Gartener

G00293176Predicts 2016: Information Strategy Published: 9 December 2015 Analyst(s): Douglas Laney, Alan D. Duncan, Mario Faria, Debra Logan, Alan Dayley, Guido De Simoni, Michael Patrick Moran, Andrew White, Saul Judah During the next several years, leading organizations will begin monetizing their data directly, will have chief data officers often hampered in various ways, and will focus information governance increasingly on the Internet of Things, metadata and master data. Key Findings ■ Businesses that can monetize their information assets outstrip their rivals by using information to reinvent, digitalize or eliminate existing business processes and products. ■ The majority of CDOs and information leaders are still learning on the job. ■ A lack of common metadata standards across business units is due to disengagement with enterprise information governance, not the enabling technology. ■ High fidelity mastering of IoT data objects will serve as a key enabler in the transformation of business models from "guaranteed levels of performance" to "guaranteed outcomes." ■ The vast majority of organizations are struggling mightily to establish the operational side of information governance (that is, information policy enforcement or information stewardship). Recommendations Information leaders, such as CDOs, should: ■ Establish an information product function that directly monetizes data. Identify information assets that can be exchanged for mutual economic advantage. ■ Map the information strategy directly to the organization's business strategy to build trust with stakeholders. Communicate information's key role in overall business success via quantifiable information metrics linked to business KPIs. ■ Launch an enterprise metadata management initiative that links existing information programs to increase investment yield and maximizes collaborative investments across projects. ■ Through 2019. warrants its own strategy to ensure its economic benefits are maximized in a multiplicity of ways. ■ By 2020. Analysis What You Need to Know The emergence of CDOs in many organizations and across industries indicates a growing recognition of information as a strategic business asset — one distinguished from the technology through which it flows. Increasingly. 50% of information governance initiatives will be enacted with policies based on metadata alone. Alan Duncan Page 2 of 12 Gartner. ■ Through 2019. Analysis by: Douglas Laney. | G00293176 . these Strategic Planning Assumptions should be considered in overall enterprise information management (EIM) and business strategy development. which is so central to an organization's success and linked with business strategy. accounted for and deployed just as traditional balance sheet assets. Information. ■ Focus data governance on data with the greatest economic potential across business units. Strategic Planning Assumptions Strategic Planning Assumption: By 2020. And even IT organizations themselves are beginning to cleave into autonomous "I" and "T" units in some major businesses and government agencies. and elevate the role of the information steward.■ Approach IoT projects with the same rigorous business requirements. of these. 10% of organizations will have a highly profitable business unit specifically for productizing and commercializing their information assets. 10% of organizations will have established operational information stewardship in line-of-business functions. 90% of large organizations will have hired a chief data officer (CDO). information is accumulated. For enterprises to realize the benefits of treating information as an actual enterprise asset. only 50% will be hailed a success. the Internet of Things (IoT) and digital business will drive requirements in 25% of new information governance and master data management (MDM) implementations. 10% of organizations will have a highly profitable business unit specifically for productizing and commercializing their information assets. Inc. architectural standards and governance that are applied to traditional information management projects. ■ By 2020. managed. Strategic Planning Assumptions ■ By 2020. and third-party sources that can be synthesized for value-adding insight. developing and productizing the market for the information asset (analogous to the product development life cycle established for managing and marketing traditional products). LexisNexis.Key Findings: The trend to see and use information as an asset is still in the "early adoption" phase. Why? In Gartner's experience. businesses in other sectors are identifying that data exchange — either by licensing raw data to partners or by sharing derived insights — can become a valuable revenue stream in its own right. digitalize or eliminate existing business processes and products. the value of information itself is still largely unrecognized or unrealized. Data brokers. ■ Established data brokers will evolve to provide both of the above services. Dun & Bradstreet. such as copyrights. Equifax. ■ Technology megavendors will begin to partner with and acquire major sources of data and content.D. | G00293176 Page 3 of 12 . even as the value of other intangibles. generating their revenue and other financial benefits from exchanging it. Yet. and J. most information and business leaders lack the experience and tools to monetize information. making doing so a competitive differentiator for leading organizations. Nielsen. This implies creating a team with a specific remit for defining. Recommendations: Information leaders should: ■ Establish an information product management team to professionalize and focus the capability for directly monetizing data. Market Implications: ■ Professional services firms will begin to develop capabilities for advising and delivering information product management and self-data brokering for their clients. ■ The number of third-party businesses for hosting and reselling others information assets (via published APIs or direct data downloads) will continue to grow before the market ultimately begins to consolidate. is measured and reported. ■ Develop and maintain an inventory of information assets from throughout the organization. have built business models based on data monetization. Power. as well as those from second. based on hundreds of client inquiries and interviews. Gartner. such as Experian. Increasingly. to achieve direct