its Big Data initiative; but in the end, it is best left tocompanies with strong Big Data/BI/analytics assets and proven real-worlddeployment experience in your industry.In summary, while service providers and many CME companies are indeed wellpositioned to leverage vast amounts of customer, service, usage, credit, billing,location, presence, context, and other data at their disposal, the Big Data projectteam that must ultimately be formed and empowered will need to evaluate theorganizations data, people, processes, and technology before moving forward withany Big Data initiative. Specifically, the team will need to evaluate the quality,relevance, availability, trustworthiness, governance, security, and accessibility ofmultistructured and unstructured data. In addition, the team will need to evaluate thetechnology and analytic skills, intra- and intergroup collaboration, as well as©2012 IDC #237013 13
  • 14. organizational structures and cultural readiness of the people within the organizationto holistically embrace a Big Data initiative. Also, the Big Data team will need toevaluate the processes of data collection, consolidation, integration, analysis,information dissemination and consumption, and decision making required. Moreover,the team will need to evaluate the appropriateness, applicability, and performancerequired of the technology and IT architecture associated with the relevant workloads,among other things.In the end, while these activities may seem daunting, IDC believes that infusing theorganization with insight throughout every major process and functional area willultimately be worthwhile for the CME company and its customers. The CMEorganization is likely to benefit from increased revenue and profitability; improvedcustomer satisfaction, acquisition, and retention; and an enhanced ability to innovatewith better business flexibility and agility. In turn, the CME companys customers willbenefit from more consistent and high-quality service experiences and improvedempowerment and control over the services they subscribe to and the managementof their account. In addition, customers will appreciate being made aware of newproducts and services that are relevant to them when, where, and how they want tobe informed of new offerings. Both the organization and its customers can benefitdramatically from Big Data and analytics initiatives if they are undertaken in astrategic, holistic, and disciplined fashion with the commensurate level of executivesponsorship and support so that the right solutions are selected, deployed, andconfigured for optimum and continual business improvement.Copyright NoticeExternal Publication of IDC Information and Data — Any IDC information that is to beused in advertising, press releases, or promotional materials requires prior writtenapproval from the appropriate IDC Vice President or Country Manager. A draft of theproposed document should accompany any such request. IDC reserves the right todeny approval of external usage for any reason.Copyright 2012 IDC. Reproduction without written permission is completely forbidden.This document was reprinted by HP with permission from IDC.14 #237013 ©2012 IDC