This year promises to be a break-out year for master data management, with a number of milestones expected to be reached. In part one of this blog I introduced research from the Master Data Management Institute’s customer advisory council, which is intended to serve as a "road map" to help Global 5000 enterprises focus efforts for their own MDM programs.
Part one focused on three of the MDM milestones for 2016. In part two, I look at the other milestones the Institute predicts. All of these themes will be explored in depth at the Institute’s 11th annual MDM & Data Governance Summit, June 8-10, in San Francisco.
Cloud MDM (Cloud-Enablement, Architecture & Integration)
During 2016, single- and multi-tenant cloud master data management will continue to attract small and mid-sized organizations (and increasingly large enterprises) looking to achieve MDM benefits without long-term project and major expense. Such offerings will provide an enticing entry point for large enterprises (for example, opex vs. capex, cost effective POCs) and the potential for infinite elasticity as well as federated architecture for geo-distributed organizations. However, native cloud MDM platforms will underwhelm market expectations relative to classical MDM, while concurrently, pricing models of cloud MDM solutions will stress mega software vendors’ EBITA near term.
Through 2016-2017, the integration of on-premise MDM with SaaS apps will arrive via SFDC, SAP BBD, et al. However, enterprises will wrestle with data integration issues between on-premise and cloud, with a majority of organizations unwilling to house master data about customers, products or suppliers in the public cloud. Enterprise reference data remains an exception to this dogma. Concurrently, MDM-enabled apps will migrate to public cloud, especially for decentralized or geographically distributed organizations.
By 2018, cloud-innate services for data quality and data governance will be more prevalent. However, enterprise operational MDM will remain “on premise” with increasing integration-to-cloud applications.
Reference Data Management (RDM)
Through 2016, reference data will continue to be a key entry point for enterprises, and will in turn unduly influence the choice of MDM for customer, product and other domains. Large enterprises will continue to mandate that reference data be part of MDM platform's native entity types.
During 2016-2017, MDM vendors will begin to market RDM to apply an MDM approach for centralized governance, stewardship and control. While many organizations will apply RDM to manage and rationalize reporting dimensions across data marts (or monster marts via Hadoop), increasingly the compelling use case is data standardization on the way into big data lakes, i.e. cleansing or taxonomizing of real-time data streams feeding the big data lakes.
By 2018, pervasive, low cost RDM will be commoditized via the efforts of Ataccama, Microsoft and Oracle. Mega vendors will respond by providing “throttled” MDM hub with RDM as licensed domain.
Through 2016, dogmatic spats regarding analytical vs. operational vs. collaborative MDM use cases will become historic artifacts, as each become business-critical MDM which demands zero downtime. Certain MDM vendors will continue to sell better in reference data user use cases due to lack of scalability imposed by their semantic flexibility. Similarly, as multi-domain MDM has become commoditized among the mega MDM vendors, the need to compete at application-level will surge. Clearly, MDM is all about improving business processes as enterprises demand enterprise-strength MDM-powered applications targeted at their industry or problem set.
During 2016-2017, enterprises will increasingly focus on 1:1 marketing, as the importance of “master relationship management” and “system of engagement” becomes a leading MDM business case for many industries. Concurrently, MDM platforms will provide in-situ capabilities to change data model, business rules, etc. … without taking MDM services offline. By 2018, this will impact way master data services are syndicated and delivered … regardless of regular ablutions such as software upgrades.
Social & Mobile MDM
During 2016, the 360° view of “X” will take on new meaning due to “data blind spots” of traditional MDM. Enterprises will realize the need to reconcile social identity with corporate and household identity, to provide authoritative master data to drive e-marketing and commerce within social networks.
Through 2016-17, next-generation MDM will address “sphere of influence” to incorporate both extended and non-obvious relationships, to grow share of wallet from individual to exo-ego network as disruptive sales strategy (vs. ego-centric marketing). “System of engagement” will begin to surpass “system of record” for most industries and use cases.
By 2017-2018, mobile location-based services, enhanced with location-specific customer info, will raise the ante for e-commerce within and outside major social networks. Data-related processes must align and real world intricacies – especially complex relationships/hierarchies of mobile customers and extended social networks.
Big Data (& In Memory)
During 2016, the performance of all major aspects of base MDM functionality will benefit from performance-enhancing capabilities of big data and in memory configurations — from batch loading of MDM hubs to real-time identity resolution to operational updates. Managing BI dimensions of “monster marts” (Hadoop) will revitalize notion of “analytical MDM” use case.
Through 2017, big data will continue to repatriate itself into MDM fabric via registry overlays as yet another source. The mining of big data to populate social MDM and perform entity matching on big data stores will help provision a 360° view of entity from public, subscription and enterprise data.
By 2016-17, very large enterprises (e.g., financial services or large government agencies) will look to real-time MDM flows and scaling of MDM solutions via elasticity of cloud-based solutions, in-memory DBs, and next-generation ETL/MDM. In-memory DB will further escalate ability of graph DB to deploy as super layer onto multiple MDMs.
Business Process Hubs
During 2016, MDM solution providers and BPM solution providers will moderately collide in the market as they acquire or build out BPM-centric MDM. Both camps will be challenged to unify domains as there exist different business processes for CDI and PIM. Again, graph DB technology will be seen as the solution to domain cross-walks and rule, data integration, and analytics.
Through 2016-2017, however, BPM-centric MDM will continue to suffer from BPM’s traditional focus on modeling and not executing MDM rules, as well as BPM-centric vendors' ineffectiveness in marketing against MDM-centric vendors.
By 2018, all mega MDM and BPM vendors will have overcome this dogmatic bias, as enterprise BPM needs to execute within governance and vice versa, to be able to execute MDM workflows within BPM.
From the enterprise perspective, a complete MDM solution requires both rules and reference data to be applied across domains.
During 2016, the number of IT professionals trained in a specific MDM solution will increase by 15 percent to 20 percent. However, IT organizations and consultancies will struggle to recruit and retain IT veterans who have had a major role in a successful MDM or DG deployment.
Through 2016-17, enterprises will continue to spend three to four times in “plan” and “build” services vs. MDM software. MDM and data integration COE leadership will increasingly evolve into CDO careers.
By 2017-18, the supply of MDM-experienced consultants will catch up with demand, and SIs will scramble to find new big data-driven opportunities for their expensively recruited and trained talent. Data governance positions will continue to demand strong native language skills and localized presence.
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