monetization of data requires focus. trademarks and patents. Businesses that can monetize their information assets outstrip their rivals by using information to reinvent. However. Inc. ■ Measure the exogenous economic value in your data to determine which of your information assets have market potential. determining which data assets can be monetized is not an easy task. and that 90% of large companies will have CDOs by 2019. Analysis by: Debra Logan. only 50% will be hailed a success. CDOs report that much of this resistance is coming from the IT department. We expect these numbers to grow. business users are apt to blame the data office and the CDO. and many newly appointed CDOs are meeting change resistance from all quarters. Related Research: "Seven Steps to Monetizing Your Information Assets" "Why and How to Measure the Value of Your Information Assets" Strategic Planning Assumption: Through 2019. of these. Because this role and its functions are new in most organizations. the majority of these data leaders are learning on the job. Their first task is to create an information strategy that improves business outcomes. While monetization of data is a relatively straightforward way to demonstrate value. Market Implications: ■ The office of the CDO initiatives are often positioned as having intangible results and rarely tie their metrics of success with business expectations. ■ Some organizations that created a CDO role but failed to invest sufficiently in it will take a step back and eliminate the role. | G00293176 . Although stakeholders are demanding better results from their information management initiatives. The most difficult issue for many CDOs is creating relevant metrics that tie the activities of information management to measurable business outcomes.000 CDOs/chief analytics officers in the world. When data and information initiatives fail. ■ CDOs are not being able to approve their budget needs easily. Inc. Politically. particularly over the control of information assets and their governance. are unsure as to the exact mechanics of making that happen. too. up from 400 in 2014. Page 4 of 12 Gartner. Mario Faria Key Findings: At the end of 2015.■ Leverage existing business partnerships to identify opportunities for mutual advantage through exchange of information assets and key insights. they. the position that the CDO holds is a difficult one. 90% of large organizations will have hired a chief data officer (CDO). there were about 1. especially the CIO. Saul Judah Key Findings: ■ Organizations are dealing with a tremendous amount of information that can inhibit them from transforming into digital businesses if not curated and governed properly. | G00293176 Page 5 of 12 . Alan Dayley. and share them with the organization.Recommendations: Information leaders should: ■ Create an information strategy based on the organization's business strategy and predominant value discipline. ■ Educate senior leaders and peers about the role that data and information play in overall business success. analytics governance needs to be considered in the context of the wider enterprise governance framework and alongside information governance policies and practices. rather than enabling technology. Related Research: "Chief Data Officers' Handbook" "Chief Data Officers Should Align Authority and Responsibility to Succeed" "Successful Organizational Design Principles for the Office of the Chief Data Officer" "How to Start Implementing the Bimodal Office of the Chief Data Officer" Strategic Planning Assumption: By 2020. Inc. ■ Tie quantifiable information metrics to quantifiable business key performance indicators (KPIs) to demonstrate tangible success. ■ Additionally. Analysis by: Guido De Simoni. Gartner. 50% of information governance initiatives will be enacted with policies based on metadata alone. ■ Adopt formal information asset measures. lack of agreement on common metadata standards across organizational business units is attributable to disengagement with enterprise information governance. ■ Work tirelessly on building trust with various business stakeholders. ■ Establish baselines on information governance and data monetization from which progress can be measured. ■ Lastly. untrusted information. however. use this metadata as a basis to launch an EMM program to ensure consistency and support across disparate information management investments and projects. this carries the risk of wrong. digital business. project or program across the organizations. It becomes important because. Most organizations will find that their current metadata management practices are different across applications. Data visualization maps can be presented to other parts of the organization and can be used to better identify the value and risk of the data. and risk and compliance requirements. line-of-business and compliance organizations to make more-informed decisions regarding classification and information governance data. data and technologies. these maps enable IT. the responsibility for breaking down these silos is beyond the scope of an EMM discipline. governance. Technologies exist that can assist in detailed mappings of metadata — for either unstructured or structured data (although usually not together). these widely reused information assets are heavily depended on to assure business process. Thus. the IoT. Organizations should use file analysis to better understand their unstructured data. as well as legal. because it provides the means to better understand the existing silos and governance rules that relate to strategic types of information assets. Inc. Most organizations have policies and procedures related to security. Thus. we often see failure to address the interrelationships between each information investment. and that these practices are siloed by the needs of different disciplines — each with their governance authority. as well as to identify and improve information practice to Page 6 of 12 Gartner. insufficient. master data and business processes. Emerging trends. ultimately. | G00293176 . illegitimate or unethical application of analytics if they are based on poorly governed. outcome and analytics integrity. Metadata is one of the critical components for ensuring that individual information investments can be linked. including where it resides and who has access to it. smart machines and. Generally speaking. practices and capabilities. EMM then helps to better align information and analytics governance. and poorly supported information policies. However. Use the EMM to help you link existing information programs — in an effort to increase investment yield. are driving the need to make analytics an integral part of any information strategy. by definition. such as big data. including information governance. are aligned and can leverage each other. privacy and governance of information assets. Enterprise metadata management (EMM) becomes especially important for strategic types of information and business assets — such as enterprise data models. Recommendations: Information leaders must: ■ Identify metadata within the organization that is consistent and represents high business value. Furthermore. EMM offers a foundational approach for aligning information and analytics governance.Market Implications: The CIO or CDO has a key responsibility to implement an enterprise-class metadata management initiative. such that the thing and the select data that it generates are both recognizable and available to business processes supported within the IT environment. more than a cumulative 25 billion things will be shipped. organizations will face a wide range of opportunities to substantially increase operational efficiency of existing business processes or completely transform their business models. By leveraging the IoT. roles. Direct support of resultant Gartner. thereby assuring the desired evidence-based business outcomes. IoT platform. the Internet of Things (IoT) and digital business will drive requirements in 25% of new information governance and master data management (MDM) implementations. | G00293176 Page 7 of 12 . standards and applications. Performance demands resulting from the continued shift — from physical to digital objects (or their proxies) — within commerce will serve as a driver to improve on the current status quo of "good enough" information governance and MDM programs prevalent today. ■ Ensure close cooperation of the information governance team with business intelligence (BI) and analytics leaders by leveraging EMM. However. Inc. support of revenue-generating business activities will require semantic consistency for those "things" and select associated data across the IoT platforms. OT or IT through business process). They must work together on information and analytics processes. ■ Leverage the data presentation features of file analysis products as key selection criteria to implement an effective metadata and content analysis initiative. High fidelity mastering of these data objects will serve as a key enabler in the transformation of business models from guaranteed levels of performance to guaranteed outcomes. Achievement will require an end-to-end capability (thing. The rise of the IoT has brought with it the need to master a new class of data objects — that of "things" (proxies for the physical object from which the sensor data is being recorded). Related Research: "Market Guide for Metadata Management Solutions" "Gartner Clarifies the Definition of Metadata" "Enterprise Metadata Management Improves Information's Accessibility and Increases Its Value" Strategic Planning Assumption: By 2020. operational technology (OT) and IT domains in which they participate. Analysis by: Michael Moran Key Findings: Gartner forecasts that by 2020.ensure consistency and support across disparate information management investments and projects. which represents an average annualized growth rate of 35% for the IoT. The combination of advanced analytics supported by aggregate data derived from real. This capability. Recommendations: Information leaders should: ■ Approach IoT projects with the same rigorous business requirements and governance that is applied to traditional line-of-business projects that drive revenue today. OT and IT domains in which they reside (that is. and thus the transformation of associated business models. Market Implications: Capabilities inherent within the IoT hold out the promise of transforming business models through increased efficiencies and business model risk reduction to degrees previously unimaginable within value chains dependent on machine technology. such as a diesel engine) will enable people to identify additional opportunities to deliver value. ■ Medium term — The above. along with semantic consistency across the IoT. will serve to enable the reduction of uncertainty to provide for the transformation of associated business models to guaranteed outcome. will require improvements in information governance. will provide for increased efficiencies. ■ Longer term — Analysis over time of real-time performance and operational status data across very large datasets will provide for improved design. coupled with advanced analytics and the ability to represent the object within business value chains. in turn. Page 8 of 12 Gartner. Achievement of these benefits. IoT things become recognized as master data objects and are managed actively within an MDM program). in combination with integration of business processes that enable tracking and billing of power consumed by the operator (known colloquially as "power by the hour") will enable the transformation of business models from guarantee of performance to guarantee of outcome. is contingent on high fidelity identification of the specific objects and instances thereof. These capabilities will serve as the catalyst to directly address levels of uncertainty intrinsic to business models based on guaranteed levels of performance. | G00293176 . This. In the example of a diesel engine manufacturer: ■ Short term — Real-time monitoring of performance and operational status of each engine. such as decreased downtime for maintenance and reduced maintenance costs. combined with predictive analytics. and in supporting MDM solutions and programs.lines of business will require step-level change above that which serves as the norm for information governance programs today.or near-real-time performance data traceable to individual things (or collective aggregates. Physical objects and their components properly engineered and outfitted with sensor technology will provide for the direct performance and operational status monitoring of a given instance of that object in its real-world application. Inc. engineering and manufacture of succeeding products. ■ Realize that the value of IoT will require semantic consistency and therefore mastering of designated things across the full spectrum of IoT. business processes will need to change and adapt to make use of it. or information stewardship. As a result. and how. The only place where this takes place well (today) is in regulated industries under the auspices of compliance. repeatable or sustainable. data advocate) for getting more value from information. ■ Understand that current business processes neither account for nor accommodate IoT data. There is massive dissonance in terms of defining the scope of the work. As IoT data becomes increasingly available within the IT environment. the great majority of Gartner. the majority of surveys we do show that the majority of organizations think information stewardship is what IT does. Market Implications: Information governance has become a very hot and important topic for our clients. the work is not being done properly or in a manner that is scalable. Related Research: "Four Essentials for Starting and Supporting MDM" "Mastering the 'Things' in the Internet of Things" Strategic Planning Assumption: Through 2019. or that every user of business apps or data warehouses are stewards. It is bandied about as the answer to making value from insight related to big data and data lakes sustainable. Evolve business processes to integrate appropriate data in support of IoT-mastered objects. It's the secret sauce. even if a different name is used (for example. Design for and implement end-to-end master data architecture to provide for high fidelity information semantic linkage between IoT. The reality is hugely different: Few organizations have actively embedded the work of policy enforcement in the context of day-to-day business operations. OT and IT domains. | G00293176 Page 9 of 12 . Thus. it remains one of the top 10 most discussed topics every month for the last two years. Inc. 10% of organizations will have established operational information stewardship in line-of-business functions. The odds are that this situation will persist for some years to come. most data-related vendors have as much experience with information governance work as do end-user organizations — virtually none. It is the silver bullet in terms of embedding MDM at the heart of business application landscapes. the vast majority of organizations are struggling to establish the operational side of information governance — that is — information policy enforcement. who should do it. In information management. Analysis by: Andrew White Key Findings: Although information governance is fast becoming a critical business-enabling business-led activity. OT and IT environments.■ Plan for and design the mastering of things within the IoT domain and platform to provide for integrity required within the IT domain. Even worse. we are taking a look back at some key predictions from previous years. and 3% are selling data via a third party. Missed: 2013 Prediction — By 2015. Communicate that information governance and stewardship are not "data issues" but "business issues. to help automate and scale the work of policy enforcement in an environment and user experience most friendly and meaningful to business users. 6% are exchanging data for goods and services. as well as one we missed. Inc. ■ Explain to business leaders and users how the work of information stewardship adds and augments business value to outcomes and business processes.information governance programs — whatever their name or scope — will fail to live up to expectations and yield the business benefit desired of them. On Target: 2013 Prediction — By 2016. ■ "Sell" the work of information stewardship as "chief problem solving" for those business outcomes and processes held hostage to information challenged. Recommendations: Information leaders must: ■ Create/define a clear role for an information steward. | G00293176 . ■ Leverage technology. However." ■ Focus on those business outcomes and processes that are most important to business users. travel/hospitality and utilities) reap economic benefits via data exchange — but do so quietly at the risk of customer backlash. telecommunications. 25% of the global demand for big data jobs will be driven by the financial services industry. Do not focus on data unrelated to these. Our research (229 clients surveyed in August 2015) indicates that 50% of organization contend they are monetizing their data directly or indirectly. Related Research: "Governing the Information Governance Board" "Toolkit: Assess Your Information Governance Initiative" "Operationalize Information Governance With Technology Support" A Look Back In response to your requests. where possible. 30% of businesses will have begun directly or indirectly monetizing their information assets via bartering or selling them outright. we believe that so many organizations (especially those in retail. Ten percent claim they are selling their data on their own. We have intentionally selected predictions from opposite ends of the scale — one where we were wholly or largely on target. Page 10 of 12 Gartner. Skill shortages are cited by 36% of organizations in 2015 (up from 30% the previous year). government.Big data infrastructure and analytics adoption have grown rapidly and become mainstream to span all industries. it does not nearly account for a quarter of all demand. travel and energy are nearly as strong. See the collection: ■ Predicts 2016: Algorithms Take Digital Business to the Next Level Gartner. Demand among telecommunications. "Why and How to Measure the Value of Your Information Assets" "How Chief Data Officers Can Help Their Information Stewards" "Survey Analysis: Practical Challenges Mount as Big Data Moves to Mainstream" "How Organizations Can Best Monetize Customer Data" "Market Trends: Innovative Pricing Helps CSPs Monetize Data and Differentiate Services" "Seven Steps to Monetizing Your Information Assets" "Governing the Information Governance Board" "How to Put an Implementable IoT Strategy in Place" "CDO Reporting Relationships Can Make or Break Your Information Management Program" "Should CIOs Aspire to the Chief Digital Officer Role?" More on This Topic This is part of an in-depth collection of research. Gartner Recommended Reading Some documents may not be available as part of your current Gartner subscription. | G00293176 Page 11 of 12 . 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